scholarly journals Regional climate models downscaling analysis of general circulation models present climate biases propagation into future change projections

2008 ◽  
Vol 35 (8) ◽  
Author(s):  
Xin-Zhong Liang ◽  
Kenneth E. Kunkel ◽  
Gerald A. Meehl ◽  
Richard G. Jones ◽  
Julian X. L. Wang
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Present Climate ◽  
Future Change

scholarly journals The spread amongst ENSEMBLES regional scenarios: regional climate models, driving general circulation models and interannual variability

2011 ◽  
Vol 38 (5-6) ◽  
pp. 951-964 ◽  
Author(s):  
M. Déqué ◽  
S. Somot ◽  
E. Sanchez-Gomez ◽  
C. M. Goodess ◽  
D. Jacob ◽  
...  
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models

scholarly journals Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1032 ◽  
Author(s):  
Ariel Wang ◽  
Francina Dominguez ◽  
Arthur Schmidt
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Precipitation Frequency ◽  
Spatio Temporal ◽  
Climate Change Assessment

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.

scholarly journals Unravelling the contribution of potential evaporation formulation to uncertainty under climate change

2021 ◽  
Author(s):  
Thibault Lemaitre-Basset ◽  
Ludovic Oudin ◽  
Guillaume Thirel ◽  
Lila Collet
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Environmental Drivers ◽  
Climate Projections ◽  
Potential Evaporation ◽  
Evaporative Demand ◽  
Impact Studies

Abstract. The increasing air temperature in a changing climate will impact actual evaporation and have consequences for water resources management in energy-limited regions. In many hydrological models, evaporation is assessed by a preliminary computation of potential evaporation (PE) representing the evaporative demand of the atmosphere. Therefore, in impact studies the quantification of uncertainties related to PE estimation, which can arise from different sources, is crucial. Indeed, a myriad of PE formulations exist and the uncertainties related to climate variables cascade into PE computation. So far, no consensus has emerged on the main source of uncertainty in the PE modelling chain for hydrological studies. In this study, we address this issue by setting up a multi-model and multi-scenario approach. We used seven different PE formulations and a set of 30 climate projections to calculate changes in PE. To estimate the uncertainties related to each step of the PE calculation process (namely Representative Concentration Pathways, General Circulation Models, Regional Climate Models and PE formulations), an analysis of variance decomposition (ANOVA) was used. Results show that PE would increase across France by the end of the century, from +40 to +130 mm/year. In ascending order, uncertainty contributions by the end of the century are explained by: PE formulations (below 10 %), then RCPs (above 20 %), RCMs (30–40 %) and GCMs (30–40 %). Finally, all PE formulations show similar future trends since climatic variables are co-dependent to temperature. While no PE formulation stands out from the others, in hydrological impact studies the Penman-Monteith formulation may be preferred as it is representative of the PE formulations ensemble mean and allows accounting for climate and environmental drivers co-evolution.

scholarly journals On the potential use of glacier and permafrost observations for verification of climate models

1997 ◽  
Vol 25 ◽  
pp. 400-406 ◽  
Author(s):  
Martin Beniston ◽  
Wilfried Haeberli ◽  
Martin Hoelzle ◽  
Alan Taylor
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Model Performance ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Model Verification ◽  
Dominant Feature

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.

scholarly journals California Wintertime Precipitation Bias in Regional and Global Climate Models

2010 ◽  
Vol 49 (10) ◽  
pp. 2147-2158 ◽  
Author(s):  
Peter Caldwell
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Model Resolution ◽  
Grid Spacing ◽  
Precipitation Frequency

Abstract In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California and compared. Several averaging methodologies are considered and all are found to give similar values when the model grid spacing is less than 3°. This suggests that California is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict California precipitation. This appears to be due mainly to the overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge–satellite observations, which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait that does not seem to be tied to model resolution. The GCM daily and interannual variabilities are generally underpredicted.

Applying the new spatially distributed Added Value Index and Climate Change Downscaling Signal for Regional Climate Models to high-resolution EURO-CORDEX and convection permitting scale simulations

2021 ◽  
Author(s):  
James Ciarlo ◽  
Erika Coppola ◽  
Emanuela Pichelli ◽  
Jose Abraham Torres Alavez ◽  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
General Circulation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Added Value ◽  
Spatially Distributed

<p>Downscaling data from General Circulation Models (GCMs) with Regional Climate Models (RCMs) is a computationally expensive process, even more so running at the convection permitting scale (CP). Despite the high-resolution products of these simulations, the Added Value (AV) of these runs compared to their driving models is an important factor for consideration. A new method was recently developed to quantify the AV of historical simulations as well as the Climate Change Downscaling Signal (CCDS) of forecast runs. This method presents these quantities spatially and thus the specific regions with the most AV can be identified and understood.</p><p>An analysis of daily precipitation from a 55-model EURO-CORDEX ensemble (at 12 km resolution) was assessed using this method. It revealed positive AV throughout the domain with greater emphasis in regions of complex topography, coast-lines, and the tropics. Similar CCDS was obtained when assessing the RCP 8.5 far future runs in these domains. This paper looks more closely at the CCDS obtained with this method and compares it to other climate change signals described in other studies.</p><p>The same method is now being applied to assess the AV and CCDS of daily precipitation from an ensemble of models at the CP scale (~3 km) over different domains within Europe. The current stage of the analysis is also looking into the AV of using hourly precipitation instead of daily.</p>

scholarly journals A new spatially distributed Added Value Index for Regional Climate Models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles

2020 ◽  
Author(s):  
James M. Ciarlo` ◽  
Erika Coppola ◽  
Adriano Fantini ◽  
XueJie Gao ◽  
Yao Tong ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
New Method ◽  
Added Value ◽  
Tropical Regions ◽  
Spatially Distributed ◽  
Rcp 8.5

<p>Regional Climate Models (RCMs) have undergone substantial development, resulting in increasingly reliable high-resolution simulations. Despite this, the added value of these simulations compared to their driving General Circulation Models (GCMs) has been a recurring issue. Past studies have used different techniques to quantify the added value of a RCM. A new method is now being presented, based on these past studies, that quantifies the added value and presents it spatially. The method was also adapted to assess the Downscaling Signal (DS) in climate change simulations and compare this to the added value.</p><p>This new method has been used to assess the daily precipitation of the 55-model EURO-CORDEX ensemble and the CORDEX-CORE ensemble, focusing especially on the higher-end of the PDFs. This revealed an overall positive added value across all domains, especially in areas of complex topography, cost-lines, and tropical regions. This DS was similar to that of the added value when looking at RCP 8.5 far-future simulations.</p>

scholarly journals On the potential use of glacier and permafrost observations for verification of climate models

1997 ◽  
Vol 25 ◽  
pp. 400-406 ◽  
Author(s):  
Martin Beniston ◽  
Wilfried Haeberli ◽  
Martin Hoelzle ◽  
Alan Taylor
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Model Performance ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Model Verification ◽  
Dominant Feature

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.

scholarly journals Evaluation of the performance of CORDEX regional climate models in simulating present climate conditions of Tanzania

2016 ◽  
Vol 66 (1) ◽  
pp. 32
Author(s):  
Philbert Luhunga ◽  
Joel Botai ◽  
Frederick Kahimba
Keyword(s):  
Air Temperature ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Model Performance ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Variable Model ◽  
Climate Conditions ◽  
Statistical Measures

Regional climate models (RCMs) are widely used in regional assessment of climate change impacts. However, the reliability of individual models needs to be assessed before using their output for impact assessment. In this study, we evaluate the performance of RCMs from the Coordinated Regional Climate Downscaling Experiment program (CORDEX) to simulate minimum air temperature (TN), maximum air temperature (TX) and rainfall over Tanzania. Output from four RCMs driven by boundary conditions from three General Circulation Models (GCMs) and ERA-Interim data are evaluated against observed data from 22 weather stations. The evaluation is based on determining how well the RCMs reproduce climatological trends, interannual, and annual cycles of TN, TX and rainfall. Statistical measures of model performance that include the bias, root mean square error, correlation and trend analysis are used. It is found that RCMs capture the annual cycle of TN, TX and rainfall well, however underestimate and overestimate the amount of rainfall in March–April–May (MAM) and October–November–December (OND) seasons respectively. Most RCMs reproduce interannual variations of TN, TX and rainfall. The source of uncertainties can be analysed when the same RCM is driven by different GCMs and different RCMs driven by same GCM simulate TN, TX and rainfall differently. It is found that the biases and errors from the RCMs and driving GCMs contribute roughly equally. Overall, the evaluation finds reasonable (although variable) model skill in representing mean climate, interannual variability and temperature trends, suggesting the potential use of CORDEX RCMs in simulating TN, TX and rainfall over Tanzania.

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