Abstract
GeoNEX is a collaborative project led by scientists from NASA, NOAA, and many other institutes around the world to generate Earth monitoring products using data streams from the latest Geostationary (GEO) sensors including the GOES-16/17 Advanced Baseline Imager (ABI), the Himawari-8/9 Advanced Himawari Imager (AHI), and more. An accurate and consistent product of the Top-Of-Atmosphere (TOA) reflectance and brightness temperature is the starting point in the scientific processing pipeline and has significant influences on the downstream products. This paper describes the main steps and the algorithms in generating the GeoNEX TOA products, starting from the conversion of digital numbers to physical quantities with the latest radiometric calibration information. We implement algorithms to detect and remove residual georegistration uncertainties automatically in both GOES and Himawari L1bdata, adjust the data for topographic relief, estimate the pixelwise data-acquisition time, and accurately calculate the solar illumination angles for each pixel in the domain at every time step. Finally, we reproject the TOA products to a globally tiled common grid in geographic coordinates in order to facilitate intercomparisons and/or synergies between the GeoNEX products and existing Earth observation datasets from polar-orbiting satellites.
Highlights
Earth monitoring has improved dramatically over the past four decades
This paper focuses on the processing of the Level 1G (L1G) GeoNEX products, namely the Top-Of-Atmosphere (TOA) Bidirectional Reflectance Factor (BRF) and brightness temperature
We will leave the intercomparisons of BRFs between the GEO (e.g., Advanced Baseline Imager (ABI)/Advanced Himawari Imager (AHI)) and Low Earth Orbits (LEO) sensors (e.g., MODIS) for a separate paper [20]
Summary
Earth monitoring has improved dramatically over the past four decades. Advances in sensor technologies coupled with sophisticated algorithms allow routine retrievals of biophysical variables useful in long-term climate monitoring, as well as operational resource management [1,2]. A majority of Earth observation satellites are on Low Earth Orbits (LEO), especially polar orbits, Geostationary (GEO) satellites such as the European Meteosat Second Generation (MSG), carrying the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), has allowed us to monitor large parts of Africa and Europe in near real-time [3,4]. The European MeteoSat Third Generation (MTG) satellite, which is to be launched in the near future, will carry advanced instruments including the Flexible Combined Imager (FCI) [10]. Compared with their predecessors, this latest third-generation of geostationary sensors has significantly improved spectral, spatial, temporal, and radiometric resolutions, poised to make significant contributions to Earth monitoring
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