Exploring geometrical stereoscopic aerosol top height retrieval from geostationary satellite imagery in East Asia

Abstract. Despite the importance of aerosol height information for events such as volcanic eruptions and long-range aerosol transport, spatial coverage of its retrieval is often limited because of a lack of appropriate instruments and algorithms. Geostationary satellite observations in particular provide constant monitoring for such events. This study assessed the application of different viewing geometries for a pair of geostationary imagers to retrieve aerosol top height (ATH) information. The stereoscopic algorithm converts a lofted aerosol layer parallax, calculated using image-matching of two visible images, to ATH. The sensitivity study provides a reliable result using a pair of Advanced Himawari Imager (AHI) and Advanced Geostationary Radiation Imager (AGRI) images at 40∘ longitudinal separation. The pair resolved aerosol layers above 1 km altitude over East Asia. In contrast, aerosol layers must be above 3 km for a pair of AHI and Advanced Meteorological Imager (AMI) images at 12.5∘ longitudinal separation to resolve their parallax. Case studies indicate that the stereoscopic ATH retrieval results are consistent with aerosol heights determined using extinction profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). Comparisons between the stereoscopic ATH and the CALIOP 90 % extinction height, defined by extinction coefficient at 532 nm data, indicated that 88.9 % of ATH estimates from the AHI and AGRI are within 2 km of CALIOP 90 % extinction heights, with a root-mean-squared difference (RMSD) of 1.66 km. Meanwhile, 24.4 % of ATH information from the AHI and AMI was within 2 km of the CALIOP 90 % extinction height, with an RMSD of 4.98 km. The ability of the stereoscopic algorithm to monitor hourly aerosol height variations is demonstrated by comparison with a Korea Aerosol Lidar Observation Network dataset.

[1]  Chian‐Yi Liu,et al.  Embedded information of aerosol type, hygroscopicity and scattering enhancement factor revealed by the relationship between PM2.5 and aerosol optical depth. , 2023, The Science of the total environment.

[2]  Colin J. Seftor,et al.  Aerosol Layer Height With Enhanced Spectral Coverage Achieved by Synergy Between VIIRS and OMPS-NM Measurements , 2021, IEEE Geoscience and Remote Sensing Letters.

[3]  Aixia Yang,et al.  Radiometric Performance Evaluation of FY-4A/AGRI Based on Aqua/MODIS , 2021, Sensors.

[4]  C. Narayanamurthy,et al.  Vertical and spatial distribution of elevated aerosol layers obtained using long-term ground-based and space-borne lidar observations , 2021 .

[5]  K. Gui,et al.  Seasonal distribution and vertical structure of different types of aerosols in southwest China observed from CALIOP , 2020 .

[6]  D. Diner,et al.  Aerosol profiling using radiometric and polarimetric spectral measurements in the O2 near infrared bands: Estimation of information content and measurement uncertainties , 2020 .

[7]  L. G. Tilstra,et al.  First validation of GOME-2/MetOp absorbing aerosol height using EARLINET lidar observations , 2020, Atmospheric Chemistry and Physics.

[8]  J. Veefkind,et al.  A first comparison of TROPOMI aerosol layer height (ALH) to CALIOP data , 2020, Atmospheric Measurement Techniques.

[9]  Jonghyuk Lee,et al.  A Cloud Top-Height Retrieval Algorithm Using Simultaneous Observations from the Himawari-8 and FY-2E Satellites , 2020, Remote. Sens..

[10]  I. Laszlo,et al.  Improving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithm , 2020, Atmospheric Measurement Techniques.

[11]  Alexis K.H. Lau,et al.  New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) , 2020, Bulletin of the American Meteorological Society.

[12]  P. Levelt,et al.  The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations , 2019, Atmospheric Measurement Techniques.

[13]  David M. Winker,et al.  The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm. , 2018, Atmospheric measurement techniques.

[14]  Jhoon Kim,et al.  AHI/Himawari-8 Yonsei Aerosol Retrieval (YAER): Algorithm, Validation and Merged Products , 2018, Remote. Sens..

[15]  Jhoon Kim,et al.  Optimal Estimation-Based Algorithm to Retrieve Aerosol Optical Properties for GEMS Measurements over Asia , 2018, Remote. Sens..

[16]  Zhiqing Zhang,et al.  Introducing the New Generation of Chinese Geostationary Weather Satellites, Fengyun-4 , 2017 .

[17]  Yuan Wang,et al.  Aerosol vertical distribution and optical properties over China from long-term satellite and ground-based remote sensing , 2017 .

[18]  Eleni Marinou,et al.  An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nmO 2 O 2 spectral band using a neural network approach , 2016 .

[19]  Brian Cairns,et al.  Passive remote sensing of aerosol layer height using near‐UV multiangle polarization measurements , 2016, Geophysical research letters.

[20]  Arata Okuyama,et al.  Himawari-8/AHI latest performance of navigation and calibration , 2016, SPIE Asia-Pacific Remote Sensing.

[21]  Eun-Ho Lee,et al.  한반도 에어로졸 라이다 네트워크(KALION)의 에어로졸 유형 구분 및 질량 농도 산출 알고리즘 , 2016 .

[22]  Klemen Zaksek,et al.  Stereoscopic Estimation of Volcanic Ash Cloud-Top Height from Two Geostationary Satellites , 2016, Remote. Sens..

[23]  Thomas F. Eck,et al.  Aerosol optical properties derived from the DRAGON-NE Asia campaign, and implications for a single-channel algorithm to retrieve aerosol optical depth in spring from Meteorological Imager (MI) on-board the Communication, Ocean, and Meteorological Satellite (COMS) , 2016 .

[24]  Ukkyo Jeong,et al.  An optimal-estimation-based aerosol retrieval algorithm using OMI near-UV observations , 2016 .

[25]  N. C. Hsu,et al.  Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations , 2015 .

[26]  Sang Seo Park,et al.  Utilization of O4 slant column density to derive aerosol layer height from a spaceborne UV-Visible hyperspectral sensor: Sensitivity and case study. , 2015, Atmospheric chemistry and physics.

[27]  J. Fischer,et al.  Retrieving aerosol height from the oxygen A band: a fast forward operator and sensitivity study concerning spectral resolution, instrumental noise, and surface inhomogeneity , 2013 .

[28]  Michael J. Garay,et al.  Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX) , 2013, Remote. Sens..

[29]  R. Fu,et al.  Seasonal and diurnal variations of aerosol extinction profile and type distribution from CALIPSO 5‐year observations , 2013, Journal of Geophysical Research: Atmospheres.

[30]  D P Edwards,et al.  Tropospheric emissions: monitoring of pollution (TEMPO) , 2012, Optics & Photonics - Optical Engineering + Applications.

[31]  Janez Zaletelj,et al.  Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites , 2012 .

[32]  W. Collins,et al.  Application of the CALIOP layer product to evaluate the vertical distribution of aerosols estimated by global models: AeroCom phase I results , 2012 .

[33]  Paul Ingmann,et al.  Requirements for the GMES Atmosphere Service and ESA's implementation concept: Sentinels-4/-5 and -5p , 2012 .

[34]  John P. Burrows,et al.  Retrieval of spectral aerosol optical thickness over land using ocean color sensors MERIS and SeaWiFS , 2010 .

[35]  D. Winker,et al.  Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms , 2009 .

[36]  H. S. Lim,et al.  Retrieving aerosol optical depth using visible and mid‐IR channels from geostationary satellite MTSAT‐1R , 2008 .

[37]  James J. Szykman,et al.  Developing Aerosol Height Product from MODIS and Synergy of MODIS and CALIPSO Measurements for Global Application , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[38]  D. Winker,et al.  Initial performance assessment of CALIOP , 2007 .

[39]  Alexander Smirnov,et al.  Ground-Based Lidar Measurements of Aerosols During ACE-2 Instrument Description, Results, and Comparisons with Other Ground-Based and Airborne Measurements , 2000 .

[40]  Tae-Hyeong Oh,et al.  Introduction of the Advanced Meteorological Imager of Geo-Kompsat-2a: In-Orbit Tests and Performance Validation , 2021, Remote. Sens..

[41]  Jun Wang,et al.  First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: Algorithm development and application for surface particulate matter estimates , 2021, Remote Sensing of Environment.

[42]  Juergen Fischer,et al.  Retrieving aerosol height from the oxygen A band : a fast forward operator and sensitivity study concerning spectral resolution , instrumental noise , and surface inhomogeneity , 2013 .

[43]  J. Purdy,et al.  Introducing new technologies into the clinic. , 2007, Frontiers of radiation therapy and oncology.