借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均降水在亚...借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均降水在亚洲的偏差分布特征,检验了三种偏差订正统计方法,并且预估了2021~2050年亚洲降水的可能变化。结果表明,在CMIP5历史气候模拟中,多模式集合降水在亚洲存在明显偏差,北方降水偏多,南方偏少,其中在青藏高原、内蒙古、蒙古国等地明显偏多达30%~40%,南亚偏少30%~40%,在越南和华南沿海偏少20%~30%等。2006~2015年预估降水偏差型与历史气候模拟相似,具有准定常性,可以通过二者之差将其消去。偏差订正检验表明,单纯除去模式气候漂移后的降水距平太小,尽管距平符号一致率较高。在暖季(5~10月),一元对数回归偏差订正结果在北方略优于一元差分回归,在冷季(11月至次年4月)与此相反,二者结合可以构成区域组合回归偏差订正法。最后,用组合订正法订正了RCP4.5情景下20个CMIP5模式集合2021~2050年亚洲降水预估偏差,又利用某些区域的去除模式漂移后的订正结果对其盲区进行了补充订正。结果表明,相对于1976~2005年气候平均,在暖季,中国南方、南亚东北部、中亚南部、阿拉伯半岛东北部等地降水可能减少10%~20%;从中国的三江源区到淮河流域带降水会增加约20%,东北南部的降水会增加约10%;新疆北部降水增加约10%,南部约20%;华北和东北大部降水减少约10%~20%;中南半岛北部降水增加约10%;亚洲高纬度地带降水也略有增加。在冷季,亚洲降水呈现北方增加,南方减少的格局,其中南亚降水减少最明显,达-10%左右,中国西南部减少约-5%;中国西部降水增加幅度为20%~40%,华北和东北增加约5%;亚洲高纬度降水增加约为10%~40%。因此,随着气候暖化,未来30年中国的淮河流域、长江和黄河上游�展开更多
虽然第六次耦合模式比较计划(Coupled Model Intercomparison Project 6,CMIP6)能很好地预测大尺度气候要素,但是其在预测流域尺度方面的效果与实测数据仍有差别,尤其是在青藏高原这种高海拔、地形复杂地区,气候模式所产生的误差更大。...虽然第六次耦合模式比较计划(Coupled Model Intercomparison Project 6,CMIP6)能很好地预测大尺度气候要素,但是其在预测流域尺度方面的效果与实测数据仍有差别,尤其是在青藏高原这种高海拔、地形复杂地区,气候模式所产生的误差更大。基于最新一代高分辨率CMIP6模式历史情景和SSP126、SSP245、SSP370、SSP585等多种未来气候排放情景,研究使用包括偏差校正、KNN、SDSM等多种统计降尺度方法进行降尺度分析,并对各自的预测性能进行了评估,在此基础上使用性能最佳的统计降尺度方式预估青藏高原地区的未来降水,对最终得到的预估降水的时空演变特征进行了详细的分析,并与青藏高原的历史降水情况进行了对比。结果表明,3种统计降尺度在青藏高原的适用性差异较大,线性回归降尺度方法的性能最佳,其次为偏差校正方法,最差为KNN类比方法。从未来降水预估情况分析,青藏高原未来80 a平均降水、降水极值等总体呈上升趋势但上升幅度较小,且空间分布情况变化不大。研究结果可为青藏高原水资源评价及规划与管理提供科学依据。展开更多
The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures i...The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures in the next decades. This study has focused its efforts to pay attention into the effect of Climate Change on precipitation and temperature from a mean and extreme event perspective. Dynamical Downscaling approach on a 4 km resolution grid has been chosen as the most appropriate methodology for the estimation of the projected climate, being able to account for local-scale factors like complex topography or local land uses properly. We selected MPI-ESM-MR as the global climate model with the best skill scores in terms of precipitation and temperature in Nicaragua. MPI-ESM-MR was coupled to a mesoscale model. We chose WRF mesoescale model as the most appropriate regional model and we optimized their physical and dynamical options in order to minimize the model uncertainty in Nicaragua. For this, model output against the available in-situ measurements from the national meteorological station network and satellite data were compared. Climate change signal was estimated by comparing the different climate statistics calculated from a model run over an historical period, 1980-2009, with a model run over a projected period, 2010-2040. The obtained results from the projected climate show an increase of the mean temperature between 0.6°C and 0.8°C and an increase of the number of days per year with maximum daily temperatures higher than 35°C. Regarding precipitation, annual projected amounts do not change remarkably with respect to the historical period. However, significant changes in the distribution of the precipitation within the wet period (May-October) were observed. Moreover, an increment between 5% and 10% of the number of days without precipitation is expected. Finally, Intensity-Duration-Frequency (IDF) projected curves show an increment of the rainfall intensity and an increment of extreme precipi展开更多
The Global Precipitation Climatology Project （GPCP） monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipi...The Global Precipitation Climatology Project （GPCP） monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipitation in China in the period from January 1980 to December 2000. Results expose significantly consistent rainfall distributions between the both data in multi-year mean, multi-year seasonal mean, and multi-year monthly mean. Departures of monthly rainfall for each dataset also show a high correlation with an over 0.8 correlation coefficient. Analysis indicates small differences of both datasets during autumn, winter, and spring, but relative large ones in summer. Generally, the GPCP has trend of overestimating the rainfall rate. Based on above good relationship of both datasets, the GPCP data, are used to represent distributions and variations of precipitation in the Tibetan Plateau and Northwest China. Results indicate positive departures of precipitation in summer in the west part of Tibetan Plateau in the 1980s and negative departures after the 1980s. For the west part of Northwest China, analysis illustrates precipitation decreases a little, but no clear variation tendency.展开更多
This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;"&g...This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;">SLP) over west Africa based on analysis of the Global Precipitation</span><span style="font-family:""><span style="font-family:Verdana;"> Climatology Project (GPCP) and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis respectively. An interconnection is found in this region, between Mean Sea Level Pressure (MSLP) anomaly (over Azores and St. Helena High) and monthly mean precipitation during summer (June to September: JJAS). We also found that over northern Senegal (15</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N;17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">13</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">W) the SLP to the north is strong;the wind converges at 200</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">hPa (corresponding to the position of the African Easterly Jet (AEJ) coming from the north-east is negative. In this region, th展开更多
文摘借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均降水在亚洲的偏差分布特征,检验了三种偏差订正统计方法,并且预估了2021~2050年亚洲降水的可能变化。结果表明,在CMIP5历史气候模拟中,多模式集合降水在亚洲存在明显偏差,北方降水偏多,南方偏少,其中在青藏高原、内蒙古、蒙古国等地明显偏多达30%~40%,南亚偏少30%~40%,在越南和华南沿海偏少20%~30%等。2006~2015年预估降水偏差型与历史气候模拟相似,具有准定常性,可以通过二者之差将其消去。偏差订正检验表明,单纯除去模式气候漂移后的降水距平太小,尽管距平符号一致率较高。在暖季(5~10月),一元对数回归偏差订正结果在北方略优于一元差分回归,在冷季(11月至次年4月)与此相反,二者结合可以构成区域组合回归偏差订正法。最后,用组合订正法订正了RCP4.5情景下20个CMIP5模式集合2021~2050年亚洲降水预估偏差,又利用某些区域的去除模式漂移后的订正结果对其盲区进行了补充订正。结果表明,相对于1976~2005年气候平均,在暖季,中国南方、南亚东北部、中亚南部、阿拉伯半岛东北部等地降水可能减少10%~20%;从中国的三江源区到淮河流域带降水会增加约20%,东北南部的降水会增加约10%;新疆北部降水增加约10%,南部约20%;华北和东北大部降水减少约10%~20%;中南半岛北部降水增加约10%;亚洲高纬度地带降水也略有增加。在冷季,亚洲降水呈现北方增加,南方减少的格局,其中南亚降水减少最明显,达-10%左右,中国西南部减少约-5%;中国西部降水增加幅度为20%~40%,华北和东北增加约5%;亚洲高纬度降水增加约为10%~40%。因此,随着气候暖化,未来30年中国的淮河流域、长江和黄河上游�
文摘The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures in the next decades. This study has focused its efforts to pay attention into the effect of Climate Change on precipitation and temperature from a mean and extreme event perspective. Dynamical Downscaling approach on a 4 km resolution grid has been chosen as the most appropriate methodology for the estimation of the projected climate, being able to account for local-scale factors like complex topography or local land uses properly. We selected MPI-ESM-MR as the global climate model with the best skill scores in terms of precipitation and temperature in Nicaragua. MPI-ESM-MR was coupled to a mesoscale model. We chose WRF mesoescale model as the most appropriate regional model and we optimized their physical and dynamical options in order to minimize the model uncertainty in Nicaragua. For this, model output against the available in-situ measurements from the national meteorological station network and satellite data were compared. Climate change signal was estimated by comparing the different climate statistics calculated from a model run over an historical period, 1980-2009, with a model run over a projected period, 2010-2040. The obtained results from the projected climate show an increase of the mean temperature between 0.6°C and 0.8°C and an increase of the number of days per year with maximum daily temperatures higher than 35°C. Regarding precipitation, annual projected amounts do not change remarkably with respect to the historical period. However, significant changes in the distribution of the precipitation within the wet period (May-October) were observed. Moreover, an increment between 5% and 10% of the number of days without precipitation is expected. Finally, Intensity-Duration-Frequency (IDF) projected curves show an increment of the rainfall intensity and an increment of extreme precipi
基金Supported by Grants of NKBRDPC (No.2004CB418304),NSFC grant of the Joint Research Fund for Overseas Chinese Young Scholars (No.40428006),NSFC (Nos.40175015 and 40375018).
文摘The Global Precipitation Climatology Project （GPCP） monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipitation in China in the period from January 1980 to December 2000. Results expose significantly consistent rainfall distributions between the both data in multi-year mean, multi-year seasonal mean, and multi-year monthly mean. Departures of monthly rainfall for each dataset also show a high correlation with an over 0.8 correlation coefficient. Analysis indicates small differences of both datasets during autumn, winter, and spring, but relative large ones in summer. Generally, the GPCP has trend of overestimating the rainfall rate. Based on above good relationship of both datasets, the GPCP data, are used to represent distributions and variations of precipitation in the Tibetan Plateau and Northwest China. Results indicate positive departures of precipitation in summer in the west part of Tibetan Plateau in the 1980s and negative departures after the 1980s. For the west part of Northwest China, analysis illustrates precipitation decreases a little, but no clear variation tendency.
文摘This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;">SLP) over west Africa based on analysis of the Global Precipitation</span><span style="font-family:""><span style="font-family:Verdana;"> Climatology Project (GPCP) and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis respectively. An interconnection is found in this region, between Mean Sea Level Pressure (MSLP) anomaly (over Azores and St. Helena High) and monthly mean precipitation during summer (June to September: JJAS). We also found that over northern Senegal (15</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N;17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">13</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">W) the SLP to the north is strong;the wind converges at 200</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">hPa (corresponding to the position of the African Easterly Jet (AEJ) coming from the north-east is negative. In this region, th
