Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A New Potential of the Deep Convective Clouds as the Calibration Target for a Geostationary UV/VIS Hyperspectral Spectrometer

Version 1 : Received: 17 December 2019 / Approved: 19 December 2019 / Online: 19 December 2019 (13:14:55 CET)

A peer-reviewed article of this Preprint also exists.

Lee, Y.; Ahn, M.-H.; Kang, M. The New Potential of Deep Convective Clouds as a Calibration Target for a Geostationary UV/VIS Hyperspectral Spectrometer. Remote Sens. 2020, 12, 446. Lee, Y.; Ahn, M.-H.; Kang, M. The New Potential of Deep Convective Clouds as a Calibration Target for a Geostationary UV/VIS Hyperspectral Spectrometer. Remote Sens. 2020, 12, 446.

Journal reference: Remote Sens. 2020, 12, 446
DOI: 10.3390/rs12030446

Abstract

As one of GEO-constellation for environmental monitoring in the next decade, Geostationary Environment Monitoring Spectrometer (GEMS) is designed to observe the Asia Pacific region to provide the information on the atmospheric chemicals, aerosol and cloud properties. For the continuous monitoring of the sensor performance after its launch in early 2020, here we suggest deep convective clouds (DCCs) as a possible target for the vicarious calibration of GEMS, the first UV/VIS hyperspectral sensor onboard a geostationary satellite. Tropospheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) are used as a proxy of GEMS, and a conventional DCC detection approach applying the thermal threshold test is used for the DCC detection based on the collocations with Advance Himawari-8 Imager (AHI) onboard Himawari-8 geostationary satellite. DCCs are frequently detected over the GEMS observation area on average over 200 pixels in a single observation scene. Considering the spatial resolution of GEMS, 3.5 km×7 km which is similar to TROPOMI, and its temporal resolution (8 times a day), availability of DCCs for vicarious calibration of GEMS is expected to be sufficient. Inspection of the DCC reflectivity spectra estimated from the OMI and TROPOMI data also shows a promising result. Even though, their observation geometry and sensor characteristics are quite a different, the estimated DCC spectra agree quite a well within a known uncertainty range with comparable spectral features. When the DCC detection is further improved by applying both visible and infrared tests, the variability of DCC reflectivity from the TROPOMI data is reduced by half, from 10% to 5%. This is mainly due to the efficient screening of cold thin cirrus with the visible test and of bright warm clouds with the infrared test. The precise DCC detection is also expected to contribute to the accurate characterization of the cloud reflectivity, which will be further investigated.

Subject Areas

GEMS; UV; VIS; hyperspectral data; deep convective cloud; vicarious calibration; OMI; TROPOMI

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