Displays

The Arctic is changing in response to ongoing warming. Multiple effects have been documented in terms of sea-ice distribution, land-ice volume and ecosystems both in the marine and terrestrial realm, which are clear responses to the overall global warming. Targeted efforts documenting individual components of the arctic system build the base-line for quantification of these effects.

Comprehensive ecosystem observational programs covering both glacial, terrestrial and marine components are rare in the Arctic but one such, the Greenland Ecosystem Monitoring (GEM) program, has now been operational for nearly 25 years at three main sites in Greenland. Zackenberg valley and Young Sund in NE Greenland is representing the high-arctic environment, Disko Island on the central west coast of Greenland at the border between the high and the low-arctic and Nuuk-Kobbefjord in SW Greenland the low-arctic.

The GEM program at all three sites cover inter-annual variation in ecosystem dynamics of glacial, terrestrial and marine ecosystems with data gathered from more than 2000 parameters some of which being automatically recorded at very high frequencies (up  to 20 Hz for micro-meteorological measurements). This present-day detailed, comprehensive and high-frequency monitoring of ecosystem dynamics calls for the question: Which historical sources may be used in order to anchor the environmental status of the monitored areas back in time?

For the composite landscape dynamics including glacier, terrestrial and near-coastal environments it is of great value to study visual, mainly photographic evidences that are available from different parts of the portfolio of arctic exploration during the 19^th and 20^th centuries. We will in this presentation review available historical archival data (early photographs, paintings, drawings) from the GEM monitoring locations and their immediate surroundings.

The different historical setting over the centennial timescale is briefly discussed and particular illustrative records from the individual sites are shown. The evidence of change hereby shown at the centennial time scale is evaluated in the perspective of results from decadal scale present day monitoring.

How to cite: Christensen, T. R., Rasmussen, K., Abermann, J., Raundrup, K., Christoffersen, K., Hansen, B. U., and Arndal, M. F.: Centennial scale environmental change at key arctic observational sites, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11193, https://doi.org/10.5194/egusphere-egu2020-11193, 2020.

Knowledge of dynamics of forest productivity, expressed in terms of Growing Stock Volume (GSV), Net Primary Production (NPP), such derivatives like current increments (net and gross growth), is crucial for understanding the impacts of forest ecosystems on the major global biogeochemical cycles and eventually – on the Earth climate system. This knowledge is not satisfactory in Russia currently (the country’s forests cover >20% of the global forest area) because 1) data of official forest inventory are obsolete and substantially biased due to the fact that about 50% of Russian forests were inventoried more than 30 years ago; 2) of the above indicators, Russian forest inventory directly defines only GSV, but by the methods, which have substantial systematic errors of unknown size; 3) remote sensing methods themselves still cannot reliably provide some necessary details, like species composition, age and age structure of stands, below ground live biomass etc. In this presentation, we attempted to provide a systematic reanalysis of the estimates of the above indicators. To this end, a special system was developed to update the data of forest inventory for periods after the latest inventory by forest enterprises (about 1700) based on all available ground-based information and a multi-sensor concept of remote sensing. Hybrid forest cover was presented as an aggregation of 12 satellite products at spatial resolution of 150m. The updating of the main biometric indicators of Russian forests was based on the models of the growth and bioproductivity of modal stands. The results of the actualization have showed substantial overestimation of areas by official inventory and underestimation (up to 20%) of GSV. Comparison of obtained results with an independent assessment of the dynamics of areas and GSV, which was made by the Space Research Institute of the Russian Academy of Sciences for the period 2000-2017, showed a high level of compatibility. Using the results of actualization, live biomass was assessed based on a new system of conversion coefficients (Schepaschenko et al. 2018), NPP - on a method described in Shvidenko et al. (2007); and current increments – using a regionally distributed modelling system on increment dynamics of modal stands. Climate were analyzed for 3 periods: “historical” (1948-1975), “current”(1975-2017) and “future” (using all 4 scenarios RCP (2020-2100)). NPP and increments were estimated for the two last periods using a model, which takes into account selected climatic indicators and fertilization effect of enhanced CO2 concentration. It is shown that use of the obtained results presents substantial possibility for improvement of estimates of the carbon budget of Russian forests, particularly those received by inventory methods, and eliminate the existing discrepancies in estimates of the carbon budget of Russian forests reported in different publications. Projections for future suppose that significant part of Russian forests under “critical” scenarios (RCP6.0 and RCP 8.5) have a high probability to reach the tipping point by end of this century.

How to cite: Shvidenko, A., Schepaschenko, D., Bartalev, S., Krasovskii, A., and Platov, A.: Recent and future productivity of Russian forests under climate change, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10316, https://doi.org/10.5194/egusphere-egu2020-10316, 2020.

The SMEAR Estonia station was established in 2012 as southernmost “Station for Ecosystem-Atmosphere Relations” in Northern Europe. The station provides continuous data since 2014 and has steadily increased the amount of measured variables. Measurements cover atmospheric gases, air ions and particulate matter, radiation and energy fluxes, forest ecosystem and soil related parameters. 
Located in the hemiboreal forest ecosystem at the southern edge of the boreal forest biome the forests are characterised  by a mix between coniferous and broadleaved species. The SMEAR Estonia station’s location near to an old growth forest, which is the oldest Estonian forest nature reserve established in 1924, allows for comparisons of atmosphere-biosphere related processes between unmanaged and managed forests. The application of continuous multi-scale data allows us to see first trends of hemiboreal ecosystem-atmosphere interactions in relation to natural and man made disturbances and climatic drivers.
Here, we report and present our available multi-scale data and research results. Our focus lies on the heterogeneity and the dynamics of atmosphere-biosphere exchange processes and feedbacks in the footprint of the SMEAR Estonia station.

How to cite: Noe, S. M., Heikki, J., Mander, Ü., Hõrrak, U., Soosaar, K., Chen, X., Krasnova, A., Krasnov, D., Kollo, J., Komsaare, K., Lipp, H., Tamme, K., and Kangur, A.: Adding pieces to the atmosphere-biosphere feedback puzzle, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11155, https://doi.org/10.5194/egusphere-egu2020-11155, 2020.

Eddy-covariance (EC) method is widely used to calculate fluxes of different gases from different ecosystems. One of the assumptions is that the footprint of eddy tower is homogeneous in terms of plant species composition, height, age, soil properties, etc. In reality that is usually not the case: European forests are mostly managed and thus have compartments of tree species. This is even more so in the hemiboreal zone that is characterized by higher heterogeneity and tree species diversity. This results in the possibility for the individual features to have stronger influence on the eddy measurements. 

Two identical EC systems (LI-7200 gas analyser + Metek uStar Class A anemometer) were placed at 30m (EC30) and 70m (EC70) height on an atmospheric tower of SMEAR Estonia (Station for Measurements of Ecosystem Atmosphere Relations) above a 20m high forest to measure CO₂ fluxes. The footprints are represented by compartments of Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and Birch trees (Betula pendula and Betula pubescens) and clear-cut areas.

According to the EC30 flux data, the mixed hemiboreal forest ecosystem was a source of CO₂ (505 gC m^-2 in 2015;  333 gC m^-2 in 2016; 276 gC m^-2 in 2017; 603 gC m^-2 in 2018), while according to EC70 data it was a minor sink in some of the years (-47 gC m^-2 in 2015;   10 gC m^-2 in 2016; -142 gC m^-2 in 2017; 151 gC m^-2 in 2018).

Both the ecosystem respiration (ER) and the gross primary production (GPP) were bigger when estimated from EC30 than in EC70 for all the years:
GPP EC30: 1738 gC m^-2 in 2015; 1669 gC m^-2 in 2016; 1892 gC m^-2 in 2017; 1654 gC m^-2 in 2018;
GPP EC70: 1242 gC m^-2 in 2015;  1192 gC m^-2 in 2016; 1215 gC m^-2 in 2017; 988 gC m^-2 in 2018;
ER EC30:  2057 gC m^-2 in 2015; 1999 gC m^-2 in 2016; 1992 gC m^-2 in 2017; 2070 gC m^-2 in 2018;
ER EC70:  1088 gC m^-2 in 2015; 1120 gC m^-2 in 2016; 1019 gC m^-2 in 2017; 1021 gC m^-2 in 2018;  

All the 4 study years (2015-2018) showed similar difference patterns between the two heights: higher EC30 nighttime NEE values and similar daytime NEE values throughout the season. The peak difference between the two systems was in the end of August - middle of September for all the years. 

How to cite: Krasnova, A., Krasnov, D., and Noe, S.: One tower - two heights: A study of mixed hemiboreal forest carbon balance estimated from two eddy covariance systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11360, https://doi.org/10.5194/egusphere-egu2020-11360, 2020.

Based on the data of meteorological observations, executed in 2013-2019 at Research Station “Ice base Cape Baranova” (RS) and original algorithm, taken into account accuracy of measurements and footprints, the components of surface heat budget are calculated. It is shown that in winter due to radiation cooling turbulent sensible heat flux (H) directs to underlying surface. In summer H due to radiation heating of surface with low albedo directs to atmosphere and reaches 25% of the incoming short-wave radiation. The turbulent latent heat flux (LE) in winter directs to atmosphere. Its value is not more than 10% of H. During summer LE has no predominant direction. 

Comprehensive monitoring carried out at RS since 2013 allowed to examine the role of large-scale processes in the polar atmosphere and hydrosphere on the formation of local climate in the region. In 2016, 2018 and 2019 sea ice cover of the Barents and Kara Seas in October, the month of active freezing of active soil layer, occupied the minimal area starting 1978 year (http://wdc.aari.ru/datasets/d0042/). This circumstance along with peculiarities of circulation processes in the atmosphere had led to anomalous of temperature and humidity regimes of lower troposphere. These years monthly mean air temperature up to 700 hPa was about -4 °C compared to -7 - -11 °C in 2013 - 2015 and 2017. In 2016 the lower troposphere was warmer by 2 - 3 °C  and specific humidity in atmospheric boundary layer was 30–60% higher its values in 2013–2015 and 2017. Even in 2018, when the area of open water adjacent to the Severnaya Zemlya archipelago was significantly larger than in 2016, specific humidity at altitudes up to 3 km was 4-12 percents less.

In 2016 monthly mean wind speed, mainly of southwestern direction, reached maximum value, more than 7 m/s. It led to weakening of atmospheric surface layer stratification (z/L <0.2). The air specific humidity  significantly increased also, up to 3.0 and 2.7 g /kg at 2 meters and at z₀ . Long-wave radiation fluxes increased by more than 15 – 20 W/m². Same time due to increase of underlying surface temperature, its long-wave radiation cooling, which was not compensated by the increase of incoming long-wave radiation increased up to -27 W/m². H, directed to the underlying surface, increased to 10 W/m²  and LE, directed to atmosphere, increased almost 2 times, up to 12 W/m². As a result of multidirectional changes of heat fluxes, defining surface heat balance, its value in October 2016 (-31.6 W/m²) was comparable to calculated for other years.

The most probable explanation of the revealed features of atmospheric boundary and surface layers in October 2016 are the absence of sea ice cover in the waters, adjacent to the archipelago, prevented cooling of atmosphere, and strong zonal component of the wind velocity, caused the transfer of warm and moist air masses of Atlantic origin into the study area.

The work had been done under financial support of the Ministry of Science and Higher Education of the Russian Federation (project no. RFMEFI61619X0108).

How to cite: Makshtas, A., Makhotina, I., Kustov, V., Laurila, T., Bolshakova, I., Sokolov, V., and Tuovinen, J.-P.: Energy exchange between surface and atmosphere on the Severnaya Zemlya archipelago in 2013 – 2019 years, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8027, https://doi.org/10.5194/egusphere-egu2020-8027, 2020.

Northern rivers transport huge quantities of water and constituents from the continents to the Arctic Ocean. Characteristics of the transport mode of chemical flow are poorly monitored, and the existing estimates of river flux are characterized by high uncertainty. Since 2018, the monitoring campaign ArcticFlux has been sampling the 4 largest Siberian rivers (Ob, Enisey, Lena and Kolyma) multiple times per year at the most downstream river crossection selected as unaffected by river mouth processes (tides, surges etc).  Using Acoustic Doppler Current Profiler (ADCP) acquisitions with sediment depth profile sampling we build a simple model to derive the bed and suspended seasonal fluxes, grain size and particulate heavy metals distributions. Study demonstrates the significance of the hydraulic control for the metal partitioning within river as well as explains spatial (inter-basin) variations in particulate flux due to local hydrology, erosion rates and catchment lithology. Using (ADCP) acquisitions with sediment depth profile sampling of the Ob, Enisey, Lena and Kolyma, we aim to build a model to derive the annual flux of the sediments and particulate flux of the selected metals.  The datasets is also used to assess the uncertainties in selected sediment quantity and quality data, including contributions from vertical and crossectional variations into fluxes estimates including requirements for sampling strategy. Based on the modeling techniques and application of erosion models for all four Arctic catchments the project will also focus on the novel quantitative assessment of bank and catchment erosion contribution into chemical flux.

How to cite: Chalov, S. and Kasimov, N.: Novel comprehensive field-based monitoring dataset of largest Siberian river particulate flux into Arctic ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10424, https://doi.org/10.5194/egusphere-egu2020-10424, 2020.

Presented is a method for the estimation of a productivity class/site index of the forest regrowth after stand replacement natural and human induced disturbances. The method uses Global Forest Change project data on spatial distribution of forest loss sites (including the information about the date of the disturbance) with a 30 m resolution based on Landsat data. Joint analysis of this data resampled to 100 m spatial resolution together with a Russian Land Cover map for 2016 developed based on 100 m PROBA-V data is used to identify reforestation sites and to determine the forest type. Based on this information an appropriate forest growth model is chosen to simulate forest characteristics' dynamics for different site indexes. Finally information on forest characteristics from satellite data-based products is compared to the modeling results for the forest age, computed as a difference between the date of the disturbance and the date of the satellite data product. Reforestation site is assigned a productivity class that yields the best consistency between modeling results and existing satellite data products information.

Application of the presented method was tested over the European part of Russia using a 100 m global growing stock volume (GSV) map developed within Globbiomass project and lidar vegetation canopy height measurements from ICESat-2/ATLAS system (ATL08 data product). It was found that ICESat-2/ATLAS data is better suited for the proposed approach.

Presented method is aimed at the development of a reference dataset on forest parameters since obtained information on forest type, age and site index together can be used to estimate other crucial characteristics, including GSV, mean height, mean stem diameter, basal area, productivity, growth and mortality parameters, using the appropriate model. It is also worth mentioning that proposed approach allows estimation of characteristics of young forests which are rarely represented in the field survey-based reference datasets.

This work was supported by the Russian Science Foundation [grant number 19-77-30015]. Data processing and analysis was carried out using resources of the Centre for collective use ‘IKI-Monitoring’ developed by the Space Research Institute of the Russian Academy of Sciences.

How to cite: Zharko, V., Bartalev, S., and Bogodukhov, M.: A method for the assessment of forest regrowth site index based on Earth observations and modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20359, https://doi.org/10.5194/egusphere-egu2020-20359, 2020.

Measurements of ultrafine particle physico-chemical properties in the Arctic region were identified as an important aspect to better understand aerosol-cloud-climate interactions. Atmospheric new particle formation (NPF) is a phenomenon observed in many different environments around the world. Although, the frequency of atmospheric NPF event occurrences is expected to increase in the Arctic region due to sea ice melt (Dall´Osto, et al., 2017), there is only a limited number of studies that focus on nucleation mode particles in this remote environment; current knowledge is limited with respect to the chemical precursors of resulting nanoparticles and the compounds involved in their subsequent growth. Therefore, it is critical to understand the mechanism leading to their role as Cloud Condensation Nuclei (CCN).

Initial steps involved in NPF and subsequent growth are usually clustering and condensation of both organic and inorganic vapors, while ions are also known to be involved in the nucleation process. If newly formed particles are not lost due to coagulation and manage to grow to sizes > 50 nm, they can act as CCN. In particular, NPF have often been observed to be related to sulfuric acid (SA). However, the extent of sulphate production by biogenic sources, including biogenic dimethyl sulfide (DMS) and methanesulfonic acid (MSA), vs. the one due to anthropogenic SO₂ remains an outstanding issue especially in the Arctic troposphere. Biogenic organics in the Arctic Ocean possibly derived from both phytoplankton and terrestrial vegetation could significantly influence the chemical properties of Arctic aerosols (Choi et al., 2019). This coincides very well with MOSAiC’s Atmosphere major interdisciplinary focus on–dimethyl sulfide, a gas produced by metabolic processes in algae and other marine microorganisms, and which, as described has a role in complex chemical processes forming aerosols.

Here we present results from one season (May-August) of continuous measurements of particle volatility will be conducted by means of a custom made and well characterized nano-volatility tandem DMA (nano-VTDMA) system installed at Zeppelin station, Ny Aalesund Svalbard. The nano-VTDMA system consists of a medium DMA (M-DMA), a Nano-TD (IAST, Switzerland), a nano-DMA (TSI) and a CPC (TSI, 3776). The nano- VTDMA measurement cycle is typically arranged into three steps: First, a monodisperse particles fraction will be selected by the first M-DMA; four particle sizes are selected (i.e. 10, 25, 50, 80). Then, the selected particles pass through the thermal denuder (Model NanoTD), operated at four selected temperatures in the range from 30 ^oC to 250 ^oC. The residual particle number size distribution are measured by the second nano-DMA and the CPC (3776). Parallel DMPS measurements are also examined to identify the NPF events under study

We analyze the observed 12 events identified with fresh particle bursts and we take into account parallel measurements of tracer gases and Black carbon in order to provide the link to natural or anthropogenic emissions. The area of air mass origin is also used as a possible clarification on where these fresh particle originate from.

How to cite: Eleftheriadis, K., Gini, M., Mendes, L., Ondracek, J., Krejci, R., and Tørseth, K.: Potential mechanisms for New Particle Formation and growth from aerosol mixing state and volatility observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21798, https://doi.org/10.5194/egusphere-egu2020-21798, 2020.

Organic compounds are of high importance in the Arctic because they contribute between one and two thirds to the submicron aerosol mass and may be co-emitted or interact with other aerosol species, such as black carbon, sulfate and metals; they also act as a vehicle of transport for persistent organic pollutants to the Arctic. Organic-containing aerosols (OA) can both absorb and scatter light, thereby changing the radiative balance, and may act as cloud condensation nuclei. OA might become increasingly important in a warming Arctic due to anthropogenic activities and natural emissions, e.g., as a result of expanded vegetation, intensified wildfires, decreasing sea ice extent and thickness leading to higher release of marine volatile organic compounds, and thawing tundra soils (permafrost) along shores and rivers. The continuous monitoring of organic carbon along with a detailed chemical analysis to determine its natural and anthropogenic sources, seasonal variability and inter-annual evolution in the Arctic is of prime importance for improved climate simulations and a realistic assessment of the effectiveness of potential mitigation or adaptation actions.

The OA chemical composition and corresponding sources remain largely unknown, partly due to the challenging measurement conditions. For example, tremendous effort is required for the deployment of online aerosol mass spectrometry at various environments for long time periods. To overcome this challenge, an offline Aerodyne aerosol mass spectrometer (AMS) technique has been introduced based on re-aerosolized liquid filter extracts. The method is capable of covering broad spatial and seasonal observations as well as determining the sources of OA (e.g. primary versus secondary, biogenic versus anthropogenic). Within the project iCUPE (Integrative and Comprehensive Understanding on Polar Environments), we extend the coverage of this technique to the most climate change sensitive region worldwide, using year-long/multi-year (from 2014 to 2019) quartz fiber filter samples collected at 8 surface stations from 68° N to 83°N, covering six Arctic Council nations including the least investigated Siberian Arctic.

Here, we present a project overview and first results from filter water extracts nebulized in Argon and measured with a high-resolution Long-Time-of-Flight AMS (average resolution ~7k). Preliminary data suggest significant variability among different sites and seasons with regard to the relative fraction of fragments-markers of certain sources, indicating largely regionally-specific sources of OA across the Arctic land surface. For example, during the same time period we observed more (roughly 90%) and more strongly oxygenated fragments (especially mass to charge ratio m/z 44) at extremely remote sites. Our average f_CO2 (m/z=44) of 0.26 ± 0.08 and CO⁺:CO₂⁺ of 0.40 ± 0.14 both indicate more oxidized OA than in continental aerosols. The Van Krevelen diagram shows that the addition of carboxylic acid groups (or alcohol+carbonyl on different C atoms) with significant fragmentation may dominate the OA oxidation at high O:C. We further discuss the integration of this analysis with advanced statistical tools for factor identification on the OA fraction. Additionally, the samples will be characterized with ultra-high-resolution mass spectrometry coupled with liquid chromatography, for a two-dimensional molecular identification of primary aerosol tracers and secondary organic aerosol precursors.

How to cite: El Haddad, I., Moschos, V., Schmale, J., Baltensperger, U., and Prévôt, A. S. H.: Characterization of organic aerosol across the Arctic land surface, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8216, https://doi.org/10.5194/egusphere-egu2020-8216, 2020.

The Siberian forests cover about 70% of the total area of the Eurasian boreal forest and are an important factor controlling global and regional climate. Forest fires and biogenic emissions from coniferous trees and forest litter are the main sources of carbonaceous aerosols emitted into the atmosphere over boreal forests. Typically, two classes of carbonaceous aerosol are commonly present in ambient air – elemental carbon (EC) (often referred to as black carbon or soot) and organic carbon (OC). Both OC and EC are important agents in the climate system, which affect the optical characteristics and thermal balance of the atmosphere both directly, by absorbing and scattering incoming solar radiation, and indirectly, by modifying cloud properties.

In 2010, a filter-based sampler was mounted at the background ZOTTO station (60.8º N and 89.4 º E; 114 m a.s.l.) for aerosol chemical analysis. We present here the time series of carbonaceous aerosol data measurements for 10 years (2010 -2019). We investigate the seasonal variations in PM, EC, and OC. These data are supplemented by measurements of aerosol absorption (PSAP) and scattering (TSI 3563) coefficients.  We analyze polluted, background and near-pristine periods, as well as the most pronounced pollution events and their sources, observed over the entire sampling campaign.

We also present ground-based measurements of aerosol-cloud condensation nuclear (CCN) properties and hygroscopicity parameter values obtained from the CCN dataset.  A method for assessing the condensation properties of aerosols from satellite measurements based on the data of the VIIRS multichannel radiometer installed on the polar satellite Suomi (USA) has been implemented. The CCN parameters of aerosol particles determined from satellite datasets have been compared with those obtained from ground-based measurements.

Acknowledgments. This work was supported by the Russian Science Foundation (grant agreement no. 18-17-00076) and Max Planck Society (MPG).

How to cite: Mikhailov, E., Ivanova, O., Vlasenko, S., Nebos’ko, E., Andreae, M., and Pöschl, U.: Long-term measurements (2010–2019) of carbonaceous aerosol at the Zotino Tall Tower Observatory (ZOTTO) in central Siberia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4908, https://doi.org/10.5194/egusphere-egu2020-4908, 2020.

Undoubtedly, urbanization level has been rising rapidly during last decades, and due to growth in the number of industries the amount of anthropogenic aerosols and gases as pollution has been increasing. Some pollutants influence humans` health when others lead to changes in different meteorological parameters. In this study the aerosols influence on selected meteorological parameters (air temperature at 2 m, specific humidity, total cloud cover, precipitation) as well as anthropogenic SO2 and SO4 atmospheric dispersion and deposition on water bodies during January and August of 2010 were evaluated using the Enviro-HIRLAM online integrated modelling system. We focused on territories of the North-West Russia (with zooming to St. Petersburg, Moscow and Helsinki) and on territories of the Kola Peninsula and Northern European countries. Four model runs were performed: CTRL (no aerosols effects), DAE (direct aerosols effect), IDAE (indirect aerosols effect) and DAE+IDAE (direct + indirect aerosols effects).

Aerosol influence was stronger during Aug 2010. DAE basically lead to decrease in air temperature at 2 m and total cloud cover. IDAE and DAE+IDAE increased these parameters. DAE decreased specific humidity in Jan and increased in Aug 2010. IDAE and DAE+IDAE increased that parameter in Jan 2010 and decreased in Aug 2010. All aerosol effects caused reduction in precipitation for both months. With zooming to the metropolitan areas, in Aug 2010, DAE decreased air temperature in St. Petersburg and Helsinki, but increased in Moscow. IDAE decreased temperature in St. Petersburg and increased in other cities. DAE+IDAE decreased air temperature in St. Petersburg and Helsinki, but increased in Moscow. DAE decreased total cloud cover in three cities when IDAE and DAE+IDAE increased. All effects led to decrease in specific humidity and precipitation for territories of three cities. DAE decreased all analyzed parameters in three cities in Jan, except for precipitation in St. Petersburg. IDAE and DAE+IDAE caused growth in all parameters, except for precipitation in Helsinki and for temperature in Moscow (DAE+IDAE).

The analysis of the modeled SO2 spatial-temporal distribution showed that the number of cases with transboundary pollution on the territory of Northern Europe was higher during Aug 2010. An anticyclonic circulation led to high concentrations of SO2 over its sources during the same period. SO2 concentration reached its maximum values with periods of highest air temperatures quite often. It was revealed that the ambient air standard for SO2 was exceeded 13 times during a whole period studied. Only once SO2 concentration was excessed on the territory of Norway (Kirkenes) and the rest - on the territory of the Kola Peninsula (Russia). For the sulphates’ wet deposition, the number of such cases as well as values were higher during Aug 2010. For Norther Europe countries, the maximum of deposited sulphates was observed on the territory of Finland, and the minimum - over Sweden.

How to cite: Nerobelov, G., Sedeeva, M., Mahura, A., Nuterman, R., and Smyshlyaev, S.: Enviro-HIRLAM modeling of atmospheric aerosols and pollution transport and feedbacks: North-West Russia and Northern Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-201, https://doi.org/10.5194/egusphere-egu2020-201, 2020.

Trace metal and nutrient fluxes into Arctic ocean by largest Siberian rivers (ArcticFlux)

Precise estimates of river runoff are one the most challenging fields of river hydrology. Quantitative assessment of the fluxes of suspended and, especially, bed load, as well as their correlation with the flow dissolved loads remains weekly studied with a crucial need of in-situ observations, especially in large rivers.

The project is focused on semi-empirical and modeling study of flows, concentrations, modes and loads of trace metals and nutrients fluxes of the major rivers of Arctic. Monitoring stations were organized at the outlets of largest Siberian rivers: Ob, Yenisei, Lena, Kolyma, which transport more than 60 % of the water flow from the Russian Arctic. Observations were made for high and low water regime periods on the regular basis, and the total number of samples today exceeds 210. For each sample analyses were made for trace metals (68 elements), nutrients and dissolved and suspended organic carbon matter content both in dissolved and particulate (suspended and bed loads) forms. These samples can determine annual and seasonal distribution to 70% of the chemical elements and substances, carried by large rivers of the Russian Arctic into the Arctic Ocean.

For more accurate flux assessment, a new sampling technique was used. It allows to determine all components of the dissolved, suspended and, especially, bed load along the river section and includes sampling at 3-5 verticals on different depth. As a result, it is possible to determine the variability of the fluxes along the width of the section. As an example, concentrations of suspended sediments on the left and right banks of the Kolyma River differ in 6-7 times (up to70 mg / dm³) and there are significant differences in Ni, Fe, Al, Cu, and Pb fluxes. Heterogeneity in the distribution of sediment and chemical flow across the width of the rivers arise due to the inflow of tributaries and as a result of permafrost melting and wave erosion of the banks. The study of the intensity of bank erosion and sedimentation at the outlets of Arctic rivers both in the field and according to remote sensing data is a significant part of the project. Based on the modeling techniques and application of erosion models for all four Arctic catchments it will also focus on the novel quantitative assessment of bank and catchment erosion contribution into chemical and sediment loads.

The project concept is considered as a part of Marine component of Pan-Eurasian program (PEEX) and builds a bridge to integrate PEEX marine components with the existing terrestrial/atmospheric PEEX

The reported study was funded by RFBR according to the research project 18-05-60219

How to cite: Efimov, V., Chalov, S., Magritsky, D., Tsyplenkov, A., Efimova, L., and Kasimov, N.: Trace metal and nutrient fluxes into Arctic ocean by largest Siberian rivers (ArcticFlux), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21193, https://doi.org/10.5194/egusphere-egu2020-21193, 2020.

In recent years, satellite methods have played an important role in CO₂ monitoring. Various satellite instruments (SCIAMACHY, AIRS, GOSAT, OCO-2, etc.) validated by ground-based and aircraft measurements allow to retrieving the column averaged CO₂ mixing ratio (X_CO2) with high accuracy (0.25–1.0%). The relatively high spatial resolution of a number of instruments (for example, OCO-2) allows studies of spatial and temporal CO₂ variations, that, under appropriate conditions, makes it possible to estimate anthropogenic emissions from different cities.

Various techniques (source pixel mass balance method, plume dispersion model and atmospheric inversion system) for determining anthropogenic greenhouse gas emissions from data of satellite measurements are considered.

On the basis of three-dimensional modeling and comparison with the results of various local and remote measurements, numerical models of the atmosphere were adapted to different megacities of Russia. Based on numerical experiments, the errors of various satellite techniques for determining emissions caused by various factors (measurement errors, quality of used a priori and additional experimental information, adequacy of used numerical atmospheric model, etc.) were evaluated. Anthropogenic CO₂ emissions in St. Petersburg, Moscow and other cities of Russia are estimated using various satellite measurements. These estimates of anthropogenic emissions are compared with data obtained by different methods and for different cities.

How to cite: Timofeyev, Y., Nerobelov, G., Smyshlyaev, S., Berezin, I., Virolainen, Y., Makarova, M., Poberovsky, A., Polyakov, A., and Foka, S.: Estimates of anthropogenic CO2 emissions from satellite and ground based measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2580, https://doi.org/10.5194/egusphere-egu2020-2580, 2020.

The continuous ground-based measurements of greenhouse gases carried out in Siberia in the past two decades allowed the long-term trends, as well as the diurnal and seasonal cycles of CO₂ and CH₄ to be derived for this poorly studied region (Belikov et al., 2019). To date, these in-situ observations are made at the joint Japan-Russia Siberian Tall Tower Inland Observation Network (JR-STATION) consisted of 6 automated stations that should be maintained several times per year. In late October to early November 2018, we have undertaken the first mobile campaign to derive a distribution of CO₂ and CH₄ concentrations at high spatial resolution while traveling to the sites of the above network. For that, we used a commercially available GHG CRDS analyzer (G4301, Picarro Inc., Santa Clara, CA, USA) installed in an off-road vehicle (Arshinov et al., 2019). Over one trip, the instrument were driven over 7000 km throughout the study area.

In March, June, August, and October 2019 we have performed four more campaigns along the same route. This enabled the seasonal pattern of CO₂ and CH₄ concentrations to be obtained over a huge area of West Siberia between 54.5° and 63.2° north latitude and between 62.3° and 85.0° east longitude, as well as to reveal a large- and small-scale spatial heterogeneity in CH₄ mixing ratios particularly over wetland regions. We plan to continue mobile campaigns to cover interannual variations.

This work was supported by the Ministry of Science and Higher Education of the Russian Federation under State Contract No. 14.616.21.0104 (ID No RFMEFI61618X0104).

Belikov, D.; Arshinov, M.; Belan, B.; Davydov, D.; Fofonov, A.; Sasakawa, M.; Machida, T. Analysis of the Diurnal, Weekly, and Seasonal Cycles and Annual Trends in Atmospheric CO₂ and CH₄ at Tower Network in Siberia from 2005 to 2016. Atmosphere 2019, 10, 689.

Arshinov, M.Yu.; Belan B.D.; Davydov D.K.;  Kozlov A.V., Fofonov A.V., and  Arshinova V. Heterogeneity of the spatial distribution of CO₂ and CH₄ concentrations in the atmospheric surface layer over West Siberia: October-November 2018, Proc. SPIE 11208, 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 1120831 (18 December 2019);https://doi.org/10.1117/12.2539205

How to cite: Arshinov, M., Belan, B., Davydov, D., Kozlov, A., Fofonov, A., and Arshinova, V.: Studying the spatial and seasonal variability of greenhouse gases across West Siberia: large-scale mobile measurement campaigns of 2018-2019, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3218, https://doi.org/10.5194/egusphere-egu2020-3218, 2020.

This research aims at the solution of environmental problems related to sustainable and economically efficient development of the North, which could enhance the quality of life and health of the population in the changing Russian Arctic. The medical geographic modeling of spatiotemporal patterns of naturally determined diseases is based on the detailed database covering the Arctic zone of Russia. The role of factors affecting the spread of diseases is unequal, with the climatic factor regarded as the most significant at all levels of territorial differentiation. At the highest (national) level, this factor determines the latitudinal zoning, which, in turn, determines the existence conditions of disease hosts and vectors and, ultimately, the foci of diseases. At regional level, the effect of climate is traced in monthly mean temperatures, temperature extremes, precipitation, snow depth, length of no-frost period, etc. Changes of these characteristics influence the poikilothermic (cold-blooded) arthropods, as well as the pathogens spending a part of their life cycles in the arthropods’ organisms. Another important factor is related to water resources, particularly, water-table height and ecological state of water bodies. Comparative analysis of hydrological and hydrochemical data, and their total impact on morbidity rates in terms of pathogenicity eco-indices, can serve as an additional tool for detecting the critical infection areas and population early warning. The original methodology is applied to evaluate the actual medical environmental situation, to forecast possible spatiotemporal changes in morbidity, including due to the most virulent infections, and to elaborate recommendations to public health authorities on planning the preventive and health-improving activities in the Arctic.

How to cite: Malkhazova, S., Orlov, D., and Bashmakova, I.: Medical geographic modeling of spatiotemporal changes of naturally determined diseases under the changing climate and economic development of the Russian Arctic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10235, https://doi.org/10.5194/egusphere-egu2020-10235, 2020.

Russian forest is a factor of global importance for implementation of international conventions on climate considering its potential for absorption and accumulation of the atmospheric carbon at an impressive scale. Considering recently adopted Paris agreement on climate the comprehensive and accurate estimation of Russian forests’ carbon budget became a top priority research and development issue on national agenda. However existing quantitative estimates of Russian forests’ carbon budget are of significant level of uncertainty. One of the most obvious reasons for such uncertainty is not sufficiently reliable and up-to-date information on characteristics of forests and their dynamics.

The Russian Science Foundation has supported an ambitious research megaproject titled “Space Observatory for Forest Carbon” (SOFC) started in year 2019 and aimed at the development of a new concept and comprehensive methods for forest carbon budget monitoring using Earth observation data and forest growth and dynamics models. The main SOFC project objectives are as follows:

- Development of a new concept and methodology for Russian forests and their carbon budget monitoring based on the integration of remote sensing and ground data along with improved models of forest structure and dynamics;

- Development of new annually updated GIS databases on the characteristics and multi-annual dynamics of Russian forests;

- Development of an informational system and technology for the continuous monitoring of Russian forests’ carbon budget.

Information necessary for carbon budget estimation includes data on various land cover types, forest characteristics (growing stock volume, species composition, age, site-index) and ecological parameters (Net Primary Production, heterotrophic respiration). Data on natural (fires, diseases and pests, windstorm, droughts) and anthropogenic (felling, pollution) forest disturbances causing deforestation, as well as information on subsequent reforestation processes are also vital.

The existing remote sensing methods can provide significant part of missing country-wide information about the land cover types and forest characteristics for the national-scale carbon budget estimation and monitoring. Multi-year time series of this data since the beginning of the century allow modelling the forest dynamics and its biophysical characteristics. The Earth observation data derived information on forest fires’ impact includes burnt area mapping over various land cover types as well as forest fire severity assessment allowing characterisation of fire induced carbon emissions. Furthermore, developed methods for processing and analysis of multi-year satellite data time series enable detection of forest cover changes caused by various destructive factors making it possible to substantially improve the accuracy of carbon budget estimation.

Obtained information on forest ecosystems’ parameters is used to improve existing and develop new approaches to forest carbon budget estimation, as well as to simulate various scenarios of Russian economy development depending on forest management practices and climate change trajectories.

This work was supported by the Russian Science Foundation [grant number 19-77-30015].

How to cite: Bartalev, S.: Space Observatory for carbon budget monitoring in Russian forests using Earth observations and modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20567, https://doi.org/10.5194/egusphere-egu2020-20567, 2020.

Climate change is proceeding fastest in the Arctic region. During past years Arctic summers have been warmer and drier elevating the risk for extensive forest fire episodes. In fact, satellite observations show, that during past two summers (2018, 2019) an increase is seen in the number of fires occurring above the Arctic Circle, especially in Siberia. While human-induced emissions of long-lived greenhouse gases are the main driving factor of global warming, short-lived climate forcers or pollutants emitted from the forest fires are also playing an important role especially in the Arctic. Absorbing aerosols can cause direct arctic warming locally. They can also alter radiative balance when depositing onto snow/ice and decreasing the surface albedo, resulting in subsequent warming. Aerosol-cloud interaction feedbacks can also enhance warming. Forest fire emissions also affect local air quality and photochemical processes in the atmosphere. For example, CO contributes to the formation of tropospheric ozone and affects the abundance of greenhouse gases such as methane and CO₂.

This study focuses on analyzing fire episodes in the Arctic for the past 10 years, as well as investigating the transport of forest fire CO and smoke aerosols to the Arctic. Smoke plumes and their transport are analyzed using Absorbing Aerosol Index (AAI) from several satellite instruments: GOME-2 onboard Metop A and B, OMI onboard Aura, and TROPOMI onboard Copernicus Sentinel-5P satellite. Observations of CO are obtained from IASI (Metop A and B) as well as from TROPOMI, while the fire observations are obtained from MODIS instruments onboard Aqua and Terra, as well as from VIIRS onboard Suomi NPP.  In addition, observations e.g. from a space-borne lidar, CALIPSO, is used to obtain vertical distribution of smoke and to estimate plume heights.

How to cite: Sundström, A.-M., Karppinen, T., Arola, A., Sogacheva, L., Lindqvist, H., de Leeuw, G., and Tamminen, J.: Satellite-Based Analysis of Fire Events and Transport of Emissions in the Arctic , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18506, https://doi.org/10.5194/egusphere-egu2020-18506, 2020.

Stable isotopes of oxygen and hydrogen in precipitation (δ¹⁸O_P, δ²H_P, d-excess) are valuable hydrological tracers linked to ocean-atmospheric processes such as moisture source, storm trajectory, and seasonal temperature cycles. However, characteristics of δ¹⁸O_P, δ²H_P and d-excess and the processes governing them are yet to be quantified across the Arctic due to a lack of long-term empirical data. The Pan-Arctic Precipitation Isotopes Network (PAPIN) is a new coordinated network of 24 stations aimed at the direct sampling, analysis, and synthesis of precipitation isotope geochemistry in the north. Our ongoing event-based sampling provides a rich spatial dataset during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (“MOSAiC”) expedition and new insight into coupled climate processes operating in the Arctic today. To date, precipitation δ¹⁸O and δ²H data (2018-2019) exhibit pronounced spatial and seasonal variability that broadly conforms to theoretical and observed understanding: (1) decreasing δ¹⁸O_P/ δ²H_P with increasing latitude and elevation, (2) decreasing δ¹⁸O_P/ δ²H_P with increasing continentality, and (3) increasing δ¹⁸O_P/ δ²H_P with increasing SAT. However, event-based sampling reveals remarkable variability among these relationships. For example, our observed Arctic mean summer -latitude slope of -0.3‰/degree of latitude is 50% smaller than the annual latitude effect in the mid-latitudes (-0.6‰/degree). This rate decreases to -0.1‰/degree of latitude in Finland and Russia, while in Alaska and northern Canadian a -0.7‰/degree latitudinal rate is observed. Similarly, we observe marked spatial differences in mean δ¹⁸O-temperature coefficients. Using back-trajectory analysis, we attribute these nuances to divergent moisture sources and transport pathways into, within, and out of the Arctic, and demonstrate how atmospheric circulation processes drive changes in isotope geochemistry and climate that are linked to sea ice concentration. For example, Alaska moisture derived from the North Pacific Ocean, Sea of Okhotsk, and the Bering Sea remains relatively enriched in ¹⁸O_P/²H due to higher sea surface temperatures, whereas moisture originating from ice-covered seas to the north is characterized by relatively depleted values. This is the first coordinated network to quantify the spatial patterns of isotopes in precipitation, simultaneously, across the entire Arctic. In combination with a Pan-Arctic network of continuous water vapor isotope analyzers, our process-level studies will resolve the patterns and processes governing the δ¹⁸O, δ²H and d-excess values of the Arctic water cycle during the MOSAiC expedition and beyond.

How to cite: Mellat, M., Bailey, H., Mustonen, K.-R., Marttila, H., Akers, P. D., Klein, E. S., and Welker, J. M. and the PAPIN: Precipitation isotope (δ¹⁸O, δ²H, d-excess) seasonality across the Pan-Arctic during MOSAiC, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13853, https://doi.org/10.5194/egusphere-egu2020-13853, 2020.

The presented study is aimed to estimate the probability of black carbon transportation from large forest wildfires in Russian boreal taiga occurred in the summer 2019 to Arctic region and to estimate its deposition to ice surface and contribution to shortwave radiative forcing.

The extreme forest fires were observed in 2019 over the territories of Krasnoyarskiy region and Yakutia republic. The Russian Informational Remote monitoring System of the Federal Forestry Agency provides data on the areas of forest lands damaged by different types of fires. These data were used to choose ten most intensive and ten most continuous fires for each region. Estimation of fuel mass available for combustion including biomass, litter and deadwood were made using the growing stock data of the State Forestry Register differentiated for the regions of the Russian Federation applying country specific conversion coefficients [Schepaschenko et al. 2018]. Emission of black carbon from forest fires was carried out using the methodology and combustion coefficients from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories and the coefficient of black carbon emissions from Akagi et al. [2011].

The main factor determining the transfer of particles is the synoptic situation. Blocking anticyclones and cyclonic series affects the circulation regime and conditions for the transport of particles to the Arctic. For these regions climatic frequency of occurrence of Southern and South-Western winds in summer is about 30-40%. The probability of atmospheric trajectory transfer from each chosen fire event to the Arctic region was estimated by the trajectory model HYSPLIT, also real synoptic data for each chosen fire event were used to analyze the probability of emission cloud transfer to northern latitudes.

The black carbon effect including concentrations in the atmosphere, deposition on the ice surface, modification of surface albedo in the ice region of Arctic and influence of additional radiation forcing associated with BC emissions from forest fires were estimates using the climate model INMCM5 [Volodin et a.l., 2017]. Aerosol sources, advection, gravitational sedimentation, surface absorption, and scavenging by precipitation are taken into account to compute aerosol concentration variations. Radiation forcing caused by BC emission from forest fires was calculated using the SNICAR model.

The study is supported by RFBR project No.18-05-60183.

REFERENCES

Volodin E. M., Mortikov E. V., Kostrykin S. V., Galin V. Ya., Lykossov V. N., Gritsun A.S., Diansky N. A., Gusev A. V., Yakovlev N.G. Simulation of the present-day climate with the climate model INMCM5, Climate Dynamics, 2017, doi:10.1007/s00382-017-3539-7.

2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 4: Agriculture, Forestry and Other Land Use (IPCC, 2006

K. Akagi, R. J. Yokelson, C. Wiedinmyer, M. J. Alvarado, J. S. Reid, T. Karl, J. D. Crounse, and P. O. Wennberg, “Emission factors for open and domestic biomass burning for use in atmospheric models,” Atmos. Chem. Phys. 11 (9), 4039–4072 (2011).

Schepaschenko D., Moltchanova E., Shvidenko A., Blyshchyk V., Dmitriev E., Martynenko O., See L., Kraxner F. (2018) Improved Estimates of Biomass Expansion Factors for Russian Forests // Forests. – 9, 312. P. 1-23. – https://doi.org/10.3390/f9060312

How to cite: Ginzburg, V., Kostrikin, S., Korotkov, V., Revokatovа, A., Polumieva, P., Chernenkov, A., and Zelenova, M.: Estimation of possible impact of black carbon emissions from 2019 large Siberian forest wildfires on the Arctic region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13095, https://doi.org/10.5194/egusphere-egu2020-13095, 2020.

Methane (CH4) is one of the most important greenhouse gases, but unexpected changes in atmospheric CH4 budgets over the past decades emphasize that many aspects regarding the role of this gas in the global climate system remain unexplained to date. With emissions and concentrations likely to continue increasing in the future, quantitative and qualitative insights into processes governing CH4 sources and sinks need to be improved in order to better predict feedbacks with a changing climate. Particularly the high northern latitudes have been identified as a potential future hotspot for global CH4 emissions, but the effective impact of rapid climate change on the mobilization of the enormous carbon reservoir currently stored in northern soils remains unclear.

Process-based modelling frameworks are the most promising tool for predicting CH4 emission trajectories under future climate scenarios. In order to improve the insights into CH4 emissions and their controls, the land-surface component of the Max Planck Earth System model, JSBACH, has been upgraded in recent years. In this context, a particular focus has been placed on refining important processes in permafrost landscapes, including freeze-thaw processes, high-resolution vertical gradients in transport and transformation of carbon in soils, and a dynamic coupling between carbon, water and energy cycles. Evaluating the performance of this model, however, remains a challenge because of the limited observational database for high Northern latitude regions.

In the presented study, we couple methane flux fields simulated by JSBACH to an atmospheric inversion scheme to evaluate model performance within the Siberian domain. Optimization of the surface-atmosphere exchange processes against an atmospheric methane mixing-ratio database will allow to identify the large-scale representativeness of JSBACH simulations, including its spatio-temporal variability in the chosen domain. We will test the impact of selected model parameter settings on the agreement between bottom-up and top-down techniques, therefore highlighting how sensitive regional scale methane budgets are to dominant processes and controls within this region.

How to cite: Goeckede, M., de Vrese, P., Brovkin, V., Koch, F.-T., and Roedenbeck, C.: Coupling bottom-up process modeling to atmospheric inversions to constrain the Siberian methane budget, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10833, https://doi.org/10.5194/egusphere-egu2020-10833, 2020.

The Arctic is a critical area in terms of global warming. Not only are the rising temperatures already causing changes in the natural conditions of this region, but the high potential of increased methane (CH₄) regional emissions are also likely to intensify global warming even stronger in the near term.

This future effect consists in the thawing and destabilization of inland and sub-sea permafrost that enhance the release of methane into the atmosphere from extensive CH₄ and organic carbon pools which have so far been shielded by ice and frozen soil. Moreover, the high latitude regions are already playing a key role in the global CH₄-budget because of such large sources as wetlands and freshwater lakes in addition to human activities, predominantly the fossil fuel industry of the Arctic nations.

However, the level of scientific understanding of the actual contribution of Arctic methane emissions to the global CH₄-budget is still relatively immature. Besides the difficulties in carrying out measurements in such remote areas, this is due to a high inhomogeneity in the spatial distribution of methane sources and sinks as well as to ongoing changes in hydrology, vegetation and carbon decomposition.

Therefore, the aim of this work is to reduce the uncertainties about methane sources and sinks in the Arctic region during the most recent years by using an atmospheric approach, in order to improve the quality of the assessment of the local and global impacts.

To do so, the data of atmospheric CH₄ concentrations measured at about 30 stations located in different Arctic nations have been analysed in regard to the trends, seasonal fluctuations and spatial patterns that they demonstrate as well as their link to regional emissions.

How to cite: Wittig, S., Berchet, A., Paris, J.-D., Arshinov, M., Machida, T., Sasakawa, M., Worthy, D., and Pison, I.: Assessment of CH4 sources in the Arctic using regional atmospheric measurements and their link to surface emissions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16584, https://doi.org/10.5194/egusphere-egu2020-16584, 2020.

Pan-Eurasian Experiment (PEEX) Programme (www.atm.helsinki.fi/peex) initiated in 2012 is an asset for INAR at the University of Helsinki and its co-partners to have high international visibility, to attract further research collaboration and to upscale the scientific impact in various arenas. The PEEX is interested in the northern high latitudes (Arctic, boreal) and on China and the new Silk Road Economic Belt regions. The PEEX scientific focus is on understanding of large-scale feedbacks and interactions between the land -atmosphere - ocean continuum under the changing climate of the Northern high latitudes and at the Arctic (Kulmala et al. 2015, Lappalainen et al. 2014; 2015; 2016; 2018, Vihma et al. 2019, Alekseychik et al. 2019, Kasimov et al. 2018) and on the transport and transformation of air pollution in China. PEEX research results have been published the PEEX Special Issue in J. Atmospheric Chemistry and Physics (www.atmos-chem-phys.net/special_issue395.html), in the Journal “Geography, Environment, Sustainability” (ges.rgo.ru/jour) and in the J. Big Data (journalofbigdata.springeropen.com).  In 2019 PEEX started comprehensive analysis on the first results over last five years based on the published peer review papers and results attained from the PEEX geographical domain.  The aim of the analysis is to study the state-of-the-art research outcome versus the PEEX large-scale research questions addressed by the Science Plan (Lappalainen et al. 2015). To facilitate the direct input from the research community, we have asked researchers to answer to a form where they could list their main scientific results and activities considered relevant to PEEX region and also include ancillary information such as type of activity or geographical extend. The preliminary metadata database covers information from over 400 scientific papers and the analysis is in progress. The key gaps of current understanding and future research needs will be discussed from the system point of view, from the land ecosystems, atmosphere, ocean & river systems and society perspectives and preliminary results will be introduced at EGU PEEX session.

How to cite: Lappalainen, H., Kerminen, V.-M., Altimir, N., Mahura, A., Ezhova, E., Vihma, T., Uuotila, P., Chalov, S., Konstantinov, P., Archinov, M., Qui, Y., Ezau, I., Kukkonen, I., Melnikov, V., Ding, A., Baklanov, A., Kasimov, N., Guo, H., Bondur, V., and Petäjä, T. and the Hanna Lappalainen: Pan-Eurasian Experiment (PEEX) Programme – Overview on the recent results , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7740, https://doi.org/10.5194/egusphere-egu2020-7740, 2020.

The Digital Belt and Road program, the DBAR, is aiming to resolve the scientific understanding of the Earth changes, and sustainable development goals along the Belt and Road regions (B&R), which was initiated in 2016, and now have been developing into its 1^st phase of implementation plan after the startup phase. With a strong collaboration and common interest, the Pan-Eurasia experiment the PEEX, and DBAR is crossed together to use the Earth observations to understanding and address the challenges for the environmental changes, especially for the Belt and Road in Asia about the changing of snow and ice, vegetation and ecosystem, disaster, urban, agriculture, water stress and etc.

With the development of the Earth Observations, either from the ground observations or the space/air borne platform, the Big Earth Data approach has been developing for addressing the societal and science challenges for the PEEX and DBAR common domain, with the eight working group efforts, and its potential contribution to the working efforts for the PEEX. In this talk, we will describe the Big Earth Data, societal challenges, its platform development, and more focus will be put in the snow and ice, urban, environment, disaster, and water as the priorities for the cross feralization with PEEX.

How to cite: Qiu, Y., Guo, H., Liu, J., Chen, F., and Menenti, M.: Big Earth Data enhance the Implementation of PEEX along the Belt and Road regions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5359, https://doi.org/10.5194/egusphere-egu2020-5359, 2020.

Climate extremes are of the major concern in the global context, since they can result in significant financial and human losses. The scale of heat wave (HW) impacts highlights the necessity to be able to measure extreme events in an informative manner, which is suitable for the geographical region and the climatic fields. Recent climatic projections show increasing in the frequency, magnitude, and duration of temperature extremes. It makes very important to determine appropriate metrics of heat / cold waves, and in particular, under climate change conditions. But to date there is no one universally acceptable heat wave definition. Because of the range of social groups and economy sectors affected by heat waves it is, of course, impossible to obtain a single index that is appropriate across each group and can be calculated from readily available climatological data.

This research therefore has the aim to calculate some absolute and relative heat wave indices for the reference period 1981-2010 to provide a comparison spatial-temporal distribution of the HW indices over territory of Ukraine according to the recommendation of WMO 2015 Technical Regulations.

The selected methodology for the heat waves investigation at this stage is based on the absolute indices proposed by Fischer  and Schar (2010), Perkins and Alexander (2012): HWM (average magnitude of all summertime heat waves), HWA (hottest day of hottest summertime event), HWN (yearly number of heat waves during summertime), HWD (length of the longest summertime event) HWF (sum of participating heat wave days in the summertime season, which meet the HW definition criteria over a 30-day interval).  Also, relative indices (Heat Wave Magnitude Index (HWMI), Russo et al. 2014 and Heat Wave Magnitude Index daily (HWMId), Russo et al. 2015) were used for the research.

Thereby, in this research 5 absolute indices and 2 relative indices for 50 weather stations of the meteorological network of the Ukrainian Hydrometeorological Centre for the summer months of the reference period 1981-2010 were calculated.

It was found that for the almost all the territory of Ukraine, the anomalies of all absolute heat wave indices in 2010 (compared to the reference period 1980-2010) were clearly noticeable. However, the analysis of the heat wave 2010 showed that a certain multicollinearity is inherent to the absolute indices calculated. The results of the statistical estimation showed that using all five heat wave indices is not necessary. In our opinion, only HWN, HWF and HWM are sufficient for the HW characteristic.

The calculated relative heat waves indexes are sufficiently sensitive to the minor changes of the daily maximum air temperature. It was found HWMId is the most sensitive between the studied indices. Therefore, on our opinion HWN, HWF, HWM and HWMId indices are the most applicable for the investigation of heat waves over the territory of Ukraine.

How to cite: Kostyrko, I., Snizhko, S., Shevchenko, O., Oliynyk, R., Svintsitska, H., and Mahura, A.: Investigation of the different heat waves indices applicability for the territory of Ukraine, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13662, https://doi.org/10.5194/egusphere-egu2020-13662, 2020.

The boreal and arctic zone of Siberia represents a «hot spot» area in the global Earth climate system, containing large and potentially vulnerable carbon stocks as well as considerable carbon dioxide (CO₂) and methane (CH₄) exchange fluxes with the atmosphere. Up to the recent time Siberian region was only sparsely covered by carbon flux measurements. Solely in the frame of EU-funded projects «Eurosiberian Carbonflux» and «Terrestrial Carbon Observing System – Siberia» (TCOS-Siberia) between 1998 and 2005 several atmospheric and terrestrial ecosystem stations were operational in European Russia and Siberia.

Since 2006, in order to monitor long-term biogeochemical changes, the Zotino Tall Tower Observatory (ZOTTO; www.zottoproject.org), a research platform for large-scale climatic observations, is operational in Central Siberia (60°48' N, 89°21' E) about 20 km west of the Yenisei river. Observatory consists of a 304-m tall mast for continuous high-precision measurements of greenhouse gases, meteorology and multitude of aerosol properties in the planetary boundary layer (PBL). Sampling of the PBL is essential for the «top-down» approach in observation strategy, since it minimizes local effects and permits to capture regional concentration signals. Such measurements are used in atmospheric inversion modelling to estimate sinks/sources at the surface over the large Siberian territory. In turn, the tall tower observations are linked with eddy covariance measurements of exchange carbon fluxes, introducing a «bottom-up» observational approach, over locally representative ecosystems: pine forest–bog complexes (60°48'N; 89°22'E); a mid-taiga dark coniferous forest (60°01'N; 89°49'E); a northern taiga mature larch forest (64°12'N; 100°27'E) and a forest-tundra ecotone (67°28'N; 86°29'E). This meridional observation network captures exchange fluxes of CO₂ and CH₄ in ecosystems of the main biogeochemical provinces for the Yenisey river basin of 2580 thousand km², that can be scaled up to the region using vegetation maps, forest biomass inventories and remote sensing information. Since 2018 observation network was expanded and a new coastal station for continuous atmospheric measurements of GHG (СО₂/СН₄/Н₂О) and meteorology is operational on the shore of the Arctic ocean (73°33'N; 80°34'E) near the Dikson settlement. Such coastal station enhances the atmospheric signal derived at «ZOTTO» regarding the budget of trace gases in Central Siberia, permits tracing ocean-continent transport of GHG and also extends the circum-Arctic observation network.

Here we summarize the scientific rationale of the observation network, infrastructure details of the stations, the local environments and provide some exemplary results obtained from measurements. The reported study was funded by the Max Planck Society (Germany), RSF project № 14-24-00113 and the RFBR projects № 18-05-00235 and 18-05-60203.

How to cite: Panov, A., Prokushkin, A., Urban, A., Zyrianov, V., Korets, M., Sidenko, N., Lavrič, J., and Heimann, M.: Large-scale quantifying of sources and sinks of atmospheric carbon in Central Siberia: from middle taiga to Arctic tundra , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13639, https://doi.org/10.5194/egusphere-egu2020-13639, 2020.

In this study we analyzed the information about the presence of different types of anthropogenic objects (settlements, transport infrastructure, mining areas, etc.) in the Arctic zone of Russia. This information was taken from open Internet-sources: maps, cartographic projects, databases, schemes of regional development of the Russian Federation. Data analysis shows than only about 20% of Russian Arctic’s area is affected by economic development, meanwhile on the other 80% of the area there are practically no anthropogenic objects.

The economic development of the Arctic region decreases from West to East of Russia. The Republic of Karelia is characterized by the highest economic development level (only 13,1% of the area are not affected by any economic activities), the lowest levels have Krasnoyarskiy krai (95,2%) and the Republic of Sakha (Yakutia) (87,2%). Data on the presence, position, and types of anthropogenic objects were subjected to the k-means method of cluster analysis in order to identify characteristic combinations of objects corresponding to different types of development. Within the Arctic zone of Russia six main types of economical use of the territory were identified. Each of these types was characterized by the dominance of a certain type of anthropogenic objects (settlements, roads, mining industry objects, oil and gas transport infrastructure, wood industry objects).

Each type of the economical use of the territory is characterized by specific anthropogenic transformation of the topography of the area. The greatest transformation of the topography and geomorphological processes was found within the open mining areas. The least influence on the topography is connected with some of the linear transport structures (unpaved roads and underground gas pipelines). In general, economic activity in Russian Arctic is relatively low. Anthropogenic transformation of topography and geomorphic processes ​​is typical for the area about 667 thousand square km, that is about 18% of the total area of ​​the Russian Arctic.

This study is supported by Russian Foundation for Basic Research (RFBR) Project № 18-05-60200 "Anthropogenic transformation of Arctic Landscapes for the last 100 years".

How to cite: Eremenko, E., Bredikhin, A., Kharchenko, S., Belyaev, Y., Matlakhova, E., Romanenko, F., Bolysov, S., and Fuzeina, Y.: Anthropogenic Transformation of Russian Arctic: dividing the area into zones based on cluster analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11705, https://doi.org/10.5194/egusphere-egu2020-11705, 2020.

Dynamics of gaseous elemental mercury during polar spring and winter

Since June 2001 the long-term monitoring of the gaseous elemental mercury (thereafter, mercury) in the surface layer of the atmospheric has been conducted near the Amderma settlement (69,72^оN; 61,62^oE; Yugor Peninsula, Russia).

During this monitoring, variations of the lowered mercury concentrations (<1.0 ng m^-3) were observed for spring (March–May) period in 2005 and 2011. For spring 2005, the intensity of the solar radiation did not affect the number of low values of mercury concentrations. With an increase of solar activity during the day there was a reverse effect: i.e. from 9 until 15 h the number of lowered values of concentration decreased. For the evening hours, the highest number of lowered concentrations and atmospheric mercury depletion events, AMDEs (12 events) were observed. For 2005, upon reaching a daily high solar activity the processes of mercury depletion were not observed. It could be because lacking of a large number of marine aerosols in the atmospheric surface layer, although the processes of photochemical reactions did not stop. For spring 2011, during increased solar activity the number of AMDEs increased to 62 events. However, there was no ice cover observed in the coastal area, and consequently, large amounts of sea aerosol could be presented in the surface layer of the atmosphere.

For the winter (December-January) period, the maximum number (in total, 495) of lowered values of mercury concentration and AMDEs (32 events) were recorded in 2010–2011. Such situation was previously observed only in winter of 2006–2007 (13 events). As there is no direct sunlight in mentioned period, the removal of mercury from the atmosphere may be caused by combination of physical and chemical processes that are not related to photochemistry. Starting mid-January, although duration of the day increases, but solar energy is not enough to activate photochemical reactions and predominant type of solar radiation is diffuse rather than direct one. However, AMDEs were still reported at that time (18 events were registered in January 2011).

After mid-March, the angle of sun’s declination increases and the incoming solar energy is sufficient to activate photochemistry. However, during March–May there was no linear relationship identified for AMDEs. The maximum number (300) of lowered values of mercury concentration and AMDEs (21 events, with duration up to 66 hours) were registered in April. Such AMDEs are connected with presence of elevated concentrations of aerosols in the absence of ice cover in the marine coastal zone. Not excluded a possibility of contribution of anthropogenic aerosols (from burning of fossil fuels) in the process of mercury deposition from the atmosphere on the underlying surface.

How to cite: Pankratov, F., Mahura, A., Popov, V., and Masloboev, V.: Dynamics of gaseous elemental mercury during polar spring and winter, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1386, https://doi.org/10.5194/egusphere-egu2020-1386, 2020.

In this study, we consider the effect on climate of one of the atmospheric aerosols - black carbon. Estimates are obtained for changes in the surface albedo and additional radiation forcing associated with account for BC emissions from forest fires. For this, we used the data of a historical experiment with the climate model INMCM5 [1] developed at the INM RAS, as well as the one-dimensional SNICAR (SNow-ICe-AErosole radiation model) [2] model of radiation transfer in the snow layer. In the historical experiment with the climate model INMCM, carried out as part of the CMIP6 project [3], the climate of the Earth system was simulated from 1850 to 2014. In this case, the external forcing on the Earth system was set as close as possible to the observed one.

Based on the monthly average model data on the height of the snow cover, as well as the flux of black carbon from the atmosphere, assuming uniform mixing of the precipitation of BC in the snow, the concentration of BC in each cell of the model grid was calculated. Then, using the obtained concentrations, radiation forcing caused by BC emission from forest fires was calculated using the SNICAR model.

Since anthropogenic emissions of black carbon far exceed emissions resulting from the burning of biomass, two seasons that differ in the intensity of forest fires were chosen to study the role of forest fires in the radiation balance. Based on the GFED (Global Fire Emission Database) [4], 1998 (corresponding to large emissions of black carbon at mid-latitudes into the atmosphere caused by biomass burning) and 2001 (corresponding to small emissions) were selected as such seasons. Moreover, it is known that the anthropogenic source for the specified period changed slightly. Additional forcing amounted to 2-3 W/m²  locally with a relative estimation error of the order of 10-15%. The results of calculations of the average annual radiation forcing for the mainland are in good agreement with [2], [5].

This work is supported by RFBR project No.18-05-60183.

List of references:

How to cite: Chernenkov, A., Kostrykin, S., and Ginzburg, V.: Evaluation of radiation forcing from snow pollution by black carbon emissions from forest fires using the SNICAR radiation model and data from the INMCM5 climate model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-763, https://doi.org/10.5194/egusphere-egu2020-763, 2020.

The main idea of our work is to find out the perspective points for the investigation of space factors which can impact physical and biological processes on Earth surface. Some decades ago the complex of those factors was named as “Space Weather”. So the main purpose of our work is to discover the connection between Space Weather and Terrestrial Weather as well as the impact of this environmental complex (Space Weather plus Terrestrial Weather) on biological objects and thereby on the human health.

The first part of the presented work contains the description of the Space Weather characteristics for the appearance moments of very long-live (more than 10 days) atmosphere pressure systems on different terrestrial latitude locations. These Long-live Pressure Systems (LPS) are interesting for us because some of them (namely anticyclones) can block pressure fields so they can create some dangerous situations for the human health as well as for the human activity. The different terrestrial latitude locations were: (1) Saint-Petersburg (59^o57‘N, 30^o19‘E) and (2) Tambov (52^o43‘N, 41^o27‘E). This latitude difference in observations is interesting for us because we know about the different affect of Space Weather variations on northern and southern places so we want to study this difference.  The time-intervals were: (1) 1999-2014 years (Saint-Petersburg), (2) 2007-2014 years (Tambov). Space Weather parameters were: (1) global  variations of Solar Activity (SA) parameters; (2) daily characteristics of the SA flare component in various bands of the electromagnetic spectrum; (3) variations of Interplanetary Space characteristics in Earth vicinity; (4) variations of daily statistics of Geomagnetic Field (GMF) characteristics. For the appearance moments of LPS we have discovered the interesting behaviour for follow Space Weather characteristics: variations of all global SA indices, variations of low energy (C-class) X-ray solar flares number, variations of proton fluxes, and variations of GMF parameters daily statistics. Also we have discovered the terrestrial-latitude difference in the atmosphere response on the Space Weather impact.

The second part of our work contains the results of investigation of environmental (Space Weather plus Terrestrial Weather) impact on human health. This study was done for Saint-Petersburg region (the northern place from the previous point of our investigation). The human health status was indicated by: (1) Cardiac Rhythm Variations (CRV) of patients in the clinic of Medicine Academy, Sudden Cardiac Deaths (SCD) in Research Institute of Emergency Medicine, facts of hard situation in 6 local clinics in different places of Saint-Petersburg and its suburb. We have found out that the dramatic cardiac events (CRV extrema, SCD maxima, hard days in clinics) are connected with variations of solar radio bursts number (the burst type is “noise storm”), the spread daily statistics (coefficient of variation) of GMF z-component and with spread daily statistics (coefficient of oscillation) of air temperature.

Results of our work may be used as the base for the hazard environmental monitoring.

How to cite: Stupishina, O. and Golovina, E.: On Space Weather factors which can impact terrestrial physical and biological processes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5892, https://doi.org/10.5194/egusphere-egu2020-5892, 2020.

The AeroRadCity urban aerosol experiment over Moscow megacity have been carried out during spring 2018 and 2019. The experiment included measurement campaign at the Moscow MSU MO and numerical experiments using COSMO-ART model (Vogel et al., 2010, Vilfand et al., 2017). We examined the dynamic of aerosol properties and their radiative effects under various meteorological conditions using both columnar and surface aerosol measurements (AERONET dataset, mass concentration of PM10, black carbon (BC), different aerosol gas-precursors, etc.). For qualifying urban pollution special attention was given to the analysis of columnar and surface Angstrom absorption coefficients, low values of which indicated the BC dominance as a result of high-temperature combustion of natural fuel in transport engines. We obtained a positive statistically significant dependence of AOD on PM and BC concentrations with a pronounced bifurcation point around PM10=0.04 mgm^-3. Model and experimental data demonstrated positive BC relationships with PM10, NO₂ and SO₂ at Moscow megacity (Chubarova et al., 2019). The analysis of radiative effects of aerosol in clear sky conditions has revealed up to 30% loss for UV irradiance and 15% - for shortwave irradiance at high AOD. Much intensive radiation attenuation is observed in the afternoon, when remote pollution sources affected solar fluxes at elevated boundary layer conditions. Negative (cooling) RF effect at TOA varied from -20 Wm^-2 to -1 Wm^-2 with average of -8 Wm^-2. The minimum (absolute) RF effect corresponded to the lowest AOT and single scattering albedo. A statistically significant regression dependence of the single scattering albedo on BC/PM10 fraction was obtained at high level of particle dispersion intensity.

The urban AOT550 calculations in COSMO-ART model were compared with the results of measurements in Moscow and Zvenigorod at the A. M. Oboukhov IFA RAS institute. They showed a satisfactory agreement between model and measured values of city aerosol pollution (respectively, dAOT= 0.017  and dAOT= 0.013). In some days the difference increased up to 0.05 in conditions with low intensity of pollutant dispersion.

During the experiment a high correlation (R²=0.95) was revealed between the insoluble component and the total mineralization of rain precipitation, which indicates that 70% of aerosol deposition occurs as the insoluble fraction. We show that at the initial concentration of C₀(PM)>10 μgm^-3 exponential washout coefficients are significant for PM (alfa (PM)=0.17+-0.09 hour^-1) and insignificant for BC (alfa (BC) =0.07+-0.10 hour^-1). At C₀(PM) <10 μgm^-3, the alfa values both for PM and BC are close to zero. According to the numerical experiments with and without account of wet deposition the alfa value was estimated to be 0.08 hour^-1, which fits the confidence interval obtained from the measurements. The work was supported by the Russian Science Foundation, grant # 18-17-00149.

References:

Chubarova N.E. et al. (2019). GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2019;12(4):114-131.

Vogel et al., (2010). In Integrated Systems of Meso-meteorological and Chemical Transport Models, Springer, pp. 75-80.

Vilfand et al. (2017). Russian Meteorology and Hydrology, vol. 42, № 5, pp. 292–298. DOI:10.3103/S106837391705003X.

How to cite: Chubarova, N., Androsova, E., Volpert, E., Kirsanov, A., Vogel, B., Vogel, H., Popovicheva, O., Eremina, I., and Rivin, G.: Urban aerosol in Moscow megacity and its radiative effects according to the AeroRadCity experiment and COSMO-ART modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4880, https://doi.org/10.5194/egusphere-egu2020-4880, 2020.

Wildfires in Siberia are a major source of aerosol in Northern Eurasia. Biomass burning (BB) aerosol can significantly impact the Earth’s radiative balance through absorption and scattering of solar radiation, interactions with clouds and changes of surface albedo due to deposition of black and brown carbon on ice and snow. There is growing evidence that atmospheric aging of BB aerosol can be associated with profound but diverse chemical and physical transformations which, in most cases, are not adequately represented in chemistry-transport and climate models that are widely used in assessments of radiative and climate effects of atmospheric pollutants.

An idea of this study is to identify changes in the optical properties of aging BB aerosol using absorption and extinction aerosol optical depths (AAOD and AOD) retrieved from the OMI and MODIS satellite observations and to elucidate key processes behind these changes using the Mie-theory-based calculations along with simulations with chemistry-transport and microphysical box models involving representation of the evolution of organic particulate matter within the VBS framework. The study focuses on a major outflow of BB plumes from Siberia into the European part of Russia in July 2016. The analysis of the satellite data is complemented by the original results of biomass burning aerosol aging experiments in a large aerosol chamber. 

The results indicate that the BB aerosol evolution during the first 10-20 hours features strong secondary organic aerosol (SOA) formation resulting in a substantial increase in the particle single scattering albedo. Further evolution is affected by the loss of organic matter, probably due to evaporation and oxidation. The results also indicate that although brown carbon contained in the primary aerosol is rapidly lost (consistently with available independent observations) due to evaporation and photochemical destruction of chromospheres, it is partly replaced by weakly absorbing low-volatile SOA.

In general, this study reveals that aging BB aerosol from wildfires in Siberia undergoes major physical and chemical transformations that have to be taken into account in assessments of the impact of Siberian fires on the radiative balance in Northern Eurasia and the Arctic. It also proposes a practical way to address these complex transformations in chemistry-transport and climate models.

The study was supported by the Russian Science Foundation (grant agreement No. 19-77-20109).

References

1. Konovalov, I.B., Beekmann, M., Berezin, E.V., Formenti, P., and Andreae, M.O.: Probing into the aging dynamics of biomass burning aerosol by using satellite measurements of aerosol optical depth and carbon monoxide, Atmos. Chem. Phys., 17, 4513–4537, 2017.
2. Konovalov, I.B., Lvova, D.A., Beekmann, M., Jethva, H., Mikhailov, E.F., Paris, J.-D., Belan, B.D., Kozlov, V.S., Ciais, P., and Andreae, M.O.: Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths, Atmos. Chem. Phys., 18, 14889–14924, 2018.
3. Konovalov, I.B., Beekmann, M., Golovushkin, N.A., and Andreae, M.O.: Nonlinear behavior of organic aerosol in biomass burning plumes: a microphysical model analysis, Atmos. Chem. Phys., 19, 12091–12119, 2019.

How to cite: Konovalov, I., Golovushkin, N., Beekmann, M., and Kozlov, V.: New insights into physical and chemical atmospheric transformations of biomass burning aerosol from wildfires in Siberia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7970, https://doi.org/10.5194/egusphere-egu2020-7970, 2020.

The Pan-Eurasian EXperiment (PEEX; www.atm.helsinki.fi/peex) programme is a long-term programme. One of the PEEX Research Infrastructure’s components is the PEEX-Modelling-Platform (PEEX-MP; www.atm.helsinki.fi/peex/index.php/modelling-platform). PEEX-MP includes more than 30 different models running at different scales, resolutions, geographical domains, resolving different physical-chemical-biological processes, etc. and used as research tools providing insights and valuable information/ output for different level assessments for environment and population. These models cover main components - atmosphere, hydrosphere, pedosphere and biosphere. The seamless coupling multi-scale and -processes modelling concept developed is important and advanced step towards realization of the PEEX research agenda presented in the PEEX Science Plan (www.atm.helsinki.fi/peex/images/PEEX_Science_Plan.pdf). Accessibility to infrastructure with High Performance Computing is important for such modelling.

In particular, the Enviro-HIRLAM (Environment – HIgh Resolution Limited Area Model) & HARMONIE (The HIRLAM-ALADIN Research for Meso-scale Operational NWP In Europe) models can be applied for multi-scale and –processes studies on interactions and feedbacks of meteorology vs aerosols/chemistry; aerosols vs. cloud formation and radiative forcing; boundary layer parameterizations; urbanization processes impact on changes in urban weather and climate; assessments for human and environment; improving prediction of extreme weather/ pollution events; etc. All these can be studied at different spatial (urban-subregional-regional) and temporal scales. In addition, added value to analysis is obtained through integration of modelling results into GIS environment for further risk/vulnerability/consequences/etc. studies.

As part of the Enviro-PEEX project (www.atm.helsinki.fi/peex/index.php/enviro), the models were used to study aerosols feedbacks and interactions in Arctic-boreal domain at regional scale & effects of radar data assimilation at mesoscale resolution, respectively.

Enviro-HIRLAM model was run in a long-term mode at 15-5 km resolutions for reference and aerosols effects (direct, indirect, combined included) with ECMWF boundary conditions and anthropogenic/ biogenic/ natural emissions pre-processed. Analysis of differences between model runs for basic statistics (avg, med, max, min, std) showed less pronounced variations of concentrations for average in Arctic regions vs other regions, and more pronounced for maximum concentration in Russian Siberia and Ural. Monthly averaged sulphur dioxide was larger over mid-latitudes (influence of anthropogenic sources) with maximum due to long-range atmospheric transport. For particular matter, it is lower in Arctic compared with mid-latitudes, but their composition is dominated by sea salt aerosols.

HARMONIE model was tested with pre-processing (optimising inner parameters) and data assimilation of radar reflectivity, which minimize a representative error (associated with discrepancy between resolutions in informational sources). The method showed improvement in prediction of precipitation rain rates and spatial pattern within radars’ location areas and better reproduction of mesoscale belts and cell patterns of few-to-ten size in precipitation fields. Compatibility between model resolution and smoothed radar observation density was achieved by “cube-smoothing” approach. This ensures equivalent presentation of precipitation (reflectivity) structures in both model and observation in a sense of equally preserving the scales of precipitation patterns.

Moreover, for selected PEEX-MP models, used by UHEL-INAR, such Enviro-HIRLAM, EC-Earth, MALTE-Box a series of science education oriented trainings/schools is organized in April & August 2020 (ums.rshu.ru & worldslargerivers.boku.ac.at/wlr/index.php/ysss.html) which are part of the PEEX Educational Platform activities as well.

How to cite: Mahura, A., Baklanov, A., Petäjä, T., Nuterman, R., Ivanov, S., Michaelides, S., Ruban, I., Makkonen, R., Lappalainen, H. K., Zilitinkevich, S., and Kulmala, M.: PEEX Integrated Multi-scales and -Process Modelling for Environmental Applications, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11582, https://doi.org/10.5194/egusphere-egu2020-11582, 2020.

The environment in the Arctic and boreal is changing rapidly due to megatrends such as globalization, new transport route development, demography and use of natural resources. These megatrends have environmental effects, particularly in terrestrial, marine and cryosphere domains which are undergoing substantial changes. Local, regional, national and international decision-making bodies require fact-based services to tackle challenges of rapid environmental change.  In this presentation we will present results from “integrative and Comprehensive Understanding on Polar Environments (iCUPE) project, which combines in-situ observations and satellite remote sensing for novel data and scientific understanding on the Arctic pollution. We will also summarize the benefits arising from integrated and co-located observations that contribute to different European environmental research infrastructures with practical scientific insights from such synthesis.

How to cite: Petäjä, T., Lappalainen, H., Bäck, J., and Kulmala, M.: Comprehensive environmental observations and their integration in the Arctic-boreal environment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22602, https://doi.org/10.5194/egusphere-egu2020-22602, 2020.

Data Mining (DM) and Machine Learning (ML) have become very popular modern statistical learning tools in solving many complex scientific problems. In this work, we present two case studies that used DM and ML techniques to enhance new-particle formation (NPF) identification and analysis. Extensive measurements and large data sets related to NPF and other ambient variables have been collected in arctic and boreal regions. The focus area of our studies is the SMEAR II station located in Hyytiälä forest, Finland that is in the area of interest of the Pan-Eurasian Experiment (PEEX).

Atmospheric NPF is an important source of climatically relevant atmospheric aerosol particles. NPF is typically observed by monitoring the time-evolution of ambient aerosol particle size distributions. Due to the noisiness of the real-world ambient data, currently the most reliable way to classify measurement days into NPF event/non-event days is through a manual visualisation method. However, manual labour, with long multi-year time series, is extremely time-consuming and human subjectivity poses challenges for comparing the results of different data sets. In this case, ML classifier is used to classify event/non-event days of NPF using a manually generated database. The results demonstrate that ML-based approaches point towards the potential of these methods and suggest further exploration in this direction.

Furthermore, NPF is a very non-linear process that includes atmospheric chemistry of precursors and clustering physics as well as subsequent growth before NPF can be observed. Thanks to ongoing efforts, now there exists a tremendous amount of atmospheric data, obtained through continuous measurements directly from the atmosphere. This fact makes the analysis by human brains difficult, on the other hand, enables the usage of modern data science techniques. Here, we demonstrate the use of DM method, named mutual information (MI) to understand NPF events and a wide variety of simultaneously monitored ambient variables. The same results are obtained by the proposed MI method which operates without supervision and without the need of understanding the physics deeply.

How to cite: Zaidan, M. A., Fung, P. L., Wraith, D., Nieminen, T., Hussein, T., Kerminen, V.-M., Petäjä, T., and Kulmala, M.: Data mining and machine learning to enhance new-particle formation identification and analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2355, https://doi.org/10.5194/egusphere-egu2020-2355, 2020.

Urban air pollution has been a global challenge, and continuous air quality measurement is important to understand the nature of the problem. However, missing data has often been an issue in air quality measurement. In this study, we presented a modified method to impute missing data by input-adaptive proxy. We used black carbon (BC) concentration data in Mäkelänkatu traffic site (TR) and Kumpula urban background site (BG) in Helsinki, Finland in 2017–2018 as training sets. The input-adaptive proxy selected input variables of other air quality variables based on their Pearson correlation coefficients with BC. In order to avoid overfitting, this proxy used the algorithm of least squares model with a bisquare weighting function and allowed a maximum of three input variables. The generated models were then evaluated and ranked by adjusted coefficient of determination (adjR²), mean absolute error and root mean square error. BC concentration was first estimated by the best model. In case of missing data in the input variables in the best model, the input-adaptive proxy then used the second-best model until all the missing data gaps were filled up.

The input-adaptive proxy managed to fill up 100% of the missing voids while traditional proxy filled only 20–80% of missing BC data. Furthermore, the overall performance of the input-adaptive proxy is reliable both in TR (adjR²=0.86–0.94) and in BG (adjR²=0.74–0.91). TR has a generally better regression performance because the level of BC can be mostly explained by traffic count, nitrogen oxides and accumulation mode. On the contrary, the source of BC in BG is more heterogeneous, which includes traffic emission and residential combustion, and the concentration of BC is influenced by meteorological parameters; therefore, the rule of including maximum three input variables might lead to the lower adjR². The proxy works slightly better for workdays scenario than in weekends in both sites. In TR, the proxy works similarly in all seasons, while in BG, the proxy performance is better in winter and autumn than in the other seasons. The simplicity, full coverage and high reliability of the input-adaptive proxy make it sound to further estimate other air quality parameters. Moreover, it can act as an air quality virtual sensor alongside with on-site instruments.

How to cite: Fung, P. L., Zaidan, M. A., Sillanpää, S., Kousa, A., Niemi, J. V., Timonen, H., Kuula, J., Saukko, E., Luoma, K., Petäjä, T., Tarkoma, S., Kulmala, M., and Hussein, T.: Input-adaptive proxy of air quality parameters: A case study for black carbon in Helsinki, Finland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2693, https://doi.org/10.5194/egusphere-egu2020-2693, 2020.

Turbulence in unstably stratified flows is traditionally considered as chaotic eddies generated on equal terms by the two very different mechanisms: mean velocity shears, and buoyancy forces. By this means, vertical buoyant plumes comprising “convective turbulence” are not distinguished form 3-dimensional shear-generated eddies comprising “mechanical turbulence”. The latter are dynamically unstable and, hence, break down to produce smaller eddies, thus performing direct cascade of turbulent kinetic energy (TKE) and other properties of turbulence from larger to smaller scales towards their molecular dissipation. The conventional theory does not distinguish convective plumes from mechanical eddies and, factually, postulates that plumes also perform the direct cascade. 

We declare that this conventional vision is erroneous except for the trivial case of domination of dynamic instability, when mechanical eddies destroy convective plumes and violently involve them into direct cascade. In geophysical convective boundary layers (CBLs), this condition is satisfied in the thin near-surface sublayer comprising usually less than one per cent of CBL. Beyond this sublayer, dominant role belongs to convective plumes that do not break down but merge to form larger plumes, thus, performing inverse cascade culminated in the conversion of convective TKE into kinetic energy of the CBL-scale self-organised structures: cells or rolls. Therewith, weak mechanical turbulence generated by the mean-flow shears performs usual direct cascade. Hence, horizontal TKE is fully mechanical, whereas vertical TKE is almost fully convective. The key role in this unorthodox picture play the rates of conversion of TKE or another property of convective turbulence into kinetic energy or anther property of the CBL-scale self-organised structures. We define this vision of unstably stratified turbulence theoretically and prove it experimentally by the example of TKE budget in horizontally homogenous atmospheric surface-layer flow.

How to cite: Zilitinkevich, S. and Repina, I.: Revision of the current theory of unstably stratified turbulence and its potential implications for PEEX, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8794, https://doi.org/10.5194/egusphere-egu2020-8794, 2020.

We analyzed the data of the numerical simulation of stably stratified turbulent shear flows. It is shown that, along with chaotic turbulence, the flows contain large organized structures. In the temperature field, these structures appear as inclined layers with weakly stable stratification, separated by very thin layers with large temperature gradients. The existence of such layered structures in nature is indirectly confirmed by the analysis of field measurements. An increase of the turbulent Prandtl number with increasing gradient Richardson number was fixed in simulation data. The hypothesis is proposed that physical mechanism for maintaining of turbulence in supercritically stable stratification is connected with the revealed  structures. It is shown that the spatial scales and the shapes of the identified organized structures can be explained using the calculation of  optimal disturbances for the simplified linear model.

This study was supported by the Russian Foundation for Basic Research (grants nos. 18-05-60126,  20-05-00776) and by Academy of Finland project ClimEco no. 314 798/799 (2018-2020).

How to cite: Glazunov, A., Mortikov, E., Zasko, G., Nechepurenko, Y., and Zilitinkevich, S.: Large organized structures in stably stratified turbulent shear flows., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9034, https://doi.org/10.5194/egusphere-egu2020-9034, 2020.

The Pan-Eurasian Experiment Program (PEEX) is an interdisciplinary scientific program bringing together ground-based in situ and remote sensing observations, satellite measurements and modeling tools aiming to improve the understanding of land-water-atmosphere interactions, feedback mechanisms and their effects on the ecosystem, climate and society in northern Eurasia, Russia and China. One of the pillars of the PEEX program is the ground-based observation system with new stations being established across the whole PEEX domain complementing existing infrastructure. However, in view of the large area covering thousands of kilometres, large gaps will remain where no or little observational information will be available. The gap can partly be filled by satellite remote sensing of relevant parameters as regards atmospheric composition, land and water surface properties including snow and ice, and vegetation.

Forest fires and corresponding emissions to the atmosphere dramatically change the atmospheric composition in case of long-lasting fire events, which might cover extended areas. In the burned areas, CO2 exchange, as well as emissions of different compounds are getting to higher levels, which might contribute to climate change by changing the radiative budget through the aerosol-cloud interaction and cloud formation. In the boreal forest, after CO2, CO and CH4, the largest emission factors for individual species were formaldehyde, followed by methanol and NO2 (Simpson et al., ACP, 2011). The emitted long-life components, e.g., black carbon, might further be transported to the distant areas and measured at the surface far from the burned areas.

 During the last few decades, several burning episodes have been observed over PEEX area by satellites (as fire counts), specifically over Siberia and central Russia. Fire activity can also be seen in increasing Aerosol Optical depth (AOD) retrieved from satellites, as well as fire radiative power (FRP) calculated using the satellite data. In the current work, we study the time series of the fire activity, FRP and AOD over PEEX area and specifically over selected cities.

How to cite: Sogacheva, L., Sundström, A.-M., de Leeuw, G., Arola, A., Petäjä, T., Lappalainen, H. K., and Kulmala, M.: Fire activity and Aerosol Optical Depth over PEEX area for the last two decades, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13175, https://doi.org/10.5194/egusphere-egu2020-13175, 2020.

The growth of greenhouse gases, primarily carbon dioxide, is the main cause of modern changes in the Earth's climate. At the same time, despite the relatively small area (~ 3%) of the territory of cities, they are responsible for more than 70% of anthropogenic emissions caused by energy supply systems. Therefore, studies of CO₂ distributions in cities and surrounding regions, as well as quantitative estimates of urban emissions are an urgent problem.

The paper presents a comparative analysis of CO₂ contents and their variations for a number of Russian cities (Moscow, St. Petersburg, Yekaterinburg, Magnitogorsk and Norilsk) on the basis of the OCO-2 satellite measurement data. The studies were carried out using satellite data sets that vary from high to average quality. These ensembles differ for all these cities in the number of measurement days, the total number of CO₂ measurements, and the spatial and temporal coverage. For example, a high-quality ensemble covers ~ 90% of the spring and summer months, i.e. provides an opportunity to study CO₂ variations in the warm season. The ensemble of measurements with average accuracy more evenly covers the entire year.

The paper studied various characteristics of the column averaged dry-air mole fraction of CO₂ (X_CO2) for 5 cities, namely, minimal and maximal values, amplitudes of variations, daily average maximal and minimal values, standard deviations, etc. Possibilities of using the OSO-2 data for estimating of anthropogenic emissions in different cities are considered.

How to cite: Nikitenko, A., Timofeyev, Y., Virolainen, Y., Berezin, I., and Polyakov, A.: Analysis of CO2 content near Russian cities from OCO-2 satellite measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2679, https://doi.org/10.5194/egusphere-egu2020-2679, 2020.

Forest fires affect environmental changes both directly, changing the type of land cover, causing local and regional air pollution through emissions of greenhouse gases and aerosols, and indirectly through a secondary effect on atmospheric, soil and hydrological processes. The increase in the number and area of uncontrolled wildfires, the degradation of permafrost in high latitude areas leads to a change in the balance of greenhouse gases in the atmosphere, and it results in the negative impact on the Earth’s climatic system.

This study examined the Arctic-Boreal territories of the Russian Federation, where huge forest fires were observed in 2018-2019. In most of these areas, forest fire detection is carried out only by means of the satellite monitoring without aviation support. The sparsely populated and inaccessible territories are a major factor of the rapid spread of fires over large areas. Most of the forest areas in the region are so-called control zones, where the authorities may decide not to extinguish the fires if they do not threaten settlements and economic facilities, and consider the salvation of forests economically unprofitable. However, there is no reliable data on the environmental consequences of large forest fires in the Arctic-Boreal territories.

Satellite monitoring of wildfires provides the detection of fire locations, an assessment of their area and burning time. In our study, we used various indices calculated from remote sensing data for the pre-fire and post-fire periods to identify the spatiotemporal patterns of environmental change caused by large wildfires. The Sentinel 5 TROPOMI time series have been analyzed for the short-term and long-term atmospheric composition anomalies detection caused by forest fires in the region. In the process of comparing the methane concentrations time series for the 2018- 2019 fire seasons the constantly high values anomaly zones were found. We believe that these anomalies are resulting from Sentinel-5 CH4 algorithm constrains, which requires additional work on data validation with relation to the local conditions.

The reported study was funded by RFBR, MOST (China) and DST (India) according to the research project № 19-55-80021

How to cite: Cherepanova, E., Bondur, V., Zamshin, V., and Feoktistova, N.: Satellite-derived spatiotemporal patterns of environmental changes caused by 2018-2019 wildfires in Arctic-Boreal Russia , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18080, https://doi.org/10.5194/egusphere-egu2020-18080, 2020.

The need to undertake a comprehensive investigation of the atmospheric composition over the Russian segment of the Arctic is caused by a serious lack and irregularity in obtaining observational data from this regio of the Earth. In addition, a comparison of the aircraft in-situ measurements with satellite data retrieved for the Kara Sea region in 2017 revealed large uncertainties in determining the vertical distribution of greenhouse gas concentrations using remote sensing methods. The development and improvement of the last ones needs at least their periodic verification by means of undertaking precise in-situ aircraft measurements.

The general scheme of the proposed experiment is as follows (map is attached): flight from Novosibirsk to Naryan-Mar via Sabetta. From Naryan-Mar, flight to a water area of the Bering Sea (up to 1000 km). Flight from Naryan-Mar to Sabetta. From here, flight to a water area of the Kara Sea (up to 1000 km). Then, flight to Tiksi. Flight from Tiksi to a water area of the Laptev Sea (up to 1000 km). Flight to Chokurdakh or Chersky. From there, flight to a water area of the East Siberian Sea (up to 1000 km). Flight to Cape Schmidt. Flight to a water area of the Chukchi Sea (up to 1000 km). Return route: Cape Shmidt–Chersky (or Chokurdah)–Yakutsk–Bratsk–Novosibirsk. It will take about 100 hours of flying time to implement the entire aircraft campaign. Campaign period is about 2-3 weeks. It is better to undertake the campaign during summer when the ocean is open. Flights over the land surface are assumed to be undertaken from 0.5 km to 11 km above ground level while above the sea from 0.2 km to 11 km. The flight profile is variable from the maximum possible height to the minimum allowed one. Vertical profiles of gas and aerosol composition will be obtained, including black carbon and organic components, as well as basic meteorological quantities.

Satellite data will be verified that do not yet provide acceptable accuracy. For the first time, unique information will be obtained over the least explored region of the Arctic, which is crucial for the whole planet in terms of climate formation and the impact of global warming.

How to cite: Belan, B. D., Antokhin, P. N., Arshinov, M. Yu., Belan, S. B., Davydov, D. K., Ivlev, G. A., Kozlov, A. V., Ptashnik, I. V., Savkin, D. E., Simonenkov, D. V., Tolmachev, G. N., and Fofonov, A. V.: Investigating chemical composition of the troposphere over the Russian Arctic using the "Optik" Tu-134 aircraft laboratory, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6795, https://doi.org/10.5194/egusphere-egu2020-6795, 2020.

Keywords:

Arctic datasets, research infrastructures, in-situ observations, PEEX e-Catalogue, INTAROS, iCUPE

The INAR is leading the Pan-Eurasian EXperiment (PEEX; www.atm.helsinki.fi/peex) initiative. The PEEX Research Infrastructure’s has 3 components: observation, data and modelling. Observations networks produce large volumes of raw data to be pre/processed/analysed and delivered in a form of datasets (or products) to research and stakeholders/end-users communities. Here, steps taken are discussed and include an overview (as PEEX-e-Catalogue) of measurement capacity of exiting stations and linkages to INTAROS (intaros.nersc.no) and iCUPE (www.atm.helsinki.fi/icupe).

In-Situ Atmospheric-Ecosystem Collaborating Stations

Although more than 200 stations are presented in the PEEX regions of interest, but so far only about 60+ Russian stations have metadata information available. The station metadata enables to categorize stations in a systematic manner and to connect them to international observation networks, such as WMO-GAWP, CERN and perform standardization of data formats. As part of the INAR activities with Russian partners, an e-catalogue was published as a living document (to be updated as new stations will joinin the PEEX network). This catalogue (www.atm.helsinki.fi/peex/index.php/peex-russia-in-situ-stations-e-catalogue) introduces information on measurements and contacts of the Russian stations in the collaboration network, and promotes research collaboration and stations as partners of the collaboration network and to give wider visibility to the stations activities.

Integrated Arctic Observation System (INTAROS)

For Arctic region, 11 stations were selected for the Atmospheric, Terrestrial and Cryospheric parts/themes. The updated metadata were obtained for these measurement stations located within the Russian Arctic territories. Metadata include basic information, physico-geographical and infrastructure description of the sites and details on atmosphere and ecosystem (soils–forest–lakes–urban–peatland–tundra) measurements. Measurements at these sites represent more local conditions of immediate surrounding environment and datasets (as time-series) are available under request. For SMEAR-I (Station for Measuring Atmosphere-Ecosystem Relations) station included in the INTAROS web-based catalogue (catalog-intaros.nersc.no/dataset), the measurement programme includes meteorological (wind speed and direction, air temperature and relative humidity), radiation (global, reflected, net), chemistry/aerosols (CO₂, SO₂, O₃, NO_x, etc.); ecosystem, photosynthesis, irradiance related measurements.

Integrative and Comprehensive Understanding on Polar Environments (iCUPE)

More than 20 open access datasets as products for researchers, decision- and policy makers, stakeholders and end-users communities are produced. A list of expected datasets is presented at www.atm.helsinki.fi/icupe/index.php/datasets/list-of-datasets-as-deliverables. These datasets are promoted to larger science and public communities through so-called “teasers” (www.atm.helsinki.fi/icupe/index.php/submitted-datasets). For the Russian Arctic regions, these also include those from the iCUPE Russian collaborators: atmospheric mercury measurements at Amderma station; elemental and organic carbon over the north-western coast of the Kandalaksha Bay of the White Sea; micro-climatic features and Urban Heat Island intensity in cities of Arctic region; and others. Delivered datasets (www.atm.helsinki.fi/icupe/index.php/datasets/delivered-datasets) are directly linked (and downloadable) at website, and corresponding Read-Me files are available with detailed description and metadata information included. Selected datasets are also to be tested for pre/post-processing/analysis on several cloud-based online platforms.

How to cite: Altimir, N., Mahura, A., Petäjä, T., Lappalainen, H. K., Borisova, A., Bashmakova, I., Noe, S., Duplissy, E.-M., Haapanala, P., Bäck, J., Pankratov, F., Schevchenko, V., Konstantinov, P., Vaventsov, M., Chalov, S., Baklanov, A., Ezau, I., Zilitinkevich, S., and Kulmala, M. and the SMEAR Measurement Concept: Arctic Datasets as Part af PEEX International Collaboration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13244, https://doi.org/10.5194/egusphere-egu2020-13244, 2020.

Detailed monitoring of the temperature of the soil layer provides a unique experimental material for studying the complex processes of heat transfer from the surface layer of the atmosphere to soils. According to the data of autonomous devices of air temperature, it was found that within each key area there are no significant differences between the observation sits. According to the annual (2011-2018) observations of the temperature regime of the soil and ground, it has been found that the microclimatic specificity of bog ecosystems is clearly manifested in the characteristics of the daily and annual variations in soil temperature. A regression model describing the change in the maximum freezing depth during the winter has been proposed, using air temperature, snow depth and bog water level as predictors. The effects of BWL and snow cover have similar values, which indicates an approximately equal contribution of BWL variations and snow depth to changes in freezing. The thickness of the seasonally frozen layer at all sites is 20-60 cm and the maximum freezing of the peat layer is reached in February-March. Degradation of the seasonally frozen layer occurs both from above and below.

It was found that similar bog ecosystems in different bog massifs have significantly different temperature regimes. The peat stratum of northern bogs can be both warmer (in winter) and colder (in summer) in comparison with bogs, located 520 km to the south and 860 km to the west.

How to cite: Bogomolov, V., Egor, D., and Victor, S.: Verification of temperature and humidity conditions of mineral soils in the active layer model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12864, https://doi.org/10.5194/egusphere-egu2020-12864, 2020.

Anthrax is a bacterial disease affecting mainly livestock but also posing a risk for humans. During the outbreak of anthrax on Yamal peninsula in 2016, 36 humans were infected and more than 2.5 thousand reindeer died or were killed to prevent further contamination [1]. Anthrax is a natural focal disease, which means that its agents depend on climatic conditions. The revival of bacteria in previously epidemiologically stable region was attributed to thawing permafrost, intensified during the heat wave of 2016. We studied recent dynamics of air temperature as well as summer and winter precipitation in the region. In addition, we analysed the effect of winter precipitation and air temperature on the dynamics of active layer thickness using data from Circumpolar Active Layer Monitoring sites [2]. Our analysis suggests that permafrost was thawing intensively during several years before the outbreak, when snowy cold winters followed warmer winters. Thick snow prevented soil from freezing and enhanced permafrost thawing. In addition, we showed that summer precipitation drastically decreased in the region of outbreak during recent years, likely contributing to the spread of disease.  

[1] Popova, A.Yu. et al. Outbreak of Anthrax in the Yamalo-Nenets Autonomous District in 2016, Epidemiological Peculiarities. Problemy Osobo Opasnykh Infektsii [Problems of Particularly Dangerous Infections]. 4, 42–46 (2016).

[2] Circumpolar Active Layer Monitoring site: https://www2.gwu.edu/~calm/ [2/08/2019].

How to cite: Ezhova, E., Orlov, D., Suhonen, E., Kaverin, D., Mahura, A., Gennadinik, V., Kukkonen, I., Drozdov, D., Lappalainen, H., Melnikov, V., Petäjä, T., Kerminen, V.-M., Zilitinkevich, S., Malkhazova, S., Christensen, T., and Kulmala, M.: The link between precipitation and recent outbreak of anthrax in North-West Siberia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10449, https://doi.org/10.5194/egusphere-egu2020-10449, 2020.

The understanding of biophysical mechanisms influencing the spatial and temporal distribution of CO₂ flux is important for predicting the response of forest ecosystem on any environmental changes. It has been shown, that the most important controlling factors responsible for CO₂ flux fluctuation from the forest soils are soil moisture, temperature and the type of the forest stand. In our work, we present three years of soil CO₂ flux measurements in the hemiboreal forest that is characterized by high spatial heterogeneity of vegetation and soil. Three sample plots that represent the main common tree species (Pinus sylvestris, Picea abies and Betula sp) were chosen to assess the influence of tree species composition on the soil CO₂ flux. The chosen sample plots have clear microtopographical structure with depressions, elevations and flat zones. The data were collected from three sample plots according to forest floor microtopography using manual closed dynamic chamber equipped with IRGA sensor (The Vaisala GMP343 probe), humidity and temperature sensors (Vaisala HMP155). Obvious temporal resolution limitation of manual chamber method is compensated by higher spatial coverage.

Previous research has indicated that one of the major sources of uncertainties in the flux estimation is the choice of the model for flux calculation. We compared the commonly used models (linear, exponential and HMR) using two available R packages: “gasflux” and “flux” packages. Additionally, we developed the algorithm that allows for automatically choosing the best model based on widely used criteria (MAE, RAE, AIC, RMSE).

The results showed that in most of the cases linear and exponential models performed better. The comparison of sample plot showed that the biggest influence of microtopography was in the birch forest but the moisture had a bigger effect in the pine forest stand.

How to cite: Krasnov, D., Krasnova, A., and Noe, S.: Soil CO2 fluxes and surface microtopography in a mixed hemiboreal forest: space, time and models., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11452, https://doi.org/10.5194/egusphere-egu2020-11452, 2020.

The winter of northern Arctic regions is characterized by strong winds that lead to frequent blowing snow and thus heterogeneous snow cover, which critically affects permafrost hydrothermal processes and the associated feedbacks across the northern regions. However until now, observations and models have not documented the blowing snow impacts. The blowing snow process has coupled into a land surface model CHANGE, and the improved model was applied to observational sites in the northeastern Siberia for 1979–2016. The simulated snow depth and soil temperature showed general agreements with the observations. To quantify the impacts of blowing snow on permafrost temperatures and the associated greenhouse gases, two decadal experiments that included or excluded blowing snow, were conducted for the observational sites and over the pan-Arctic scale. The differences between the two experiments represent impacts of the blowing snow on the analytical components. The blowing snow-induced thinner snow depth resulted in cooler permafrost temperature and lower active layer thickness; this lower temperature limited the vegetation photosynthetic activity due to the increased soil moisture stress in terms of larger soil ice portion and hence lower ecosystem productivity. The cooler permafrost temperature is also linked to less decomposition of soil organic matter and lower releases of CO2 and CH4 to the atmosphere. These results suggest that the most land models without a blowing snow component likely overestimate the release of greenhouse gases from the tundra regions. There is a strong need to improve land surface models for better simulations and future projections of the northern environmental changes.

How to cite: Park, H. and Kim, Y.: Heterogenous snow cover derived uncertainty in Arctic carbon budget, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21045, https://doi.org/10.5194/egusphere-egu2020-21045, 2020.

The systematic temperature biases over the Arctic Sea in the CMIP5 models are decomposed into partial biases due to physical and dynamical processes, based upon the climate feedback-responses analysis method (CFRAM). In the frame of the CFRAM, physical processes are also divided into water vapor, cloud, and albedo feedbacks. Though the Arctic temperature biases largely depend on models, considerable cold bias are found in most of models and ensemble mean. Overall, temperature biases corresponding to physical and dynamical processes tend to cancel each other out and total biases equal to their sums are geographically similar to those related to physical processes. For the physics-related biases, a contribution of albedo feedback is the largest, followed by cloud and water vapor feedbacks in turn. Quantitative contributions of the processes to temperature biases are evaluated from area-mean values over the entire Arctic Sea, Barents-Kara Sea, and Beaufort Sea. While relationships between total and partial biases over the Arctic Sea show the large model-dependency, in the local-scale, total temperature biases over Barents-Kara Sea and Beaufort Sea are made from consistent contributions among models. An overestimate (underestimate) of specific humidity and cloud fraction in models are responsible for an overall warm (cold) biases through longwave heating rates of the greenhouse effect. Shortwave cloud forcing by cloud fraction biases offsets a substantial part of biases related to longwave cloud forcing, while shortwave effect of specific humidity bias plays a minor role on water vapor feedback. The fact that geographical distribution of sea-ice biases is mostly opposite to that of partial temperature bias due to albedo feedback indicates that the biased simulation of sea-ice in models are the main contributors in albedo feedback.

How to cite: Park, T.-W. and Park, D.-S.: A Decomposition of Feedback Contributions to the Arctic Temperature Biases in the CMIP5 Climate Models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2437, https://doi.org/10.5194/egusphere-egu2020-2437, 2020.

We examined the relationships linking in-situ measurements of gas-phase methanesulfonic acid (MSA), sulfuric acid (SA), iodic acid (HIO3), Highly Oxidized Organic Molecules (HOM) and aerosol size-distributions with satellite-derived chlorophyll (Chl-a) and oceanic primary production (PP). Atmospheric data were collected at Ny-Ålesund site during spring-summer 2017 (30th March-4th August). We compared ocean color data from Barents Sea and Greenland Sea with concentrations of low-volatile vapours and new particle formation. The aim is to understand the main factors controlling the concentrations of atmospheric components in the Arctic in different ocean domains and seasons. Early phytoplanktonic bloom starting in April at the marginal ice zone caused Chl-a and PP in the Barents Sea to be higher than in the Greenland Sea during spring, whereas the pattern was opposite in summer. We found the correlation between ocean color data (Chl-a and PP) and MSA decreasing from spring to summer in Barents Sea and increasing in Greenland Sea. This establishes relationship between sea ice melting and phytoplanktonic bloom, which starts by sea ice melting. Similar pattern was observed for SA. Also HIO3 in both ocean domains correlated with Chl-a and PP during spring time. Greenland Sea was more active than Barents Sea. These results suggest that marine phytoplankton metabolism is an important source of MSA and SA, as expected, but also a source of HIO3 precursors (such as I2). HOMs had low correlation with ocean color parameters in comparison to other atmospheric vapours in this study both in spring and summer. The plausible explanation for low correlation is that the primary source of Volatile Organic Compounds (VOC) – precursors of HOM – is the soil of Svalbard archipelago rather than ocean. During spring, nucleation mode particles were found to correlate with Chl-a at Barents Sea and with PP at Greenland Sea. This means that biogenic productivity has a strong impact on new particle formation in spring although small particles are not related to biogenic parameters in summer.

How to cite: Marbouti, M., Jang, S., Becagli, S., Nieminen, T., Navarro, G., Kerminen, V.-M., Sipilä, M., and Kulmala, M.: Relationships linking satellite-retrieved ocean color data with atmospheric components in the Arctic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19377, https://doi.org/10.5194/egusphere-egu2020-19377, 2020.

The lateral migration of dissolved carbon dioxide (CO₂) with soil solutions to fresh water aquatic systems and in situ mineralization of soil-derived organic carbon (OC) often causes supersaturation of the inland waters with CO₂. An evasion of excess CO₂ from lake and stream surfaces to the atmosphere is important, but underestimated, pathway of carbon flux in the coupled terrestrial-aquatic carbon cycle. As a result, the loss of terrestrial OC as CO₂ through the drainage networks remains poorly accounted in regional carbon budgets estimated on the basis of eddy covariance measurements. In this study we have made an attempt to quantify fluxes of dissolved CO₂ (pCO₂) and CO₂ emissions (fCO₂) in fluvial and lacustrine waterbodies located within the peat-bog dominated landscape of Western Siberia (ZOTTO area, 60^oN, 89^oE). For two consecutive years (2018-2019) we studied the seasonal and diurnal dynamics of pCO₂ and fCO₂ in several different order streams (1-4) and ponds within a peatbog. Dissolved pCO₂ was measured by portable IRGA Vaisala GMP222 placed in PTFE membrane. Carbon dioxide emissions were analyzed using floating chamber equipped with same portable IRGA (Vaisala GMP222). Despite, the pCO₂ values were highest in winter season (350-820 umol/l) we did not detect sizeable emissions from water surface in that period. The peaks of pCO₂ in summer-fall season (up to 360 umol/l) occurred at stormflow regimes. The frost-free season emission of CO₂ from stream surfaces ranged from 0.2 to 7.5 umol/m²/s and decreased with the order of stream. An averaged for the season CO₂ evasion from the Razvilki stream (2^nd order stream) was 4.9±1.3 umol/m²/s, which is comparable to the seasonal mean of soil CO₂ emissions in the study area. However, in opposite to soil respiration, which maxima often corresponds to highest soil temperatures, peaks of CO₂ outgassing occur at high flow regimes. The fCO₂ values were correlated with discharge (r = 0.60, p<0.05) and DOC concentrations (r = 0.69, p<0.05). Aquatic C losses are still under analysis in terms of surface water area estimation.

How to cite: Anatoly, P., Alexey, P., Daria, P., Anastasia, U., and Jan, K.: The outgassing of carbon dioxide from aquatic ecosystems of Western Siberia (ZOTTO area) and implications for the regional carbon budget, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12485, https://doi.org/10.5194/egusphere-egu2020-12485, 2020.

Climate changes can cause a change of pattern of the atmospheric interaction between polar and middle latitudes, which can cause a change in the cyclone formation regime, which in turn can provoke extreme and hazardous phenomena intensification. Therefore, it is essential to understand the nature of the atmospheric interaction in question clearly.

Due to climatic features, it is precisely in the Siberian part of Eurasia that the most extensive snow cover forms, causing significant radiation cooling in this territory. The snow cover area, and consequently the intensity of radiation cooling, can vary significantly from year to year. It can make a significant impact on the interaction of the troposphere and lower stratosphere of middle and Arctic latitudes not only during the establishment of snow cover but also in the following winter season. Knowledge of the features and patterns of the manifestation of the influence of local disturbances (arising on the surface in the autumn due to the formation of autumn snow cover) on the atmospheric conditions of the following winter can be used as additional information when making seasonal weather forecasts.

The present study aims to assess the response of the troposphere and lower stratosphere over Northern Eurasia during the autumn-winter period to a rate of the snow cover formation in Siberia.

We separated the years with the sharp intensive and smooth slow snow cover formation. We analyzed for them the baroclinicity index and its components (the zonal and meridional potential temperature gradient and the Brent-Väisälä frequency) for various isobaric levels (up to 200 hPa), and Eliassen-Palm flux. The results obtained suggest that anomalies in the snow cover formation rate in Siberia can contribute and cause anomalies in atmospheric circulation in the autumn-winter period. However, there is no complete clarity regarding the mechanism of distribution of this influence.

This work was supported by the Russian Science Foundation grant No. 19-17-00248.

How to cite: Martynova, Y. V. and Krupchatnikov, V. N.: Interseasonal impact of Siberian snow cover formation rate on the baroclinicity and wave activity over Northern Eurasia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10114, https://doi.org/10.5194/egusphere-egu2020-10114, 2020.

This observational study reports variations of surface fluxes (turbulent, radiative, and soil heat) and ancillary atmospheric/surface/soil data based on in-situ measurements conducted at Mukhrino field station located in the middle taiga zone of the West Siberian Lowland. We estimated carbon dioxide flux and energy budget in a typical wetland of the western Siberian based on July measurements in 2019. Turbulent fluxes of momentum, sensible and latent heat, and CO₂ were measured with the eddy covariance technique. The footprint of measured fluxes consisted of a homogeneous surface with tree-covered and smooth moss-covered surface. Measurements in the atmosphere were supplemented by measurements of heat flux through the soil, net radiation components and soil temperature at several depths. Turbulent heat fluxes (sensible and latent) show a diurnal variation typical of land ecosystems, being in phase with net radiation. Most of the available energy is released as latent heat flux, while maximum sensible heat fluxes are more than 3 times lower. Net CO₂ sink was high but was typical for a wetland area. The influence of moss cover on the temperature regime of soil is considered. Based on soil temperature and heat flux measurements the thermal conductivity of moss layer was estimated. The thermal and dynamic roughness lengths of the moss-covered surface in the summer were also studied. The dependence of the dynamic roughness length on the atmospheric stability is established, and the coefficients relating the ratio of thermal and dynamic roughness length to the roughness Reynolds number are determined. The parametrizations obtained in this work can be used in Earth System models to represent wetland surfaces. The work was supported by RFBR grant 18-05-60126.

How to cite: Repina, I., Stepanenko, V., and Artamonov, A.: The energy budget of West Siberian wetland in summer, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3851, https://doi.org/10.5194/egusphere-egu2020-3851, 2020.

How to cite: Xia, S., Meng, Z., Teng, J., and Yu, X.: Carrying capacity of winter geese in the largest freshwater floodplain in different hydrological scenarios, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6249, https://doi.org/10.5194/egusphere-egu2020-6249, 2020.

In 2019 three Ukrainian institutions (Taras Shevchenko National University of Kyiv, Ukrainian Hydrometeorological Institute and Odessa State Environmental University) joined the Pan-Eurasian Experiment (PEEX). This can be considered as a practical result of implementation of the Erasmus+ international educational project of ‘Adaptive Learning Environment for Competence in Economic and Societal Impacts of Local Weather, Air Quality and Climate’ (ECOIMPACT) being in line with the ideology of PEEX (research – research infrastructure – education) and covering part of the project’s geographic region.

Inclusion of the Ukrainian institutions in the project will make it possible to develop studies into climate change issues, their impact on air quality, dynamics of carbon cycles in ecosystems, biodiversity loss, greenhouse gas emissions and forest fires, public health, chemization of industry and agriculture, food provision, energy production and access to fresh water in Ukraine –  all those tasks which are designated as priority ones in the PEEX project.

Under the framework of Infrastructure subprogramme of the PEEX, Ukrainian partners plan to create a long-term research infrastructure to consist of an extensive network of research stations, being only standard meteorological stations so far. Unfortunately, in Ukraine there are no FluxNet micrometeorological stations, let alone flagship research stations, to provide for measurement of a complete set of characteristics of the ecosystem-to-atmosphere interaction.

Having regard to the joint research plan of the Ukrainian project partners for 2020 it is supposed to revise the capacities of the existing network of hydrometeorological stations and the feasibility of its expansion by means of automatic weather stations ‘Inspector-Meteo’ (AWS-IM) and air quality transmitters ‘Vaisala’ AQT-420 available at three Ukrainian universities as a result of the Erasmus+ project ECOIMPACT, as well as acquisition of data from the network of automatic stations of the Ukrainian company IT-LYNX, which established a network of 55 AWS-IM for agribusiness purposes. The AWS-IM will expand the range of standard meteorological observations, and supplementation of it with models of environmental processes will make it possible to simulate the state of natural and man-made ecosystems in spatial and temporal scales.

It is additionally proposed to include AQT-420 transmitters available to the three Ukrainian universities due to the acquisition under the Erasmus+  project ECOIMPACT into the programme of monitoring air quality in large cities of Ukraine, with a view to the probable subsequent co-operation with the MegaSense project.

A detailed research plan of the Ukrainian participants for PEEX programme collaboration for the year 2020 is to be presented at the PEEX Inter- and Transdisciplinary Session at the EGU General Assembly.

Participation of Ukrainian universities, being the project partners in the PEEX educational subprogramme Transfer of Knowledge, is also important in order to provide training for a new generation of researchers in Ukraine who will use the new opportunities and tools gained over the course of implementation of the PEEX programme, including those ones that could be aimed at adaptation, mitigation of the climate change effects as well as dissemination of new knowledge and technologies acquired under the project to all concerned decision makers and the wider public.

How to cite: Stepanenko, S. and Polovyi, A.: Participation of Ukrainian Educational and Research Institutions in Implementation of the Tasks of the Pan-Eurasian Experiment (PEEX), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5907, https://doi.org/10.5194/egusphere-egu2020-5907, 2020.

MODEST (Modernization of Doctoral Education in Science and Improvement Teaching Methodologies) is a new capacity building project funded by the Erasmus+ programme. The project is coordinated by the University of Latvia. There are three other EU partners (from Finland, Poland and the United Kingdom) and a total of ten partners from three partner countries (Russia, Belarus and Armenia). Aims of the project include:

The work is carried out in three phases: preparation, development, and dissemination & exploitation. In the preparation phase, a detailed analysis of organization of doctoral studies and research management structures is done in both EU and partner countries. The development phase includes preparation of training materials, a series of study visits and training sessions, and creation of DTC’s. The dissemination & exploitation phase includes open access learning material, dissemination conferences, publications and workshop/conference presentations, as well as events and open resources for stakeholders, policymakers, students and the general public.To partly serve similar purposes as MODEST, University of Helsinki and Russian State Hydrometeorological University have introduced a new project, PEEX-AC (PEEX Academic Challenge). The aims of PEEX-AC are to share knowledge and experience, to promote state-of-the-art research and educational tools through organization of research training intensive course on “Multi-Scales and -Processes Modelling and Assessment for Environmental Applications”, to improve added value of research-oriented education in Finnish and Russian Universities, and to boost the PEEX international collaboration.The MODEST and PEEX-AC projects serve as a great examples of transfer of good practices in higher education, especially on doctoral level, but they also create new connections for educational and scientific collaboration. From the PEEX perspective, MODEST is an important initiative strengthening connections between European universities and institutions in Russia, Belarus and Armenia. The project will continue until autumn 2022.

How to cite: Lauri, K. A., Karppinen, S., Mahura, A., Vesala, T., Petaja, T., Skendere, I., and Obukhova, I.: Transfering best practices of doctoral training between EU, Russia, Belarus and Armenia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22604, https://doi.org/10.5194/egusphere-egu2020-22604, 2020.

In a transdisciplinary and pan-region programme like PEEX, building a strong communications platform with an efficient reach across countries is vital to foster collaborations, announce local findings or events to a wider audience, and build a sense of international community. In addition to its website, PEEX offers a quarterly e-newsletter and online Blog to its community.

The PEEX e-newsletter is sent to ~650 international subscribers, where the majority of readers come from Russia, China, Northern Europe and the USA. It is particularly important given that China and Russia have their own national social media channels like Weebo, WeChat and VK, which are popular alternatives to Twitter, Facebook or Instagram. Thus, having an online platform that integrates readers from Russia and China is vital for information exchange.

In addition to having an international readership, your article contribution to the PEEX Blog and e-newsletter facilitates your own efforts of dissemination. All articles have their unique web link, hosted in the PEEX blog, and hence can be embedded in your own research group’s website, news, social media accounts, etc.

The PEEX blog and newsletter welcomes articles from early career scientists. Great examples of these include field work stories that communicate the research aim but also the infrastructure or instrumentation available across the PEEX domain. Additionally, it provides a training opportunity for students to write popular scientific articles.

UArctic and FutureEarth are both partner programmes of PEEX. As the PEEX newsletter evolves, the aim is to integrate more overlapping relevant news and opportunities across these partners. Presently, UArctic shares the PEEX newsletter among its channels, as part of the thematic network the Arctic Boreal Hub.

Expanding the offer of channels for dissemination within the PEEX community and overall public will allow us to discuss science in a more collaborative, open and inclusive manner.

How to cite: Buenrostro Mazon, S., Borisova, A., Altimir, N., Mahura, A., and Lappalainen, H. K.: Communication channels to build a stronger PEEX network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15881, https://doi.org/10.5194/egusphere-egu2020-15881, 2020.