scholarly journals Evaluation of Regional Climate Models (RCMs) Using Precipitation and Temperature-Based Climatic Indices: A Case Study of Florida, USA

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2411
Author(s):  
Yared Bayissa ◽  
Assefa Melesse ◽  
Mahadev Bhat ◽  
Tsegaye Tadesse ◽  
Andualem Shiferaw
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
The Other ◽  
Model Simulations ◽  
Climatic Indices ◽  
Pattern Correlation ◽  
Ensemble Mean ◽  
Climate Model Simulations

The overarching objective of this study was to evaluate the performance of nine precipitation-based and twelve temperature-based climatic indices derived from four regional climate models (CRCM5-UQUAM, CanRCM4, RCA4 and HIRHAM5) driven by three global circulation models (CanESM2, EC-EARTH and MPI-ESM-LR) and their ensemble mean for the reference period of 31 years (1975–2005). The absolute biases, pattern correlation, the reduction of variance (RV) and the Standardized Precipitation Evapotranspiration Index (SPEI at 3-, 6- and 12-month aggregate periods) techniques were used to evaluate the climate model simulations. The result, in general, shows each climate model has a skill in reproducing at least one of the climatic indices considered in this study. Based on the pattern correlation result, however, EC-EARTH.HIRHAM5 and MPI-ESM-LR.CRCM5-UQAM RCMs showed a relatively good skill in reproducing the observed climatic indices as compared to the other climate model simulations. EC-EARTH.RCA4, CanESM2.RCA4 and MPI-ESM-LR.CRCM5-UQAM RCMs showed a good skill when evaluated using the reduction of variance. The ensemble mean of the RCMs showed relatively better skill in reproducing the observed temperature-based climatic indices as compared to the precipitation-based climatic indices. There were no exceptional differences observed among the performance of the climate models compared to the SPEI, but CanESM2.CRCM5-UQAM, EC-EARTH.RCA4 and the ensemble mean of the RCMs performed relatively good in comparison to the other climate models. The good performance of some of the RCMs has good implications for their potential application for climate change impact studies and future trend analysis of extreme events. They could help in developing an early warning system to mitigate and prepare for possible future impacts of climate extremes (e.g., drought) and vulnerability to climate change across Florida.

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 Future Changes in Euro-Mediterranean Daytime Severe Thunderstorm Environments Based on an RCP8.5 Med-CORDEX Simulation

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 822
Author(s):  
Abdullah Kahraman ◽  
Deniz Ural ◽  
Barış Önol
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Regional Climate Models ◽  
Severe Thunderstorm ◽  
Convective Scale ◽  
Thermodynamic Conditions ◽  
The Mediterranean ◽  
Climate Model Simulations

Convective scale processes and, therefore, thunderstorm-related hazards cannot be simulated using regional climate models with horizontal grid spacing in the order of 10 km. However, larger-scale environmental conditions of these local high-impact phenomena can be diagnosed to assess their frequency in current and future climates. In this study, we present a daytime climatology of severe thunderstorm environments and its evolution for a wide Euro-Mediterranean domain through the 21st century, using regional climate model simulations forced by Representative Concentration Pathway (RCP) 8.5 scenario. Currently, severe convective weather is more frequently favored around Central Europe and the Mediterranean Sea. Our results suggest that with a steady progress until the end of the century, Mediterranean coasts are projected to experience a significantly higher frequency of severe thunderstorm environments, while a slight decrease over parts of continental Europe is evaluated. The increase across the Mediterranean is mostly owed to the warming sea surface, which strengthens thermodynamic conditions in the wintertime, while local factors arguably keep the shear frequency relatively higher than the entire region. On the other hand, future northward extension of the subtropical belt over Europe in the warm season reduces the number of days with severe thunderstorm environments.

scholarly journals Greenhouse Gas–Induced Changes in Summer Precipitation over Colorado in NARCCAP Regional Climate Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8690-8697 ◽  
Author(s):  
Michael A. Alexander ◽  
James D. Scott ◽  
Kelly Mahoney ◽  
Joseph Barsugli
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Summer Precipitation ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
Specific Humidity ◽  
The North ◽  
Climate Model Simulations ◽  
Climate Change Assessment

Abstract Precipitation changes between 32-yr periods in the late twentieth and mid-twenty-first centuries are investigated using regional climate model simulations provided by the North American Regional Climate Change Assessment Program (NARCCAP). The simulations generally indicate drier summers in the future over most of Colorado and the border regions of the adjoining states. The decrease in precipitation occurs despite an increase in the surface specific humidity. The domain-averaged decrease in daily summer precipitation occurs in all of the models from the 50th through the 95th percentile, but without a clear agreement on the sign of change for the most extreme (top 1% of) events.

scholarly journals Regional climate model simulations as input for hydrological applications: evaluation of uncertainties

2005 ◽  
Vol 5 ◽  
pp. 119-125 ◽  
Author(s):  
S. Kotlarski ◽  
A. Block ◽  
U. Böhm ◽  
D. Jacob ◽  
K. Keuler ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Reference Data ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Mean Annual Precipitation ◽  
Data Sets ◽  
Data Set ◽  
Climate Model Simulations ◽  
Hydrological Applications

Abstract. The ERA15 Reanalysis (1979-1993) has been dynamically downscaled over Central Europe using 4 different regional climate models. The regional simulations were analysed with respect to 2m temperature and total precipitation, the main input parameters for hydrological applications. Model results were validated against three reference data sets (ERA15, CRU, DWD) and uncertainty ranges were derived. For mean annual 2 m temperature over Germany, the simulation bias lies between -1.1°C and +0.9°C depending on the combination of model and reference data set. The bias of mean annual precipitation varies between -31 and +108 mm/year. Differences between RCM results are of the same magnitude as differences between the reference data sets.

scholarly journals The representation of location by regional climate models in complex terrain

2015 ◽  
Vol 12 (3) ◽  
pp. 3011-3028 ◽  
Author(s):  
D. Maraun ◽  
M. Widmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Signal ◽  
Model Errors ◽  
Model Simulations ◽  
Local Grid ◽  
Climate Model Simulations

Abstract. To assess potential impacts of climate change for a specific location, one typically employs climate model simulations at the grid box corresponding to the same geographical location. But based on regional climate model simulations, we show that simulated climate might be systematically displaced compared to observations. In particular in the rain shadow of moutain ranges, a local grid box is therefore often not representative of observed climate: the simulated windward weather does not flow far enough across the mountains; local grid boxes experience the wrong airmasses and atmospheric circulation. In some cases, also the local climate change signal is deteriorated. Classical bias correction methods fail to correct these location errors. Often, however, a distant simulated time series is representative of the considered observed precipitation, such that a non-local bias correction is possible. These findings also clarify limitations of bias correcting global model errors, and of bias correction against station data.

scholarly journals Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Hyung-Il Eum ◽  
Philippe Gachon ◽  
René Laprise
Keyword(s):  
Climate Change ◽  
Spatial Variability ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Model Bias ◽  
Model Simulations ◽  
Seasonal Climate ◽  
Ensemble Mean ◽  
Climate Model Simulations

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affected by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. These results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.

Supporting users to implement uncertainty of climate change information in adaptation studies

2020 ◽  
Author(s):  
Gabriella Zsebeházi ◽  
Beatrix Bán
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Web Portals ◽  
Climate Data ◽  
Adaptation Studies ◽  
Climate Services ◽  
Model Simulations

<p>There is a growing need to develop climate services both at national and international level, to bridge the gap between the providers and the end-users of climate information. Several national climate services are aiming to serve the local users’ needs by creating web portals. Thanks to this trend, the number of available climate data (both measured and modelled) is rapidly growing and often there is not any personal contact between the users and the climate scientists via the web portals. Therefore, it is important to make this service usable and informative and train the potential users about the nature, strengths and limits of climate data.</p><p>Within the framework of a national funded project (KlimAdat), the regional climate model projections of the Hungarian Meteorological Service are extended and a representative climate database is developed. Regular workshops are organised, where we get hands-on information about the requirements and give training about climate modelling in exchange. One of the most discussed issue during the workshops is tackling with uncertainty information of climate projections in climate change adaptation studies. The future changes are quantified in probabilistic form, applying ensemble technique, i.e. several climate model simulations prepared with different global and regional climate models and anthropogenic scenarios are evaluated simultaneously.</p><p>In order to help the users orienting through the mushrooming climate projections, a user guide is prepared. Topics are e.g. how to select model simulations, how to take into account model validation results and what is the difference between signal and noise. The guideline is based on 24 simulations of the 12-km resolution Euro-CORDEX regional climate models, driven by the RCP4.5 and RCP8.5 scenarios. Two target groups are distinguished based on the required level of post-processing climate data: 1) climate impact modellers, who need large amount of raw or bias corrected data to drive their own impact model; 2) decision makers and planners, who need heavily processed but lightweight data. The purpose of our guideline is to provide insight into the customized methodologies used at the Hungarian Meteorological Service for fulfilling users’ needs.</p>

scholarly journals Summertime precipitation extremes in a EURO-CORDEX 0.11° ensemble at an hourly resolution

2019 ◽  
Vol 19 (4) ◽  
pp. 957-971 ◽  
Author(s):  
Peter Berg ◽  
Ole B. Christensen ◽  
Katharina Klehmet ◽  
Geert Lenderink ◽  
Jonas Olsson ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Strong Relationship ◽  
Precipitation Extremes ◽  
High Temporal Resolution ◽  
Relative Depth ◽  
Model Simulations ◽  
Projected Changes

Abstract. Regional climate model simulations have routinely been applied to assess changes in precipitation extremes at daily time steps. However, shorter sub-daily extremes have not received as much attention. This is likely because of the limited availability of high temporal resolution data, both for observations and for model outputs. Here, summertime depth duration frequencies of a subset of the EURO-CORDEX 0.11∘ ensemble are evaluated with observations for several European countries for durations of 1 to 12 h. Most of the model simulations strongly underestimate 10-year depths for durations up to a few hours but perform better at longer durations. The spatial patterns over Germany are reproduced at least partly at a 12 h duration, but all models fail at shorter durations. Projected changes are assessed by relating relative depth changes to mean temperature changes. A strong relationship with temperature is found across different subregions of Europe, emission scenarios and future time periods. However, the scaling varies considerably between different combinations of global and regional climate models, with a spread in scaling of around 1–10 % K−1 at a 12 h duration and generally higher values at shorter durations.

scholarly journals Changes in Twentieth-Century Extreme Temperature and Precipitation over the Western United States Based on Observations and Regional Climate Model Simulations*

2013 ◽  
Vol 26 (21) ◽  
pp. 8556-8575 ◽  
Author(s):  
Valérie Dulière ◽  
Yongxin Zhang ◽  
Eric P. Salathé
Keyword(s):  
United States ◽  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Western United States ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations

Abstract Trends in extreme temperature and precipitation in two regional climate model simulations forced by two global climate models are compared with observed trends over the western United States. The observed temperature extremes show substantial and statistically significant trends across the western United States during the late twentieth century, with consistent results among individual stations. The two regional climate models simulate temporal trends that are consistent with the observed trends and reflect the anthropogenic warming signal. In contrast, no such clear trends or correspondence between the observations and simulations is found for extreme precipitation, likely resulting from the dominance of the natural variability over systematic climate change during the period. However, further analysis of the variability of precipitation extremes shows strong correspondence between the observed precipitation indices and increasing oceanic Niño index (ONI), with regionally coherent patterns found for the U.S. Northwest and Southwest. Both regional climate simulations reproduce the observed relationship with ONI, indicating that the models can represent the large-scale climatic links with extreme precipitation. The regional climate model simulations use the Weather Research and Forecasting (WRF) Model and Hadley Centre Regional Model (HadRM) forced by the ECHAM5 and the Hadley Centre Climate Model (HadCM) global models for the 1970–2007 time period. Comparisons are made to station observations from the Historical Climatology Network (HCN) locations over the western United States. This study focused on temperature and precipitation extreme indices recommended by the Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI).

scholarly journals Evaluation of drought representation and propagation in Regional Climate Model simulations over Spain

2018 ◽  
Author(s):  
Anaïs Barella-Ortiz ◽  
Pere Quintana-Seguí
Keyword(s):  
Soil Moisture ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Meteorological Drought ◽  
Regional Climate Models ◽  
Model Formulation ◽  
Streamflow Variability ◽  
Climate Model Simulations ◽  
Hydrological Droughts

Abstract. Drought is an important climatic risk, of complex modeling due to the interaction of different processes and their corresponding temporal scales. It is expected to increase in intensity, frequency and duration due to a warmer climate. Therefore, it is vital to know the evolution of drought in relation to climate change. For this, the better understanding of processes involved in it is key. The study here presented, analyses drought representation and propagation by regional climate models from Med-CORDEX simulations by means of standardized indices. The models used are RCSM4, CCLM4, and PROMES. Focus is made on three types of drought: meteorological, soil moisture and hydrological. Results show that these models improve meteorological drought representation, but large uncertainties are identified in its propagation and the way soil moisture and hydrological droughts are characterised. These are mainly due to the relevance of model formulation. For instance, it affects the temporal scale at which precipitation variability propagates to soil moisture and streamflow. In addition, downscaling is also seen to affect streamflow variability, and thus hydrological drought.

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