scholarly journals Climate Extremes over the Arabian Peninsula Using RegCM4 for Present Conditions Forced by Several CMIP5 Models

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 675 ◽  
Author(s):  
Almazroui
Keyword(s):  
Land Surface ◽  
Arabian Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled Model ◽  
Climate Extremes ◽  
Maximum Temperature ◽  
Cmip5 Models ◽  
Study Region ◽  
Temperature And Precipitation

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region.

scholarly journals Temperature Changes over the CORDEX-MENA Domain in the 21st Century Using CMIP5 Data Downscaled with RegCM4: A Focus on the Arabian Peninsula

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Mansour Almazroui
Keyword(s):  
Arabian Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Temperature Changes ◽  
Entire Domain ◽  
Hot Days ◽  
Using Data

This paper examined the temperature changes from the COordinated Regional climate Downscaling Experiment (CORDEX) over the Middle East and North Africa (MENA) domain called CORDEX-MENA. The focus is on the Arabian Peninsula in the 21st century, using data from three Coupled Model Intercomparison Project Phase 5 (CMIP5) models downscaled by RegCM4, a regional climate model. The analysis includes surface observations along with RegCM4 simulations and changes in threshold based on extreme temperature at the end of the 21st century relative to the base period (1971–2000). Irrespective of the driving CMIP5 models, the RegCM4 simulations show enhanced future temperature changes for RCP8.5 as compared to RCP4.5. The Arabian Peninsula will warm at a faster rate (0.83°C per decade) as compared to the entire domain (0.79°C per decade) for RCP8.5 during the period 2071–2100. Moreover, the number of hot days (Tmax ≥ 50°C) (cold nights: Tmin ≤ 5°C) will increase (decrease) faster in the Arabian Peninsula as compared to the entire domain. This increase (decrease) of hot days (cold nights) will be more prominent in the far future (2071–2100) as compared to the near future (2021–2050) period. Moreover, the future changes in temperature over the main cities in Saudi Arabia are also projected. The RegCM4-based temperature simulation data from two suitable CMIP5 models are recommended as a useful database for further climate-change-related studies.

scholarly journals Future Changes in Climate over the Arabian Peninsula based on CMIP6 Multimodel Simulations

2020 ◽  
Vol 4 (4) ◽  
pp. 611-630
Author(s):  
Mansour Almazroui ◽  
M. Nazrul Islam ◽  
Sajjad Saeed ◽  
Fahad Saeed ◽  
Muhammad Ismail
Keyword(s):  
Confidence Level ◽  
Climate Models ◽  
Arabian Peninsula ◽  
Ghg Emissions ◽  
Coupled Model ◽  
First Century ◽  
Cmip5 Models ◽  
Temperature And Precipitation ◽  
Twenty First Century ◽  
Far Future

AbstractThis paper presents the changes in projected temperature and precipitation over the Arabian Peninsula for the twenty-first century using the Coupled Model Intercomparison Project phase 6 (CMIP6) dataset. The changes are obtained by analyzing the multimodel ensemble from 31 CMIP6 models for the near (2030–2059) and far (2070–2099) future periods, with reference to the base period 1981–2010, under three future Shared Socioeconomic Pathways (SSPs). Observations show that the annual temperature is rising at the rate of 0.63 ˚C decade–1 (significant at the 99% confidence level), while annual precipitation is decreasing at the rate of 6.3 mm decade–1 (significant at the 90% confidence level), averaged over Saudi Arabia. For the near (far) future period, the 66% likely ranges of annual-averaged temperature is projected to increase by 1.2–1.9 (1.2–2.1) ˚C, 1.4–2.1 (2.3–3.4) ˚C, and 1.8–2.7 (4.1–5.8) ˚C under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. Higher warming is projected in the summer than in the winter, while the Northern Arabian Peninsula (NAP) is projected to warm more than Southern Arabian Peninsula (SAP), by the end of the twenty-first century. For precipitation, a dipole-like pattern is found, with a robust increase in annual mean precipitation over the SAP, and a decrease over the NAP. The 66% likely ranges of annual-averaged precipitation over the whole Arabian Peninsula is projected to change by 5 to 28 (–3 to 29) %, 5 to 31 (4 to 49) %, and 1 to 38 (12 to 107) % under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively, in the near (far) future. Overall, the full ranges in CMIP6 remain higher than the CMIP5 models, which points towards a higher climate sensitivity of some of the CMIP6 climate models to greenhouse gas (GHG) emissions as compared to the CMIP5. The CMIP6 dataset confirmed previous findings of changes in future climate over the Arabian Peninsula based on CMIP3 and CMIP5 datasets. The results presented in this study will be useful for impact studies, and ultimately in devising future policies for adaptation in the region.

scholarly journals Biases and Model Agreement in Projections of Climate Extremes over the Tropical Pacific

2011 ◽  
Vol 15 (24) ◽  
pp. 1-36 ◽  
Author(s):  
Sarah E. Perkins
Keyword(s):  
Minimum Temperature ◽  
General Circulation ◽  
Coupled Model ◽  
Climate Extremes ◽  
General Circulation Models ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Temperature And Precipitation ◽  
Return Levels ◽  
The Mean

Abstract Using the Coupled Model Intercomparison Project phase 3 (CMIP3) general circulation models (GCMs), projections of a range of climate extremes are explored for the western Pacific. These projections include the 1-in-20-yr return levels and a selection of climate indices for minimum temperature, maximum temperature, and precipitation, and they are compared to corresponding mean projections for the Special Report on Emission Scenarios (SRES) A2 scenario during 2081–2100. Models are evaluated per variable based on their ability to simulate current extremes, as well as the overall daily distribution. Using the standardized evaluation scores for each variable, models are divided into four subsets where ensemble variability is calculated to measure model uncertainty and biases are calculated in respect to the multimodel ensemble (MME). Results show that higher uncertainty in projections of climate extremes exists when compared to the mean, even in those subsets consisting of higher-skilled models. Higher uncertainty exists for precipitation projections than for temperature, and biases and uncertainties in the 1-in-20-yr precipitation events are an order of magnitude higher than the corresponding mean. Poorer performing models exhibit a cooler bias in the mean and 1-in-20-yr return levels for maximum and minimum temperature, and ensemble variability is low among all subsets of mean minimum temperature, especially the lower-skilled subsets. Higher-skilled models project 1-in-20-yr precipitation return levels that are more intense than in the MME. The frequency of temperature extremes increase dramatically; however, this is explained by the underpinning small temperature range of the region. Although some systematic biases occur in the higher- and lower-skilled models and omitting the poorer performers is recommended, great care should be exercised when interpreting the reduction of uncertainty because the ensemble variability among the remaining models is comparable and in some cases greater than the MME. Such results should be treated on a case-by-case basis.

scholarly journals Land surface model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v3.9 model over North America

2020 ◽  
Vol 13 (11) ◽  
pp. 5345-5366
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation ◽  
Model Ensembles ◽  
Precipitation Events

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we analyze land–atmosphere interactions within four simulations performed by the WRF model from 1980 to 2012 over North America, using three different LSMs. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Our results show that the WRF simulation of the climatology of heat extremes can be 5 ∘C warmer and 6 d longer depending on the employed LSM component, and similarly for cold extremes and heavy precipitation events. Areas showing large uncertainty in WRF-simulated extreme events are also identified in a model ensemble from three different regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. Thus, studies based on multi-model ensembles and reanalyses should include a variety of LSM configurations to account for the uncertainty arising from this model component or to test the performance of the selected LSM component before running the whole simulation. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating extreme temperature and precipitation events, which in turn will help to reduce uncertainties in climate model projections.

scholarly journals Land Surface Model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v.3.9 model over North America

2020 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
North America ◽  
Regional Climate Model ◽  
Extreme Events ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we evaluate land-atmosphere interactions within four simulations performed by the WRF model using three different LSMs from 1980 to 2012 over North America. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Areas showing large uncertainty in WRF simulated extreme events are also identified in a model ensemble from three different Regional Climate Model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating temperature and precipitation extreme events, which in turn will help to reduce uncertainties in climate model projections.

Land Surface Model influence on the simulated climatologies of extreme temperature and precipitation events within the WRF model over North America

2020 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Precipitation Events

<p class="western"><span>The representation and projection of extreme temperature and precipitation events in climate models are of major importance for developing polices to build communities’ resilience in the face of climate change. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensities, durations and frequencies of these extremes. </span></p> <p class="western"><span>Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM) to determine the influence of the choice of land surface model (LSM) component on the uncertainty in the simulation of extreme event statistics. First, we evaluate land-atmosphere interactions within four simulations performed with the WRF model coupled to three different LSMs from 1980 to 2012 over North America. Results show regional differences among simulations for the frequency of events when surface conditions are altered by atmospheric forcing or by land surface processes. Second, we find a large inter-model range of extreme statistics across the ensemble of WRF-LSM simulations. This is particularly the case for indices related to the intensity and duration of temperature and precipitation extremes. </span></p> <p class="western"><span>Regions displaying large uncertainty in the WRF simulation of extreme events are also identified in a model ensemble experiment carried out with three different RCMs participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. This agreement between the model simulations performed in this work and the set of CORDEX simulations suggests that the implications of our results are valid for other model ensembles. This study illustrates the importance of supporting the development of new multi-LSM modeling studies to understand inter-model differences in simulating extreme events, ultimately helping to narrow down the range across climate model projections.</span></p>

scholarly journals Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Natalie Melissa McLean ◽  
Tannecia Sydia Stephenson ◽  
Michael Alexander Taylor ◽  
Jayaka Danaco Campbell
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Climate Extremes ◽  
Extreme Rainfall ◽  
Maximum Temperature ◽  
Temperature Extremes ◽  
Intense Rainfall ◽  
Drying Trend

End-of-century changes in Caribbean climate extremes are derived from the Providing Regional Climate for Impact Studies (PRECIS) regional climate model (RCM) under the A2 and B2 emission scenarios across five rainfall zones. Trends in rainfall, maximum temperature, and minimum temperature extremes from the RCM are validated against meteorological stations over 1979–1989. The model displays greater skill at representing trends in consecutive wet days (CWD) and extreme rainfall (R95P) than consecutive dry days (CDD), wet days (R10), and maximum 5-day precipitation (RX5). Trends in warm nights, cool days, and warm days were generally well reproduced. Projections for 2071–2099 relative to 1961–1989 are obtained from the ECHAM5 driven RCM. Northern and eastern zones are projected to experience more intense rainfall under A2 and B2. There is less consensus across scenarios with respect to changes in the dry and wet spell lengths. However, there is indication that a drying trend may be manifest over zone 5 (Trinidad and northern Guyana). Changes in the extreme temperature indices generally suggest a warmer Caribbean towards the end of century across both scenarios with the strongest changes over zone 4 (eastern Caribbean).

Evaluation of CMIP5 Models in the Context of Dynamical Downscaling over Europe

2015 ◽  
Vol 28 (14) ◽  
pp. 5575-5582 ◽  
Author(s):  
Martin W. Jury ◽  
Andreas F. Prein ◽  
Heimo Truhetz ◽  
Andreas Gobiet
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Circulation Model ◽  
Cmip5 Models ◽  
Lateral Boundary ◽  
Study Region ◽  
Near Surface

Abstract The quality of regional climate model (RCM) simulations is strongly dependent on the quality of data provided as lateral boundary conditions (LBCs). Frequently, the quality of near-surface variables of general circulation model (GCM) simulations like those from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is analyzed in the region of interest. However, such analysis does not necessarily lead to the selection of high-quality LBCs, as demonstrated in this study. The study region is the European domain of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX), where a model performance index (MPI) is used to evaluate the skill of CMIP5 GCMs to reproduce near-surface variables within the EURO-CORDEX domain and free atmosphere variables along its lateral boundaries as a proxy for LBCs used in regional climate modeling. The results suggest that a GCM’s skill in simulating near-surface variables is correlated with 0.62 (Spearman’s r) to its skill in simulating LBCs for regional climate simulations. However, there is hardly any correlation between the performances of different variables, implying that a GCM evaluation solely based on surface parameters or a few variables is inadequate to select suitable driving data for regional climate models. The selection should include the evaluation of all variables passed to the RCM as LBCs in the lateral boundary zone (LBZ) on at least one midtropospheric level.

scholarly journals An observation-constrained multi-physics RCM ensemble for simulating European mega-heatwaves

2014 ◽  
Vol 7 (6) ◽  
pp. 7861-7886 ◽  
Author(s):  
A. I. Stegehuis ◽  
R. Vautard ◽  
P. Ciais ◽  
A. J. Teuling ◽  
D. G. Miralles ◽  
...  
Keyword(s):  
Land Surface ◽  
Western Europe ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Extremes ◽  
Poor Performance ◽  
Wave Radiation ◽  
Cold Bias ◽  
The Impact

Abstract. Climate models are often not evaluated or calibrated against observations of past climate extremes, resulting in poor performance during for instance heatwave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, with the goal of detecting the most sensitive ones and identifying those that appear most suitable for simulating the heatwave events of 2003 in Western Europe and 2010 in Russia. 55 Out of 216 simulations combining different atmospheric physical schemes can reproduce the extreme temperatures observed during heatwaves, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heatwaves, and short wave radiation is slightly underestimated. Convection is found to be the most sensitive process impacting simulated heatwave temperature, across 4 different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme combinations, which may be used in the future to perform heatwave analysis and to investigate the impact of climate change in summer in Europe. Future studies could include the use of different land surface models together with varied physics scheme.

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