Kumar et al. (2025) All-sky radiance assimilation of INSAT-3DS imager water vapour channel in the weather research and forecasting model

Identification

• Journal: Atmospheric Research
• Year: 2025
• Date: 2025-12-04
• Authors: Prashant Kumar, P. K. Thapliyal, V. S. Prasad
• DOI: 10.1016/j.atmosres.2025.108674

Research Groups

• AOSG, EPSA, Space Applications Centre, ISRO, Ahmedabad, India
• NCMRWF, MoES, New Delhi, India

Short Summary

This study evaluates the impact of assimilating all-sky water vapour radiance observations from the recently launched INSAT-3DS satellite into the Weather Research and Forecasting (WRF) model. It demonstrates that all-sky assimilation significantly increases the number of assimilated observations and improves short-range weather forecasts, particularly for moisture and temperature fields, compared to clear-sky assimilation.

Objective

• To assess the impact of all-sky water vapour (WV) radiance observations from the INSAT-3DS imager on the Weather Research and Forecasting (WRF) model's analyses and short-range forecasts.

Study Configuration

• Spatial Scale: South Asia
• Temporal Scale: July 2024 (for assimilation experiments); short-range forecast evaluations

Methodology and Data

• Models used: Weather Research and Forecasting (WRF) model
• Data sources:
  • INSAT-3DS Imager water vapour channel radiance observations (primary)
  • Advanced Technology Microwave Sounder (ATMS) (for independent validation)
  • High-Resolution Infrared Sounder/4 (HIRS/4) (for independent validation)
  • Microwave Humidity Sounder (MHS) (for independent validation)

Main Results

• All-sky assimilation significantly increased the number of assimilated observations by approximately 300 % compared to clear-sky assimilation.
• Analyses derived from all-sky assimilation were more consistent with independent satellite measurements from ATMS, HIRS/4, and MHS.
• Short-range forecasts using all-sky radiance assimilation showed improved predictions of simulated water vapour brightness temperature, moisture, and temperature fields compared to clear-sky radiance assimilation.
• Forecasts from the all-sky assimilation run consistently exhibited reduced bias and root mean square deviation (RMSD) when verified against INSAT-3DS WV channel observations, compared to clear-sky and control runs.
• The study highlights the potential of all-sky radiance assimilation to enhance WRF model prediction accuracy, especially in summer monsoon-affected regions where cloud-affected radiances are crucial.

Contributions

• This study is among the first to assimilate all-sky water vapour radiance observations from the recently launched Indian geostationary satellite, INSAT-3DS, into a numerical weather prediction model.
• It quantitatively demonstrates the substantial advantage of all-sky assimilation over traditional clear-sky methods, significantly increasing the utilization of satellite data and improving short-range forecast accuracy for key atmospheric variables.
• The findings underscore the importance of all-sky radiance assimilation for better representation of atmospheric moisture and advancing short-range weather forecasts, particularly in cloud-prone regions like those affected by the summer monsoon.

Funding

Not specified in the provided text.

Citation

@article{Kumar2025Allsky,
  author = {Kumar, Prashant and Thapliyal, P. K. and Prasad, V. S.},
  title = {All-sky radiance assimilation of INSAT-3DS imager water vapour channel in the weather research and forecasting model},
  journal = {Atmospheric Research},
  year = {2025},
  doi = {10.1016/j.atmosres.2025.108674},
  url = {https://doi.org/10.1016/j.atmosres.2025.108674}
}