Scenna (2026) Evaluating rainfall and precipitation estimations of seven gridded products across space and time.

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-01-05
• Authors: Luca N. Scenna
• DOI: 10.17632/hc2cs9trbj.3

Research Groups

Instituto de Investigaciones Fisiologicas y Ecologicas Vinculadas a la Agricultura

Short Summary

This dataset provides daily, monthly, and annual rainfall and precipitation data from 93 stations and 7 gridded products, intended for the evaluation of these products' estimations across spatial and temporal scales.

Objective

• To provide a comprehensive dataset for evaluating the accuracy of seven gridded rainfall and precipitation products against station observations across various spatial and temporal scales.

Study Configuration

• Spatial Scale: 93 ground stations (65 for rainfall products) primarily located in Argentina, covering a regional to continental extent.
• Temporal Scale: Daily, monthly, and annual data.

Methodology and Data

• Models used: ERA5-Land, GSMaP, IMERG, NASAPOWER, TERRACLIMATE, CHIRPS, SM2RAIN-ASCAT (these are the gridded products being evaluated).
• Data sources: Ground-based observations from 93 stations (65 for rainfall) and gridded precipitation products (ERA5-Land, GSMaP, IMERG, NASAPOWER, TERRACLIMATE, CHIRPS, SM2RAIN-ASCAT).

Main Results

• This document describes a dataset comprising daily, monthly, and annual rainfall/precipitation data from 93 ground stations and 7 gridded products. The dataset is intended for use in evaluating the performance of the gridded products; the results of such an evaluation are not presented here.

Contributions

• Provision of a multi-product, multi-temporal, and multi-spatial dataset for rigorous evaluation of gridded precipitation products, facilitating future research on their accuracy and applicability.

Funding

• Not specified in the provided text.

Citation

@article{Scenna2026Evaluating,
  author = {Scenna, Luca N.},
  title = {Evaluating rainfall and precipitation estimations of seven gridded products across space and time.},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/hc2cs9trbj.3},
  url = {https://doi.org/10.17632/hc2cs9trbj.3}
}