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Atmosphere
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Cryosphere in and around Regional Climate Models
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Cryosphere in and around Regional Climate Models

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (24 April 2020) | Viewed by 30913

Special Issue Editor

Dr. Sven Kotlarski

E-Mail Website
Guest Editor
Head of Climate Evolution, Climate Division, Federal Office of Meteorology and Climatology MeteoSwiss, P.O. Box 257, CH-8058 Zurich-Airport, Switzerland
Interests: process studies; atmosphere; climate; global warming; hydrosphere; cryosphere; climatic effects; climate statistics; regional climate modelling; climate services
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The cryosphere is an important and heavily-interacting component of the global climate system. Cryosphere-climate feedbacks occur at different spatial and temporal scales, and climate model development seeks to integrate the most important and relevant feedbacks. At regional scales, these primarily occur through the modification of surface and sub-surface features by the presence of snow and ice. Especially, in alpine terrain shaped by topography but also in polar environments, a comparatively high spatial resolution, such as being employed by regional climate models (RCMs), is required to appropriately account for these processes. The representation of the terrestrial cryosphere in RCMs has, therefore, gained particular attention in recent years, and sophisticated online parameterization schemes have been developed and applied. The same is true for the representation of sea ice in coupled regional atmosphere–ocean models. Furthermore, RCMs are increasingly employed to drive dedicated cryospheric impact models in an offline mode.

This Special Issue seeks to bring together studies that are concerned with

  1. the online representation of cryospheric features (snowfall, snow cover, glaciers, permafrost, sea ice) within RCMs in order to adequately account for cryosphere-climate feedbacks (Cryosphere IN RCMs);
  2. the offline forcing of cryospheric models by RCM output in order to assess sensitivities of the cryosphere with respect to climate change and variability or to assess future climate change impacts on the cryosphere (Cryosphere AROUND RCMs).

In addition, further topics, such as the use of cryospheric data sets for RCM validation or the assessment of cryosphere-related continental-scale teleconnections are warmly welcome.

Dr. Sven Kotlarski
Guest Editor

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Keywords

  • cryosphere-climate feedbacks
  • glaciers
  • snow
  • snowfall
  • permafrost
  • sea ice
  • regional climate models
  • parameterization
  • snow-albedo feedback
  • mountain climates

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Published Papers (5 papers)

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Research

20 pages, 2743 KiB  
Article
Evaluating Snow in EURO-CORDEX Regional Climate Models with Observations for the European Alps: Biases and Their Relationship to Orography, Temperature, and Precipitation Mismatches
by Michael Matiu, Marcello Petitta, Claudia Notarnicola and Marc Zebisch
Atmosphere 2020, 11(1), 46; https://doi.org/10.3390/atmos11010046 - 29 Dec 2019
Cited by 23 | Viewed by 4336
Abstract
Climate models are important tools to assess current and future climate. While they have been extensively used for studying temperature and precipitation, only recently regional climate models (RCMs) arrived at horizontal resolutions that allow studies of snow in complex mountain terrain. Here, we [...] Read more.
Climate models are important tools to assess current and future climate. While they have been extensively used for studying temperature and precipitation, only recently regional climate models (RCMs) arrived at horizontal resolutions that allow studies of snow in complex mountain terrain. Here, we present an evaluation of the snow variables in the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) RCMs with gridded observations of snow cover (from MODIS remote sensing) and temperature and precipitation (E-OBS), as well as with point (station) observations of snow depth and temperature for the European Alps. Large scale snow cover dynamics were reproduced well with some over- and under-estimations depending on month and RCM. The orography, temperature, and precipitation mismatches could on average explain 31% of the variability in snow cover bias across grid-cells, and even more than 50% in the winter period November–April. Biases in average monthly snow depth were remarkably low for reanalysis driven RCMs (<approx. 30 cm), and large for the GCM driven ones (up to 200 cm), when averaged over all stations within 400 m of altitude difference with RCM orography. Some RCMs indicated low snow cover biases and at the same time high snow depth biases, and vice versa. In summary, RCMs showed good skills in reproducing alpine snow cover conditions with regard to their limited horizontal resolution. Detected shortcomings in the models depended on the considered snow variable, season and individual RCM. Full article
(This article belongs to the Special Issue Cryosphere in and around Regional Climate Models)
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18 pages, 1829 KiB  
Article
Projections of Alpine Snow-Cover in a High-Resolution Climate Simulation
by Samuel Lüthi, Nikolina Ban, Sven Kotlarski, Christian R. Steger, Tobias Jonas and Christoph Schär
Atmosphere 2019, 10(8), 463; https://doi.org/10.3390/atmos10080463 - 13 Aug 2019
Cited by 32 | Viewed by 7236
Abstract
The recent development of high-resolution climate models offers a promising approach in improving the simulation of precipitation, clouds and temperature. However, higher grid spacing is also a promising feature to improve the simulation of snow cover. In particular, it provides a refined representation [...] Read more.
The recent development of high-resolution climate models offers a promising approach in improving the simulation of precipitation, clouds and temperature. However, higher grid spacing is also a promising feature to improve the simulation of snow cover. In particular, it provides a refined representation of topography and allows for an explicit simulation of convective precipitation processes. In this study we analyze the snow cover in a set of decade-long high-resolution climate simulation with horizontal grid spacing of 2.2 km over the greater Alpine region. Results are compared against observations and lower resolution models (12 and 50 km), which use parameterized convection. The simulations are integrated using the COSMO (Consortium for Small-Scale Modeling) model. The evaluation of snow water equivalent (SWE) in the simulation of present-day climate, driven by the ERA-Interim reanalysis, against an observational dataset, reveals that the high-resolution simulation clearly outperforms simulations with grid spacing of 12 and 50 km. The latter simulations underestimate the cumulative amount of SWE over Switzerland over the whole annual cycle by 33% (12 km simulation) and 56% (50 km simulation) while the high-resolution simulation shows a spatially and temporally averaged difference of less than 1%. Scenario simulations driven by GCM MPI-ESM-LR (2081–2090 RCP8.5 vs. 1991–2000) reveal a strong decrease of SWE over the Alps, consistent with previous studies. Previous studies had found that the relative decrease becomes gradually smaller with elevation, but this finding was limited to low and intermediate altitudes (as a 12 km simulation resolves the topography up to 2500 m). In the current study we find that the height gradient reverses sign, and relative reductions in snow cover increases above 3000 m asl, where important parts of the cryosphere are present. In addition, the simulations project a transition from permanent to seasonal snow cover at high altitudes, with potentially important impacts to Alpine permafrost. This transition and the more pronounced decline of SWE emphasize the value of the higher grid spacing. Overall, we show that high-resolution climate models offer a promising approach in improving the simulation of snow cover in Alpine terrain. Full article
(This article belongs to the Special Issue Cryosphere in and around Regional Climate Models)
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16 pages, 5136 KiB  
Article
Arctic Intense Summer Storms and Their Impacts on Sea Ice—A Regional Climate Modeling Study
by Alexander Semenov, Xiangdong Zhang, Annette Rinke, Wolfgang Dorn and Klaus Dethloff
Atmosphere 2019, 10(4), 218; https://doi.org/10.3390/atmos10040218 - 23 Apr 2019
Cited by 21 | Viewed by 6977
Abstract
Various temporal and spatial changes have manifested in Arctic storm activities, including the occurrence of the anomalously intense storms in the summers of 2012 and 2016, along with the amplified warming and rapidly decreased sea ice. To detect the variability of and changes [...] Read more.
Various temporal and spatial changes have manifested in Arctic storm activities, including the occurrence of the anomalously intense storms in the summers of 2012 and 2016, along with the amplified warming and rapidly decreased sea ice. To detect the variability of and changes in storm activity and understand its role in sea ice changes, we examined summer storm count and intensity year-by-year from ensemble hindcast simulations with an Arctic regional coupled climate model for the period of 1948–2008. The results indicated that the model realistically simulated the climatological spatial structure of the storm activity, characterized by the storm count and intensity. The simulated storm count captures the variability derived from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP–NCAR) reanalysis, though the simulated one is higher than that in the reanalysis. This could be attributed to the higher resolution of the model that may better represent smaller and shallower cyclones. The composite analysis shows that intense storms tend to form a low-pressure pattern with centers over the Kara Sea and Chukchi Sea, respectively, generating cyclonic circulation over the North Atlantic and North Pacific Arctic Ocean. The former drives intensification of the transpolar drift and Fram Strait sea ice export, and the latter suppresses thick ice transport from the Canada Basin to the Beaufort–Chukchi Seas, in spite of an increase in sea ice transport to the East Siberian Sea. Associated with these changes in sea ice transport, sea ice concentration and thickness show large decreases in the Barents–Kara Seas and the Chukchi–East-Siberian Seas, respectively. Energy budgets analysis suggests that more numerous intense storms substantially decrease the downward net sea ice heat fluxes, including net radiative fluxes, turbulent fluxes, and oceanic heat fluxes, compared with that when a lower number of intense storms occur. The decrease in the heat fluxes could be attributable to an increased cloudiness and the resultant reduction of downward shortwave radiation, as well as a destabilized boundary layer induced increase in upward turbulent fluxes. Full article
(This article belongs to the Special Issue Cryosphere in and around Regional Climate Models)
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24 pages, 5264 KiB  
Article
Sensitivity of Glacier Runoff to Winter Snow Thickness Investigated for Vatnajökull Ice Cap, Iceland, Using Numerical Models and Observations
by Louise Steffensen Schmidt, Peter L. Langen, Guðfinna Aðalgeirsdóttir, Finnur Pálsson, Sverrir Guðmundsson and Andri Gunnarsson
Atmosphere 2018, 9(11), 450; https://doi.org/10.3390/atmos9110450 - 15 Nov 2018
Cited by 11 | Viewed by 6379
Abstract
Several simulations of the surface climate and energy balance of Vatnajökull ice cap, Iceland, are used to estimate the glacier runoff for the period 1980–2015 and the sensitivity of runoff to the spring conditions (e.g., snow thickness). The simulations are calculated using the [...] Read more.
Several simulations of the surface climate and energy balance of Vatnajökull ice cap, Iceland, are used to estimate the glacier runoff for the period 1980–2015 and the sensitivity of runoff to the spring conditions (e.g., snow thickness). The simulations are calculated using the snow pack scheme from the regional climate model HIRHAM5, forced with incoming mass and energy fluxes from the numerical weather prediction model HARMONIE-AROME. The modeled runoff is compared to available observations from two outlet glaciers to assess the quality of the simulations. To test the sensitivity of the runoff to spring conditions, simulations are repeated for the spring conditions of each of the years 1980–2015, followed by the weather of all summers in the same period. We find that for the whole ice cap, the variability in runoff as a function of varying spring conditions was on average 31% of the variability due to changing summer weather. However, some outlet glaciers are very sensitive to the amount of snow in the spring, as e.g., the variation in runoff from Brúarjökull due to changing spring conditions was on average 50% of the variability due to varying summer weather. Full article
(This article belongs to the Special Issue Cryosphere in and around Regional Climate Models)
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13 pages, 4927 KiB  
Article
A Multidecadal Analysis of Föhn Winds over Larsen C Ice Shelf from a Combination of Observations and Modeling
by Jasper M. Wiesenekker, Peter Kuipers Munneke, Michiel R. Van den Broeke and C. J. P. Paul Smeets
Atmosphere 2018, 9(5), 172; https://doi.org/10.3390/atmos9050172 - 5 May 2018
Cited by 26 | Viewed by 4815
Abstract
The southward progression of ice shelf collapse in the Antarctic Peninsula is partially attributed to a strengthening of the circumpolar westerlies and the associated increase in föhn conditions over its eastern ice shelves. We used observations from an automatic weather station at Cabinet [...] Read more.
The southward progression of ice shelf collapse in the Antarctic Peninsula is partially attributed to a strengthening of the circumpolar westerlies and the associated increase in föhn conditions over its eastern ice shelves. We used observations from an automatic weather station at Cabinet Inlet on the northern Larsen C ice shelf between 25 November 2014 and 31 December 2016 to describe föhn dynamics. Observed föhn frequency was compared to the latest version of the regional climate model RACMO2.3p2, run over the Antarctic Peninsula at 5.5-km horizontal resolution. A föhn identification scheme based on observed wind conditions was employed to check for model biases in föhn representation. Seasonal variation in total föhn event duration was resolved with sufficient skill. The analysis was extended to the model period (1979–2016) to obtain a multidecadal perspective of föhn occurrence over Larsen C ice shelf. Föhn occurrence at Cabinet Inlet strongly correlates with near-surface air temperature, and both are found to relate strongly to the location and strength of the Amundsen Sea Low. Furthermore, we demonstrated that föhn occurrence over Larsen C ice shelf shows high variability in space and time. Full article
(This article belongs to the Special Issue Cryosphere in and around Regional Climate Models)
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