论文标题
偶联模型对比项目-6（CMIP6）的偏置校正的气候预测
Bias-corrected climate projections from Coupled Model Intercomparison Project-6 (CMIP6) for South Asia
论文作者
论文摘要
气候变化可能会对农业，水资源，基础设施以及居住在南亚的数百万人口构成巨大挑战。在这里，我们每天在南亚（印度，巴基斯坦，孟加拉国，尼泊尔，不丹，不丹和斯里兰卡）和位于印度次次陆地的18个空间分辨率的降水量，最高和最低温度的每日偏见数据，最高和最低温度。偏置校正的数据集是使用历史悠久的（1951-2014）的经验分位映射（EQM）开发的，并预测了四种情况（SSP126，SSP245，SSP370，SSP585）的气候（2015-2100）气候，使用13 CMIP6-GCM的输出。对偏置校正的数据集进行了评估，以针对降水，最高和最低温度的平均值和极端观察结果进行评估。偏见校正了13个CMIP6-GCMS项目的预测，在21世纪，南亚的温暖（3-5°C）和潮湿（13-30％）气候。 CMIP6-GCMS的偏见校正预测可用于南亚的气候变化影响评估以及次大陆河流盆地的水文影响评估。
Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951-2014) and projected (2015-2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 CMIP6-GCMs. The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3-5°C) and wetter (13-30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.
