scholarly journals Assessment of Regional Climate Model Simulations of the Katabatic Boundary Layer Structure over Greenland

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 571
Author(s):  
Günther Heinemann
Keyword(s):  
Boundary Layer ◽  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Layer Structure ◽  
Regional Climate ◽  
Regional Climate Models ◽  
The Arctic ◽  
Temperature Cycle ◽  
Katabatic Wind

The parameterization of the boundary layer is a challenge for regional climate models of the Arctic. In particular, the stable boundary layer (SBL) over Greenland, being the main driver for substantial katabatic winds over the slopes, is simulated differently by different regional climate models or using different parameterizations of the same model. However, verification data sets with high-resolution profiles of the katabatic wind are rare. In the present paper, detailed aircraft measurements of profiles in the katabatic wind and automatic weather station data during the experiment KABEG (Katabatic wind and boundary-layer front experiment around Greenland) in April and May 1997 are used for the verification of the regional climate model COSMO-CLM (CCLM) nested in ERA-Interim reanalyses. CCLM is used in a forecast mode for the whole Arctic with 15 km resolution and is run in the standard configuration of SBL parameterization and with modified SBL parameterization. In the modified version, turbulent kinetic energy (TKE) production and the transfer coefficients for turbulent fluxes in the SBL are reduced, leading to higher stability of the SBL. This leads to a more realistic representation of the daily temperature cycle and of the SBL structure in terms of temperature and wind profiles for the lowest 200 m.

Regional Climate Model Inter-Comparison for Antarctica within a Data Science Framework

2021 ◽  
Author(s):  
Jeremy Carter ◽  
Amber Leeson ◽  
Andrew Orr ◽  
Christoph Kittel ◽  
Melchior van Wessem
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate Change ◽  
Near Surface ◽  
Virtual Lab ◽  
Model Variability ◽  
The Antarctic

<p>Understanding the surface climatology of the Antarctic ice sheet is essential if we are to adequately predict its response to future climate change. This includes both primary impacts such as increased ice melting and secondary impacts such as ice shelf collapse events. Given its size, and inhospitable environment, weather stations on Antarctica are sparse. Thus, we rely on regional climate models to 1) develop our understanding of how the climate of Antarctica varies in both time and space and 2) provide data to use as context for remote sensing studies and forcing for dynamical process models. Given that there are a number of different regional climate models available that explicitly simulate Antarctic climate, understanding inter- and intra model variability is important.</p><p>Here, inter- and intra-model variability in Antarctic-wide regional climate model output is assessed for: snowfall; rainfall; snowmelt and near-surface air temperature within a cloud-based virtual lab framework. State-of-the-art regional climate model runs from the Antarctic-CORDEX project using the RACMO, MAR and MetUM models are used, together with the ERA5 and ERA-Interim reanalyses products. Multiple simulations using the same model and domain boundary but run at either different spatial resolutions or with different driving data are used. Traditional analysis techniques are exploited and the question of potential added value from more modern and involved methods such as the use of Gaussian Processes is investigated. The advantages of using a virtual lab in a cloud based environment for increasing transparency and reproducibility, are demonstrated, with a view to ultimately make the code and methods used widely available for other research groups.</p>

scholarly journals Regional Climate Models Add Value to Global Model Data: A Review and Selected Examples

2011 ◽  
Vol 92 (9) ◽  
pp. 1181-1192 ◽  
Author(s):  
Frauke Feser ◽  
Burkhardt Rockel ◽  
Hans von Storch ◽  
Jörg Winterfeldt ◽  
Matthias Zahn
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Spatial Scales ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Small Scale ◽  
Model Data ◽  
Polar Lows

An important challenge in current climate modeling is to realistically describe small-scale weather statistics, such as topographic precipitation and coastal wind patterns, or regional phenomena like polar lows. Global climate models simulate atmospheric processes with increasingly higher resolutions, but still regional climate models have a lot of advantages. They consume less computation time because of their limited simulation area and thereby allow for higher resolution both in time and space as well as for longer integration times. Regional climate models can be used for dynamical down-scaling purposes because their output data can be processed to produce higher resolved atmospheric fields, allowing the representation of small-scale processes and a more detailed description of physiographic details (such as mountain ranges, coastal zones, and details of soil properties). However, does higher resolution add value when compared to global model results? Most studies implicitly assume that dynamical downscaling leads to output fields that are superior to the driving global data, but little work has been carried out to substantiate these expectations. Here a series of articles is reviewed that evaluate the benefit of dynamical downscaling by explicitly comparing results of global and regional climate model data to the observations. These studies show that the regional climate model generally performs better for the medium spatial scales, but not always for the larger spatial scales. Regional models can add value, but only for certain variables and locations—particularly those influenced by regional specifics, such as coasts, or mesoscale dynamics, such as polar lows. Therefore, the decision of whether a regional climate model simulation is required depends crucially on the scientific question being addressed.

Intercomparison of Arctic Regional Climate Models: Modeling Clouds and Radiation for SHEBA in May 1998

2006 ◽  
Vol 19 (17) ◽  
pp. 4167-4178 ◽  
Author(s):  
Jun Inoue ◽  
Jiping Liu ◽  
James O. Pinto ◽  
Judith A. Curry
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Cloud Microphysics ◽  
Surface Heat ◽  
The Arctic ◽  
Surface Boundary ◽  
Simulated Surface

Abstract To improve simulations of the Arctic climate and to quantify climate model errors, four regional climate models [the Arctic Regional Climate System Model (ARCSYM), the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS), the High-Resolution Limited-Area Model (HIRHAM), and the Rossby Center Atmospheric Model (RCA)] have simulated the annual Surface Heat Budget of the Arctic Ocean (SHEBA) under the Arctic Regional Climate Model Intercomparison Project (ARCMIP). The same lateral boundary and ocean surface boundary conditions (i.e., ice concentration and surface temperature) drive all of the models. This study evaluated modeled surface heat fluxes and cloud fields during May 1998, a month that included the onset of the surface icemelt. In general, observations agreed with simulated surface pressure and near-surface air properties. Simulation errors due to surface fluxes and cloud effects biased the net simulated surface heat flux, which in turn affected the timing of the simulated icemelt. Modeled cloud geometry and precipitation suggest that the RCA model produced the most accurate cloud scheme, followed by the HIRHAM model. Evaluation of a relationship between cloud water paths and radiation showed that a radiative transfer scheme in ARCSYM was closely matched with the observation when liquid clouds were dominant. Clouds and radiation are of course closely linked, and an additional comparison of the radiative transfer codes for ARCSYM and COAMPS was performed for clear-sky conditions, thereby excluding cloud effects. Overall, the schemes for radiative transfer in ARCSYM and for cloud microphysics in RCA potentially have some advantages for modeling the springtime Arctic.

scholarly journals Uncertainties in climate change projections and regional downscaling: implications for water resources management

2010 ◽  
Vol 7 (2) ◽  
pp. 1821-1848 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Regional Climate Model ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

scholarly journals Regional climate change projections for the Barents region

2016 ◽  
Author(s):  
Andreas Dobler ◽  
Jan Erik Haugen ◽  
Rasmus Emil Benestad
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Barents Sea ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Barents Region ◽  
The Barents Sea

Abstract. Regional climate models can provide estimates for quantities that are difficult to study in empirical studies, such as cloud cover, wind, sea-ice or dependencies between variables. In this study, the regional climate model COSMO-CLM was used to simulate local climate conditions over the Barents region and provide projections for the three emission scenarios RCP2.6, RCP4.5 and RCP8.5. The results indicate that the most pronounced local warming can be expected in winter in the high Arctic near the present sea-ice border. The changes reach up to 20K, resulting in future temperatures close to melting. Similar spatial patterns are seen for changes in precipitation and wind in all scenarios, but with different amplitudes. Precipitation sensitivities, however, show the highest values along the west coast of Norway and in the Arctic during summer. For clouds, the projections show a decrease in winter mean cloud cover over sea and an increase over land, dominated by changes in low layer clouds. Over the Barents sea, convective cloud fraction is projected to increase, together with an increases in convective and total precipitation. In contrast to the COSMO-CLM and two other regional climate models taken into account, the ensemble mean of the driving global models shows an increasing trend in total cloud cover over the Barents sea. An analysis of the opposing trends reveals that there is an added value in the regional climate model projections for the Barents region.

scholarly journals Regional Climate Modeling for the Developing World: The ICTP RegCM3 and RegCNET

2007 ◽  
Vol 88 (9) ◽  
pp. 1395-1410 ◽  
Author(s):  
Jeremy S. Pal ◽  
Filippo Giorgi ◽  
Xunqiang Bi ◽  
Nellie Elguindi ◽  
Fabien Solmon ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Regional Climate Modeling ◽  
Theoretical Physics ◽  
Research Network ◽  
Diverse Range

Regional climate models are important research tools available to scientists around the world, including in economically developing nations (EDNs). The Earth Systems Physics (ESP) group of the Abdus Salam International Centre for Theoretical Physics (ICTP) maintains and distributes a state-of-the-science regional climate model called the ICTP Regional Climate Model version 3 (RegCM3), which is currently being used by a large research community for a diverse range of climate-related studies. The RegCM3 is the central, but not only, tool of the ICTP-maintained Regional Climate Research Network (RegCNET) aimed at creating south–south and north–south scientific interactions on the topic of climate and associated impacts research and modeling. In this paper, RegCNET, RegCM3, and illustrative results from RegCM3 benchmark simulations applied over south Asia, Africa, and South America are presented. It is shown that RegCM3 performs reasonably well over these regions and is therefore useful for climate studies in EDNs.

First results of a comparison study of multi-domain REMO CORDEX simulations between 0.11° and 0.22° resolution with ERA-Interim forcing

2020 ◽  
Author(s):  
Martina Schubert-Frisius ◽  
Susanne Pfeifer ◽  
Armelle Reca Remedio ◽  
Claas Teichmann ◽  
Lars Buntemeyer ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Virtual Water ◽  
Regional Climate Models ◽  
Added Value ◽  
The Arctic ◽  
Climate Projections ◽  
First Results

<p>Within the framework of WCRP CORDEX, the CORE (CORDEX Coordinated Output for Regional Evaluations) experiment provides a homogeneous ensemble of regional climate projections for 9 domains covering all land areas of the globe with the exception of the Arctic and Antarctic regions (http://www.cordex.org/experiment-guidelines/cordex-core/). CORDEX-CORE provides data from two regional climate models (REMO2015 and RegCM), driven by 3 GCMs and under 2 RCP scenario conditions at a resolution of about 25 km. In addition, within the same framework, simulations of the current climate, driven by ERA-Interim, were carried out for all areas with REMO2015 at a grid resolution of approx. 25 km.</p><p>Within the German Project ViWA (Virtual Water Values, https://viwa.geographie-muenchen.de), simulations with the regional climate model REMO2015, driven by ERA-INTERIM analyses were carried out for the same regions globally, but on a significantly higher spatial resolution of approx. 12.5 km. These simulations cover the time period from 2015 to 2018. Comparing these highly resolved simulations to the coarsely resolved CORDEX-CORE simulations, can give indications, in which regions and for which processes the CORDEX-CORE resolution of 25 km is sufficient and where a higher resolution brings a clear added value.</p><p>We will show first results of this comparison, focusing on selected regions and processes which potentially benefit from higher spatial resolution of the simulations.</p>

REMOLAND: New high-resolution surface boundary data for the regional climate model REMO and their impacts

2020 ◽  
Author(s):  
Katrin Ziegler ◽  
Felix Pollinger ◽  
Daniel Abel ◽  
Heiko Paeth
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Data Sets ◽  
Surface Boundary ◽  
Local Climate

<p class="western" align="justify"><span lang="en-US">In cooperation with the Climate Service Center Germany (GERICS) we want to improve the land surface module in the regional climate model REMO. Due to the need of high-resolution regional climate models to get information about local climate change, new data and new processes have to be integrated in these models.</span></p> <p class="western" align="justify"><span lang="en-US">Based on the REMO2015 version and focusing on EUR-CORDEX region we included and compared five different high-resolution topographic data sets. To improve the thermal and hydrological processes in the model’s soil we also tested three new soil data sets with a much higher spatial resolution and with new parameters for a new soil parameterization.</span></p>

scholarly journals The regional climate model (REG-IN) for forecasting the adaptivity of forest ecosystems in Belgrade

2019 ◽  
pp. 127-139
Author(s):  
Tatjana Ratknić ◽  
Mihailo Ratknić ◽  
Lazar Vukadinović
Keyword(s):  
Regional Climate Model ◽  
Forest Ecosystems ◽  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Regional Climate Modeling ◽  
Climate Modelling ◽  
Wide Range

Regional climate modelling with regional climate models has become a part of modern research with a wide range of applications. This article examines the latest segments in the study of regional climate modeling used to assess the adaptivity and survival of particular forest species in changing conditions. It presents the results of the regional climate model (acronym REG-IN) used to predict the adaptive capacity of forest ecosystems in Belgrade. Compared to the SXG and E-P models, the REG-IN model exhibits certain deviations due to the specific environmental conditions of the area. These data have made it possible to predict the future rate of survival of individual forest ecosystems

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