TROPOspheric Monitoring Instrument observations of total column water vapour: Algorithm and validation

• Published in: The Science of the total environment Vol. 821; p. 153232
• Main Authors: Chan, Ka Lok, Xu, Jian, Slijkhuis, Sander, Valks, Pieter, Loyola, Diego
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.05.2022
• Subjects: Air Pollutants - analysis; Algorithms; Environmental Monitoring - methods; GOME-2; MODIS; Ozone - analysis; Sentinel-5P; SSMIS; Steam; TROPOMI; Water vapour; Sentinel-5P; GOME-2; Water vapour; TROPOMI; MODIS; SSMIS
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2022.153232

In this paper, we present the total column water vapour (TCWV) retrieval for the TROPOspheric Monitoring Instrument (TROPOMI) observations in the visible blue spectral band. The TROPOMI TCWV algorithm is being optimized and validated in the framework of the Sentinel 5 Precursor Product Algorithm Laboratory (S5P-PAL) project from the European Space Agency (ESA). The retrieval was first developed to retrieve TCWV from the Global Ozone Monitoring Experiment 2 (GOME-2). We have optimized the settings of the retrieval to adapt it for TROPOMI observations. The TROPOMI TCWV algorithm follows the typical two step approach, using spectral fit retrieval of slant columns, and conversion of the slant columns to vertical columns using air mass factors (AMFs). An iterative optimization algorithm is developed to dynamically find the optimal a priori water vapour profile for the AMF calculation. Further optimizations on the spectral retrieval, air mass factor calculations as well as a new surface albedo retrieval approach are implemented. The TCWV retrieval algorithm is applied to TROPOMI observations from May 2018 to May 2021. The results are validated by comparing them to ERA5 reanalysis data, GOME-2, MODerate resolution Imaging Spectroradiometer (MODIS) and Special Sensor Microwave Imager Sounder (SSMIS) satellite observations. TCWV derived from TROPOMI observations agree well with the other data sets with Pearson correlation coefficient (R) ranging from 0.96 to 0.99. The mean bias between TROPOMI and ERA5 data is −1.24 kg m−2 for measurements over land and 0.73 kg m−2 for measurements over water. The comparison to MODIS observations show similar results with small dry bias of 1.51,kg m−2 for measurements over land and a small wet bias of 1.25 kg m−2 for measurements over water. Slightly larger dry bias of 1.98 kg m−2 for measurements over land and 1.74 kg m−2 for measurements over water are found when compared to GOME-2 obserations. Compared to SSMIS data over water, TROPOMI observations are bias low by 3.25 kg m−2. The small discrepancies found between TROPOMI and reference data sets are related to the differences in measurement technique, measurement time, surface albedo issue, as well as cloud and aerosol contamination. This study demonstrates that the algorithm can provide stable and consistent results on a global scale and can be applied to generate operational TCWV products from TROPOMI and the forthcoming Copernicus missions Sentinel-4 and Sentinel-5. We have also demonstrated the capability of retrieving fine scale water vapour structures in a case study over the Amazon. This indicates that the TROPOMI data set is also useful for local and regional climate studies. [Display omitted] •A TCWV retrieval algorithm in the blue band is developed for TROPOMI.•The retrieval is optimized for spectral retrieval, AMF and surface albedo algorithm.•The results are validated against reanalysis and other satellite observations.•The capability of retrieving fine scale water vapour structures is demonstrated