scholarly journals The Influence of the Amundsen–Bellingshausen Seas Low on the Climate of West Antarctica and Its Representation in Coupled Climate Model Simulations

2013 ◽  
Vol 26 (17) ◽  
pp. 6633-6648 ◽  
Author(s):  
J. Scott Hosking ◽  
Andrew Orr ◽  
Gareth J. Marshall ◽  
John Turner ◽  
Tony Phillips
Keyword(s):  
Annual Cycle ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Southern Annular Mode ◽  
Central Pressure ◽  
West Antarctica ◽  
Pressure System ◽  
Longitudinal Position

Abstract In contrast to earlier studies, the authors describe the climatological deep low pressure system that exists over the South Pacific sector of the Southern Ocean, referred to as the Amundsen–Bellingshausen Seas low (ABSL), in terms of its relative (rather than actual) central pressure by removing the background area-averaged mean sea level pressure (MSLP). Doing so removes much of the influence of large-scale variability across the ABSL sector region (e.g., due to the southern annular mode), allowing a clearer understanding of ABSL variability and its effect on the regional climate of West Antarctica. Using ECMWF Interim Re-Analysis (ERA-Interim) fields, the annual cycle of the relative central pressure of the ABSL for the period from 1979 to 2011 shows a minimum (maximum) during winter (summer), differing considerably from the earlier studies based on actual central pressure, which suggests a semiannual oscillation. The annual cycle of the longitudinal position of the ABSL is insensitive to the background pressure, and shows it shifting westward from ∼250° to ∼220°E between summer and winter, in agreement with earlier studies. The authors demonstrate that ABSL variability, and in particular its longitudinal position, play an important role in controlling the surface climate of West Antarctica and the surrounding ocean by quantifying its influence on key meteorological parameters. Examination of the ABSL annual cycle in 17 CMIP5 climate models run with historical forcing shows that the majority of them have definite biases, especially in terms of longitudinal position, and a correspondingly poor representation of West Antarctic climate.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

Large-Scale Atmospheric Drivers of Snowfall on Thwaites Glacier

2020 ◽  
Author(s):  
Michelle Maclennan ◽  
Jan Lenaerts
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Southern Annular Mode ◽  
Spatial And Temporal Variability ◽  
Atmospheric Conditions ◽  
Amundsen Sea ◽  
Weather Patterns

<p>High snowfall events on Thwaites Glacier are a key influencer of its ice mass change. In this study, we diagnose the mechanisms for orographic precipitation on Thwaites Glacier by analyzing the atmospheric conditions that lead to high snowfall events. A high-resolution regional climate model, RACMO2, is used in conjunction with MERRA-2 and ERA5 reanalysis to map snowfall and associated atmospheric conditions over the Amundsen Sea Embayment. We examine these conditions during high snowfall events over Thwaites Glacier to characterize the drivers of the precipitation and their spatial and temporal variability. Then we examine the seasonal differences in the associated weather patterns and their correlations with El Nino Southern Oscillation and the Southern Annular Mode. Understanding the large-scale atmospheric drivers of snowfall events allows us to recognize how these atmospheric drivers and consequent snowfall climatology will change in the future, which will ultimately improve predictions of accumulation on Thwaites Glacier.</p>

Dependence of benefits of convection permitting models on large-scale conditions

2020 ◽  
Author(s):  
Danijel Belusic ◽  
Petter Lind ◽  
Oskar Landgren ◽  
Dominic Matte ◽  
Rasmus Anker Pedersen ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Rapid Change ◽  
Winter Season ◽  
Storm Track ◽  
Summer Precipitation ◽  
Weather Conditions ◽  
Special Focus

<p>Current literature strongly indicates large benefits of convection permitting models for subdaily summer precipitation extremes. There has been less insight about other variables, seasons and weather conditions. We examine new climate simulations over the Nordic region, performed with the HCLIM38 regional climate model at both convection permitting and coarser scales, searching for benefits of using convection permitting resolutions. The Nordic climate is influenced by the North Atlantic storm track and characterised by large seasonal contrasts in temperature and precipitation. It is also in rapid change, most notably in the winter season when feedback processes involving retreating snow and ice lead to larger warming than in many other regions. This makes the area an ideal testbed for regional climate models. We explore the effects of higher resolution and better reproduction of convection on various aspects of the climate, such as snow in the mountains, coastal and other thermal circulations, convective storms and precipitation with a special focus on extreme events. We investigate how the benefits of convection permitting models change with different variables and seasons, and also their sensitivity to different circulation regimes.</p>

scholarly journals Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change?

2017 ◽  
Vol 98 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
Nikolina Ban ◽  
Nigel M. Roberts ◽  
Hayley J. Fowler ◽  
Malcolm J. Roberts ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Convective Storms ◽  
Wide Range

Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.

How uncertain are climate model projections of water availability indicators across the Middle East?

2010 ◽  
Vol 368 (1931) ◽  
pp. 5117-5135 ◽  
Author(s):  
Debbie Hemming ◽  
Carlo Buontempo ◽  
Eleanor Burke ◽  
Mat Collins ◽  
Neil Kaye
Keyword(s):  
Middle East ◽  
Water Availability ◽  
Large Scale ◽  
Drought Index ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
General Distribution ◽  
The North ◽  
Run Off

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961–1990 and 2021–2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between −5 and −25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

scholarly journals Increased variability in Greenland Ice Sheet runoff from satellite observations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Thomas Slater ◽  
Andrew Shepherd ◽  
Malcolm McMillan ◽  
Amber Leeson ◽  
Lin Gilbert ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Model Simulations ◽  
Climate Model Simulations

AbstractRunoff from the Greenland Ice Sheet has increased over recent decades affecting global sea level, regional ocean circulation, and coastal marine ecosystems, and it now accounts for most of the contemporary mass imbalance. Estimates of runoff are typically derived from regional climate models because satellite records have been limited to assessments of melting extent. Here, we use CryoSat-2 satellite altimetry to produce direct measurements of Greenland’s runoff variability, based on seasonal changes in the ice sheet’s surface elevation. Between 2011 and 2020, Greenland’s ablation zone thinned on average by 1.4 ± 0.4 m each summer and thickened by 0.9 ± 0.4 m each winter. By adjusting for the steady-state divergence of ice, we estimate that runoff was 357 ± 58 Gt/yr on average – in close agreement with regional climate model simulations (root mean square difference of 47 to 60 Gt/yr). As well as being 21 % higher between 2011 and 2020 than over the preceding three decades, runoff is now also 60 % more variable from year-to-year as a consequence of large-scale fluctuations in atmospheric circulation. Because this variability is not captured in global climate model simulations, our satellite record of runoff should help to refine them and improve confidence in their projections.

scholarly journals Soil Control on Runoff Response to Climate Change in Regional Climate Model Simulations

2005 ◽  
Vol 18 (17) ◽  
pp. 3536-3551 ◽  
Author(s):  
Bart van den Hurk ◽  
Martin Hirschi ◽  
Christoph Schär ◽  
Geert Lenderink ◽  
Erik van Meijgaard ◽  
...  
Keyword(s):  
Climate Change ◽  
Annual Cycle ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Water Storage ◽  
Climate Simulation ◽  
Discharge Data ◽  
And Storage

Abstract Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections.

scholarly journals Impact of Lateral Boundary Errors on the Simulation of Clouds with a Nonhydrostatic Regional Climate Model

2017 ◽  
Vol 145 (12) ◽  
pp. 5059-5082 ◽  
Author(s):  
Junya Uchida ◽  
Masato Mori ◽  
Masayuki Hara ◽  
Masaki Satoh ◽  
Daisuke Goto ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Convective Precipitation ◽  
Uniform Grid ◽  
Lateral Boundary Condition ◽  
Limited Area ◽  
Lateral Boundary ◽  
Precipitation Distribution

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.

scholarly journals Exploring Perturbed Physics Ensembles in a Regional Climate Model

2012 ◽  
Vol 25 (13) ◽  
pp. 4582-4599 ◽  
Author(s):  
Omar Bellprat ◽  
Sven Kotlarski ◽  
Daniel Lüthi ◽  
Christoph Schär
Keyword(s):  
Regional Climate Model ◽  
Annual Cycle ◽  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Total Cloud Cover ◽  
Observational Uncertainty ◽  
Perturbed Physics ◽  
Perturbed Physics Ensembles

Abstract Perturbed physics ensembles (PPEs) have been widely used to assess climate model uncertainties and have provided new estimates of climate sensitivity and parametric uncertainty in state-of-the-art climate models. So far, mainly global climate models were used to generate PPEs, and little work has been conducted with regional climate models. This paper discusses the parameter uncertainty in two PPEs of a regional climate model driven by reanalysis data for the present climate over Europe. The uncertainty is evaluated for the variables of 2-m temperature, precipitation, and total cloud cover, with a focus on the annual cycle, interannual variability, and selected extremes. The authors show that the simulated spread of the PPEs encompasses the observations at a regional scale in terms of the annual cycle and the interannual variability, provided observational uncertainty is taken into account. To rank the PPEs a new skill metric is proposed, which takes into account observational uncertainty and natural variability. The metric is a generalization of the climate prediction index (CPI) and is compared to metrics used in other studies. The consideration of observational uncertainty is particularly important for total cloud cover and reveals that current observations do not allow for a systematic evaluation of high precipitation intensities over the entire European domain. The skill framework is additionally used to identify important model parameters, which are of interest for an objective model calibration.

Constraining hydrological impact simulations over Europe through weighting the climatic forcing

2020 ◽  
Author(s):  
Peter Greve ◽  
Peter Burek ◽  
Renate Wilcke ◽  
Lukas Brunner ◽  
Carol McSweeney ◽  
...  
Keyword(s):  
Input Data ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Hydrological Impact ◽  
Model Ensembles ◽  
Hydrological Extreme ◽  
Impact Simulations

<p><span>Global hydrological models (GHMs) have become an established tool to simulate water resources on continental scales. To assess the future of water availability and various impacts related to hydrological extreme events, these models usually use sets of atmospheric variables (such as e.g., precipitation, humidity, temperature) obtained from (regional) climate model simulations as input data. The uncertainty associated with the climate projections is transferred onwards into the impact simulations and is usually accounted for through the use of large model ensembles. These ensembles thus enable assessments addressing the robustness of projected hydrological changes and impacts. Given recent efforts within the European Climate Prediction (EUCP) project to test existing and develop new techniques to constrain/weight climate model ensembles, we use here different methods to specify the large-scale meteorological input to an ensemble of regional climate models that provide the input data for a state-of-the-art GHM. The climate models are weighted/constrained based on the key large-scale climatic and meteorological drivers shaping the hydrological characteristics in different regions and large river basins across Europe. To assess the potential benefits of the different techniques, we compare simulation ensembles using unweighted input data obtained from the full ensemble of regional climate models against an ensemble based on constrained/weighted forcing data. Given the large uncertainties usually associated with hydrological impact simulations forced by the full range of available climate models, processing the ensemble output of GHMs based on uncertainty assessments of the underlying climate forcing could lead to more robust projections of water resources in general and hydrological extreme events in particular. </span></p>

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