Evaluation of Arctic land snow cover characteristics, surface albedo and temperature during the transition seasons from regional climate model simulations and satellite data

This paper evaluates the simulated Arctic land snow cover duration, snow water equivalent, snow cover fraction, surface albedo and land surface temperature in the regional climate model HIRHAM5 during 2008-2010, compared with various satellite and reanalysis data and one further regional climate model (COSMO-CLM). HIRHAM5 shows a general agreement in the spatial patterns and annual course of these variables, although distinct biases for specific regions and months are obvious. The most prominent biases occur for east Siberian deciduous forest albedo, which is overestimated in the simulation for snow covered conditions in spring. This may be caused by the simplified albedo parameterization (e.g. non-consideration of different forest types and neglecting the effect of fallen leaves and branches on snow for deciduous tree forest). The land surface temperature biases mirror the albedo biases in their spatial and temporal structures. The snow cover fraction and albedo biases can explain the simulated land surface temperature bias of ca. -3 °C over the Siberian forest area in spring

ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model

For the first time, the Limited-Area Mode of the new ICON (Icosahedral Nonhydrostatic) weather and climate model has been used for a continuous long-term regional climate simulation over Europe. Built upon the Limited-Area Mode of ICON (ICON-LAM), ICON-CLM (ICON in Climate Limited-area Mode, hereafter ICON-CLM, available in ICON release version 2.6.1) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP_betal). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Tests with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. ICON-CLM was also able to reproduce the large-scale atmospheric information from the global driving model. Comparison was done between ICON-CLM and the COnsortium for Small-scale MOdeling (COSMO)-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run of ICON-CLM with ERA-Interim boundary conditions was carried out with the setup similar to the COSMO-CLM recommended optimal setup. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. While this COSMO-CLM simulation was carried out with the latest model version which has been developed and was carefully tuned for climate simulations on the European domain, ICON-CLM was not tuned yet. Nevertheless, ICON-CLM showed a better performance for air temperature and its daily extremes, and slightly better performance for total cloud cover. For precipitation and mean sea level pressure, COSMO-CLM was closer to observations than ICON-CLM. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain

COSMO-CLM Starter Package

<p>The COSMO-CLM, which is the COSMO (COnsortium for SMall scale MOdeling) model in CLimate Mode (CLM), is the non-hydrostatic regional Community-Model for the German climate research.</p> <p>Training courses are offered by the German weather service (DWD) each year in early spring consisting of lectures on the components of the COSMO model, as well as practical classes for runnning the COSMO model in forecast and climate mode. The lecturers of the practical experiments in climate mode are members from the CLM-Community (www.clm-community.eu). In the course the climate simulation experiments are performed with the starter package of the COSMO-CLM (CCLM_SP).</p> <p>The main part of the starter package is a runtime environment for performing climate simulations with the regional climate model COSMO-CLM on the super computer at the German Climate Computing Center (Deutsches Klimarechenzentrum, DKRZ).</p> <p>Documentation: <a href="https://clm-docs.scrollhelp.site/cclm-sp-doc/index.html">COSMO-CLM_SP documentation web site</a></p> <p> </p&gt

COSMO-CLM Starter Package

<p>The COSMO-CLM, which is the COSMO (COnsortium for SMall scale MOdeling) model in CLimate Mode (CLM), is the non-hydrostatic regional Community-Model for the German climate research.</p> <p>Training courses are offered by the German weather service (DWD) each year in early spring consisting of lectures on the components of the COSMO model, as well as practical classes for runnning the COSMO model in forecast and climate mode. The lecturers of the practical experiments in climate mode are members from the CLM-Community (www.clm-community.eu). In the course the climate simulation experiments are performed with the starter package of the COSMO-CLM (CCLM_SP).</p> <p>The main part of the starter package is a runtime environment for performing climate simulations with the regional climate model COSMO-CLM on the super computer at the German Climate Computing Center (Deutsches Klimarechenzentrum, DKRZ).</p> <p>Documentation: <a href="https://clm-docs.scrollhelp.site/cclm-sp-doc/index.html">COSMO-CLM_SP documentation web site</a></p> <p> </p&gt

SPICE (Starter Package for ICON-CLM Experiments)

<p>The main part of SPICE (Starter Package for ICON-CLM Experiments) is a runtime environment for performing climate simulations with the regional climate model ICON-CLM</p> <p>ICON-CLM is the regional climate model that has been developed by the Deutscher Wetterdienst (DWD) and the Climate Limited-area Modeling Community (CLM-Community) since 2017. ICON-CLM is the Climate Mode of ICON-LAM (ICON-Limited Area Mode, based on the numerical weather prediction model ICON-NWP) of the ICON (Icosahedral Nonhydrostatic) model (Zängl et al., 2015). ICON has been developed since 2001 as the result of a cooperation between DWD and Max Planck Institute for Meteorology (MPI-M) (see an overview of ICON).</p> <p>Documentation: <a href="https://spice.clm-community.eu">https://spice.clm-community.eu</a></p> <p> </p> <p> </p&gt

Einfluß von Atmosphäre-Ozean Wechselwirkungen auf Starkniederschläge über Europa

Einfluß von Atmosphäre-Ozean Wechselwirkungen auf Starkniederschläge über Europa: Trotz der wichtigen Rolle, die die Ozeane für Wetter und Klima spielen, wurden erst kürzlich gekoppelte regionale Atmosphäre-Ozean-Modelle entwickelt und nur in einigen wenigen Gebieten der Welt angewendet. Hier geben wir einen Überblick über die gekoppelte Atmosphäre-Ozean Modellierung für Europa im Allgemeinen und den Einfluss auf extreme Niederschläge im Besonderen. Der Schwerpunkt liegt hierbei auf zwei Regionen, der Nord- und Ostseeregion sowie der Mittelmeerregion. Die Verdunstung aus diesen Randmeeren ist neben der aus dem Nordatlantik die Hauptquelle für die Bildung starker Regenfälle in Europa. Influence of Atmospheric Ocean interactions on heavy rainfall over Europe: In spite of the important role of oceans in shaping our climate and weather patterns, coupled regional atmosphere-ocean models have just recently been developed and only over a few areas in the world. Here we present an overview of air-sea coupled modelling for the European area in general and the effect of this coupling on extreme precipitation in particular. We will focus on the North and Baltic Sea region as well as the Mediterranean Sea region. Evaporation from these marginal seas, in addition to the North Atlantic, is the major moisture source for heavy rainfall over Europe

Evaluation of Arctic land snow cover characteristics, surface albedo and temperature during the transition seasons from regional climate model simulations and satellite data

This paper evaluates the simulated Arctic land snow cover duration, snow water equivalent, snow cover fraction, surface albedo and land surface temperature in the regional climate model HIRHAM5 during 2008-2010, compared with various satellite and reanalysis data and one further regional climate model (COSMO-CLM). HIRHAM5 shows a general agreement in the spatial patterns and annual course of these variables, although distinct biases for specific regions and months are obvious. The most prominent biases occur for east Siberian deciduous forest albedo, which is overestimated in the simulation for snow covered conditions in spring. This may be caused by the simplified albedo parameterization (e.g. non-consideration of different forest types and neglecting the effect of fallen leaves and branches on snow for deciduous tree forest). The land surface temperature biases mirror the albedo biases in their spatial and temporal structures. The snow cover fraction and albedo biases can explain the simulated land surface temperature bias of ca. -3 °C over the Siberian forest area in spring