Bias corrected and downscaled climate projections over Upper Indus Basin (based on CORDEX-RCM'S)

This dataset is a by-product of my doctoral research on the hydrological impacts of climate change in the Upper Indus Basin (UIB).

The data provided here covers the full extent of UIB and is provided as bias-corrected and downscaled versions of 5 RCM-GCM experiments (by CORDEX-SA). The \"Precipitation\" (PCP), and \"Temperature\" (TMP) projections are in the shape of “point data” for 173 sub-basin centroids, in a ready-to-use format for input to SWAT hydrological model. Additionally, data (with future dates) for other required parameters by the Hydrological Model “SWAT”, such as \"Humidity\" (RHU), \"Solar-radiation\" (SLR), and \"wind\" (WND) is also provided.

It includes bias-corrected and downscaled projections from selected General Circulation Models (GCMs) under the RCP 4.5 and RCP 8.5 scenarios. The selection process involved evaluating GCMs based on mean and extreme changes, as well as their ability to reproduce past climate. To account for uncertainties in high mountainous regions like the UIB, a wide range of future GCM climate projections, including wet-warm, wet-cold, dry-warm, and dry-cold scenarios, were considered. The final selection of GCMs was based on a weighted score assigned to each criterion.

It was found that the Coordinated Regional Downscaling Experiment (CORDEX) already had RCM data for our “top-ranked” GCMs, therefore Dynamically downscaled climate projections from five CORDEX-SA experiments *(IPSL-CM5A-MR_RCA4, MPI-ESM-LR_RCA4, NorESM1-M_RCA4, Can ESM2_RegCM4-4, and GFDL-ESM2M_RCA4)* were downloaded and further statistically downscaled (bias-corrected) over the UIB. These experiments used two different Regional Climate Models (RCMs), RCA4 and RegCM4, resulting in finer-scale outputs (0.44°) than the source GCMs.

The downscaled projections for the year 2100 indicate temperature increases ranging from 2.3°C to 9.0°C and precipitation changes ranging from a slight annual increase of 2.2% under drier scenarios to a high increase of 15.9% in wet scenarios. In all scenarios, future precipitation is expected to be more extreme, with a decrease in the probability of wet days and an increase in precipitation intensities. Spatially, there is a distinct precipitation decrease over the southeastern parts of the basin and an increase in the northeastern parts, particularly pronounced in \"Dry-Warm\" and \"Median\" scenarios over the late 21st century.

Full details of the study can be found at:

Khan, A.J.; Koch, M. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB). Climate 2018, 6, 89. https://doi.org/10.3390/cli6040089

本数据集源自笔者针对印度河上游流域（Upper Indus Basin, 缩写UIB）开展的气候变化水文影响博士研究的副产品。

本次提供的数据覆盖印度河上游流域全域，包含经偏差校正与降尺度处理的5项区域气候模式-全球气候模式（RCM-GCM）试验结果（由南亚协调区域降尺度试验计划CORDEX-SA提供）。其中“降水（Precipitation, PCP）”与“气温（Temperature, TMP）”预测数据以173个子流域质心的点数据形式呈现，格式适配SWAT（Soil and Water Assessment Tool）水文模型的输入要求，可直接使用。此外还提供了SWAT水文模型所需的其他未来时段参数数据，包括“相对湿度（Humidity, RHU）”、“太阳辐射（Solar-radiation, SLR）”与“风速（Wind, WND）”。

本数据集包含典型浓度路径（Representative Concentration Pathway, RCP）4.5与RCP8.5情景下，经筛选的全球气候模式（General Circulation Model, GCM）的偏差校正与降尺度预测结果。筛选过程基于气候均值与极端变化特征，以及模式再现过去气候的能力进行评估。考虑到印度河上游流域这类高海拔山区的不确定性，研究纳入了湿暖、湿冷、干暖、干冷等多类未来GCM气候预测情景。最终的GCM筛选以各评估准则的加权得分作为依据。

研究发现，协调区域降尺度试验计划（Coordinated Regional Downscaling Experiment, CORDEX）已针对本研究“顶级排名”的GCMs提供了区域气候模式（Regional Climate Model, RCM）数据，因此下载了5项CORDEX-SA试验的动力降尺度气候预测结果，分别为：IPSL-CM5A-MR_RCA4、MPI-ESM-LR_RCA4、NorESM1-M_RCA4、Can ESM2_RegCM4-4及GFDL-ESM2M_RCA4，并在印度河上游流域范围内进一步完成统计降尺度（偏差校正）处理。上述试验采用了RCA4与RegCM4两种不同的区域气候模式，输出的空间分辨率（0.44°）优于原始全球气候模式。

针对2100年的降尺度预测结果显示，气温升幅介于2.3℃至9.0℃之间，降水变化则从干旱情景下的年均小幅增长2.2%，到湿润情景下的显著增长15.9%不等。所有情景下，未来降水均将更趋极端：湿日发生概率降低，而降水强度提升。空间分布上，流域东南部降水呈现显著减少趋势，东北部则有所增加，这一特征在21世纪后期的“干暖”与“中等”情景中尤为明显。

本研究的完整细节可参阅以下文献：
Khan, A.J.; Koch, M. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB). Climate 2018, 6, 89. https://doi.org/10.3390/cli6040089