Preprints
https://doi.org/10.5194/egusphere-2023-1658
https://doi.org/10.5194/egusphere-2023-1658
13 Sep 2023
 | 13 Sep 2023

Assessment of smoke plume height products derived from multisource satellite observations for wildfire in the western US

Jingting Huang, S. Marcela Loría-Salazar, Min Deng, Jaehwa Lee, and Heather A. Holmes

Abstract. As wildfires intensify and fire seasons lengthen across the western U.S., the development of applicable models that can predict the density of smoke plumes and track wildfire-induced air pollution exposures has become critical. Wildfire smoke plume height is a key indicator of the vertical placement of plume mass emitted from wildfire-related aerosol sources in climate and air quality models. With advancements in Earth observation (EO) satellites, spaceborne products for aerosol layer height or plume injection height have recently emerged with increased global-scale spatiotemporal resolution. However, to evaluate column radiative effects and refine satellite algorithms, vertical profiles of regionally representative aerosol data from wildfire emissions need to be measured directly in the field. In this study, we conduct the first comprehensive evaluation of four passive satellite remote sensing techniques specifically designed to retrieve plume height distribution for wildfire smoke. We compare these satellite products with the airborne Wyoming Cloud Lidar (WCL) measurements during the 2018 Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign in the western U.S. Two definitions, namely “plume top” and “extinction-weighted mean plume height”, are used to derive representative heights of wildfire smoke plumes, based on the WCL-retrieved vertical aerosol extinction coefficient profiles. We also perform a comparative analysis of multisource satellite-derived plume height products for wildfire smoke using these two definitions. With the aim to discuss which satellite product is most appropriate under various aerosol loadings and in determining plume height characteristics near a fire-event location or downwind plume rise equivalent height. Our findings highlight the importance of understanding the sensitivity of different passive remote sensing techniques to space-based wildfire smoke plume height observations, in order to resolve ambiguity surrounding the concept of “effective smoke plume height”. As additional aerosol-observing satellites are expected to be launched in the coming years, our results will inform future remote sensing missions and EO data selection. This will help bridge the gap between satellite observations and plume rise modeling to further investigate the vertical distribution of wildfire smoke aerosols.

Jingting Huang, S. Marcela Loría-Salazar, Min Deng, Jaehwa Lee, and Heather A. Holmes

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1658', Anonymous Referee #1, 23 Oct 2023
  • RC2: 'Comment on egusphere-2023-1658', Anonymous Referee #2, 28 Oct 2023
  • AC1: 'Response to Reviewers', Jingting Huang, 07 Dec 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1658', Anonymous Referee #1, 23 Oct 2023
  • RC2: 'Comment on egusphere-2023-1658', Anonymous Referee #2, 28 Oct 2023
  • AC1: 'Response to Reviewers', Jingting Huang, 07 Dec 2023
Jingting Huang, S. Marcela Loría-Salazar, Min Deng, Jaehwa Lee, and Heather A. Holmes
Jingting Huang, S. Marcela Loría-Salazar, Min Deng, Jaehwa Lee, and Heather A. Holmes

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Short summary
Large western U.S. wildfire smoke plumes have risen taller and spread farther as extreme heatwaves continue, degrading air quality over a wider area. By examining the lidar-measured vertical structure of wildfire smoke, we establish two simple and effective height metrics. When comparing four novel satellite-based products, we find they often miss complex smoke layers or thin plumes. Our work sets the stage for improved plume rise modeling using refined satellite data assimilation.