Rajesh Kumar , Scott Meech , Prafull P. Yadav , William Y.Y. Cheng , Sachin D. Ghude , Stefano Alessandrini , Rajmal Jat , Gaurav Govardhan
{"title":"吸收VIIRS的AOD数据能像吸收MODIS的AOD那样改善新德里的空气污染预测吗?","authors":"Rajesh Kumar , Scott Meech , Prafull P. Yadav , William Y.Y. Cheng , Sachin D. Ghude , Stefano Alessandrini , Rajmal Jat , Gaurav Govardhan","doi":"10.1016/j.atmosenv.2025.121526","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines whether fine particulate matter (PM<sub>2.5</sub>) forecasts in New Delhi will continue to benefit from assimilation of Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth (AOD) retrievals in the same way as has been seen from assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD assimilation. Three experiments were conducted with and without constraining aerosols initialization through assimilation of MODIS and VIIRS AOD retrievals in Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Satellite AOD assimilation significantly improves the agreement between modeled and Aerosol Robotic Network (AERONET) AOD at Kanpur with most of the changes in PM<sub>2.5</sub> vertical distribution limited to altitudes below 5 km. Consequently, the assimilation of either MODIS or VIIRS AOD retrievals also reduces the mean bias in 72 h PM<sub>2.5</sub> forecasts by 70–86 % and root mean squared error by 20–31 % with improvements of ∼200 μg/m<sup>3</sup> during an acute air pollution episode in November 2017. However, the improvements due to VIIRS assimilation are slightly lower (0.5–3 %) than those due to MODIS assimilation. We conclude that VIIRS AOD can effectively replace MODIS in the operational air quality forecasting system after MODIS's end of life and can continue to support air quality management efforts in New Delhi.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"361 ","pages":"Article 121526"},"PeriodicalIF":3.7000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Will assimilating VIIRS AOD data improve New Delhi's air pollution forecasts as much as assimilating MODIS AOD?\",\"authors\":\"Rajesh Kumar , Scott Meech , Prafull P. Yadav , William Y.Y. Cheng , Sachin D. Ghude , Stefano Alessandrini , Rajmal Jat , Gaurav Govardhan\",\"doi\":\"10.1016/j.atmosenv.2025.121526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study examines whether fine particulate matter (PM<sub>2.5</sub>) forecasts in New Delhi will continue to benefit from assimilation of Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth (AOD) retrievals in the same way as has been seen from assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD assimilation. Three experiments were conducted with and without constraining aerosols initialization through assimilation of MODIS and VIIRS AOD retrievals in Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Satellite AOD assimilation significantly improves the agreement between modeled and Aerosol Robotic Network (AERONET) AOD at Kanpur with most of the changes in PM<sub>2.5</sub> vertical distribution limited to altitudes below 5 km. Consequently, the assimilation of either MODIS or VIIRS AOD retrievals also reduces the mean bias in 72 h PM<sub>2.5</sub> forecasts by 70–86 % and root mean squared error by 20–31 % with improvements of ∼200 μg/m<sup>3</sup> during an acute air pollution episode in November 2017. However, the improvements due to VIIRS assimilation are slightly lower (0.5–3 %) than those due to MODIS assimilation. We conclude that VIIRS AOD can effectively replace MODIS in the operational air quality forecasting system after MODIS's end of life and can continue to support air quality management efforts in New Delhi.</div></div>\",\"PeriodicalId\":250,\"journal\":{\"name\":\"Atmospheric Environment\",\"volume\":\"361 \",\"pages\":\"Article 121526\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Environment\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1352231025005011\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Environment","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1352231025005011","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Will assimilating VIIRS AOD data improve New Delhi's air pollution forecasts as much as assimilating MODIS AOD?
This study examines whether fine particulate matter (PM2.5) forecasts in New Delhi will continue to benefit from assimilation of Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth (AOD) retrievals in the same way as has been seen from assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD assimilation. Three experiments were conducted with and without constraining aerosols initialization through assimilation of MODIS and VIIRS AOD retrievals in Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Satellite AOD assimilation significantly improves the agreement between modeled and Aerosol Robotic Network (AERONET) AOD at Kanpur with most of the changes in PM2.5 vertical distribution limited to altitudes below 5 km. Consequently, the assimilation of either MODIS or VIIRS AOD retrievals also reduces the mean bias in 72 h PM2.5 forecasts by 70–86 % and root mean squared error by 20–31 % with improvements of ∼200 μg/m3 during an acute air pollution episode in November 2017. However, the improvements due to VIIRS assimilation are slightly lower (0.5–3 %) than those due to MODIS assimilation. We conclude that VIIRS AOD can effectively replace MODIS in the operational air quality forecasting system after MODIS's end of life and can continue to support air quality management efforts in New Delhi.
期刊介绍:
Atmospheric Environment has an open access mirror journal Atmospheric Environment: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review.
Atmospheric Environment is the international journal for scientists in different disciplines related to atmospheric composition and its impacts. The journal publishes scientific articles with atmospheric relevance of emissions and depositions of gaseous and particulate compounds, chemical processes and physical effects in the atmosphere, as well as impacts of the changing atmospheric composition on human health, air quality, climate change, and ecosystems.