Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

Author(s):  
Peihua Qin ◽  
Zhenghui Xie ◽  
Jing Zou ◽  
Shuang Liu ◽  
Si Chen
2009 ◽  
Vol 22 (8) ◽  
pp. 1944-1961 ◽  
Author(s):  
Bariş Önol ◽  
Fredrick H. M. Semazzi

Abstract In this study, the potential role of global warming in modulating the future climate over the eastern Mediterranean (EM) region has been investigated. The primary vehicle of this investigation is the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 (ICTP-RegCM3), which was used to downscale the present and future climate scenario simulations generated by the NASA’s finite-volume GCM (fvGCM). The present-day (1961–90; RF) simulations and the future climate change projections (2071–2100; A2) are based on the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) emissions. During the Northern Hemispheric winter season, the general increase in precipitation over the northern sector of the EM region is present both in the fvGCM and RegCM3 model simulations. The regional model simulations reveal a significant increase (10%–50%) in winter precipitation over the Carpathian Mountains and along the east coast of the Black Sea, over the Kackar Mountains, and over the Caucasus Mountains. The large decrease in precipitation over the southeastern Turkey region that recharges the Euphrates and Tigris River basins could become a major source of concern for the countries downstream of this region. The model results also indicate that the autumn rains, which are primarily confined over Turkey for the current climate, will expand into Syria and Iraq in the future, which is consistent with the corresponding changes in the circulation pattern. The climate change over EM tends to manifest itself in terms of the modulation of North Atlantic Oscillation. During summer, temperature increase is as large as 7°C over the Balkan countries while changes for the rest of the region are in the range of 3°–4°C. Overall the temperature increase in summer is much greater than the corresponding changes during winter. Presentation of the climate change projections in terms of individual country averages is highly advantageous for the practical interpretation of the results. The consistence of the country averages for the RF RegCM3 projections with the corresponding averaged station data is compelling evidence of the added value of regional climate model downscaling.


2020 ◽  
Author(s):  
Hussain Alsarraf

<p>The purpose of this study is to examine the impact of climate change on the changes on summer surface temperatures between present (2000-2010) and future (2050-2060) over the Arabian Peninsula and Kuwait. In this study, the influence of climate change in the Arabian Peninsula and especially in Kuwait was investigated by high resolution (36, 12, and 4 km grid spacing) dynamic downscaling from the Community Climate System Model CCSM4 using the WRF Weather Research and Forecasting model. The downscaling results were first validated by comparing National Centers for Environmental Prediction NCEP model outputs with the observational data. The global climate change dynamic downscaling model was run using WRF regional climate model simulations (2000-2010) and future projections (2050-2060). The influence of climate change in the Arabian Peninsula can be projected from the differences between the two period’s model simulations. The regional model simulations of the average maximum surface temperature in summertime predicted an increase from 1◦C to 3 ◦C over the summertime in Kuwait by midcentury.</p><p><strong> </strong></p>


2021 ◽  
Author(s):  
Clemens Schwingshackl ◽  
Anne Sophie Daloz ◽  
Carley Iles ◽  
Nina Schuhen ◽  
Jana Sillmann

<p>Cities are hotspots of human heat stress due to their large number of inhabitants and the urban heat island effect leading to amplified temperatures. Exposure to heat stress in urban areas is projected to further increase in the future, mainly due to climate change and expected increases in the number of people living in cities. The impacts of climate change in cities have been investigated in numerous studies, but rarely using climate models due to their coarse spatial resolution compared to the typical areal extent of cities. Recent advances in regional climate modelling now give access to an ensemble of high-resolution simulations for Europe, allowing for much more detailed analyses of small-scale features, such as city climate.</p><p>Focusing on Europe, we compare the evolution of several heat stress indicators for 36 major European cities, based on regional climate model simulations from EURO-CORDEX. The applied EURO-CORDEX ensemble (Vautard et al., 2020) has a spatial resolution of 0.11° (~11 km; comparable to the extent of large cities) and contains over 60 ensemble members, allowing thus for robust multi-model analyses of climate change on city levels. We analyze changes in heat stress both relative to the climatological heat stress variability in each city during 1981-2010 using the Heat Wave Magnitude Index daily (HWMId, Russo et al., 2015) and in absolute terms by counting the yearly number of exceedances of impact-relevant thresholds. Relative and absolute heat stress increase throughout Europe but with distinct patterns. Absolute heat stress increases predominantly in Southern Europe, primarily due to the hotter climate in the South. Relative changes are also highest in Southern Europe but exhibit a secondary maximum in Northern Europe, while being lowest in Central Europe. The main reason for this pattern is that day-to-day variability in heat stress indicators during present climate conditions is highest in Central Europe but lower in Southern and Northern Europe. Large Northern European cities, which are all located at the shore, are further influenced by different heat stress evolutions over land and sea surfaces.</p><p>As human vulnerability does not only depend on the absolute heat stress but also on what people are adapted to (i.e., the climatological range), the results of this study highlight that cities in all parts of Europe – including in Northern Europe – must prepare for higher heat stress in the future.</p><p> </p><p>References:</p><p>Russo, S., et al. (2015). Top ten European heatwaves since 1950 and their occurrence in the coming decades. Environmental Research Letters, 10(12). doi:10.1088/1748-9326/10/12/124003</p><p>Vautard, R., et al. (2020). Evaluation of the large EURO‐CORDEX regional climate model ensemble. Journal of Geophysical Research: Atmospheres. doi:10.1029/2019jd032344</p>


2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Hyung-Il Eum ◽  
Philippe Gachon ◽  
René Laprise

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.


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