scholarly journals Atmospheric Blocking and Mean Biases in Climate Models

2010 ◽  
Vol 23 (23) ◽  
pp. 6143-6152 ◽  
Author(s):  
Adam A. Scaife ◽  
Tim Woollings ◽  
Jeff Knight ◽  
Gill Martin ◽  
Tim Hinton
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Small Scale ◽  
Model Data ◽  
Atmospheric Blocking ◽  
Intergovernmental Panel ◽  
Weather And Climate ◽  
Main Culprit

Abstract Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

scholarly journals Antarctic precipitation and climate-change predictions: horizontal resolution and margin vs plateau issues

2009 ◽  
Vol 50 (50) ◽  
pp. 55-60 ◽  
Author(s):  
C. Genthon ◽  
G. Krinner ◽  
H. Castebrunet
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Models ◽  
Prediction Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Horizontal Resolution ◽  
Intergovernmental Panel ◽  
Precipitation Increase ◽  
Antarctic Precipitation

AbstractAll climate models participating in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, as made available by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) as the Coupled Model Intercomparison Project 3 (CMIP3) archive, predict a significant surface warming of Antarctica by the end of the 21st century under a moderate (SRESA1B) greenhouse-gas scenario. All models but one predict a concurrent precipitation increase but with a large scatter of results. The models with finer horizontal resolution tend to predict a larger precipitation increase. Because modeled Antarctic surface mass balance is known to be sensitive to horizontal resolution, extrapolating predictions from the different models with respect to model resolution may provide simple yet better multi-model estimates of Antarctic precipitation change than mere averaging or even more complex approaches. Using such extrapolation, a conservative estimate of the predicted precipitation increase at the end of the 21st century is +30 kg m–2 a–1 on the grounded ice sheet, corresponding to a >1m ma–1 sea-level rise. About three-quarters of this rise originates from the marginal regions of the Antarctic ice sheet with surface elevation below 2250 m. This is where field programs are most urgently needed to better understand and monitor accumulation at the surface of Antarctica, and to improve and verify prediction models.

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.

scholarly journals Abrupt Circulation Responses to Tropical Upper-Tropospheric Warming in a Relatively Simple Stratosphere-Resolving AGCM

2012 ◽  
Vol 25 (12) ◽  
pp. 4097-4115 ◽  
Author(s):  
Shuguang Wang ◽  
Edwin P. Gerber ◽  
Lorenzo M. Polvani
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Polar Vortex ◽  
Circulation Model ◽  
Hadley Cell ◽  
Critical Threshold ◽  
Intergovernmental Panel ◽  
Upper Troposphere

Abstract The circulation response of the atmosphere to climate change–like thermal forcing is explored with a relatively simple, stratosphere-resolving general circulation model. The model is forced with highly idealized physics, but integrates the primitive equations at resolution comparable to comprehensive climate models. An imposed forcing mimics the warming induced by greenhouse gasses in the low-latitude upper troposphere. The forcing amplitude is progressively increased over a range comparable in magnitude to the warming projected by Intergovernmental Panel on Climate Change coupled climate model scenarios. For weak to moderate warming, the circulation response is remarkably similar to that found in comprehensive models: the Hadley cell widens and weakens, the tropospheric midlatitude jets shift poleward, and the Brewer–Dobson circulation (BDC) increases. However, when the warming of the tropical upper troposphere exceeds a critical threshold, ~5 K, an abrupt change of the atmospheric circulation is observed. In the troposphere the extratropical eddy-driven jet jumps poleward nearly 10°. In the stratosphere the polar vortex intensifies and the BDC weakens as the intraseasonal coupling between the troposphere and the stratosphere shuts down. The key result of this study is that an abrupt climate transition can be effected by changes in atmospheric dynamics alone, without need for the strong nonlinearities typically associated with physical parameterizations. It is verified that the abrupt climate shift reported here is not an artifact of the model’s resolution or numerics.

scholarly journals Quantifying the Likelihood of Regional Climate Change: A Hybridized Approach

2013 ◽  
Vol 26 (10) ◽  
pp. 3394-3414 ◽  
Author(s):  
C. Adam Schlosser ◽  
Xiang Gao ◽  
Kenneth Strzepek ◽  
Andrei Sokolov ◽  
Chris E. Forest ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Projections ◽  
Massachusetts Institute Of Technology ◽  
Adaptation To Climate Change ◽  
Intergovernmental Panel ◽  
Near Surface ◽  
Institute Of Technology

Abstract The growing need for risk-based assessments of impacts and adaptation to climate change calls for increased capability in climate projections: specifically, the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Herein, the authors present a technique that extends the latitudinal projections of the 2D atmospheric model of the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate model projections archived from exercises carried out for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a set of transformation coefficients, and this approach is demonstrated in application to near-surface air temperature and precipitation, for which high-quality observational datasets and model simulations of climate change are available. The current climatology of the transformation coefficients is observationally based. To estimate how these coefficients may alter with climate, the authors characterize the climate models’ spatial responses, relative to their zonal mean, from transient increases in trace-gas concentrations and then normalize these responses against their corresponding transient global temperature responses. This procedure allows for the construction of metaensembles of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with regionally resolved patterns from the archived IPCC climate model projections. This hybridization of the climate model longitudinal projections with the global and latitudinal patterns projected by the IGSM can, in principle, be applied to any given state or flux variable that has the sufficient observational and model-based information.

scholarly journals Análisis de anomalías climáticas para la cuenca del río La Villa, Panamá, basado en los escenarios RCP

2020 ◽  
Vol 16 (1) ◽  
pp. 83-89
Author(s):  
Cassilda Saavedra
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Small Scale ◽  
Climate Projections ◽  
Adaptation To Climate Change ◽  
Climate Change Projections ◽  
Intergovernmental Panel ◽  
Rcp Scenarios ◽  
Mitigation And Adaptation ◽  
Del Rio

The use of climate change projections is crucial for mitigation and adaptation, which are the basis for creating resilience. However, access to these scientific products is scarce in Latin America and the existing studies lack of an appropriate resolution to analyze small but highly vulnerable regions, such as river basins for planning purposes.   La Villa river basin, Republic of Panama, is one of the watersheds of highest priority for adaptation to climate change. This study used downscaled projections from four climate models. The models are based on the Representative Concentration Pathways (RCP), presented in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change-IPCC. Results of this study suggest increases of the annual average precipitation in the watershed for the years 2050 and 2070. Meanwhile, maximum and minimum temperatures will increase an average of 1-2 ° C and near 4 ° C by the end of the 21st century. With these results, we observed that the use of small-scale climate projections in the RCP scenarios is feasible to determine the effects of climate change on small regions.

CMIP6 data documentation and citation in IPCC's Sixth Assessment Report (AR6)

2021 ◽  
Author(s):  
Martina Stockhause ◽  
Robin Matthews ◽  
Anna Pirani ◽  
Anne Marie Treguier ◽  
Ozge Yelekci
Keyword(s):  
Climate Change ◽  
Working Group ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Data ◽  
Intergovernmental Panel ◽  
Assessment Report ◽  
Data Usage ◽  
Group I

<p>The the amount of work and resources invested by the modelling centers to provide CMIP6 (Coupled Model Intercomparison Project Phase 6) experiments and climate projection datasets is huge, and therefore it is extremely important that the teams receive proper credit for their work. The Citation Service makes CMIP6 data citable with DOI references for the evolving CMIP6 model data published in the Earth System Grid Federation (ESGF). The Citation Service as a new piece of the CMIP6 infrastructure was developed upon the request from the CMIP Panel.</p><p>CMIP6 provides new global climate model data assessed in the IPCC's (Intergovernmental Panel on Climate Change) Sixth Assessment Report (AR6). Led by the Technical Support Unit of IPCC Working Group I (WGI TSU), the IPCC Task Group on Data Support for Climate Change Assessment (TG-Data) developed FAIR data guidelines, for implementation by the TSUs of the three IPCC WGs and the IPCC Data Distribution Centre (DDC) Partners. A central part of the FAIR data guidelines are the documentation and citation of data used in the report.</p><p>The contribution will show how CMIP6 data usage is documented in IPCC WGI AR6 from three angles: technical implementation, collection of CMIP6 data usage information from the IPCC authors, and a report users’ perspective.</p><p> </p><p>Links:</p><ul><li>CMIP6 Citation Service: http://cmip6cite.wdc-climate.de</li> <li>CMIP6: https://pcmdi.llnl.gov/CMIP6/</li> <li>IPCC AR6: https://www.ipcc.ch/assessment-report/ar6/</li> <li>IPCC AR6 WGI report: https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/</li> <li>IPCC TG-Data: https://www.ipcc.ch/data/</li> </ul>

scholarly journals Controls on the Diversity in Climate Model Projections of Early Summer Drying over Southern Africa

2019 ◽  
Vol 32 (12) ◽  
pp. 3707-3725 ◽  
Author(s):  
C. Munday ◽  
R. Washington
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Stability ◽  
Coupled Model ◽  
Early Summer ◽  
Intergovernmental Panel ◽  
Surface Temperature Change

Abstract Ninety-five percent of climate models contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) project early summer [October–December (OND)] rainfall declines over subtropical southern Africa by the end of the century, under all emissions forcing pathways. The intermodel consensus underlies the Intergovernmental Panel on Climate Change (IPCC) assessment that rainfall declines are “likely” and implies that significant climate change adaptation is needed. However, model consensus is not necessarily a good indicator of confidence, especially given that there is an order of magnitude difference in the scale of rainfall decline among models in OND (from <10 mm season−1 to ~100 mm season−1), and that the CMIP5 ensemble systematically overestimates present-day OND precipitation over subtropical southern Africa (in some models by a factor of 2). In this paper we investigate the uncertainty in the OND drying signal by evaluating the climate mechanisms that underlie the diversity in model rainfall projections. Models projecting the highest-magnitude drying simulate the largest increases in tropospheric stability over subtropical southern Africa associated with anomalous upper-level subsidence, reduced evaporation, and amplified surface temperature change. Intermodel differences in rainfall projections are in turn related to the large-scale adjustment of the tropical atmosphere to emissions forcing: models with the strongest relative warming of the northern tropical sea surface temperatures compared to the tropical mean warming simulate the largest rainfall declines. The models with extreme rainfall declines also tend to simulate large present-day biases in rainfall and in atmospheric stability, leading the authors to suggest that projections of high-magnitude drying require further critical attention.

Importance of Ocean Heat Uptake Efficacy to Transient Climate Change

2010 ◽  
Vol 23 (9) ◽  
pp. 2333-2344 ◽  
Author(s):  
Michael Winton ◽  
Ken Takahashi ◽  
Isaac M. Held
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Balance Model ◽  
Intergovernmental Panel ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Warming ◽  
Global Mean Temperature ◽  
Heat Uptake

Abstract This article proposes a modification to the standard forcing–feedback diagnostic energy balance model to account for 1) differences between effective and equilibrium climate sensitivities and 2) the variation of effective sensitivity over time in climate change experiments with coupled atmosphere–ocean climate models. In the spirit of Hansen et al. an efficacy factor is applied to the ocean heat uptake. Comparing the time evolution of the surface warming in high and low efficacy models demonstrates the role of this efficacy in the transient response to CO2 forcing. Abrupt CO2 increase experiments show that the large efficacy of the Geophysical Fluid Dynamics Laboratory’s Climate Model version 2.1 (CM2.1) sets up in the first two decades following the increase in forcing. The use of an efficacy is necessary to fit this model’s global mean temperature evolution in periods with both increasing and stable forcing. The intermodel correlation of transient climate response with ocean heat uptake efficacy is greater than its correlation with equilibrium climate sensitivity in an ensemble of climate models used for the third and fourth Intergovernmental Panel on Climate Change (IPCC) assessments. When computed at the time of doubling in the standard experiment with 1% yr−1 increase in CO2, the efficacy is variable amongst the models but is generally greater than 1, averages between 1.3 and 1.4, and is as large as 1.75 in several models.

scholarly journals An Investigation of cold-wet Compound Events in Greece

2021 ◽  
Author(s):  
Iason Markantonis ◽  
Diamando Vlachogiannis ◽  
Thanasis Sfetsos ◽  
Ioannis Kioutsioukis ◽  
Nadia Politi
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Extreme Event ◽  
Global Climate ◽  
Global Climate Model ◽  
Horizontal Resolution ◽  
Daily Minimum Temperature ◽  
Historical Period ◽  
Compound Events

<p>Climate change is set to affect extreme climate and meteorological events. The combination of interacting physical processes (climate drivers) across various spatial and temporal scales resulting to an extreme event is referred to as compound event. So far, climate change impacts on compound events in Greece such as daily cold-wet events have not been explored. The complex geography and topography of Greece forms a variety of regions with different local climate and a great range in daily minimum temperature and precipitation distributions. This leads to the assumption that there we will also observe a variety in the distribution of cold-wet events depending on the region. Aim of our study in this work is first to identify the cold-wet events based on observational data and then to examine the predictive capability of regional different climate models and ERA-Interim against observations from the Hellenic National Meteorological Service (HNMS) stations for the occurrence of cold-wet compound events in the present climate. The study will focus on the colder and wetter period of the year (November-April) to determine the extremes for this period. Specifically, the datasets employed are from two EURO-CORDEX Regional Climate Models (RCMs) with 0.11° horizontal resolution and validated ERA-Interim Reanalysis downscaled with the Weather Research and Forecasting (WRF) model at 5km horizontal resolution, for the historical period 1980-2004. In particular, the RCM datasets analyses have been produced from SMHI-RCA4 driven by MPI-M-MPI-ESM-LR Global Climate Model (GCM) and CLMcom-CLM-CCLM4-8-17 driven by MOHC-HadGEM2-ES GCM. After the comparison with the observations, the gridded data from the models will give us the ability to observe the spatial distribution of the compound events.</p>

scholarly journals Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19

2016 ◽  
Vol 9 (9) ◽  
pp. 3393-3412 ◽  
Author(s):  
David Leutwyler ◽  
Oliver Fuhrer ◽  
Xavier Lapillonne ◽  
Daniel Lüthi ◽  
Christoph Schär
Keyword(s):  
Graphics Processing Units ◽  
Climate Models ◽  
Climate Model ◽  
Deep Convection ◽  
Regional Climate ◽  
Small Scale ◽  
Moist Convection ◽  
Cosmo Model ◽  
Climate Simulations ◽  
Weather And Climate

Abstract. The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Using horizontal grid spacings of O(1km), convection-resolving weather and climate models allows one to explicitly resolve deep convection. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in supercomputing have led to new hybrid node designs, mixing conventional multi-core hardware and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to these architectures is the COSMO (Consortium for Small-scale Modeling) model.Here we present the convection-resolving COSMO model on continental scales using a version of the model capable of using GPU accelerators. The verification of a week-long simulation containing winter storm Kyrill shows that, for this case, convection-parameterizing simulations and convection-resolving simulations agree well. Furthermore, we demonstrate the applicability of the approach to longer simulations by conducting a 3-month-long simulation of the summer season 2006. Its results corroborate the findings found on smaller domains such as more credible representation of the diurnal cycle of precipitation in convection-resolving models and a tendency to produce more intensive hourly precipitation events. Both simulations also show how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. This includes the formation of sharp cold frontal structures, convection embedded in fronts and small eddies, or the formation and organization of propagating cold pools. Finally, we assess the performance gain from using heterogeneous hardware equipped with GPUs relative to multi-core hardware. With the COSMO model, we now use a weather and climate model that has all the necessary modules required for real-case convection-resolving regional climate simulations on GPUs.

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