Disaggregating IMERG satellite precipitation over Czech Republic: an innovative approach using hybrid Extreme Gradient Boosting based on Fuzzy Spatial-Temporal Multivariate Clustering

1 Introduction
The data archive provides a reconstructed dataset capturing annual runoff across Europe, partitioned into a grid format and preserved in NetCDFv4 (.nc) format for enhanced geospatial information.
1.1 Coordinate system and spatial resolution
Each grid cell in the dataset corresponds to a spatial resolution of 0.009090951 degrees, using the World Geodetic System 1984 (WGS84) as the standard coordinate frame.
1.2 Temporal resolution
The data encapsulates a yearly temporal resolution, offering a comprehensive outlook from 2000-06-01 to 2021-08-01.
1.3 Units
Precipitation measurements are quantified in millimetres per month (mm/month), providing hydrological data throughout the specified time frame.

1.4 Example
library ( terra )
> dr < - rast ( " disaggregated _ imerg _ precipitation . nc " )
> dr
class : SpatRaster
size : 2 7 5 , 7 4 4 , 2 5 5 ( nrow , ncol , nlyr )
resolution : 0 . 0 0 9 0 9 0 9 5 1 , 0 . 0 0 9 0 9 0 9 5 1 (x , y )
extent : 1 2 . 1 0 0 0 6 , 1 8 . 8 6 3 7 2 , 4 8 . 5 5 4 7 7 , 5 1 . 0 5 4 7 8 ( xmin , xmax , ymin , ymax )
coord . ref . : lon / lat WGS 8 4 ( EPSG : 4 3 2 6 )
source : disaggregated _ imerg _ precipitation . nc
varname : precip ( Disaggregated IMERG Precipitation ( Hybrid XGB - Fuzzy STMC ))
names : precip _ 1 , precip _ 2 , precip _ 3 , precip _ 4 , precip _ 5 , precip _ 6 ,
...
unit : mm / month
time ( days ) : 2 0 0 0 -0 6 -0 1 to 2 0 2 1 -0 8 -0 1 ( 2 5 5 steps )

1.5 Citation
The specific data file, named ’disaggregated imerg precipitation.nc,’ is conveniently structured to facilitate easy handling and interpretation of the information.
Please ensure to attribute the correct citation when utilising this dataset, adhering to the subsequent reference: [Singh et al., 2025]

1.6 Funding
This study was funded by the Internal Grant Agency of the Faculty of Environmental Sciences of the Czech University of Life Sciences (Grant No. 2021B0021, 2022B0018 and 2023B0032 to the Corresponding author, Ujjwal Singh). This publication has been produced as part of the project RUR - Region for university, university for region (Reg. No. CZ.10.02.01/00/22 002/0000210), with the financial support of the European Union. This research has also been supported by the Ministry of Education, Youth and Sports of the Czech Republic (grant AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation (CZ.02.01.01/00/22 008/0004635)).

References
Ujjwal Singh, Sadaf Nasreen, Gaurav Tripathi, Pragya Mehrishi, Rajani Kumar Pradhan, Poppov´a Bestakova, Vivek Vikram Singh, KC Gouda, Laxmi Kant Sharma, Kiran Jalem, et al. Disaggregating imerg satellite precipitation over the Czech Republic: an innovative approach using hybrid extreme gradient boosting based on fuzzy spatial-temporal multivariate clustering. Journal of Big Data, 12(1):151, 2025.