StageIV-IRC: A High-resolution Dataset of Extreme Orographic Quantitative Precipitation Estimates (QPE) Constrained to Water Budget Closure for Historical Floods in the Appalachian Mountains

Abstract. Quantitative Flood Estimation (QFE) in complex terrain remains a grand challenge in operational hydrology due to the lack of accurate high-resolution Quantitative Precipitation Estimates (QPE) for operational forecasting and for calibrating hydrologic models. Here, we present a high-resolution (i.e., 250 m, 5-minute-hourly) QPE dataset for 215 extreme rainfall events occurred in 26 gauged mountainous basins in the Appalachian Mountains from 2008 to 2024. This dataset is developed by applying inverse rainfall corrections (IRC) derived from physically-based rainfall-runoff modeling (Liao and Barros, 2022 and 2023) to the Next Generation Weather Radar (NEXRAD) Stage IV analysis (4 km resolution, hourly). The corrected Stage IV analysis QPE is referred to as StageIV-IRC (StageIV with Inverse Rainfall Correction). The unique advantage of this StageIV-IRC QPE dataset is its agreement with ground-based rainfall measurements while achieving water budget closure at the storm-flood event scale within observational uncertainty of streamflow observations, which is the gold standard in hydrological modeling. This dataset is the first QPE dataset aiming to improve QFE in the complex terrain by reducing biases for extreme precipitation events, and it can be used to evaluate the skill of hydrologic models in the same basins and support model calibration. The StageIV-IRC QPE dataset is publicly available at https://doi.org/10.5281/zenodo.14028866, and improved initial soil moisture maps for the studied extreme precipitation events, derived from the same IRC framework, are available in the same repository (Liao and Barros, 2025c).