Bias characterization of ATMS low-level channels under clear-sky and cloudy conditions

Qi LI, Xiaolei ZOU

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PDF(6831 KB)
Front. Earth Sci. ›› 2019, Vol. 13 ›› Issue (2) : 277-289. DOI: 10.1007/s11707-019-0750-3
RESEARCH ARTICLE
RESEARCH ARTICLE

Bias characterization of ATMS low-level channels under clear-sky and cloudy conditions

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Abstract

The Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-Orbiting Partnership satellite is a cross-track scanning instrument containing 22 sounding channels in total. In this study, the bias characteristics of channels 1–6, which could have significant cloud contamination in heavy precipitation, are first analyzed based on the differences between ATMS observations (O) and model simulations (B) under clear-sky conditions over oceans. Latitudinal dependencies of the biases of window channels 1–3 are greater than those of channels 4–6. Biases of all nadir-only observations examined in different latitudinal bands [μ1(ϕ)] are positive and no more than 7.0 K. Biases at higher latitudes are larger. Channels 1–5 have a generally symmetric scan bias pattern [μ2(α)]. The global distributions of brightness temperature differences after subtracting the biases, i.e., O-B-m1(ϕ)-μ2(α), for channels 3–6 spatially match the liquid water path distributions. Excluding ice-affected observations, channel 3–6 O-B differences systematically increase as the liquid water path increases under cloudy conditions. Further investigation is needed to apply these findings for ATMS data assimilation under both clear-sky and cloudy conditions.

Keywords

ATMS / O-B / clear-sky bias characteristics / impact of clouds on biases

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Qi LI, Xiaolei ZOU. Bias characterization of ATMS low-level channels under clear-sky and cloudy conditions. Front. Earth Sci., 2019, 13(2): 277‒289 https://doi.org/10.1007/s11707-019-0750-3

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Acknowledgements

The author was supported by the National Key R&D Program of China (No. 2018YFC1507302), and the Mathematical Theories and Methods of Data Assimilation supported by the National Natural Science Foundation of China (Grant No. 91730304).

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2019 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
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