A review of the remote sensing of lower tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles
-
- Yoshida Satoru
- Meteorological Research Institute
-
- Yokota Sho
- Meteorological Research Institute
-
- Seko Hiromu
- Meteorological Research Institute
-
- Sakai Tetsu
- Meteorological Research Institute
-
- Nagai Tomohiro
- Meteorological Research Institute
書誌事項
- タイトル別名
-
- Observation System Simulation Experiments of Water Vapor Profiles Observed by Raman Lidar Using LETKF System
説明
<p>We conducted observation system simulation experiments (OSSE) to investigate the effects of water vapor vertical profiles observed by Raman lidar (RL) on forecasts of heavy precipitation in Hiroshima, Japan, on August 19, 2014 using a local ensemble transform Kalman filter. We employed a simulation result similar to reality as nature-run (NR) and performed two OSSEs. In the first experiment (DaQv), conventional observation data and vertical profiles of water vapor mixing ratio in air (qv) estimated from NR were assimilated. In the second experiment (CNTL), only conventional observation data were assimilated. In DaQv, we assumed that the RL was in the low-level inflow that supplied water vapor to the heavy precipitation in Hiroshima. Assimilating qv for several hours increased qv around the RL observation station, especially at low level. The regions modified by the assimilation of qv moved to Hiroshima by low-level inflow, resulting in 9-hour precipitation being approximately 28% greater than that of CNTL, and was thus closer to that of the NR. The OSSEs suggest that water vapor RL observations on the windward side of the heavy precipitation are a useful approach for improving precipitation forecasts.</p>
収録刊行物
-
- SOLA
-
SOLA 16 (0), 43-50, 2020
公益社団法人 日本気象学会
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390290699451762944
-
- NII論文ID
- 130007797803
-
- ISSN
- 13496476
-
- 本文言語コード
- en
-
- 資料種別
- journal article
-
- データソース種別
-
- JaLC
- Crossref
- CiNii Articles
- KAKEN
-
- 抄録ライセンスフラグ
- 使用不可