Pradhan et al. (2025) Diurnal variability of global precipitation: insights from hourly satellite and reanalysis datasets

Identification

• Journal: Hydrology and earth system sciences
• Year: 2025
• Date: 2025-10-02
• Authors: Rajani Kumar Pradhan, Yannis Markonis, Francesco Marra, Efthymios I. Nikolopoulos, Simon Michael Papalexiou, Vincenzo Levizzani
• DOI: 10.5194/hess-29-4929-2025

Research Groups

• Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Czech Republic
• Department of Geosciences, University of Padua, Italy
• Department of Civil and Environmental Engineering, Rutgers University, USA
• Department of Civil Engineering, University of Calgary, Canada
• Institute for Global Water Security, Hamburg University of Technology, Germany
• Institute of Atmospheric Sciences and Climate, National Research Council of Italy, Italy

Short Summary

This study comprehensively intercompared the diurnal variability of global precipitation using five state-of-the-art hourly satellite and reanalysis datasets, revealing consistent broad spatial patterns but significant regional uncertainties in precipitation amount, frequency, and intensity, particularly at higher latitudes.

Objective

• To comprehensively explore and intercompare the diurnal cycle of precipitation (amount, frequency, and intensity) using five state-of-the-art hourly satellite and reanalysis precipitation products at a quasi-global scale (60° N–60° S) over two decades.

Study Configuration

• Spatial Scale: Quasi-global (60° N–60° S), remapped to a common 0.25° × 0.25° resolution.
• Temporal Scale: Hourly resolution, covering the period from 2001 to 2020.

Methodology and Data

• Models used: Integrated Multi-satellitE Retrievals for GPM (IMERG), Global Satellite Mapping of Precipitation (GSMaP), Climate Prediction Center Morphing (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and ECMWF Reanalysis v5 (ERA5).
• Data sources: Satellite-based (IMERG, GSMaP, CMORPH, PERSIANN) and reanalysis (ERA5). IMERG and GSMaP incorporate gauge corrections (GPCC and CPC, respectively), while CMORPH uses bias correction (CPC, GPCP). PERSIANN relies on infrared images and artificial neural networks. All datasets were remapped to a common 0.25° spatial and 1-hour temporal resolution. Diurnal variability was evaluated using precipitation amount, frequency (defined as precipitation > 0.1 mm/h), and intensity. K-means clustering was applied to identify distinct diurnal patterns.

Main Results

• All products consistently depict major global precipitation features (e.g., ITCZ, SPCZ) and the general diurnal pattern of an afternoon peak over land and an early-morning peak over the ocean.
• Significant uncertainties exist among datasets, particularly at high latitudes (30° to 60° N/S), with larger discrepancies in the Southern Hemisphere (35° to 60° S).
• ERA5 consistently overestimates precipitation frequency (e.g., up to 40% at ITCZ, double other products) and underestimates intensity, attributed to a "drizzle problem" with light precipitation.
• CMORPH shows the highest precipitation intensity (exceeding 1.25 mm/h), while ERA5 and GSMaP (especially over land) show the lowest.
• ERA5 exhibits an earlier diurnal peak over land (around 15:00 LST) compared to satellite products (16:00–18:00 LST).
• IMERG and CMORPH demonstrate high agreement in diurnal shapes and regional peak hour patterns, including nocturnal peaks over specific land regions (e.g., Great Plains, northern Africa).

Contributions

• Provides the first comprehensive global-scale analysis of the diurnal cycle of precipitation (amount, frequency, intensity) using an ensemble of five state-of-the-art hourly satellite and reanalysis products over a two-decade period (2001–2020).
• Quantifies and highlights region-specific strengths and limitations, as well as agreements and disagreements, among these diverse precipitation datasets at sub-daily scales.
• Serves as a global-scale reference for understanding and quantifying uncertainties in the representation of diurnal precipitation from global precipitation datasets, emphasizing the need for multi-dataset integration.

Funding

• Internal Grant Agency, Czech University of Life Sciences Prague (project no. 2023B0028)
• Czech Science Foundation (grant 22-33266M) for the project “Investigation of Terrestrial HydrologicAl Cycle Acceleration (ITHACA)”

Citation

@article{Pradhan2025Diurnal,
  author = {Pradhan, Rajani Kumar and Markonis, Yannis and Marra, Francesco and Nikolopoulos, Efthymios I. and Papalexiou, Simon Michael and Levizzani, Vincenzo},
  title = {Diurnal variability of global precipitation: insights from hourly satellite and reanalysis datasets},
  journal = {Hydrology and earth system sciences},
  year = {2025},
  doi = {10.5194/hess-29-4929-2025},
  url = {https://doi.org/10.5194/hess-29-4929-2025}
}