- Observations and measurement campaigns including the observation of optical properties of clouds and aerosols
- Radiative transfer in cloud-free and cloudy atmosphere including three-dimensional aspects and complex topography as well as radiative properties of the surface
- Parametrizations of radiation and clouds
- Modelling of radiation and clouds on all time-scales from nowcasting over short- and medium range numerical weather predication to decadal predictions and climate projections
- Verification of NWP and climate model outputs using satellite and ground-based observations
- Validation of satellite products using ground-based observations
- Use of modelled and observed radiation and cloud data in various applications such as renewable energy and agriculture.
Radiation in the atmosphere provides the energy that drives atmospheric dynamics and physics on all scales, from cloud particle growth to global weather and climate. Radiation schemes in global weather and climate models have to simplify the complex interaction of radiation with the Earth system. Capturing the interactions of gases and clouds with radiation is particularly challenging, since gas effects are extremely wavelength-dependent, while clouds vary strongly on small spatial and temporal scales, and they both interact strongly with radiation. Uncertainties in the radiation scheme and the cloud, aerosol and gas and inputs lead to uncertainties in weather and climate processes, such as energy balance, cloud development and dynamics.
The radiation scheme ecRad (Hogan & Bozzo 2018) has been operational in the IFS model at ECMWF since 2017 and in ICON at Deutscher Wetterdienst (DWD) since 2021 and will be the next radiation scheme in the operational numerical weather prediction models AROME and ARPEGE, the climate model ARPEGE-Climat and the regional research model Méso-NH at Météo-France. As a modular scheme, ecRad provides the opportunity to vary parametrisations and assumptions individually. Several options are available for the radiation solver, cloud vertical overlap and horizontal inhomogeneity treatment and cloud hydrometeor optical property parametrisations. The solver SPARTACUS is the only radiation solver in a global model that can treat 3D radiative effects. The new gas optics model ecCKD can improve both precision and cost of the gas optics calculation, as can recent code optimisations.
We will present the status of and future plans for implementation in the Météo-France models, and show first evaluation results for radiation, energy balance and clouds on various scales scales. We will also investigate the impact of cloud and aerosol input and search for the best settings for radiation balance, model energy and physics and forecast performance. Finally, we will present future plans for radiation work in the Météo-France models.
Reference:
Hogan, R. J., & Bozzo, A. (2018), A flexible and efficient radiation scheme for the ECMWF model. Journal of Advances in Modeling Earth Systems, 10, 1990-2008. https://doi.org/10.1029/2018MS001364
How to cite: Schäfer, S., Hogan, R., Rodier, Q., Libois, Q., Seity, Y., Roehrig, R., and Ukkonen, P.: First results and future plans for ecRad radiation in Météo-France models, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-172, https://doi.org/10.5194/ems2024-172, 2024.
Long-range transported mineral dust has a wide range of direct and indirect effects as a pollutant, nutrient and climate-forcer. On 21–23 February 2021, dust from a sand and dust storm in northern Africa was transported to Finland, north of 60°N. The episode was predicted 5 days in advance by the global operational SILAM forecast (silam.fmi.fi). The scavenging of dust by snowfall and freezing rain in Finland resulted in a rare case of substantial mineral dust contamination of snow surfaces over a large area in the southern part of the country. A citizen science campaign was set up to collect contaminated snow samples prepared according to the scientists’ instructions. The campaign gained wide national interest in television, radio, newspapers and social media, and dust samples were received from 525 locations in Finland, up to 64.3°N. The samples were utilised in investigating the ability of an atmospheric dispersion model to simulate the dust episode. The magnetic properties and mineralogy of the particles combined with modeling confirmed that dust came from a wide Sahara and Sahel area from 5000 km away. The modeled deposition area agreed well with the citizen observations and measured particle size distributions. Overall, our results revealed the features of this rare event and demonstrate how deposition samples can be used to evaluate the skills and limitations of current atmospheric models. Previously, a strong Saharan dust deposition in Finland has been documented for northern Finland in 1991. It is estimated that Saharan dust reaches Finland every year, but most often the dust remains in the atmosphere and deposits on the ground only seldom in Finland.
References
Meinander, O., Kouznetsov, R., Uppstu, A. et al. African dust transport and deposition modelling verified through a citizen science campaign in Finland. Sci Rep 13, 21379 (2023). https://doi.org/10.1038/s41598-023-46321-7
How to cite: Meinander, O., Kouznetsov, R., Uppstu, A., Sofiev, M., Kaakinen, A., Salminen, J., Rontu, L., Welti, A., Francis, D., A. Piedehierro, A., Heikkilä, P., Heikkinen, E., and Laaksonen, A.: Saharan dust in the Finnish atmosphere and on the ground: Citizen science to verify transport and deposition modeling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-323, https://doi.org/10.5194/ems2024-323, 2024.
High-resolution information on short wave radiation fluxes and sunshine duration is important for a wide range of applications in the context of energy and mobility transition, sustainable energy planning and climate change adaptation.
We present a comprehensively refactored and updated version of the solar radiation model STRAHLGRID. The broadband model is used to compute diffuse and direct solar radiation on both horizontal and real (inclined) surfaces, as well as the sunshine duration in a spectral range of 0.3-3 μm covering Austria‘s national territory. Model output is available on a near-real-time basis with a temporal resolution of 15 minutes and a spatial resolution of 100 x 100 meters. The model takes atmospheric turbidity, cloudiness and terrain shading into account. For an accurate representation of temporal variations in atmospheric turbidity, precipitable water and visibility fields from the nowcasting model INCA are included. Terrain characteristics (elevation, aspect, slope, horizon angle and sky view factor) are derived from a digital elevation model that has been aggregated to a spatial resolution of 100 m.
Model validation was conducted using quality controlled global solar radiation and sunshine duration data from 178 automatic weather stations in Austria as well as gridded reanalysis data sets. Comparisons with station data, COSMO REA 6 and CERRA reanalysis showcase the benefits of STRAHLGRID.
The model is used to provide input for modelling tasks on different temporal and spatial scales (e.g., combination with airborne laser scanning data to incorporate local shading effects) and to derive products related to solar energy applications (longterm means and variability).
This presentation covers the conceptual framework behind STRAHLGRID as well as the methods used for modelling, and offers insights to validation and usage of the dataset. The dataset is accessible through the GeoSphere Austria DataHub (https://data.hub.geosphere.at/) at daily resolution.
How to cite: Seitner, V., Göbel, M., Schlögl, M., and Olefs, M.: STRAHLGRID - A solar radiation model with applications across different spatial scales, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-366, https://doi.org/10.5194/ems2024-366, 2024.
The accurate forecasting of the solar irradiance is crucial for the grid stability, energy management, and maximizing the efficiency of the solar energy systems. The increasing reliance on solar energy as a key element of its renewable energy strategy highlights the need for accurate solar irradiance forecasting not only globally but also in South Korea. However, the variability of solar irradiance greatly influenced by the weather conditions poses challenges to its integration into the energy grid. To address this issue, we simulate two numerical weather prediction models---Weather Research and Forecasting (WRF) and WRF-Solar---during high-demand summer seasons for electricity and then utilize various observational data, such as satellite and in-situ measurements, to investigate the prediction performance of the solar irradiance. The WRF-Solar model was specialized for the solar irradiance prediction and fully integrates cloud-aerosol-radiation feedback to enhance solar irradiance prediction performance. Through the evaluation of these models, we aim to enhance the prediction accuracy of the solar irradiance in South Korea. Preliminary findings indicate that WRF-Solar exhibits better performance compared to the WRF model in South Korea. These results emphasize the potential benefits of integrating the solar radiation physics and specialized algorithms into forecasting models. By doing so, WRF-Solar shows potential in overcoming the challenges associated with solar irradiance forecasting. In the future, we need more research to better understand the abilities and limitations of WRF-Solar, and to improve its forecasting accuracy. With this knowledge, we can make solar irradiance predictions more accurate and help solar energy grow in South Korea.
How to cite: Yoon, J. W., Kim, H., Lee, S., and Park, S. K.: Comparative Evaluation of WRF and WRF-Solar for solar irradiance in South Korea, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-802, https://doi.org/10.5194/ems2024-802, 2024.
Meteorological conditions significantly affect the frequency and duration of air pollution events. A large number of studies have shown that atmospheric circulation driven and regulated by various external forcing factors can affect haze pollution by influencing meteorological variables related to haze pollution. Since changes in external forcing factors usually precede circulation, they can be used as precursors to predict haze pollution. This study analyzed the spatiotemporal variations of PM2.5 concentration anomalies over the past 39 years (1980–2018) in winter (November to January) over eastern China based on the empirical orthogonal function (EOF) method. Regression analysis is conducted on external forcing factors such as sea ice, sea temperature, and snow cover in the pre-autumn (September to October) using the time series of the first three modes. Nine key factors were selected, which further led to establishing a model for predicting winter PM2.5 concentration in eastern China using the long short-term Memory deep learning algorithm (LSTM). Independent verification revealed that the predicted and observed PM2.5 concentration distributions were consistent, with the absolute value of deviation within 15 μg·m−3 between 2016 and 2018. The correlation coefficients between the predicted and observed values were between 0.42 and 0.93 over eight key cities in the past 10 years (2009–2018). The contribution rates of the nine factors to PM2.5 concentration were calculated to explore their impact on PM2.5 concentration during winter. The Arctic sea ice (ASI) was found to be the key contributor to the winter PM2.5 concentration in eastern China. The predictors can be monitored in real time; hence, the model provides a real-time predictive tool, improving the prospects of predicting seasonal PM2.5 pollution, especially in vulnerable regions such as eastern China.
How to cite: Ma, J.: Climate modulation of external forcing factors on air quality change in Eastern China: implications for PM2.5 seasonal prediction, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-60, https://doi.org/10.5194/ems2024-60, 2024.
The European Partnership on Metrology (EPM) joint research project BIOSPHERE investigates how the increasing ionization of the atmosphere, caused by extraterrestrial radiation fields (cosmic rays and solar UV radiation) and amplified by anthropogenic emissions, affects the human and ecological health of our planet. One main aspect is how these extraterrestrial radiation fields impact the stratospheric ozone (enforced depletion), resulting in an increase of Ultraviolet (UV) radiation on the ground.
To assess the influence of extraterrestrial radiation fields on atmospheric parameters and on solar UV radiation on the Earth surface, BIOSPHERE organizes four measurement campaigns with colocated SCR (Secondary Cosmic Rays) measurements (revealing the cosmic rays events) and solar UV radiation measurements, in GHI (global horizontal irradiance) and DNI (direct-sun normalized irradiance) geometries of observation. From the DNI UV radiation measurements we extract some atmospheric parameters: the total ozone column (TOC) in dobson units (DU) and the aerosol optical depth (AOD) for the UV wavelength range (290 nm - 400 nm).
The measurement campaigns took place at Athens (near urban site) in summer, in Brussels (urban site) in winter, in Milesovka (Czech Republic, rural mountain site) in spring/summer and will take place in Lindenberg (North-East Germany, rural flatland site) in autumn.
In addition to the correlation study confronting SCR measurements to TOC, AOD and UV measurements, we focus here on the quality of the UV radiation and atmospheric parameters’ measurements during the first campaigns: UV radiation (GHI) and especially the UV index from spectroradiometers (array spectrometers: Gigahertz-Optik BTS2048-UV-S-WP, Bentham DTMc300 double monochromators) are compared to measurements from UVB pyranometers and a multi-channel filters radiometer (GUV-511 from BIOSPHERICAL Inc.) on the same site. TOC and AOD measurements done with UV DNI spectral measurements with an array spectrometer (Gigahertz-Optik BTS-Solar based on BTS2048-UV-S-WP) are compared to Brewer and photometer measurements done on geographically close sites. This survey analyzes the measurement differences, considering the instrumentation itself, the measurement retrieval procedures, and the spatial heterogeneity of the atmospheric parameters when the measurements that are compared to each other are not done at the same site.
How to cite: Doppler, L., Bolsée, D., Van Laeken, L., and Zuber, R.: UV spectra and atmospheric parameters measured with ultraviolet solar radiation instruments in EURAMET BIOSPHERE campaigns, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-803, https://doi.org/10.5194/ems2024-803, 2024.
The Cloud-Aerosol Transition Zone (TZ) corresponds to particle aggregates showing properties between that of cloud and clear air (though containing some aerosol load). Its potential impact on Earth's radiation budget is becoming increasingly recognized. Furthermore, its characterisation is also crucial to better understand aerosol-cloud interactions and improve satellite retrieval of aerosol properties. This study aims to evaluate the extent and vertical distribution of TZ aggregates for different cloud regimes using the cloud-aerosol discrimination (CAD) score of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the CALIPSO satellite. The CAD score classifies clouds and aerosols by the probability density functions of attenuated backscatter (AB), total colour ratio (TCR), volume depolarization ratio (VDR), altitude and latitude. The TZ has been assessed similarly to Fuchs and Cermak (2015), by quantifying the detected layers within the no-confidence range (NCR; CAD values between ─20 and 20) and applying several filters, such as analysing only tropospheric features and applying an IAB QA factor threshold (integrated attenuated backscatter quality-assured above a feature). As shown in previous literature, the AB-TCR and AB-VDR distributions of the detected features present an overlap between the characteristics of clouds and aerosols, and the CAD algorithm tends to classify uncertain features as clouds to avoid cloud contamination in aerosol profiles. This methodology has enabled us to identify the heights and regions where the TZ is most prevalent, as well as the vertical distribution of clouds and aerosols. For instance, we have observed that most NCR values are located near cloud edges, smoke plumes and dense dust. This result is based on the analysis of several retrievals within the same ground track across the southeastern Atlantic Ocean coast (the region with the highest NCR values) where stratocumulus, deep convective clouds, and high aerosol loads from biomass burning are prevalent. The vertical distribution analysis has revealed that there are more NCR detections at low altitudes (below 3 km) than over 6 km. On the other hand, in the horizontal direction most TZ aggregates are found within the first 15 km from the nearest high confidence cloud (CAD score over 70), with higher frequencies closer to the cloud.
Acknowledgements
This study has been funded through project NUBESOL-2 (PID2019-105901RB-I00) of the Spanish Ministry of Science and Innovation (MICINN). Jaume Ruiz de Morales is supported by an IFUdG-AE 2022 fellowship.
References
Fuchs, J., & Cermak, J. (2015). Where Aerosols become clouds - Potential for global analysis based on CALIPSO data. Rem. Sens., 7(4).
How to cite: Ruiz de Morales, J., Andersen, H., Calbó, J., Cermak, J., Fuchs, J., González, J. A., and Sola, Y.: Using CALIPSO to characterise the Cloud-Aerosol Transition Zone, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-680, https://doi.org/10.5194/ems2024-680, 2024.
Clouds are vital for Earth's radiative balance and affect industrial sectors like solar energy, airports, and ground-to-space
optical communication. Cloud cover day and night measurement uncertainties persist due to subjective observations.
Various ground instruments like radiometers and ceilometers offer improved accuracy, while infrared all-sky cameras
like the Sky InSight™ offer more granular cloud cover descriptions. We aim to compare cloud cover data from these
methods and suggest ways to address any disparities.
We analyze cloud cover time series from the NOAA Surfrad Radiation Budget Network (SURFRAD) Table Mountain site
in Boulder, Colorado, USA, for 2023. Data are collected using a pyrgeometer (Eppley’s PIR), pyranometers (diffuse - Eppley 8-48, global - Spectrosun SR-75), a ceilometer (Vaisala’s CL51), and an infrared all-sky camera (Reuniwatt’s Sky InSight™). Different methodologies are
applied depending on the instrument used. For the radiometers, we utilize the existing NOAA RadFlux product (Riihimaki
et al. 2019). For the ceilometer, we calculate a weighted average of low-mid cloud occurrences over the previous 30 minutes
following the approaches in Wagner et al. (2015). With the Sky InSight™, we employ the provided cloud mask image
and compute the ratio of cloudy pixels over the total number of pixels with a zenith angle below 70°, as well as on a
narrow view close to the zenith used to emulate a ceilometer.
The predominant readings are clear skies (0 and 1 octa) or overcast (7 or 8 octas), accounting for 70.1% of cases for
the pyrgeometer, 87.8% for the ceilometer, and approximately 76.1% for the Sky InSight™ hemispherical and ground
cloud covers. Overall, cross-instrument accuracy within one octa across all methods ranges between 70% and 75%,
although this must be considered in the context of the high occurrence of clear and overcast skies at the site. For
partial cloud cover cases (octas 2-6), cross-instrument accuracies drop to 25%-46%, with the ceilometer showing the
most divergence and the camera and pyrgeometer tending to agree more often. The camera emulation of a
ceilometer significantly improves agreement between the two instruments, suggesting between 25% and 35% of the
ceilometer’s variance is due to the reduced field of view and averaging window.
Analysis reveals that ceilometer measurements often miss cloud edges or gaps in the cloud cover due to their narrow
spatial constraints, making partial cloud cover readings less frequent. They are also more sensitive to optically thin
clouds than the other instruments. Conversely, while both the camera and pyrgeometer are sensitive to the entire sky
dome, the latter tends to underestimate cloud cover for thin overcast skies (altostratus), whereas the former may miss
some high-altitude cirrus clouds.
How to cite: Ben Slama, M., Liandrat, O., Balmes, K. A., Riihimaki, L. D., Hodges, G. B., and Schmutz, N.: Comparison of cloud cover measurement techniques, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-243, https://doi.org/10.5194/ems2024-243, 2024.
In 2014 the Catalan Weather Service started in some of the weather observatories in Catalonia the systematic daily observation of clouds caused by human activities (Mazon et al., 2012), the homogenitus clouds defined by the WMO in 2017 (https://cloudatlas.wmo.int/en/homogenitus.html ). It was a pioneer initiative that aimed to account by direct observations the contribution of human activities to the cloud cover. After 10 years of systematic observations, a daily homogenitus clouds observation database has been built in one of these observation locations, la Selva del Camp observatory (located near 100 km south to Barcelona city). By using this datase, two analysis have been performed. The first one has been a statistical analysis, focused on the high homogenitus clouds, caused by aircrafts. The analysis has been done at different temporal scale, from daily, to annual and interannual, which allows us to quantify the average percentage of cloud cover by high clouds produced by aircrafts (contrails), and the annual and seasonal trend within this period. The second analysis focusses on those days with contrails covering more than 2 and 3 octas. A synoptic and temperature analysis has been done at sea level, 850 and 500 hPa of geopotential height during the previous days and the day of the peak of the anthropic clouds, which allows to stablish the relationship between extreme events of high anthropic clouds and geopotential height at 850 and 500 hPa.
Mazón, J., Costa, M., Pino, D. and Lorente, J. (2012), Clouds caused by human activities. Weather, 67: 302-306. https://doi.org/10.1002/wea.1949
How to cite: Costa, M., Escoda, J., Mazon, J., Pino, D., Ripoll, R., and Del Amo, X.: Analysis of the 10-years daily observation of homogenitus clouds in Catalonia (2014-2024)., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-432, https://doi.org/10.5194/ems2024-432, 2024.
The importance and impact of clouds on the surface radiation balance has been much discussed in recent research. Estimation of cloudiness mostly relied on human observers for many years, before measurements from satellites, sky cameras, ceilometers and lidars became available. Yet, despite these tools, evaluation in polar regions still remains difficult because of a relative lack of measurements. Throughout the years several methods to evaluate cloudiness from surface broadband radiation measurements, both shortwave and longwave, have been developed. They are able to provide information on cloudiness where direct observations are lacking. Furthermore, combining all-sky broadband radiation measurements and clear sky estimates, the cloud radiative effect on the surface radiation budget can be estimated. In this work we present the challenges of the implementation of such methods for Antarctica using measurements from seven stations representing different geographic areas of the continent. Marambio (64°14’50’’S - 56°37’39’’W, 196 asl) and Professor Julio Escudero (62°12’57’’S - 58°57’35’’W, 10 asl) stations are located in the Antarctic Peninsula; Concordia (75°05’59’’S – 123°19’57’’E, 3233 asl) and Amundsen-Scott South Pole (90°S – 0°E, 2835 asl) stations in the Antarctic Plateau; Shōwa (60° 0’ 25.1’S - 39° 35’ 1.5’’E, 29 asl), Neumayer III (70°41’00’’S - 08°16’00’’W, 43 asl) and Jang Bogo station (74°37’38’’S - 164°14’16’’E, 36.6 asl) are in the East Antarctica coastal sector. Four belong to the Baseline Surface Radiation Network[1], and therefore collect high quality measurements for all radiation components following specific quality standards. We will illustrate how to apply different methods for deriving cloudiness parameters radiometrically using these data sets. To maximize the information that can be obtained at the different sites, the evaluated methods are: Kasten and Czeplak[2], Long[3], BrightSun[4], RADFLUX[5], APCADA[6], Van den Broeke[7], and Solomon[8]. The last four are based on (or include) longwave and meteorological data and are particularly useful in Antarctica for their potential to provide data during the polar night and at unstaffed locations.
Bibliography
[1] Driemel et al. (2018): Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017). doi: 10.5194/essd-10-1491-2018
[2] Kasten and Czeplak (1980): Solar and terrestrial radiation dependent on the amount and type of cloud. doi: 10.1016/0038-092X(80)90391-6
[3] Long et al. (2006): Estimation of fractional sky cover from broadband shortwave radiometer measurements. doi.org: 10.1029/2005JD006475
[4] Bright et al. (2020): Bright-Sun: A globally applicable 1-min irradiance clear-sky detection model. doi: 10.1016/j.rser.2020.109706
[5] Riihimaki et al. (2019): Radiative Flux Analysis (RADFLUXANAL) Value-Added Product [...] . doi: 10.2172/1569477
[6] Dürr and Philipona (2004): Automatic cloud amount detection by surface longwave downward radiation measurements. doi: 10.1029/2003JD004182
[7] Van Den Broeke et al. (2004): Surface radiation balance in Antarctica as measured with automatic weather stations. doi: 10.1029/2003JD004394
[8] Solomon et al. (2023): The winter central Arctic surface energy budget: A model evaluation using observations from the MOSAiC campaign. doi: 10.1525/elementa.2022.00104
How to cite: Frangipani, C., Ahn, S., Choi, T., Cordero, R., Cox, C., Di Carlo, P., Gulisano, A. M., Lanconelli, C., Lupi, A., Mazzola, M., Ochoa, H. A., Riihimaki, L., Rowe, P., Vitale, V., and Wacker, S.: Estimation of cloudiness in different areas of Antarctica from broadband radiation measurements , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-535, https://doi.org/10.5194/ems2024-535, 2024.
The BSRN site was established at the Meteorological Observatory Lindenberg – Richard Aßmann Observatory (MOL-RAO) of the German Meteorological Service (DWD) in 1994. Since then, incoming shortwave and longwave irradiances have been observed continuously and with high accuracy. We will discuss the methods of operations and the uncertainties of the observations.
The primary applications of the BSRN data are the i) validation of climate model projections and surface products derived from satellite data, and ii) monitoring of the shortwave and longwave radiative components and their changes with the best methods currently available. We will present such results from the radiation records. While the observed increase in the incoming longwave radiation of 3.5 Wm-2 per decade due to increasing air temperature, humidity and greenhouse gas concentrations is consistent with the corresponding projections from climate models, the interpretation of the continuous increase in total solar irradiance of 3.5 Wm-2 per decade since the 1990s - referred to as brightening - is more complex. The first period of this brightening may be solely attributed to the decrease in the aerosol load. However, aerosol loads have then stabilized at low levels at the beginning of the 21th century and thus the direct aerosol effect might have been less dominant in recent years. Instead, changes in cloudiness may have become more important. Indeed, calculations of the cloud radiative effect indicate a decrease in the magnitude over the past 30 years, which may imply a decrease in cloud cover, a shift towards a different cloud type and/or changes in microphysical cloud properties. However, these results are related to substantial uncertainties and thus are not conclusive.
How to cite: Wacker, S. and Becker, R.: 30 years of observations of incoming radiative fluxes at the Lindenberg BSRN site: methods, applications and results, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-945, https://doi.org/10.5194/ems2024-945, 2024.
The aim of this presentation is to give an overview on the state of our knowledge on decadal changes in surface radiative fluxes, with a focus on both shortwave and longwave changes. With respect to changes in the shortwave, the focus will be on recent studies on the solar dimming and brightening phenomenon. This phenomenon refers to the increasing evidence that solar radiation at the Earth’s surface is not stable over time, but undergoes substantial multidecadal variations (i.e., dimming and brightening). An inadequate representation of these effects in climate models can for example lead to an inaccurate reproduction of the observed decadal warming rates, as evidenced in different studies. A growing number of studies assess the magnitude of dimming and brightening also in remote areas. Artificial intelligence methods have recently been applied in attempts to expand station data information over larger areas. Studies using methods to filter out clouds in the observational data records allow for more insight into the relative contribution of direct aerosol and cloud effects to the dimming and brightening trends. Modelling studies help to quantify the contribution of unforced climate system-inherent variability to this phenomenon, and provide projections of future availability of the solar resource e.g. for energy applications.
In the longwave, climate models simulate an increase in downward longwave radiation at the surface at a rate of approx. 2 Wm-2 / decade under current forcings globally, due to the enhanced greenhouse effect. Current model projections suggest that this rate will increase or decrease over the coming decades depending on future emission scenarios. Reanalyses suggest an increase of around 1.5 Wm-2 over recent decades. This is supported by station observations from the Baseline Surface Radiation Network (BSRN), which overall also indicate an increase in downward longwave radiation over recent decades.
How to cite: Wild, M.: Decadal Changes in Surface Radiative Fluxes , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-201, https://doi.org/10.5194/ems2024-201, 2024.
The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates and distributes high quality long-term climate data records (CDR) of energy and water cycle parameters, which are freely available.
The incoming surface solar radiation is an essential climate variable as defined by GCOS. Long term monitoring of this part of the earth’s energy budget is required to gain insights on the state and variability of the climate system.
The CM SAF SARAH-3 climate data record is based on satellite observations from the first and second METEOSAT generations and provides various surface radiation parameters, including global radiation, direct radiation, sunshine duration, photosynthetic active radiation and others. The SARAH-3 climate data records are accompanied by a corresponding near-realtime processing (so-called interim climate data records). With that, SARAH-3 covers the time period since 1983 with a timeliness of 1 day and offers 30-minute instantaneous data as well as daily and monthly means on a regular 0.05° x 0.05° lon/ lat grid. SARAH-3 enables a wide range of applications – from operational climate monitoring and model verification to renewable energy assessments.
The presentation will include validation and climate analysis of the SARAH-3 surface solar radiation parameters. A focus will be on the assessment of the temporal stability of the data record by comparison to alternative data records and surface reference measurements. Further, the climate variability and trends of the surface solar radiation will be analyzed. SARAH-3 reveals that there is a positive trend of surface solar radiation in Europe during the last decades, superimposed by decadal and regional variability. Also, potential causes for the found variability and trends (clouds, aerosols) will be discussed. Finally, an outlook on planned further developments will be given.
How to cite: Pfeifroth, U. and Trentmann, J.: Analyzing climate variability of surface solar radiation parameters from the CM SAF SARAH-3 climate data record , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-989, https://doi.org/10.5194/ems2024-989, 2024.
The shortwave (SW) feedback to El Niño–Southern Oscillation (ENSO) is one of the largest biases in climate models, as the feedback includes atmosphere–ocean interactions and cloud processes. In this study, the performance of SW feedbackover tropical Pacific in 19 models from the 6th Coupled Model Intercomparison Project (CMIP6) is evaluated against observations or reanalysis datasets, and the biases are attributed using the historical and Atmospheric Model Intercomparison Project (AMIP) runs and two coupled assimilation experiments. The results demonstrate that while superior to CMIP5 counterparts, most CMIP6 models still underestimate the strength of SW feedback to different degree. The underestimates of SW feedback arise mainly from the biased feedbacks to El Niño in the four models with relatively better skills, while from both underestimated negative feedbacks to El Niño and overestimated positive feedbacks to La Niña in other models, which reproduce better seasonal variations than corresponding CMIP5 models. Furthermore, the SW feedback bias is connected to weak convective/stratiform rainfall feedback, which is sensitive/insensitive to sea surface temperature (SST) biases during El Niño/La Niña. The total rainfall feedbacks and dynamical feedbacks are underestimated in the historical runs, more than in CMIP5, and shows close relationship with each other. Finally, several data assimilation experiments are conducted using FGOALS-g3, one of models in CMIP6 model ensemble, and the Dimension-Reduced Projection Four-Dimensional Variational (DRP-4DVar) data assimilation system to verify the causes and relationships between feedbacks and mean states, further conclusiona are made.
How to cite: Huang, J., Li, L., He, Y., Ran, H., Liu, J., Wang, B., Feng, T., Chang, Y., and Liu, Y.: Evaluation and Attribution of Shortwave Feedbacks to ENSO in CMIP6 Models, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-42, https://doi.org/10.5194/ems2024-42, 2024.
Building a homogenous and reliable cloud climatology requires merging observations collected over decades with generations of satellites. Each generation introduces improved instrumentation, causing heterogeneity in terms of spatial, radiometric, and/or spectral resolution. Even if a specific spectral channel is preserved on different satellites (heritage bands), detailed characteristic of a channel may still be different among individual devices. Specifically, each sensor will reveal a different sensitivity to radiation of given vale length, a feature quantitatively defined by the sensor’s Spectral Response Function (SRF).
In this study we evaluate how the differences in SRFs impact the homogeneity of global cloud climatology. We focus on specific type of clouds (deep convective clouds, DCCs), and consider all generations of the Meteosat satellites that have been in service since 1977. Over that time Meteosats featured the three following imagers: MVIRI (Meteosat Visible Infra-Red Imager; first generation of Meteosat), SEVIRI (Spinning Enhanced Visible Infra-Red Imager; second generation), and FCI (Flexible Combined Imager; third generation).
In order to meet the study goal we simulate radiances for MVIRI, SEVIRI and FCI by convolving sensors’ SRF with a high-spectral-resolution data collected globally with the Infrared Atmospheric Sounding Interferometer (IASI) onboard MetOp satellite. Two infrared heritage channels of Meteosat are examined: the infrared window channel (IR, ~11 mm) and the water vapor absorption channel (WV, ~6.5 mm). Both are essential for DCC detection.
Based on simulated radiances we detect deep convective clouds examining brightness temperature difference between WV and IR channels. Whenever the difference is greater than 0K, an IASI pixel is flagged ‘DCC’. Then a DCC frequency is computed globally, and individually for MVIRI, SEVIRI and FCI. Statistics is developed for three summer months of 2013 (June-August).
The results demonstrate how much of a difference in DCC cloud amount between MVIRI, SEVIRI, and FCI may be attributed to a different spectral sensitivity in IR/WV for that sensors. More generally, we address the question how sensitive is a (DCC) cloud climatology to spectral evolution of clouds observing instrumentation.
This research was funded by the National Science Centre of Poland. Grant no. UMO-2020/39/B/ST10/00850.
How to cite: Wojciechowska, I. and Kotarba, A.: Sensitivity of deep convective cloud climatology to inconsistency of spectral response functions among various generations of satellite sensors, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-476, https://doi.org/10.5194/ems2024-476, 2024.
This study evaluates the performance of the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) in forecasting a mega Asian Dust Storm (ADS) event that occurred over Korea on March 28–29, 2021. Since the introduction of the ADS crisis warning system in Korea in 2015, a nationwide caution stage was announced for the first time in six years on March 29, 2021. We specifically evaluated a combination of parameterization schemes: five for dust emission and four for land surface schemes, which are crucial for the accurate numerical forecasting of dust storms. Using in-situ and remote sensing data, we comprehensively evaluated meteorological and air quality variables, including 2 m temperature, 2 m relative humidity, 10 m wind speed, PM10, and aerosol optical depth (AOD) over Korea. Our results indicate that the prediction performance of surface meteorological variables was influenced more by the land surface scheme than by the dust emission scheme, with scheme combinations based on Noah land surface model with Multiple Parameterization options (Noah-MP) generally showing good performance. In contrast, in predicting air quality variables, including Particulate Matter 10 (PM10) and AOD, there was a very large difference in performance depending on the scheme combinations due to the influence of the dust emission scheme, which is directly related to the generation and amount of dust. Based on the evaluation results of various combinations of dust emission and land surface schemes in this study, we can suggest appropriate combination schemes for the WRF-Chem model in cases of mega ADSs affecting Korea.
How to cite: Yoon, J. W., Lee, S., Lee, E., and Park, S. K.: Numerical Sensitivity Study on a Mega Sand Dust Storm in Korea Using WRF-Chem, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-824, https://doi.org/10.5194/ems2024-824, 2024.
Geostationary Environmental Monitoring Spectrometer (GEMS), on-board Geostationary Korea Multi-Purpose Satellite-2B (GK-2B), is the first geostationary environmental instrument to be the Asian component of the global geostationary constellation for pollution monitoring together with the European Sentinel-4 and the North American Tropospheric Emissions: Monitoring of Pollution (TEMPO). GEMS is a hyper grating spectrometer that hourly measure backscattered solar spectral radiance from the ultraviolet to visible (300 to 500 nm) with 0.6 nm spectral resolution and 3.5 (7 for trace gases) * 8 km2 spatial resolution over the Seoul in the daytime. These radiances are used to retrieve spatial and temporal distributions of aerosol and trace gases such as O3, NO2, SO2 and HCHO. Since the performance of trace gas retrieval strongly depends on the quality of raw data, the in-flight characteristics have been analyzed and calibrated in detector, radiometric and spectral aspects. Furthermore long-term performance of GEMS have been monitored and analyzed for the dark current, electronic offsets, non-linearity, diffuser and the output of the internal light sources. The orbital performance of GEMS shows that the number of incurred dead and bad pixels due to cosmic-ray impacts is 0.05% increased over the three full year since the operations. The dark signal distributions of on-orbit dark images show 9.02% increased dark mean which indicates a gradually degraded detector CCD performance. The orbital electronic biases from averaging trailing pixels show quite stable status in orbit around 900-1050 counts depending on each quadrant. In-orbit PRNU (< 7%) and non-linearity(< 2%) of 5-95% CCD full well signals meet the system requirements and show stable status. However, there is a possibility that remaining 10% non-linearity effects on the shortwave signals under the 5% CCD full well in early morning or late afternoon. Trends over the three full year of nominal operations indicates stable status of GEMS with gradually degraded detector and diffuser performances. The detailed results and the orbital and long-term stability for internal light source (LED), dark currents and solar irradiance measurements are going to be presented.
How to cite: Eo, M., Ahn, M., Kang, M., and Lee, Y.: In-flight calibration and performance monitoring of Geostationary Environment Monitoring Spectrometer (GEMS), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1007, https://doi.org/10.5194/ems2024-1007, 2024.
The distribution of diffuse sky radiance over the sky hemisphere is frequently required in many fields and applications, like predicting the solar irradiance on sloped planes or titled solar collectors, quantifying the spectral angular effects on photovoltaics (PV) device performance, etc. Atmospheric clouds constitute the most dominant factor for solar radiation attenuation in the atmosphere, and their accurate representation in radiative transfer models is more than necessary. However, cloud information in radiative transfer models remains a challenging process characterized by uncertainties due to the incomplete knowledge of cloud optical properties, vertical structure, and their high spatiotemporal variability, reflecting high uncertainties in solar resource estimations. These uncertainties frequently stem from the use of two-dimensional (2D) information about clouds, like pixel-level image information from geostationary satellites. Radiative transfer calculations cannot neglect the inherent three-dimensional (3D) cloud structure in order to alleviate the uncertainties in the estimation of solar resource. In this study, we investigate the potential to derive the 3D morphology of clouds with a network of all-sky imagers. Their spatial displacement and synchronized exposure times provide the necessary information for a 3D reconstruction within the area around the cameras. The main objective is to combine, under different cloud conditions, the 3D reconstructed cloud fields and radiance measurements from all-sky imagers in radiative transfer simulations. In particular, the 3D reconstructed cloud fields will be used as input to 3D radiative transfer simulations (Monte Carlo code for the physically correct Tracing of photons In Cloudy atmospheres (MYSTIC) algorithm, included in the libRadtran software package) in order to calculate solar irradiance maps.
How to cite: Logothetis, S.-A., Panagopoulos, O., Tzoumanikas, P., Kosmopoulos, G., and Kazantzidis, A.: Solar radiation modeling under 3D reconstructed cloud fields, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-944, https://doi.org/10.5194/ems2024-944, 2024.
