Abstract

Clouds act as a major reflector that changes the amount of sunlight reflected to space. Change in radiance intensity due to the presence of clouds interrupts the retrieval of trace gas or aerosol properties from satellite data. In this paper, we developed a fast and robust algorithm, named the fast cloud retrieval algorithm, using a triplet of wavelengths (469, 477, and 485 nm) of the O2–O2 absorption band around 477 nm (CLDTO4) to derive the cloud information such as cloud top pressure (CTP) and cloud fraction (CF) for the Geostationary Environment Monitoring Spectrometer (GEMS). The novel algorithm is based on the fact that the difference in the optical path through which light passes with regard to the altitude of clouds causes a change in radiance due to the absorption of O2–O2 at the three selected wavelengths. To reduce the time required for algorithm calculations, the look-up table (LUT) method was applied. The LUT was pre-constructed for various conditions of geometry using Vectorized Linearized Discrete Ordinate Radiative Transfer (VLIDORT) to consider the polarization of the scattered light. The GEMS was launched in February 2020, but the observed data of GEMS have not yet been widely released. To evaluate the performance of the algorithm, the retrieved CTP and CF using observational data from the Global Ozone Monitoring Experiment-2 (GOME-2), which cover the spectral range of GEMS, were compared with the results of the Fast Retrieval Scheme for Clouds from the Oxygen A band (FRESCO) algorithm, which is based on the O2 A-band. There was good agreement between the results, despite small discrepancies for low clouds.

Highlights

  • Clouds play an important role as a reflector that causes change in the amount of reflected sunlight in the ultraviolet–visible (UV–Vis) region

  • The variables, except for the radiance and geometry of the satellite used in CLDTO4, were adopted by climatology data

  • When cloud parameters are derived by applying CLDTO4 to Geostationary Environment Monitoring Spectrometer (GEMS), cloud structure information on a smaller scale can be provided because the spatial resolution of GEMS is smaller than that of Global Ozone Monitoring Experiment-2 (GOME-2)

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Summary

Introduction

Clouds play an important role as a reflector that causes change in the amount of reflected sunlight in the ultraviolet–visible (UV–Vis) region. Clouds significantly attenuate the polarization of the atmosphere [1,2,3]. Clouds affect the accuracy of the retrieval of trace gases and aerosols from satellites. Considering the spatial resolution of satellites, only 5–15% of the observed pixels correspond to clear sky conditions [4]. It is essential to provide cloud information for the pixels where cloud exists. The amount of ozone under cloud is corrected using the climatic value since the cloud serves as a shield preventing sunlight from penetrating the atmosphere under the cloud [5,6]. It is necessary to obtain accurate cloud information to calculate the amount of ozone precisely

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