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Adjoint-Based Observation Impact of Advanced Microwave Sounding Unit-A (AMSU-A) on the Short-Range Forecast in East Asia

수반 모델에 기반한 관측영향 진단법을 이용하여 동아시아 지역의 단기예보에 AMSU-A 자료 동화가 미치는 영향 분석

  • Kim, Sung-Min (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Hyun Mee (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University)
  • 김성민 (연세대학교 대기과학과 대기예측성 및 자료동화연구실) ;
  • 김현미 (연세대학교 대기과학과 대기예측성 및 자료동화연구실)
  • Received : 2016.12.20
  • Accepted : 2017.03.15
  • Published : 2017.03.31

Abstract

The effect of Advanced Microwave Sounding Unit-A (AMSU-A) observations on the short-range forecast in East Asia (EA) was investigated for the Northern Hemispheric (NH) summer and winter months, using the Forecast Sensitivity to Observations (FSO) method. For both periods, the contribution of radiosonde (TEMP) to the EA forecast was largest, followed by AIRCRAFT, AMSU-A, Infrared Atmospheric Sounding Interferometer (IASI), and the atmospheric motion vector of Communication, Ocean and Meteorological Satellite (COMS) or Multi-functional Transport Satellite (MTSAT). The contribution of AMSU-A sensor was largely originated from the NOAA 19, NOAA 18, and MetOp-A (NOAA 19 and 18) satellites in the NH summer (winter). The contribution of AMSU-A sensor on the MetOp-A (NOAA 18 and 19) satellites was large at 00 and 12 UTC (06 and 18 UTC) analysis times, which was associated with the scanning track of four satellites. The MetOp-A provided the radiance data over the Korea Peninsula in the morning (08:00~11:30 LST), which was important to the morning forecast. In the NH summer, the channel 5 observations on MetOp-A, NOAA 18, 19 along the seaside (along the ridge of the subtropical high) increased (decreased) the forecast error slightly (largely). In the NH winter, the channel 8 observations on NOAA 18 (NOAA 15 and MetOp-A) over the Eastern China (Tibetan Plateau) decreased (increased) the forecast error. The FSO provides useful information on the effect of each AMSU-A sensor on the EA forecasts, which leads guidance to better use of AMSU-A observations for EA regional numerical weather prediction.

Keywords

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