Response of Wintertime Antarctic Temperatures to the Antarctic Oscillation: Results of a Regional Climate Model

2013 ◽  
pp. 43-58 ◽  
Author(s):  
Michiel R. Van Den Broeke ◽  
Nicole P. M. Van Lipzig
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Antarctic Oscillation ◽  
The Antarctic

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 Antarctic 20th Century Accumulation Changes Based on Regional Climate Model Simulations

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Klaus Dethloff ◽  
Ksenia Glushak ◽  
Annette Rinke ◽  
Dörthe Handorf
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
East Antarctica ◽  
Transient Pressure ◽  
Near Surface ◽  
Surface Mass ◽  
The Antarctic

The regional climate model HIRHAM has been applied to Antarctica driven at the lateral and lower boundaries by European Reanalysis data ERA-40 for the period 1958–1998. Simulations over 4 decades, carried out with a horizontal resolution of 50 km, deliver a realistic simulation of the Antarctic atmospheric circulation, synoptic-scale pressure systems, and the spatial distribution of precipitation minus sublimation (P-E) structures. The simulated P-E pattern is in qualitative agreement with glaciological estimates. The estimated (P-E) trends demonstrate surfacemass accumulation increase at the West Antarctic coasts and reductions in parts of East Antarctica. The influence of the Antarctic Oscillation (AAO) on the near-surface climate and the surface mass accumulation over Antarctica have been investigated on the basis of ERA-40 data and HIRHAM simulations. It is shown that the regional accumulation changes are largely driven by changes in the transient activity around the Antarctic coasts due to the varying AAO phases. During positive AAO, more transient pressure systems travelling towards the continent, and Western Antarctica and parts of South-Eastern Antarctica gain more precipitation and mass. Over central Antarctica the prevailing anticyclone causes a strengthening of polar desertification connected with a reduced surface mass balance in the northern part of East Antarctica.

scholarly journals Brief Communication: Upper air relaxation in RACMO2 significantly improves modelled interannual SMB variability in Antarctica

2015 ◽  
Vol 9 (5) ◽  
pp. 4981-4995
Author(s):  
W. J. van de Berg ◽  
B. Medley
Keyword(s):  
Regional Climate Model ◽  
Interannual Variability ◽  
Antarctic Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
West Antarctica ◽  
Steep Topography ◽  
The Antarctic

Abstract. The regional climate model RACMO2 has been a powerful tool for improving SMB estimates from GCMs or reanalyses. However, new yearly SMB observations for West Antarctica show that the modelled interannual variability in SMB is poorly simulated by RACMO2, in contrast to ERA-Interim, which resolves this variability well. In an attempt to remedy RACMO2 performance, we included additional upper air relaxation (UAR) in RACMO2. With UAR, the correlation to observations is similar for RACMO2 and ERA-Interim. The spatial SMB patterns and ice sheet integrated SMB modelled using UAR remain very similar to the estimates of RACMO2 without UAR. We only observe an upstream smoothing of precipitation in regions with very steep topography like the Antarctic Peninsula. We conclude that UAR is a useful improvement for RCM simulations, although results in regions with steep topography should be treated with care.

scholarly journals Melting over the East Antarctic Peninsula (1999–2009): evaluation of a high-resolution regional climate model

2017 ◽  
Author(s):  
Rajashree T. Datta ◽  
Marco Tedesco ◽  
Cecile Agosta ◽  
Xavier Fettweis ◽  
Peter Kuipers Munneke ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Spatial Resolution ◽  
Antarctic Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Shelf ◽  
Circulation Patterns ◽  
The Antarctic ◽  
Microwave Data

Abstract. Surface melting over the Antarctic Peninsula (AP) plays a crucial role for the stability of ice shelves and dynamics of grounded ice, hence modulating the mass balance in a region of the world which is particularly sensitive to increasing surface temperatures. Understanding the processes that drive melting using surface energy and mass balance models is fundamental to improving estimates of current and future surface melting and associated sea level rise through ice-shelf collapse. This is even more important in view of both the paucity of in-situ measurements in Antarctica generally and the specific challenges presented by the circulation patterns over the Antarctic Peninsula. In this study, we evaluate the regional climate model Modèle Atmosphérique Régionale (MAR) over the Antarctic Peninsula (AP) at a 10 km spatial resolution between 1999 and 2009, a period which coincides with the availability of active microwave data from the QuikSCAT mission. This is the first time that this model, which has been validated extensively over Greenland, has been applied to the Antarctic Peninsula at a high resolution. We compare melt occurrence modeled by MAR with a combination of estimates from passive and active microwave data. Our primary regional focus is the northern East Antarctic Peninsula (East AP), where we evaluate MAR against wind and temperature data collected by three automatic weather stations (AWS). Our results indicate that satellites estimates show greater melt frequency, a larger melt extent, and a quicker expansion to peak melt extent than MAR in the center and east of the Larsen C ice shelf. The difference between the remote sensing and modeled estimates reduces in the north and west of the East AP. Melting in the East AP can be initiated by both sporadic westerly föhn flow over the AP and northerly winds advecting warm air from lower latitudes. To quantify MAR's ability to simulate different circulation patterns that affect melt, we take a unique approach to evaluate melt occurrence (using satellite data) and concurrent temperature biases associated with specific wind direction biases using AWS data over the Larsen Ice Shelf. Our results indicate that although MAR shows an overall warm bias, it also shows fewer warm, strong westerly winds than reported by AWS stations, which may lead to an underestimation of melt. The underestimation of föhn flow in the east of the Larsen C may potentially be resolved by removing the hydrostatic assumption in MAR or increasing spatial resolution. The underestimation of southwesterly flow in particular may be reduced by using higher-resolution topography.

scholarly journals Recent Near-surface Temperature Trends in the Antarctic Peninsula from Observed, Reanalysis and Regional Climate Model Data

2020 ◽  
Vol 37 (5) ◽  
pp. 477-493
Author(s):  
Deniz Bozkurt ◽  
David H. Bromwich ◽  
Jorge Carrasco ◽  
Keith M. Hines ◽  
Juan Carlos Maureira ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Regional Climate Model ◽  
Antarctic Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Model Data ◽  
Near Surface ◽  
Temperature Trends ◽  
The Antarctic

Qinghai-Xizang (Tibetan) Plateau climate simulation using the regional climate model RegCM3

2013 ◽  
Vol 57 (3) ◽  
pp. 173-186 ◽  
Author(s):  
X Wang ◽  
M Yang ◽  
G Wan ◽  
X Chen ◽  
G Pang
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Simulation

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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