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-μ1(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.
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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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Qi Li received a B.S. degree in meteorology from Nanjing University of Information Science and Technology, Nanjing, China in 2016, where she is currently working toward a Master’s degree in meteorology. Her research interests include satellite radiance data quality control and data assimilation.
Xiaolei Zou received her Ph.D degree from the Institute of Atmospheric Physics, Academia Sinica, Beijing, China in 1988.
She developed the National Meteorological Center (now the National Centers for Environmental Prediction) medium-range global forecast model 4D-Var system with full physics during 1989–1993, and the 5th generation Penn State/NCAR Mesoscale Model (MM5) 4D-Var system during 1993–1997. She has worked on GPS radio occultation data assimilation since 1993. From 1997–2014, she was a Professor in the Department of Earth, Ocean, and Atmospheric Science, Florida State University. Since Fall 2014, she has been working mainly on satellite data assimilation for quantitative precipitation forecasts and hurricane track and intensity forecasts at the Earth System Science Interdisciplinary Center, University of Maryland. She has published over 165 papers in peer-reviewed journals.
Dr. Zou was the recipient of the 2008 American Meteorological Society Fellow Award for her outstanding contributions to the applications of satellite data in numerical-weather-prediction models and to education in data assimilation.
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Li, Q., Zou, X. Bias characterization of ATMS low-level channels under clear-sky and cloudy conditions. Front. Earth Sci. 13, 277–289 (2019). https://doi.org/10.1007/s11707-019-0750-3
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DOI: https://doi.org/10.1007/s11707-019-0750-3