Chujie Gao

The Influence of Topography on East African October to December Climate: Sensitivity Experiments with RegCM4

The influence of topography on east African climate is investigated using the International Centre for Theoretical Physics Regional Climate Model, with focus on October to December season. Results show that the mean rainfall (temperature) significantly reduces (increases) over the region when topography elevation is reduced. Based on the model, when topography over the selected region (KTU) is reduced to 25%, the mean rainfall (temperature) over east Africa is reduced (increased) by about 19% (1.4°C). The maximum rainfall (temperature) reduction (increase) is however observed around the region over which topography is reduced. The reduction in topography elevation resulted in an anomalous moisture divergence at low level and descending motion over the region. KTU topography enhances the surface heat flux over KTU region and tends to enhance convection over both KTU and the east African region. The topography also helps in the generation of the high frequency mesoscale and subsynoptic disturbances over the region. These disturbances produce precipitation over the region and may also enhance precipitation systems over remote areas due to propagation of the disturbances. The magnitude of the zonal wind speed at 850 hpa increases with the decrease in topography elevation.

On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China

Under the exacerbation of climate change, climate extreme events, especially for drought, happened frequently and intensively across the globe with greater spatial differences. We used the Standardized Precipitation-Evapotranspiration Index computed from the routine meteorological observations at 269 sites in Southwest China (SWC) to study the drought characteristics (e.g., extent, duration and intensity) and their decadal variations during 1971–2012. It was revealed that the drought, in responses to the coupling between decadal precipitation and potential evapotranspiration (PET) anomalies, differed among regions and periods. For the entire SWC, droughts in 1970s and 2000s+ was generally stronger than in 1980s and 1990s with respect to their spatial extent, duration and intensity, especially in 2000s+. It was well-known that drought was closely related with a lack of precipitation; however, the impact of atmospheric demand of evaporation (reflected by PET here) on drought (e.g., duration and intensity) was rarely paid enough attentions. To that end, a spatial multi-linear regression approach was proposed in this study for quantifying the contributions of decadal PET and precipitation variations to drought duration and intensity. We have found that the contributions of decadal PET anomalies to drought duration and intensity could exceed those of precipitation, e.g., during 1980s and 1990s in SWC. Additionally, despite the strongest droughts in 2000s+, it was suggested that PET could exert comparable impacts on drought anomalies as precipitation. All these findings implied that PET plays a critical role in drought event, which acts to amplify drought duration and intensity. To sum up, this study stressed the need for enough attentions for PET processes in drought studies.

Attributing the Changes in Reference Evapotranspiration in Southwestern China Using a New Separation Method

AbstractThis study investigated monthly and annual reference evapotranspiration changes over southwestern China (SWC) from 1960 to 2012, using the Food and Agriculture Organization of the United Nations’ report 56 (FAO-56) Penman–Monteith equation and routine meteorological observations at 269 weather sites. During 1960–2012, the monthly and annual decreased at most sites. Moreover, the SWC regional average trend in annual was significantly negative (p < 0.05); this trend was the same in most months. A new separation method using several numerical experiments was proposed to quantify each driving factor’s contribution to changes and exhibited higher accuracy based on several validation criteria, after which an attribution analysis was performed. Across SWC, the declining annual was mainly due to decreased net radiation (RN). Spatially, the annual changes at most sites in eastern SWC (excluding southeastern West Guangxi) were generally due to RN, whereas wind speed (WND) or vapor pressure deficit (VPD) was...

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951–2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October–December (OND) and March–May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

Large discrepancy between measured and remotely sensed snow water equivalent in the northern Europe and western Siberia during boreal winter

Accurate information on snowpack conditions is crucial for understanding changes in the hydrological cycle and its impacts on the climate system, especially at the middle and high latitudes. Two satellite-derived products that cover Eurasia from 1979 to 2006, i.e., the snow water equivalent (SWE) data provided by the National Snow and Ice Data Center (NSIDC; SWENSIDC) and the GlobSnow dataset provided by the Finnish Meteorological Institute (FMI) (SWEGS) are selected for examination in the present study. The performances of these datasets in representing snowpack conditions are evaluated by comparing the datasets with the observations of snow depth (SD) recorded in the Historical Soviet Daily Snow Depth (HSDSD; SDHSDSD) dataset. The results indicate that the SWEGS dataset is more consistent with the SDHSDSD dataset over northern Eurasia than the SWENSIDC dataset. In particular, the SWENSIDC dataset exhibits large discrepancies in northern Europe and western Siberia (NE-WS), indicating problems or even errors in the SWENSIDC dataset. Based on snow formation criteria (e.g., temperature and precipitation), we further explore and confirm the existence of problems in the SWENSIDC dataset. These problems may be associated with the retrieval method used to generate this dataset; this method is based on a static algorithm. Our findings suggest that satellite-derived SWE datasets (e.g., SWENSIDC) should be used with caution when investigating the impacts of snow in different research fields (e.g., climatology, hydrology, and ecology).

Regional Features and Seasonality of Land–Atmosphere Coupling over Eastern China

Land–atmosphere coupling is a key process of the climate system, and various coupling mechanisms have been proposed before based on observational and numerical analyses. The impact of soil moisture (SM) on evapotranspiration (ET) and further surface temperature (ST) is an important aspect of such coupling. Using ERA-Interim data and CLM4.0 offline simulation results, this study further explores the relationships between SM/ST and ET to better understand the complex nature of the land–atmosphere coupling (i.e., spatial and seasonal variations) in eastern China, a typical monsoon area. It is found that two diagnostics of land–atmosphere coupling (i.e., SM–ET correlation and ST–ET correlation) are highly dependent on the climatology of SM and ST. By combining the SM–ET and ST–ET relationships, two “hot spots” of land–atmosphere coupling over eastern China are identified: Southwest China and North China. In Southwest China, ST is relatively high throughout the year, but SM is lowest in spring, resulting in a strong coupling in spring. However, in North China, SM is relatively low throughout the year, but ST is highest in summer, which leads to the strongest coupling in summer. Our results emphasize the dependence of land–atmosphere coupling on the seasonal evolution of climatic conditions and have implications for future studies related to land surface feedbacks.摘 要陆-气耦合是气候系统中的重要过程, 已经有大量基于观测和数值模拟的研究提出了各种耦合机制. 土壤湿度影响蒸散发进而引起地表温度异常是陆-气耦合研究中的重要组成部分. 利用ERA-Interim再分析资料和CLM4.0模拟结果, 本研究进一步探讨了土壤湿度/地表温度与蒸散发之间的关系, 以更好地理解中国东部地区陆-气耦合的复杂性质(即空间和季节变化). 本研究发现陆-气耦合的两个诊断量(即土壤湿度与蒸散发的相关系数和地表温度与蒸散发的相关系数)的变化主要依赖土壤湿度和地表温度的气候状态, 存在明显的空间变化和季节演变. 结合两个相关系数, 本研究确定了中国东部的两个陆-气耦合的关键区: 西南和华北地区. 在西南地区, 土壤湿润, 温度较高, 但在旱季的时候土壤湿度显著下降, 春季达到最低, 因此春季表现为较强的陆气耦合. 而在华北地区, 土壤湿度在年内维持在较低的水平, 仅在较为温暖的季节才有足够的能量将土壤中的水分蒸发至大气, 因此陆-气耦合强度随着温度的季节变化而发生改变, 夏季最强. 本文的研究结果强调了陆-气耦合对气候条件季节演变的依赖性, 为未来有关陆面过程反馈的研究提供一定的参考.