Hybrid Bias Correction of IMERG Late Run V07 over Indonesia (2001-2025): Input Data, Land-Sea Masks, and Corrected Products

This deposit contains the full input, mask, and output data bundle for the hybrid statistical-deep learning bias correction of daily IMERG Late Run V07 precipitation over Indonesia (95-141 deg E, -11 to 6 deg N) for the period 2001-2025. The bundle accompanies the companion manuscript (Istanto, in preparation) and the open-source code at https://github.com/bennyistanto/hybrid-bias-correction.

The framework combines three correction stages applied per 10-day window (dekad). Linear Scaling matches the long-term mean. Empirical Quantile Mapping with a Generalized Pareto Distribution tail (80th-percentile threshold) reshapes the full daily distribution. A lightweight two-layer convolutional network refines the spatial residual on extreme days. A station-density confidence mask, built from the BMKG gauge network, modulates the CNN influence so that the correction degrades gracefully to LSEQM in gauge-sparse areas.

The input folder contains

1. IMERG Late Run V07 (idn_imergl.nc4, 2001-01-01 to 2025-12-31)
2. IMERG Final Run V07 baseline (idn_imergf.nc4, 2001-01-01 to 2025-09-30)
3. CPC-UNI regridded to 0.1 deg (idn_cpcuni.nc4) and at its native 0.5 deg resolution (idn_cpcuni_native05.nc4)
4. BMKG station location and daily observation CSVs.

The mask folder contains the Indonesia land-sea mask at 0.1 deg together with the area-of-interest subsets used for clipping (`idn_subset.nc`).

The output folder contains

1. Per-method corrected products (corrected_ls, corrected_lseqm, corrected_lseqmdl)
2. Trained CNN models per dekad (trained_models)
3. Per-method performance metrics (metrics_ls, metrics_lseqm, metrics_lseqmdl)
4. Continuous Quality Index outputs (quality_ls, quality_lseqm, quality_lseqmdl)
5. Station-density confidence mask
6. Independent BMKG station validation CSVs
7. Figures

All gridded files are CF-1.8 compliant NetCDF (float32, zlib compression) on a common 0.1 deg lat-lon grid. The CPC-UNI 0.5 deg file is kept on the original gauge-analysis grid and is used by the parameter-fitting path that avoids the 5x5 nearest-neighbour block boundary. Global attributes record the framework version (v2026.01), the source IMERG and CPC files, and the sensitivity parameters used in the run (blend_alpha = 0.70, gpd_threshold_percentile = 80, station_density saturation_count = 3). These three parameters were not formally optimised and were chosen by inspection. Users adapting the framework to another region should treat them as sensitivity parameters rather than fixed defaults.

To reproduce the outputs from the inputs, clone the code repository, point config.yml at the directories in this bundle, and run notebooks 02 through 06 in sequence. A smaller Bali example (about 11 MB) ships with the code repository so users can validate the toolchain on a free Google Colab session before downloading the full Indonesia bundle. Full documentation is available at https://bennyistanto.github.io/hybrid-bias-correction. If you use these data, please cite both this Zenodo deposit and the companion manuscript (DOI to be added on publication).

NASA GPM IMERG V07 data are courtesy of the NASA Goddard Earth Sciences Data and Information Services Center. CPC Unified gauge-based daily precipitation data are provided by the NOAA Physical Sciences Laboratory. BMKG station observations are provided by the Indonesian Agency for Meteorology, Climatology and Geophysics.