Abstract

The Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite launched on December 23, 2017, observes various geophysical parameters with the aim of a better understanding of the global climate system. As part of that aim, SGLI has great potential to unravel several uncertainties related to clouds by providing new cloud products along with several other atmospheric products related to cloud climatology, including aerosol products from polarization channels. However, a very little is known about the quality of the SGLI cloud products. This study uses data about clouds and global irradiances observed from the Earth’s surface using a sky radiometer and a pyranometer, respectively, to understand the quality of the two most fundamental cloud properties—cloud optical depth (COD) and cloud-particle effective radius (CER)—of both water and ice clouds. The SGLI-observed COD agrees well with values observed from the surface, although it agrees better for water clouds than for ice clouds, while the SGLI-observed CER exhibits poorer agreement than does the COD, with the SGLI values being generally higher than the sky radiometer values. These comparisons between the SGLI and sky radiometer cloud properties are found to differ for different cloud types of both the water and ice cloud phases and different solar and satellite viewing angles by agreeing better for relatively uniform and flat cloud type and for relatively low solar zenith angle. Analyses of SGLI-observed reflectance functions and values calculated by assuming plane-parallel cloud layers suggest that SGLI-retrieved cloud properties can have biases on the solar and satellite viewing angles, similar to other satellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS). Furthermore, it is found that the SGLI-observed cloud properties reproduce global irradiances quite satisfactorily for both water and ice clouds by resembling several important features of the COD comparison, such as the better agreement for water clouds than for ice clouds and the tendency to underestimate (resp. overestimate) the COD in SGLI observations for optically thick (resp. thin) clouds.

Highlights

  • Clouds play important roles in changing the Earth’s climate system (Ramanathan et al, 1989), with profound impacts on the atmospheric heat budget and the hydrological cycle (Rosenfeld et al, 2014)

  • Cloud remotespatial coverage and continuous observations at specific time intervals, satellite cloud products have been used or artificial intelligence (e.g., Masunaga et al, 2008; Letu et al, 2020, 2021), for a better understanding of cloud and cloud-particle effective radius (CER) are obtained using the reflectance observed at two different wavelengths by assuming clouds to be plane-parallel horizontal (PPH) layers), assessing the quality of such cloud products is a fundamental requirement for using them in scientific research, policy making, and other application areas

  • The mean bias error (MBE) values are positive and nearly the same for water and ice clouds. These positive MBE values suggest smaller cloud optical depth (COD) from SGLI than from the sky radiometer for both water and ice clouds, but upon closer on the COD value; we have underestimated values from SGLI for relatively high COD for both water and ice clouds, whereas most of the data samples show an overestimated COD from SGLI when they are less than ~20 and ~10 for water and ice clouds, respectively

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Summary

Introduction

Clouds play important roles in changing the Earth’s climate system (Ramanathan et al, 1989), with profound impacts on the atmospheric heat budget and the hydrological cycle (Rosenfeld et al, 2014). Spatial and temporal variations as well as their complex interactions with aerosols and meteorology Because of their benefits of wide broadly either independently (e.g., Khatri et al, 2021) or combined with technologies such as numerical simulation climatology as well as energy and water budgets.

SKYNET
Pyranometer into transmittances
Study method
Results and discussion
Overall comparison
Comparison between modeled and observed global irradiances
Conclusions
Full Text

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