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首页> 外文期刊>Journal of Applied Meteorology and Climatology >Combined Dynamical and Statistical Downscaling for High-Resolution Projections of Multiple Climate Variables in the Beijing-Tianjin-Hebei Region of China
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Combined Dynamical and Statistical Downscaling for High-Resolution Projections of Multiple Climate Variables in the Beijing-Tianjin-Hebei Region of China

机译：中国北京天津 - 河北地区多重气候变量的高分辨率预测组合动态及统计划分

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High-resolution combined dynamical and statistical downscaling for multivariables (HDM) was performed in the Beijing-Tianjin-Hebei (BTH) region by using observations from China Meteorological Administration Land Data Assimilation System (CLDAS), a regional climate model (RCM), and quantile mapping. This resulted in the production of a daily product with six variables (daily mean, maximum, and minimum temperature; precipitation; relative humidity; and wind speed), five ensemble members, a multidecadal time span (1980-2099), and a high resolution (6.25 km) for climate change projections under the RCP4.5 scenario. The evaluation showed that the HDM output could reproduce well the mean states of all variables and most extreme indices except the consecutive dry and wet days. The biases in the magnitude of interannual variability in HDM were mostly inherited from the RCM. By using the HDM, future projection over BTH was conducted. The results indicated that the annual mean temperature and precipitation as well as extreme heat and heavy precipitation events will increase over most regions. The warming magnitudes over the mountainous and coastal area at the northern BTH and the wetting magnitudes over the Daqinghe River basin (DRB) within BTH will be relatively stronger. The increases in extreme heat events will be much larger in the plain area. More than one-half of regions with the large extreme precipitation increase will be located within DRB. Both the number of models with the same sign of change and the ensemble standard deviation were used to estimate the projection uncertainty. The projected changes and uncertainties over DRB and subregions and Xiong'an city within the basin for each season are also discussed.
机译：通过使用来自中国气象管理土地数据同化系统（CLDAS），区域气候模型（RCM）的观测，在北京 - 天津 - 河北（BTH）地区进行了高分辨率的多变量（HDM）的高分辨率动态和统计划分定量映射。这导致生产具有六个变量的每日产品（每日平均值，最大值和最小温度;降水;相对湿度;和风速），五个集合成员，多数时间范围（1980-2099），以及高分辨率（6.25 km）在RCP4.5场景下的气候变化预测。评估表明，HDM输出可以再繁殖所有变量的平均状态以及除连续干燥和潮湿的日子之外的所有变量和最极端的指标。 HDM中续际变异性的偏差大多是从RCM继承。通过使用HDM，进行了对BTH的未来投影。结果表明，年平均温度和降水以及极端热量和重度降水事件将增加大多数地区。 BTH北部山区和沿海地区的变暖大小和大清河流域（BTB）内的润湿量相对较强。极端热事件的增加在平原区域将大得多。在DRB中，超过极端降水量增加超过一半的地区。使用相同的变化符号的模型数量和集合标准偏差都用于估计投影不确定性。还讨论了每个季节的DRB和次区域和次区域和熊县的预计变化和不确定性。

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