[A-CG36] Satellite Earth Environment Observation

[ACG36-P14] CloudSat/CPR and CALIPSO/CALIOP observations of a precipitation area formed on the Antarctic ice sheet on January 17, 2015 associated with a synoptic-scale disturbance

*Naohiko Hirasawa^1,2, Kyohei Yamada³, Masanori Yabuki⁴ (1.National Institute of Polar Research, 2.Graduate University for Advanced Studies (SOKENDAI), 3.National Institute for Environmental Studies, 4.Kyoto University)

Keywords:Antarctica, Precipitation, Satellite observation, Numerical modeling

Satellite observations are effective for understanding precipitation over a wide area in the Antarctic region. Cloud detection by passive sensors, which observe natural radiation from the earth's surface, can provide the horizontal scale and distribution of precipitation systems all around. Active sensors using radar and lidar can provide vertical distributions of clouds and precipitation particles and estimate their amounts, albeit over a limited area along satellite orbits (e.g., Palerme et al., 2014, Listowski et al., 2019). However, satellite data have various limitations and cannot capture the full range of precipitation phenomena. The purpose of this study is to gain insight into Antarctic precipitation through ground-based observations, numerical modeling, climate reanalysis data, and satellite data. In this presentation, we show the characteristics of the precipitation observed by CloudSat/CPR and CALIPSO/CALIOP for one case in which the precipitation area expanded from the Antarctic coastal region to the Antarctic inland region from time to time in association with an enhanced synoptic-scale disturbance (Yamada and Hirasawa, 2018). We will also discuss the limitations of each sensor's precipitation observation in the Antarctic region based on this case. This study was supported by the Japanese Antarctic Research Expedition (JARE) program and JAXA-EORA3.

1. Palerme, C. et al., 2014, The Cryos., 8(4), 1577–1587. https://doi.org/10.5194/tc-8-1577-2014
2. Listowski, C. et al., 2019, ACP, 19(10), 6771–6808. https://doi.org/10.5194/acp-19-6771-2019
3. Yamada, K. and N. Hirasawa, 2018, JGR: Atmos., 123(24), 13,643-13,657. https://doi.org/10.1029/2018JD028877