Future Intensity-Duration-Frequency relationship of Precipitation across India based on CMIP6 projections

The Future precipitation Intensity-duration-frequency (IDF) relationships across India are prepared based simulated data from the 6th phase of Coupled Model Intercomparison Project (CMIP6). Twelve General Circulation Models i.e. ACCESS-CM2, ACCESS-ESM1-5, AWI-ESM-1-REcoM, CESM2-WACCM, CMCC-CM2-SR5, EC-Earth3, EC-Earth3-veg, INM-CM4-8, INM-CM4-8, IPSL-CM6A-LR, MPI-ESM1-2-HR, MPI-ESM1-2-LR considering three climate change scenarios (SSP126, SSP245, SSP585) from CMIP6 are considered. The future data is bias-corrected against two reanalysis data i.e. Indian Monsoon Data Assimilation and Analysis (IMDAA) and 5th generation European Centre for Medium-Range Weather Forecasts (ERA5) separately. The future projections are divided in two separate time periods i.e epoch-1 (2022-2060), and epoch-2 (2061-2100) and the future data from twelve GCMs are averaged using Reliability Ensemble Averaging method to obtain a weighted future data. Scale-invariance method is used to obtain sub-daily future data from daily data. The future IDF relationship is presented for 7 duration (1-, 2-, 3-, 6-, 9-, 12-, 24- hour) and 6 return periods (2-, 5-, 10, -25, 50, 100- year) considering two future periods and three climate change scenarios. The data is available at 0.25×0.25° spatial resolution across India.本数据集基于第六次耦合模式比较计划（Coupled Model Intercomparison Project Phase 6, CMIP6）的模拟数据，构建了印度全境的未来降水强度-历时-频率（Intensity-duration-frequency, IDF）关系。研究选取了12个大气环流模式（General Circulation Models, GCMs），即ACCESS-CM2、ACCESS-ESM1-5、AWI-ESM-1-REcoM、CESM2-WACCM、CMCC-CM2-SR5、EC-Earth3、EC-Earth3-veg、INM-CM4-8、INM-CM4-8、IPSL-CM6A-LR、MPI-ESM1-2-HR、MPI-ESM1-2-LR，并纳入CMIP6框架下的三种气候变化情景：SSP126、SSP245、SSP585。未来模拟降水数据分别以两套再分析资料——印度季风数据同化与分析（Indian Monsoon Data Assimilation and Analysis, IMDAA）与欧洲中期天气预报中心第五代再分析资料（ERA5）——进行偏差校正。未来降水预测结果被划分为两个独立时段：时段1（2022-2060年）与时段2（2061-2100年），并采用可靠性集合平均（Reliability Ensemble Averaging）法对12个GCM的未来数据进行平均，得到加权融合后的未来降水数据集。此外，通过尺度不变性（Scale-invariance）方法，由日尺度降水数据推导出次日尺度的未来降水数据。本数据集提供了7个历时（1、2、3、6、9、12、24小时）与6个重现期（2、5、10、25、50、100年）下的未来IDF关系，覆盖两个未来时段与三种气候变化情景，空间分辨率为0.25°×0.25°，覆盖印度全境。