2026-10-07T02:14:57Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34031508 2026-09-30T15:38:04Z category_25759 item_type_9 month_year_09_2026

Python code for compound drought–extreme precipitation event identification, exposure calculation and exposure inequality analysis Xinyue Zhai (17002555) Liang Yao (823113) Bo Jiang (76119) Zhe Chen (196097) Dingtao Shen (11826248) Hao Wu (65943) Climatology Compound drought–extreme precipitation events CMIP6 Global Scale Risk exposure Inequality <p dir="ltr">Python code for identifying compound drought–extreme precipitation events (CDEPs) and calculating the associated population and agricultural exposure. It matches each drought event with an extreme-precipitation event beginning within three days of its end, computes exposure as event frequency × population or cropland area, decomposes the exposure change into climate, exposure-factor and interaction terms, and derives P80 hotspots and income-group exposure-burden ratios. Requires Python 3.10 with numpy, pandas, xarray, netCDF4 and pyarrow.</p> 2026-09-30T15:38:04Z Software Software 10.6084/m9.figshare.34031508.v1 https://figshare.com/articles/software/Python_code_for_compound_drought_extreme_precipitation_event_identification_exposure_calculation_and_exposure_inequality_analysis/34031508 CC BY 4.0