Abstract

Accurate and stable in-orbit radiometric calibration of a satellite instrument is fundamental to Earth geophysical parameter estimation. This article addresses the intercalibration of the microwave temperature sounder (MWTS) on the Chinese second-generation polar-orbiting meteorological satellite, Fengyun 3D (FY-3D), against the advanced technology microwave sounder (ATMS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. First, ocean and land microwave radiative transfer models (RTM) are constructed by combining the sea and land surface emissivity models and atmospheric absorption model, as well as the intercalibration equations. Then, the MWTS and ATMS observations are resampled into a 1° × 1° regular grid space, and the matching brightness temperatures (TBs) under clear-sky/near clear-sky conditions are collected. Next, the TBs at top-of-atmosphere are simulated using the RTM and the fifth generation of European Centre for Medium-Range Weather Forecast atmospheric reanalysis (ERA5) data. After that, the double differences between FY-3D MWTS and S-NPP ATMS and the theoretical observations in FY-3D MWTS channels are calculated. Finally, the radiometric calibration coefficients of FY-3D MWTS are successfully derived from the observations of S-NPP ATMS by linear fits on the matching TBs. In contrast to the ATMS measurements, FY-3D MWTS observations are generally overestimated, and the in-orbit radiometric calibration errors (mean ± standard deviation at the mean) are 1.83 ± 1.45, 0.45 ± 0.94, 1.87 ± 0.60, −0.20 ± 0.36, −0.02 ± 0.37, 0.19 ± 0.24, 1.69 ± 0.28, 2.25 ± 0.29, 1.97 ± 0.33, 1.74 ± 0.42, 2.84 ± 0.42, 0.07 ± 0.65, and 0.32 ± 1.18 K in FY-3D MWTS channels 1–13, respectively. The results with Hewison's semi-empirical land surface emissivity (LSE) model and the results with LSEs derived from the coincident ATMS observations at 50.3 GHz are consistent. Moreover, the intercalibration results obtained by the RTM in this work also agree well with the results obtained by the community radiative transfer model.

Highlights

  • THE fourth satellite of Chinese second-generation polarorbiting meteorological satellite, Fengyun 3D (FY-3D), was successfully launched into space on November 15, 2017.FY-3D crosses the equator in the ascending node around 14:00 local time, and it is referred to as an afternoon satellite

  • This paper presented the intercalibration of FY-3D Microwave Temperature Sounder (MWTS) against Suomi National Polarorbiting Partnership (S-NPP) Advanced Technology Microwave Sounder (ATMS) over both sea and land surfaces using the microwave radiative transfer models (RTM) and the ERA5 data

  • Non-ignorable O-B differences exist between different models, the final intercalibration results obtained by the RTM in this work agree well with those obtained by the Community Radiative Transfer Model (CRTM)

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Summary

Introduction

THE fourth satellite of Chinese second-generation polarorbiting meteorological satellite, Fengyun 3D (FY-3D), was successfully launched into space on November 15, 2017.FY-3D crosses the equator in the ascending node around 14:00 local time, and it is referred to as an afternoon satellite. FY-3D MWTS cross-track scans Earth surfaces and atmospheres with thirteen oxygen absorption channels between 50 and 60 GHz at Quasihorizontal (QH) polarization, and the Earth Incidence Angle (EIA) ranges between 0° and 58.5°. FY-3D MWTS operationally provides global measurements which can be used to derive the vertical structure of atmospheric temperature from the Earth’s surface to a height of 1 hPa [1]. A classical two-point calibration system is set up on FY-3D MWTS, and it converts original counts into microwave radiance by nonlinearity calibration and antenna correction, in which the nonlinear parameters were measured by T/V (thermal-vacuum) testing before launch [2]. A comprehensive assessment of FY-3D MWTS’s in-orbit calibration is necessary before its data application in numerical weather prediction and many other applications, e.g., the atmospheric temperature retrieval

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