Displays

AS2.8

Clouds play an important role in the polar climate due to their interaction with atmospheric radiation and their role in the hydrological cycle linking poleward water vapour transport with precipitation, thereby affecting the mass balance of the polar ice sheets. Cloud-radiative feedbacks have also an important influence on sea ice. Cloud and precipitation properties depend strongly on the atmospheric dynamics and moisture sources and transport, as well as on aerosol particles, which can act as cloud condensation and ice nuclei.

This session aims at bringing together researchers using observational and/or modeling approaches (at various scales) to improve our understanding of polar tropospheric clouds, precipitation, and related mechanisms and impacts. Contributions are invited on various relevant processes including (but not limited to):


- Drivers of cloud/precipitation microphysics at high latitudes,
- Sources of cloud nuclei both at local and long range,

- Linkages of polar clouds/precipitation to the moisture sources and transport,

- Relationship of the poleward moisture transport to processes in the tropics and extra-tropics, including extreme transport events (e.g., atmospheric rivers, moisture intrusions),

- Relationship of moisture/cloud/precipitation processes to the atmospheric dynamics, ranging from synoptic and meso-scale processes to teleconnections and climate indices,

- Role of the surface-atmosphere interaction in terms of mass, energy, and cloud nuclei particles (evaporation, precipitation, albedo changes, cloud nuclei sources, etc)
- Impacts that the clouds/precipitation in the Polar Regions have on the polar and global climate system, surface mass and energy balance, sea ice and ecosystems.

Papers including new methodologies specific to polar regions are encouraged, such as (i) improving polar cloud/precipitation parameterizations in atmospheric models, moisture transport events detection and attribution methods specifically in the high latitudes, and (ii) advancing observations of polar clouds and precipitation. We would like to emphasize collaborative observational and modeling activities, such as the Year of Polar Prediction (YOPP), Polar-CORDEX, the (AC)3 project on Arctic Amplification, SOCRATES, ACE and other campaigns in the Arctic and Southern Ocean/Antarctica, and encourage related contributions.

The session is endorsed by the SCAR Antarctic Clouds and Aerosols Action Group.


Public information:
Dear Authors,

Thank you all for your great contributions to this session. Hopefully, you have all already successfully uploaded your display material - if not please try to do it on Tuesday (before the Live Chat). If this is not possible - you can do it also during this month. Everyone in any case is welcome to participate in the Live Chat to share their work.

We invite everyone to check the posted material before our session's Live Chat, which is scheduled on 6 May, 08:30–10:15 (CEST=UTC+2). The Live Chat will be open from 8:15 to 10:45 CEST and is only by text chatting.

During the Live Chat we (conveners) will call the authors in the order of the Displays (which will be visible on the right from the chat's window) to shortly introduce their work (motivation.. main points..). It will be easier if everyone has this SHORT text prepared before hand. Please avoid copy/pasting the entire abstract, as all session participants have had the possibility to read the abstract and the posted material prior to the chat session. Then the chat will be open for questions and comments from all participants (we also recommend if possible to prepare your questions beforehand). With 21 abstracts we will have about 5 min to discuss each display.

If there are authors who are certainly not available to be present during the Live Chat - please let us know. You are also welcome to ask your co-authors or colleagues to present your work if the main author is not available at the chat time.

The Chat will be not recorded or stored. Only abstracts and displays will be available after this session. Everyone is welcome to post their comments directly to the Displays (commenting will be open until 1 June). This provides more freedom to discuss.

Looking forward to this new way of science sharing! Hope it goes smoothly:)

Best wishes to you all

Irina, Susanne, Manfred, Tom, Nicole

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Co-organized by CL2/CR7
Convener: Irina V. Gorodetskaya | Co-conveners: Susanne Crewell, Tom Lachlan-Cope, Nicole van Lipzig, Manfred Wendisch
Displays
| Attendance Wed, 06 May, 08:30–10:15 (CEST)

Files for download

Download all presentations (201MB)

Chat time: Wednesday, 6 May 2020, 08:30–10:15

Chairperson: Irina Gorodetskaya, Tom Lachlan-Cope, Susanne Crewell, Manfred Wendisch
D3024 |
EGU2020-2850<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
| solicited
Étienne Vignon, Josué Gehring, Simon P. Alexander, Georgia Sotiropoulou, Nikola Besic, Nicolas Jullien, Noémie Planat, Jean-Baptiste Madeleine, and Franziska Gerber

The current assessment of the Antarctic surface mass balance mostly relies on reanalysis products or climate model simulations. The ability of models to reproduce the precipitation field at the regional and continental scales not only depends on the simulation of the atmospheric dynamics over the Southern Ocean and of the advection of moisture towards the ice sheet, but also on the representation of the microphysical processes that govern the formation and growth of ice crystals and snowflakes. This presentation reviews recent studies to stress the importance and challenges of evaluating the precipitation microphysics over Antarctica in climate models. It also discusses how recent observational campaigns including ground-based remote-sensing instruments can help pinpoint key processes that should be represented in models. We then present tangible examples of evaluation and improvement of microphysical schemes in the Polar WRF model thanks to radar and lidar observations acquired near Dumont d’Urville and Mawson stations on the Antarctic coast. Particular attention is devoted to three processes : i) the sublimation of snowfall within the katabatic layer that considerably reduces the amount of precipitation that actually reaches the surface ; ii) the snowflake aggregation responsible for rapid depletion of crystals within clouds ; iii) the generation of supercooled liquid water in frontal clouds that leads to crystal/snowflake riming. Such studies, albeit preliminary, could pave the way for further evaluations of clouds and precipitation in climate models in different Antarctic contexts, especially in the cold and pristine atmosphere of the Plateau.

How to cite: Vignon, É., Gehring, J., Alexander, S. P., Sotiropoulou, G., Besic, N., Jullien, N., Planat, N., Madeleine, J.-B., and Gerber, F.: Microphysics of Antarctic precipitation in climate models : recent advances and challenges, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2850, https://doi.org/10.5194/egusphere-egu2020-2850, 2020

D3025 |
EGU2020-2603<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
| solicited
Heike Kalesse, Patric Seifert, Martin Radenz, Johannes Bühl, Teresa Vogl, Willi Schimmel, Andreas Foth, Audrey Teisseire, Holger Baars, Ronny Engelmann, Boris Barja, Jonas Witthuhn, Frank Stratmann, Albert Ansmann, and Felix Zamorano

The southern midlatitudes and Sub-Antarctica are a key region for the Earth’s climate and a source for uncertainties in climate modelling. The low concentration of ice nucleating particles is considered to diminish the efficiency of heterogeneous ice formation. Climate models underestimate the supercooled liquid water content which causes shortwave radiation biases.

The project DACAPO-PESO (Dynamics, Aerosol, Cloud And Precipitation Observations in the Pristine Environment of the Southern Ocean) which is being conducted in Punta Arenas (53°S, 71°W), Chile from Nov 2018 – March 2020 is endorsed by YOPP (Year of Polar Prediction) and fills an observational gap in the Southern Oceans, for which to date hardly any combined observations of lidar, cloud radar and microwave radiometer are available.

During that field experiment, LACROS (Leipzig Aerosol and Cloud Remote Observations System) of Leibniz Institute for Tropospheric Research (TROPOS) which comprises numerous remote sensing instruments, including multi-wavelength polarization Raman lidar, cloud radars, microwave radiometer, radiation sensors among others is deployed. From March 2019 onwards, additionally in-situ observations of the INP and cloud condensation nuclei properties were collected by TROPOS on a 623m high mountain 10 km upwind of the LACROS site. Meso-scale numerical modeling will provide support for interpretation of the results.

The presentation will be dedicated to

  1. a) provide an overview of the setup of DACAPO-PESO
  2. b) show case studies of how instrument synergies are used to characterize aerosol-cloud-interaction processes in the pristine atmosphere over Punta Arenas and
  3. c) show a case study of an Atmospheric River event which was also observed in Antarctica.

How to cite: Kalesse, H., Seifert, P., Radenz, M., Bühl, J., Vogl, T., Schimmel, W., Foth, A., Teisseire, A., Baars, H., Engelmann, R., Barja, B., Witthuhn, J., Stratmann, F., Ansmann, A., and Zamorano, F.: DACAPO-PESO: Remote Sensing and In-situ Observations in Sub-Antarctica (53°S,71°W) to Enhance the Understanding of Aerosol-Moisture-Cloud-Precipitation Interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2603, https://doi.org/10.5194/egusphere-egu2020-2603, 2020

D3026 |
EGU2020-12003<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
| Highlight
Linette Boisvert, Mircea Grecu, and Chung-Lin Shie

The Arctic climate system is undergoing rapid and drastic change in recent decades, with the thinning and loss of sea ice coverage and a warming and moistening atmosphere since the 2000’s; coining the term the ‘New Arctic’. This New Arctic ice pack is more vulnerable to external forcings, and with the increase in open water and warmer temperatures it is suggested that this could impact the moisture transport into the Arctic. In fact, all aspects of the hydrologic cycle are likely affected by and also feedback on these large and rapid changes in the New Arctic. However, the majority of the precipitation and moisture transported into the Arctic Ocean is that associated with cyclones, but one caveat is that the true magnitude of precipitation during these events remain uncertain, and a better understanding of the intensity, frequency, and phase of this precipitation is critically needed specifically for the freshwater and energy budget of the New Arctic.

 

Our work aims to track the moisture and precipitation associated with strong cyclones that terminate in the Arctic in order to improve our knowledge of the frequency, intensity and phase of the moisture, how and if it is changing in the New Arctic on an annual, seasonal and regional basis. In order to do this we will create a database of strong Arctic cyclone trajectories and Lagrangian track the moisture associated with them using ERA-Interim reanalysis. To balance the moisture budget we will constrain the net precipitation using NASA GPM precipitation and AIRS evaporation data at each time step. We propose a novel approach to achieve a more comprehensive, balanced moisture transport associated with Arctic cyclones in an Optimal Estimation and Lagrangian Framework (OELaF) allowing for the fundamental moisture processes associated with Arctic cyclones to be better observed and investigated. In this new work, we plan to apply this method with a few cyclones in the winter months of 2015-2017.

 

How to cite: Boisvert, L., Grecu, M., and Shie, C.-L.: Understanding moisture transport associated with strong cyclones in the New Arctic , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12003, https://doi.org/10.5194/egusphere-egu2020-12003, 2020

D3027 |
EGU2020-209<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Gesa Eirund, Ulrike Lohmann, and Anna Possner

Around the globe, clouds tend to organize into cellular patterns. This phenomenon has gained growing attention in recent years, mainly due to albedo changes associated with different cloud regimes. Transitions between cloud regimes can be impacted by environmental factors such as tropospheric moisture content, large-scale subsidence, surface temperature and the ambient aerosol concentration or, more locally, precipitation formation, turbulence and boundary layer characteristics. It has been suggested that cold pool formation caused by evaporative cooling of precipitation can induce small-scale overturning circulations that promote cloud cell growth in open-cell stratocumulus clouds.

Cloud organization has so far been primarily studied for the subtropical trade wind region or deep convective clouds. In the mid and high latitudes organized cloud structures have been attributed to frontal systems in low pressure systems or cold air outbreaks. However, cloud patterns are also observed away from these large-scale phenomena in the higher latitudes. As low-level clouds in the high latitudes are mostly mixed-phase, various processes can shape cloud formation, occurrence and breakup. Processes related to the ice phase remain poorly understood and especially with regard to cloud organization remain completely unexplored.

In cloud-resolving model simulations using COSMO-LES we investigate the processes driving organization in open-cell mixed-phase stratocumuli. Similar to warm-phase clouds, MPCs develop a sub-cloud circulation caused by evaporated/sublimated precipitation, cold pool formation, and consecutive updrafts driving new convective cells. For a larger ice to liquid water ratio, we find locally stronger precipitation and larger cloud cells. Hence, a higher concentration of ice nucleating particles can induce a breakup of the stratocumulus organization, with implications for the radiative balance at the surface. A decrease in cloud condensation nuclei concentration is also found to intensify precipitation and impact cloud organization.

How to cite: Eirund, G., Lohmann, U., and Possner, A.: Cloud ice processes enhance spatial scales of organization in Arctic stratocumulus, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-209, https://doi.org/10.5194/egusphere-egu2020-209, 2019

D3028 |
EGU2020-6138<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Kyle Fitch, Tim Garrett, and Ahmad Talaei
Riming is a critical process for both numerical modeling and microwave remote sensing because of the significant changes to hydrometeor shape and density that occur. Basic continuous collection theory invokes a simple model that assumes a relatively large, massive graupel falls through a homogeneous field of much smaller, suspended supercooled droplets in still air. However, numerous studies have shown that turbulence enhances the rate of collisions between liquid droplets, and even more so for graupel-droplet collisions. Modeling and observational studies of turbulence-induced riming enhancement have all focused on convective clouds with relatively large dissipation rates. Here we combine theoretical work on the analytical solutions of precipitation size distributions with observations and simulations of Arctic graupel to show that this enhancement is common in “thin” Arctic boundary layer clouds with LWP<50gm-2. The median enhancement of rime mass over that expected from continuous collection ranges from 6.4 to 10.7 (for collection efficiencies ranging from 1 to 0.6) for 1,628 carefully selected graupel falling from thin clouds. Analytical solutions for precipitation size distributions imply that average updraft speed must be approximately one-third of particle settling speed to explain the enhancement quantitatively using bulk cloud and precipitation measurements. Analysis of an 8-day thin cloud case revealed that the two days of thin-cloud graupel occurred in conjunction with boundary layer capping inversions that were significantly weaker than on other days of the period. These graupel days were also preceded by boundary layer profiles indicating two days of very strong cloud top radiative cooling – implying that this generated a mixed layer that eroded the capping inversion. Finally, 1-D Lagrangian simulations of graupel settling in turbulent flow show that the particles spend more time in strong updrafts where riming time increases to a significant degree. These findings challenge the current understanding of riming growth and extent turbulence-induced collision enhancement to thin mixed-phase boundary layer clouds in the Arctic. Such enhanced riming leads to increased bulk density of precipitation particles and is therefore expected have strong implications for cloud lifecycles and corresponding radiative balance in the Arctic.

How to cite: Fitch, K., Garrett, T., and Talaei, A.: Large Graupel Produced by Thin Clouds in the Arctic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6138, https://doi.org/10.5194/egusphere-egu2020-6138, 2020

D3029 |
EGU2020-1735<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Yueyue Yu, Patrick Taylor, and Ming Cai

Using CALIPSO‐CloudSat‐Clouds and the Earth's Radiant Energy System (CERES)‐Moderate Resolution Imaging Spectrometer (MODIS) (C3M) dataset, this study documents the seasonal variation of sea ice, cloud, and atmospheric properties in the Arctic (70°N–82°N) for 2007–2010. A surface type stratification—consisting Permanent Ocean, Land, Permanent Ice, and Transient Sea Ice—is used to investigate the influence of surface type on low-level Arctic cloud liquid water path (LWP) seasonality. The results show significant variations in the Arctic low-level cloud LWP by surface type linked to differences in thermodynamic state. Subdividing the Transient Ice region (seasonal sea ice zone) by melt/freeze season onset dates reveals a complex influence of sea ice variations on low cloud LWP seasonality. We find that lower tropospheric stability (LTS) is the primary factor affecting the seasonality of cloud LWP. Our results suggest that variations in sea ice melt/freeze onset have a significant influence on the seasonality of low-level cloud LWP by modulating the lower tropospheric thermal structure and not by modifying the surface evaporation rate in late spring and mid-summer. We find no significant dependence of the May low-level cloud LWP peak on the melt/freeze onset dates, whereas and September/October low-level cloud LWP maximum shifts later in the season for earlier melt/later freeze onset regions. The Arctic low cloud LWP seasonality is controlled by several surface-atmosphere interaction processes; the importance of each varies seasonally due to the thermodynamic properties of sea ice. Our results demonstrate that when analyzing Arctic cloud-sea ice interactions, a seasonal perspective is critical.

How to cite: Yu, Y., Taylor, P., and Cai, M.: Seasonal Variations of Arctic Low‐Level Clouds and Its Linkage to Sea Ice Seasonal Variations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1735, https://doi.org/10.5194/egusphere-egu2020-1735, 2019

D3030 |
EGU2020-20244<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Anne-Katrine Faber, Harald Sodemann, and Hans Christian Steen-Larsen
The interpretation of the climate ice core isotope signal relies on the knowledge on the underlying moisture transport and variability hereof. From ice core records from Greenland and Antarctica we have access to unique climate archives that provide knowledge of past climate changes and variability.  Availability of water vapor, formation of clouds and precipitation are all essential for shaping the radiative and hydrological conditions of the polar climate system. Understanding the mean state and the spatiotemporal variability of moisture transport towards the polar ice sheets is thus vital for exploring moisture and cloud processes affecting the energy and surface mass balance of the Greenland Ice sheet.   
 

This study identifies moisture sources for  both Greenland precipitation and near-surface vapor using a combination of backward trajectories and moisture source diagnostics. Using the Lagrangian moisture source diagnostic WaterSip, based on a global transport climatology calculated with the FLEXPART model, and spanning the entire ERA-Interim dataset, we identify Greenland moisture sources for present-day conditions (1980-2018). We focus on six deep ice core sites and identify the key moisture source areas and their patterns of variability. The role of land vs. ocean moisture sources are investigated, with a particular focus on land sources from North America and Greenland. Further, we evaluate moisture transport in relation to Greenland ice core isotopic composition observations of snow and ice, and explore how moisture sources of precipitation and near-source vapor can differ.

Results show that the deep ice core sites have different spatial patterns of moisture sources. Seasonality is important and large spatial variability with season exists due to precipitation seasonality.  Land-sources are found to be dominating the full moisture uptake budget during summer for some ice core sites.Differences are found between transport patterns for sources of near-surface vapor and sources of precipitation at the same site. This finding highlight that sources and transport of  respectively near-surface moisture and precipitation at the Greenland Ice Sheet are not necessarily comparable.  This suggest that the atmospheric drivers and variability of moisture sources over the Greenland Ice Sheet  can be different for near-surface vapor and precipating clouds at higher altitudes.  This is relevant for a better understanding of  isotope surface processes  related to how the climate signal gets imprinted in the snow. Furthermore these results elucidate the mean state and variability of Greenland moisture sources at different altitudes above the ice surface. This analysis of drivers of Greenland moisture transport therefore contribute to the understanding on how moisture variability influences the energy budget and  surface mass balance of the Greenland Ice sheet. 

 

How to cite: Faber, A.-K., Sodemann, H., and Steen-Larsen, H. C.: Moisture sources for Greenland ice core sites: Seasonality and land/ocean contributions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20244, https://doi.org/10.5194/egusphere-egu2020-20244, 2020

D3031 |
EGU2020-506<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Hélène Bresson, Annette Rinke, Vera Schemann, Susanne Crewell, Carolina Viceto, and Irina Gorodetskaya
The Arctic climate changes faster than the ones of other regions, but the relative role of the individual feedback mechanisms contributing to Arctic amplification is still unclear. Atmospheric Rivers (ARs) are narrow and transient river-style moisture flows arriving from the sub-polar regions. The
integrated water vapour transport associated with ARs can explain up to 70% of the precipitation variance north of 70°N. However, there are still un-
certainties regarding the specific role and the impact of ARs on the Arctic climate variability.
For the first time, the high-resolution ICON modelling framework is used over the Arctic region (from 13 km down to ca. 6 and 3 km) to investigate processes related with anomalous moisture transport into the Arctic. Based on a case study for Svalbard, the representation of the atmospheric circulation and the spatio-temporal structure of water vapour, temperature, and precipitation and snowfall within the limited-area mode (LAM) of the ICON model is assessed. Preliminary results show that the moisture intrusion is relatively well represented in the ICON-LAM simulations. The impact on the surface energy budget will also be calculated.

How to cite: Bresson, H., Rinke, A., Schemann, V., Crewell, S., Viceto, C., and Gorodetskaya, I.: Atmospheric Rivers over the Arctic with the ICON model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-506, https://doi.org/10.5194/egusphere-egu2020-506, 2019

D3032 |
EGU2020-12989<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Melanie Lauer, Annette Rinke, Irina Gorodetskaya, and Susanne Crewell

There are many factors which could contribute to the Arctic warming: feedback processes like the lapse rate and ice-albedo feedback, the increasing downward longwave radiation caused by clouds and water vapour, and the reduction of sea ice in summer that leads to absorption of solar radiation and increase in local evaporation and more clouds. But also the atmospheric moisture transport from the lower latitudes can contribute to the surface warming in high-latitudes. This poleward moisture transport is mostly accomplished by extra-tropical cyclones, with especially strong contribution by the Atmospheric Rivers (ARs). ARs are long, narrow bands of enhanced water vapour transport which are responsible for over 90% of the poleward water vapour transport in and across mid-latitudes. Furthermore, they are responsible for producing significant levels of rain and snow. In addition, the greenhouse effect of water vapour and the formation of clouds increase the downward longwave radiation which can cause a thinning and melting of Arctic sea ice and snow.

In this study, we investigate the contribution of ARs to Arctic precipitation. Firstly, we look into different case studies for which observational data from the campaigns within the Collaborative Research Center “Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3” exist. The data include enhanced observations at/around Svalbard performed during the ACLOUD and the AFLUX campaigns.

Previous studies have shown that ARs reaching into the Arctic have different origins, including the Atlantic and the Pacific pathways and also Siberia. Here we examine which pathway is more common and which one transports more moisture into the Arctic for these case studies by using existing AR catalogues from global and polar-specific algorithms. Furthermore, the variability of precipitation influences the surface mass and energy balance of polar sea ice and ice sheets. Therefore, we will analyse the influence of ARs on precipitation in terms of frequency, intensity, and type of precipitation (rain or snow) for the different case studies. For this purpose, we will use reanalyses and observational data for the water vapour transport, total precipitation, rain and snow profiles.The occurrence of ARs and its influence on precipitation will be extended from case studies to the long-term statistics (for at least 10 years).

How to cite: Lauer, M., Rinke, A., Gorodetskaya, I., and Crewell, S.: Poleward moisture transport and its influence on precipitation in the Arctic: From case studies to long-term statistics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12989, https://doi.org/10.5194/egusphere-egu2020-12989, 2020

D3033 |
EGU2020-4428<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Tiina Nygård, Tuomas Naakka, and Timo Vihma

The Arctic has experienced regionally and seasonally variable moistening of the atmosphere during the recent decades. Compared to the accompanying amplified warming and dramatic sea ice decline, the moistening has so far remained less studied.

We address the regional and seasonal trends in the horizontal moisture transport in the Arctic during the last four decades, in 1979–2018, based on data of ERA5 reanalysis of European Centre for Medium-Range Weather Forecasts. We show that regional trends in moisture transport are large and mainly driven by changes in atmospheric circulation. We demonstrate that the regional moistening patterns in the Arctic during the last four decades have dominantly been shaped by these strong trends in horizontal moisture transport. Changes in local evaporation in the Arctic have only had a minor role in shaping the moistening patterns. We show that increasing trends in evaporation have been restricted to the vicinity of sea-ice margin over a limited period during the local sea-ice decline, and this step-wise increase has been followed by negative trends in evaporation in open sea, due to suppressing effect of horizontal moisture transport.

Both evaporation and the horizontal moisture transport have been affected by the diminishing sea-ice cover during the cold seasons from autumn to spring, and their trends have been dependent on the flow direction. We summarize the current understanding and the new results of flow-dependency of the trends in moisture transport and evaporation near the sea-ice margin, and the cloud response to those.

For the first time, we provide a detailed picture of both the drastic regional changes in the moisture transport within the Arctic and changes in local evaporation, and demonstrate large impacts of these changes on the climate of the Arctic. We suggest that also in the future, moisture and cloud distributions in the Arctic are expected to respond to changes in atmospheric pressure patterns; circulation and moisture transport will also control where and when efficient surface evaporation can occur.

How to cite: Nygård, T., Naakka, T., and Vihma, T.: Horizontal moisture transport shapes the regional moistening patterns in the Arctic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4428, https://doi.org/10.5194/egusphere-egu2020-4428, 2020

D3034 |
EGU2020-12762<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Penny Rowe, Von Walden, Matthew Fergoda, Connor Krill, Jonathon Gero, and Steven Neshyba

Clouds exert a strong radiative impact on the surface and have complicated effects that are still not well understood, particularly in the Antarctic. The amount of supercooled liquid water in Antarctic clouds, for example, is still poorly constrained, due to the low number of observations on the continent. It is also not clear how the radiative properties of supercooled liquid in those clouds should be represented in climate models. In particular, the complex refractive index (CRI) of liquid water is known to depend on temperature, but this dependence is typically ignored in climate models.

Here, we present cloud properties retrieved from Antarctic downwelling infrared radiance measurements made by an Atmospheric Emitted Radiance Interferometer (AERI) and by the Polar AERI (PAERI), using the CLoud and Atmospheric Radiation Retrieval Algorithm (CLARRA). Preliminary retrievals were made of cloud height, optical depth, thermodynamic phase, and effective radius for field experiments at Amundsen-Scott South Pole Station (2001) and at McMurdo Station (2016).

At South Pole, we find that clouds are typically thin and near the surface, in keeping with prior work. For thin clouds, the mode of the effective radii of liquid droplets (~4 μm) and ice particles (~15 μm in summer, ~12 μm in winter) at South Pole are found to be smaller than typical Arctic values (~9 μm for liquid and 17 to 25 μm for ice). Although ice cloud was found to dominate year-round at South Pole, significant supercooled liquid water was present in the summer. Cloud properties retrieved at South Pole will be compared to retrievals from McMurdo.

We further find that ignoring the temperature dependence of the CRI of supercooled liquid cloud leads to negative biases in part of the atmospheric window region (700 – 1000 cm-1), indicating underestimation of the greenhouse effect. These biases are expected to be partially offset by positive biases below 600 cm-1. Based on these considerations, we recommend using temperature-dependent CRI for infrared radiance simulations of supercooled liquid water cloud.

How to cite: Rowe, P., Walden, V., Fergoda, M., Krill, C., Gero, J., and Neshyba, S.: Antarctic Cloud Property Retrievals from Infrared Radiances, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12762, https://doi.org/10.5194/egusphere-egu2020-12762, 2020

D3035 |
EGU2020-1396<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Georgia Sotiropoulou, Etienne Vignon, Gillian Young, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes

In-situ measurements of Antarctic clouds frequently show that ice crystal number concentrations  are much higher than the available ice-nucleating particles, suggesting that Secondary Ice Production (SIP) may be active. Here we investigate the impact of two SIP mechanisms, Hallett-Mossop (H-M)and collisional break-up (BR), on a case from the Microphysics of Antarctic Clouds (MAC) campaign in Weddell Sea using the Weather and Research Forecasting (WRF) model. H-M is already included in the default version of the Morrison microphysics scheme in WRF; for BR we implement different parameterizations and compare their performance. H-M alone is not effective enough to reproduce the observed concentrations. In contrast, BR can result in realistic ice multiplication, independently of whether H-M is active or not. In particular, the Phillips parameterization results in very good agreement with observations, but its performance depends on the prescribed rimed fraction of the colliding ice particles. Finally, our results show low sensitivity to primary ice nucleation, as long as there are enough primary ice crystals to initiate ice-ice collisions. Our findings suggest that BR is a potentially important SIP mechanism in the pristine Antarctic atmosphere that is currently not represented in weather-prediction and climate models.

How to cite: Sotiropoulou, G., Vignon, E., Young, G., Lachlan-Cope, T., Berne, A., and Nenes, A.: Secondary Ice Production in Antarctic Clouds: a process neglected in large-scale models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1396, https://doi.org/10.5194/egusphere-egu2020-1396, 2019

D3036 |
EGU2020-3019<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Nicolas Jullien, Etienne Vignon, Michael Sprenger, Franziska Aemisegger, and Alexis Berne

Precipitation falling over the coastal regions of Antarctica often experiences low-level sublimation within the dry katabatic layer. The amount of water that reaches the ground surface is thereby considerably reduced. We investigate the synoptic conditions and the atmospheric transport pathways of moisture that lead to virga – when precipitation is completely sublimated – or actual surface precipitation at Dumont d’Urville (DDU) station, coastal Adélie Land, Antarctica. We combine ground-based radar measurements, Lagrangian back-trajectories, Eulerian diagnostics of extratropical cyclones and fronts as well as with moisture source estimations based on ERA5 reanalyses. Virga periods – corresponding to 36% of the precipitating events – often precede and sometimes follow surface precipitation periods. Pre-precipitation virga, surface precipitation and post-precipitation virga correspond to different phases of the same precipitating system. Precipitation and virga are always associated with the warm front of an extratropical cyclone that sets to the west of coastal Adélie Land but the exact locations of the cyclone and front differ between the three phases. On their way to DDU, the air parcels that ultimately precipitate above the station experience a large-scale lifting across the warm front. The lifting generally occurs earlier in time and farther from the station for virga than for precipitation. It is further shown that water contained in the precipitation falling above DDU during pre-precipitation virga has an oceanic origin farther away (30 degrees more to the west) from Adélie Land than the one that precipitates down to the ground surface.

How to cite: Jullien, N., Vignon, E., Sprenger, M., Aemisegger, F., and Berne, A.: Synoptic conditions and atmospheric moisture pathways associated with virga and precipitation over coastal Adélie Land, Antarctica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3019, https://doi.org/10.5194/egusphere-egu2020-3019, 2020

D3037 |
EGU2020-651<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Philipp Richter, Mathias Palm, Christine Weinzierl, Penny Rowe, and Justus Notholt

As a precursor of the current MOSAiC campaign, the PASCAL campaign took place in summer 2017 around Svalbard [1]. In the scope of the project (AC)3, infrared radiation emitted by clouds was measured using a calibrated Fourier Transform Infrared Spectrometer (EM-FTIR). EM-FTIR can be used for different purposes, like the observation of trace gases or microphysical cloud parameters (MCP) like cloud optical depths and cloud effective droplet radii. In the observation of MCP, EM-FTIR can be used to measure optically thin clouds with very low amounts of liquid water paths below 30 gm-2, where microwave radiometer face problems because of their larger measuring uncertainty. 

The retrieval of the MCP is performed using the newly introduced retrieval code CLARRA [2]. CLARRA shows a high accuracy in the retrieval of MCP from low-level clouds, which were often observed during the measurements. 

The measurements were performed between June 2017 and August 2017 around Svalbard and include measurements of clouds over sea ice and open water. The spatial distribution of the MCP around Svalbard and a comparison to model results will be shown. This dataset can later serve as a reference for the question, how representative the measurements in Ny-Alesund on Spitzbergen are for the nearby arctic region.

[1] Wendisch et al., 2019: The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multi-Platform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification, Bull. Amer. Meteor. Soc., 100 (5), 841–871, doi:10.1175/BAMS-D-18-0072.1
[2] Rowe et al., 2019: Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties, Atmos. Meas. Tech., 12, 5071–5086, https://doi.org/10.5194/amt-12-5071-2019

How to cite: Richter, P., Palm, M., Weinzierl, C., Rowe, P., and Notholt, J.: Microphysical cloud parameters of optically thin clouds in the Arctic in summer 2017, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-651, https://doi.org/10.5194/egusphere-egu2020-651, 2019

D3038 |
EGU2020-2562<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Carola Barrientos Velasco, Hartwig Deneke, Andre Ehrlich, Matthias Gottschalk, Hannes Griesche, Anja Hünerbein, Patric Seifert, Johannes Stapf, and Andreas Macke

The surface in the Arctic is warming at double the rate than the global average. This phenomenon, named Arctic amplification, makes the Arctic a sensitive and important location to investigate climate change. The principal mechanisms contributing to Arctic Amplification are still under debate due to lack of observations and comprehension of different mechanisms.
With the aim to collect additional observations for the investigation of several processes related to Arctic amplification, the project (AC)³ (Arctic Amplification: Climate Relevant Atmospheric and SurfaCe Processes and Feedback Mechanisms) established two major field campaigns in summer of 2017. Both performed in situ and remote sensing observations over the ocean with PASCAL and in the air with ACLOUD (Macke and
Flores, 2018, Wendisch et al., 2019).
The PASCAL expedition took place on board of the German research vessel Polarstern which was equipped with active and passive remote sensing instrumentation. The synergistic operation of this instrumentation was used to derive macro and microphysical properties of clouds by applying the Cloudnet algorithm. These retrievals together with vertical profiles of temperature and relative humidity are used as input to the Rapid
Radiative Transfer Model for GCM applications (RRTMG). We used the RRMG outputs of solar and terrestrial broadband irradiances and compare them to observations to assess the radiative closure.
In the scope of this study, the difference in radiative fluxes arriving at the surface by using model profiles instead of radiosonde data as thermodynamic driver is quantified, focusing on the representation of temperature and humidity inversions. Furthermore, a sensitivity study is given of the variation of cloud optical properties and their radiative effects at the surface. To test the radiative closure performance at different scales, an inter-comparison is made among airborne, tethered balloon-borne and ship-borne broadband solar and terrestrial radiation in different case studies.
The methodology described is also applicable to the current Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition which started in September 2019. First results will be presented for the first leg which will allow a direct comparison of the contrasting properties of cloud radiative effects during summer and winter.


Acknowledgements
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 268020496 – TRR 172, within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³.


References
Macke, A. and Flores, H. (2018): The Expeditions PS106/1 and 2 of the Research Vessel POLARSTERN to the Arctic Ocean in 2017 , Berichte zur Polar- und Meeresforschung = Reports on polar and marine research, Bremerhaven, Alfred Wegener Institute for Polar and Marine Research, 719 , 171 p. http://hdl.handle.net/10013/epic.4ff2b0cd-1b2f-4444-a97f-0cd9f1d917ab
Wendisch, M., and coauthors. (2019): The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification. Bull. Amer. Meteor. Soc., 100, 841–871, https://doi.org/10.1175/BAMS-D-18-0072.1

How to cite: Barrientos Velasco, C., Deneke, H., Ehrlich, A., Gottschalk, M., Griesche, H., Hünerbein, A., Seifert, P., Stapf, J., and Macke, A.: Investigation of cloud radiative effects and closure in the Central Arctic based on ship-borne remote sensing observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2562, https://doi.org/10.5194/egusphere-egu2020-2562, 2020

D3039 |
EGU2020-4541<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Pei-Hsin Liu, Jen-Ping Chen, Xiquan Dong, and Yi-Chiu Lin

Arctic stratiform clouds (ASC) often exhibit phase inversion structure (i.e., liquid top and mixed- or ice-phase below) and can persist for a very long time. According to past studies, the phase inversion structure is the result of persistent liquid cloud generation aloft and gravitational ice precipitation; however, observation reveals that the largest cloud reflectivity appears in the middle of the cloud, implying that the gravitational ice precipitation cannot fully explain the mechanism of phase inversion structure. Also, the role of ice nucleation in ASC is not fully addressed before. Ice nucleation processes are affected by temperature, ice nuclei (IN) species and number concentration. As the result, strong inversion or strong vertical gradient of IN number concentration may favor ice nucleation to occur in the lower levels and result in phase inversion.

This study aims to find out the mechanism of phase inversion and the dominant ice nucleation processes in ASC. Weather Research and Forecasting (WRF) model with detailed ice nucleation mechanisms is applied. The ice nucleation scheme used in the model takes different ice nucleation processes and IN species into account. Dust and soot, taken from MERRA-2, are the two main IN considered in this study and are fitted into lognormal distributions for providing the initial and boundary conditions. The 2008 Mar 04-05 case, chosen from the Atmospheric Radiation Measurement (ARM) program, is simulated. From observation, ASC and the phase inversion structure persisted for half a day. Temperature decreases with height in cloud, indicating that temperature inversion is not the mechanism of phase inversion in this case. More dust in the lower levels is seen from the model simulation results. In this case, strong vertical gradient of IN number concentration serves as the main mechanism of phase inversion, suggesting that ice nucleation process plays an important role in ASC. The role of soot particles will also be addressed.

How to cite: Liu, P.-H., Chen, J.-P., Dong, X., and Lin, Y.-C.: Mechanism of Phase Inversion in Arctic Stratiform Clouds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4541, https://doi.org/10.5194/egusphere-egu2020-4541, 2020

D3040 |
EGU2020-5264<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Juilin Li, Mark Richardson, Wei-Liang Lee, Jonathan Jiang, Kuan-Man Xu, Yi-Hui Wang, Eric Fetzer, Yinghui Liu, Jia-Yuh Yu, and Graeme Stephens

Recent Arctic sea ice retreat has been quicker than the projection in most general circulation model (GCM) simulations. Natural factors may have amplified this, but reliable attribution and projection requires accurate representation of relevant physical processes. In the meeting, we will present results indicating robust links between CloudSat-CALIPSO falling ice and Arctic sea ice melting from observations and global climate modelings.  Most current GCMs don’t fully represent falling ice radiative effects (FIREs).  We find that a small set of Coupled Model Intercomparison Project, phase 5 (CMIP5) models that include FIREs tend to show a faster Arctic sea ice retreat. We investigate this using controlled simulation with the CESM1-CAM5 model both in present-day and 1%CO2 scenarios. With FIREs, CESM1-CAM5 simulates more realistic present-day annual and seasonal variations of radiation and skin temperatures and Arctic sea ice coverage and thickness. Over 60—90 °N oceans, simulated radiative flux trends are similar but the current-day state differs substantially due to FIREs. Falling ice reduces downward shortwave and increase downward longwave, resulting in an improved agreement with the satellite-based CERES-EBAF surface dataset. Under 1pctCO2 simulations, including FIREs results in the first occurrence of an “ice free” Arctic (extent < 1×106 km2) in year 64, compared with year 91 otherwise. We propose that the equivalent greenhouse effects from falling ice results in fewer safe spaces in which sea ice can thicken during winter, resulting in a thinner pack whose retreat is more easily triggered by global warming. However, this explanation does not apply across the CMIP5 ensemble members. Our results therefore only apply to one model but we have shown that this can have substantial implications for Arctic sea ice projection. Given that falling ice interaction with radiation in reality, we propose that including FIREs in models is a high priority.

How to cite: Li, J., Richardson, M., Lee, W.-L., Jiang, J., Xu, K.-M., Wang, Y.-H., Fetzer, E., Liu, Y., Yu, J.-Y., and Stephens, G.: Arctic Sea Ice: Observations and Global Climate Modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5264, https://doi.org/10.5194/egusphere-egu2020-5264, 2020

D3041 |
EGU2020-10331<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Kerstin Ebell, Tatiana Nomokonova, Marion Maturilli, and Christoph Ritter

Clouds strongly impact the available energy at the surface and at the top of the atmosphere as well as its vertical distribution within the atmosphere by modifying the shortwave (SW) and longwave (LW) fluxes and heating rates. The so-called cloud radiative effect (CRE) and the cloud radiative forcing (CRF), i.e. the difference between the all-sky and clear-sky fluxes and heating rates, respectively, strongly depend on the cloud macrophysical (e.g. frequency of occurrence, cloud vertical distribution) and microphysical (e.g. phase, water content, hydrometeor size distribution) properties.

In the Arctic, the cloud–radiative interactions are even more complex due to low temperatures, frequently occurring temperature inversions, the dryness of the atmosphere, large solar zenith angles and a high surface albedo. In particular (supercooled) liquid containing clouds, which frequently occur in the Arctic and often have very low amounts of liquid water, exhibit a strong impact on the radiative fluxes.

Recently, Ebell et al. (2020) have analysed for the first time the radiative effect of clouds for the Arctic site Ny-Ålesund exploiting more than 2 years (06/2016 -10/2018) of continuous vertical cloud measurements at the French-German research station AWIPEV. They showed that at Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m-2.

Based on the same data set, we will now investigate in more detail how clouds modify the LW and SW heating rates in the atmospheric profile. First results show that the net CRF is dominated by the LW CRF with warming taking place in principal below the height of the maximum frequency of occurrence of liquid around 1 km, and cooling above. The strength of this cooling and warming is closely related to the amount of liquid. We will also analyze heating rates for different cloud types similar to the study by Turner et al. (2017) who found characteristic heating rate profiles for the Arctic site Barrow. In this way, we will gain insight into the representastiveness of these heating rate profiles throughout the Arctic.

We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 268020496 – TRR 172,  within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes,   and    Feedback Mechanisms (AC)³”.

References

Ebell, K., T. Nomokonova, M. Maturilli, and C. Ritter, 2020: Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations. J. Appl. Meteor. Climatol., 59, 3–22, https://doi.org/10.1175/JAMC-D-19-0080.1

Turner, D.D., M.D. Shupe, and A.B. Zwink, 2018: Characteristic Atmospheric Radiative Heating Rate Profiles in Arctic Clouds as Observed at Barrow, Alaska. J. Appl. Meteor. Climatol., 57, 953–968, https://doi.org/10.1175/JAMC-D-17-0252.1

How to cite: Ebell, K., Nomokonova, T., Maturilli, M., and Ritter, C.: Impact of clouds on atmospheric heating rate profiles at Ny-Ålesund, Svalbard, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10331, https://doi.org/10.5194/egusphere-egu2020-10331, 2020

D3042 |
EGU2020-20196<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Tuomas Naakka, Tiina Nygård, and Timo Vihma

Atmospheric humidity profiles control occurrence of clouds, which in turn has a large impact on radiative fluxes in the Antarctic. In addition, humidity profiles strongly interact with surface moisture fluxes, which are an important component in the water cycle. Despite their important role in the climate system, specific and relative humidity profiles in the Antarctic have not so far been comprehensively studied. Here, we address the vertical structure of tropospheric specific and relative humidity in the area south of 50°S and focus on interactions of this structure with horizontal and vertical moisture transport and surface fluxes of sensible and latent heat. The study is based on ERA5 reanalysis data from 15-years period, 2004 - 2018. 

We show that in the Antarctic, both moisture transport and surface fluxes shape the vertical structure of specific and relative humidity, but their relative contributions and effects vary considerably between regions. Therefore, we examined humidity profiles dividing the study area into five sub-regions: 1) open sea, 2) seasonal sea-ice area, 3) slopes of East Antarctica, 4) East Antarctica high plateau, and 5) West Antarctica. Expect west Antarctica, within each region the vertical structure of air moisture is relatively homogenous. Results indicate that each of these regions has own key processes (evaporation, condensation, vertical and horizontal moisture fluxes) controlling the vertical structure of relative and specific humidity.

The open ocean is a source area for atmospheric moisture. Over the open sea, a thin unsaturated well-mixed layer is seen near the surface, which is caused by year-around upward moisture flux (evaporation) and upward sensible heat flux. Above this layer, there is a layer of high relative humidity and frequently occurring cloud cover. Over sea ice, seasonal variability is large. During most of the year, moisture surface fluxes over sea ice are small, near-surface relative humidity is high, and specific humidity inversions are frequent. In summer, however, evaporation over sea ice increases, near-surface relative humidity is lower, and humidity inversions are uncommon.

The high plateau is the area where absolutely dry air masses are formed, as a consequence of near-surface condensation and downward moisture transport. There, the near-surface air is often saturated with respect to ice, and strong but thin surface-based specific humidity inversions are present during most of the year. On the slopes, adiabatic warming, due to katabatic winds, causes decrease of relative humidity when the air mass is advected downwards from the plateau. This leads to relatively high surface evaporation and makes surface-based specific humidity inversions rarer.

This study comprehensively describes the vertical structure of relative and specific humidity in the Antarctic, and increases understanding on how this vertical structure interacts with moisture transport and surface fluxes. The results can further contribute to understanding of processes related to cloud formation and water cycle in the high southern latitudes.

How to cite: Naakka, T., Nygård, T., and Vihma, T.: Humidity profiles and their interactions with moisture transport and surface fluxes in the Antarctic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20196, https://doi.org/10.5194/egusphere-egu2020-20196, 2020

D3043 |
EGU2020-14421<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
dae hui Kim, Hyun Mee Kim, and Jinkyu Hong

In the Arctic region, cloud is an important factor affecting surface radiation and heat flux. Despite the development of cloud microphysics schemes in the Polar WRF, clouds in the Arctic region still have uncertainties. In this study, the possibility of improving cloud simulations by using data assimilation (DA) and its effects on the enhancement of the forecast accuracy for surface fluxes and meteorological variables are evaluated. The experimental period is from 1 to 19 September 2017.

Forecasts from both the cold start experiment without DA and the warm start experiment with DA underestimated summer arctic clouds. When satellite radiances (AMSU-A and MHS) were assimilated at the analysis time, the distribution and quantity of water vapor were simulated more realistically, which results in the improvement of cloud simulations at the forecast time. As a result, the 25–30 hour forecast error of the downward shortwave (longwave) radiation flux in the warm start experiment which assimilated both conventional observations and satellite radiance data was reduced by 8.1% (12.7%), compared to that in the cold start experiment. The 25–30 hour forecast error of the upward latent (sensible) heat flux in the warm start experiment was also reduced by 7.8% (3.3%), compared to that in the cold start experiment. For the 2 m temperature and 10 m wind, the forecast error with DA was less than that without DA at almost all observation stations. More detailed results will be presented in the conference.

Acknowledgments

This work was supported by the Korea Polar Research Institute (KOPRI, PN20081) and the Korea Meteorological Administration Research and Development Program under grant KMI2018-03712. The simulations are mostly carried out by utilising the supercomputer system supported by the National Center for Meteorological Supercomputer of Korea Meteorological Administration (KMA).

How to cite: Kim, D. H., Kim, H. M., and Hong, J.: Cloud, radiation, and surface heat flux simulations using Polar WRF with 3DVAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14421, https://doi.org/10.5194/egusphere-egu2020-14421, 2020

D3044 |
EGU2020-21307<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Birte Solveig Kulla, Elena Ruiz-Donoso, Leif-Leonard Kliesch, Vera Schemann, Christoph Ritter, Mario Mech, and Susanne Crewell
Despite their importance, our knowledge on arctic clouds and in particular their vertical structure is limited.
In the essentially remote regions of the Arctic, the only continuous measurements available usually are those of satellites, like the A-Train constellation. Climatologies have been derived from A-Train products, i.e. the combination of radar and lidar. However, due to the coarser resolution and bigger footprints of the sensors and the blind zone of CLOUDSAT in the boundary layer many features are missed. In the framework of the Collaborative Research Centre TR 172 “Arctic Amplification” four major aircraft campaigns with the AWI research aircraft POLAR5 took and will take place in the vicinity of Svalbard with emphasis on the Atlantic Arctic region close to the marginal sea ice zone. 
 
On board of the POLAR5 aircraft active measurements by radar (MiRAC) and lidar (AMALi) were performed and supported by microwave radiometer measurements in 9 frequency channels and a high spectral resolution solar imager (AISA Eagle/Hawk). We have calibrated and processed radar and lidar measurements and deduced highly resolved (7.5 m, 1.3 Hz) vertical profiles of backscatter, attenuation and reflectivity and retrieved a preliminary classification of cloud top. The potential of these measurements for a detailed characterization of Arctic clouds is assessed via the comparison with CALIPSO and CLOUDSAT as well as MODIS measurements for an A-Train underflight. Measurements cover a cold air outbreak in May 2017 with a complex situation with multiple layers of mixed phase clouds and several inversions evident in the thermodynamic structure given by dropsondes. A high resolution model simulation with ICON, which reproduces the general features of this situation, is used together with instrument simulators to investigate how much information on cloud processes can be gained from the measurements. 

How to cite: Kulla, B. S., Ruiz-Donoso, E., Kliesch, L.-L., Schemann, V., Ritter, C., Mech, M., and Crewell, S.: Zooming in on Arctic clouds: A case study comparing A-Train and airborne remote sensing measurements.       , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21307, https://doi.org/10.5194/egusphere-egu2020-21307, 2020