Evidence map›Paper›PMID 41225035›Full record

ArticleScientific reports2025

Assimilation of high-resolution Ocean Color Monitor (OCM) aerosol optical depth in WRF-Chem improves PM₂.₅ forecasts over the Indian region.

Prafull P Yadav, Sachin D Ghude, Rajesh Kumar, Gaurav Govardhan, Rajmal Jat, Shivani Shah, B P Shukla, Manoj K Mishra, Deepak Putrevu, P K Thapliyal and 1 more

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

11 authors.

Prafull P YadavIndian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India. prafull.yadav@tropmet.res.in.
Sachin D GhudeIndian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India. sachinghude@tropmet.res.in.
Rajesh KumarNational Science Foundation National Center for Atmospheric Research, Boulder, CO, USA.
Gaurav GovardhanIndian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.
Rajmal JatIndian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.
Shivani ShahSpace Applications Centre, Ahmedabad, India.
B P ShuklaSpace Applications Centre, Ahmedabad, India.
Manoj K MishraSpace Applications Centre, Ahmedabad, India.
Deepak PutrevuSpace Applications Centre, Ahmedabad, India.
P K ThapliyalSpace Applications Centre, Ahmedabad, India.
Rashmi SharmaSpace Applications Centre, Ahmedabad, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the impact of assimilating high resolution (770 m) Aerosol Optical Depth (AOD) retrieval derived from the Oceansat-3 Ocean Colour Monitor (OCM) sensor into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for the first time, aiming to improve fine particulate matter (PM₂.₅) forecasts over India. AOD assimilation, evaluated over the period 01-15 November 2023, leads to substantial improvements in model accuracy, reducing PM₂.₅ biases by 30-70% and lowering root mean square error (RMSE) across critical regions such as Delhi, Punjab, Bihar, and West Bengal. The assimilation substantially improves initial conditions of surface PM₂.₅ estimates by approximately 60 µg/m³. Forecast accuracy is the highest on the first day, with an RMSE of 21.35 µg/m³ and a correlation coefficient (R) of 0.75, followed by increasing RMSE values of 30.40 µg/m³ on Day 2 and 32 µg/m³ on Day 3, with correlations of 0.73 and 0.70, respectively, reflecting degradation of assimilation benefits by model uncertainties over time. With MODIS nearing phase-out, high-resolutionOCM AOD retrievals offer a reliable alternate choice for future AOD assimilation in the AIRWISE forecasting system over India.

Indexed as

Ocean Color Monitor (OCM)Satellite data assimilationWRF-Chem

Identifiers

PMID41225035
PMCPMC12612248

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