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Korean Meteorological Society (한국기상학회)
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Assimilation of Satellite-Based Soil Moisture (SMAP) in KMA GloSea6: The Results of the First Preliminary Experiment

기상청 GloSea의 위성관측 기반 토양수분(SMAP) 동화: 예비 실험 분석

  • Ji, Hee-Sook (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Hwang, Seung-On (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Lee, Johan (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Hyun, Yu-Kyung (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Ryu, Young (Forecast and Control Division, Yeongsan River Flood Control Office) ;
  • Boo, Kyung-On (Climate Research Division, National Institute of Meteorological Sciences)
  • 지희숙 (국립기상과학원 기후연구부) ;
  • 황승언 (국립기상과학원 기후연구부) ;
  • 이조한 (국립기상과학원 기후연구부) ;
  • 현유경 (국립기상과학원 기후연구부) ;
  • 류영 (환경부 영산강홍수통제소 예보통제과) ;
  • 부경온 (국립기상과학원 기후연구부)
  • Received : 2022.10.08
  • Accepted : 2022.10.28
  • Published : 2022.12.31
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Abstract

A new soil moisture initialization scheme is applied to the Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6). It is designed to ingest the microwave soil moisture retrievals from Soil Moisture Active Passive (SMAP) radiometer using the Local Ensemble Transform Kalman Filter (LETKF). In this technical note, we describe the procedure of the newly-adopted initialization scheme, the change of soil moisture states by assimilation, and the forecast skill differences for the surface temperature and precipitation by GloSea6 simulation from two preliminary experiments. Based on a 4-year analysis experiment, the soil moisture from the land-surface model of current operational GloSea6 is found to be drier generally comparing to SMAP observation. LETKF data assimilation shows a tendency toward being wet globally, especially in arid area such as deserts and Tibetan Plateau. Also, it increases soil moisture analysis increments in most soil levels of wetness in land than current operation. The other experiment of GloSea6 forecast with application of the new initialization system for the heat wave case in 2020 summer shows that the memory of soil moisture anomalies obtained by the new initialization system is persistent throughout the entire forecast period of three months. However, averaged forecast improvements are not substantial and mixed over Eurasia during the period of forecast: forecast skill for the precipitation improved slightly but for the surface air temperature rather degraded. Our preliminary results suggest that additional elaborate developments in the soil moisture initialization are still required to improve overall forecast skills.

Keywords

Acknowledgement

본 연구를 위해 자료동화시스템을 제공해주신 울산과학기술대학교 도시환경공학과 이명인 교수 연구팀과 서은교 박사님께 감사드립니다. 이 연구는 기상청 국립기상과학원 「기후예측 현업시스템 개발」(KMA2018-00322)의 지원으로 수행되었습니다.

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