An assessment of the impact of ATMS and CrIS data assimilation on precipitation prediction over the Tibetan Plateau
An assessment of the impact of ATMS and CrIS data assimilation on precipitation prediction over the Tibetan Plateau
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ATMS和CrIS资料同化对青藏高原降水预测的影响评估
DOI：
10.5194/amt-10-2517-2017
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发表时间：
2016-12
影响因子：
3.8
通讯作者：
Min SHAO
中科院分区：
文献类型：
--
作者：
Tong XUE;Jianjun XU;Zhaoyong GUAN;Han-Ching CHEN;Long S. CHIU;Min SHAO
抽象的。利用国家海洋和大气管理局的GridPoint统计内插数据同化系统和国家大气研究中心的高级研究天气研究和预报(WRF-ARW)区域模式，评估了同化先进技术微波探测仪(ATMS)和跨轨红外探测仪(CRIS)卫星资料对2015年7月青藏高原降水预报的影响。设计了四个实验：一个对照实验和三个数据同化实验，注入了不同的数据集：仅有常规数据、常规数据和ATMS卫星数据的组合以及常规卫星数据和CRIS卫星数据的组合。结果表明，月平均降水量在模拟中向北移动，并表现出地形偏差，表现为高估山脉上风，低估雨带南部。虽然主要雨型得到了较好的模拟，但雨影对雨量预报的影响较大。对于累积日降水量的前24 h和后24 h，模型总体上高估了降水量，但在7月3-5日、13-16和22-25日的暴雨时段，模式低估了降水量。从青藏高原东南部观测到的水汽输送大于模式模拟的水汽输送，这导致了对7月3-5日暴雨的预报不准确。资料同化试验，特别是ATMS同化试验，比对照更接近暴雨过程的观测结果。总体而言，基于2015年7月的试验，卫星资料同化在一定程度上改进了对青藏高原降水型的预测，尽管没有资料同化的雨带模拟显示了区域移位。
Abstract. Using the National Oceanic and Atmospheric Administration's Gridpoint Statistical Interpolation data assimilation system and the National Center for Atmospheric Research's Advanced Research Weather Research and Forecasting (WRF-ARW) regional model, the impact of assimilating Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) satellite data on precipitation prediction over the Tibetan Plateau in July 2015 was evaluated. Four experiments were designed: a control experiment and three data assimilation experiments with different data sets injected: conventional data only, a combination of conventional and ATMS satellite data, and a combination of conventional and CrIS satellite data. The results showed that the monthly mean of precipitation is shifted northward in the simulations and showed an orographic bias described as an overestimation upwind of the mountains and an underestimation in the south of the rain belt. The rain shadow mainly influenced prediction of the quantity of precipitation, although the main rainfall pattern was well simulated. For the first 24 h and last 24 h of accumulated daily precipitation, the model generally overestimated the amount of precipitation, but it was underestimated in the heavy-rainfall periods of 3–5, 13–16, and 22–25 July. The observed water vapor conveyance from the southeastern Tibetan Plateau was larger than in the model simulations, which induced inaccuracies in the forecast of heavy rain on 3–5 July. The data assimilation experiments, particularly the ATMS assimilation, were closer to the observations for the heavy-rainfall process than the control. Overall, based on the experiments in July 2015, the satellite data assimilation improved to some extent the prediction of the precipitation pattern over the Tibetan Plateau, although the simulation of the rain belt without data assimilation shows the regional shifting.
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影响因子：
4.6
作者：
Romain Marteau;Y. Richard;B. Pohl;Carmela Chateau Smith;T. Castel
通讯作者：
Romain Marteau;Y. Richard;B. Pohl;Carmela Chateau Smith;T. Castel
影响因子：
3.2
作者：
X. Zou;Zhengkun Qin;F. Weng
通讯作者：
X. Zou;Zhengkun Qin;F. Weng
DOI：
--
发表时间：
2011
期刊：
--
影响因子：
--
作者：
Wu Ping
通讯作者：
Wu Ping
影响因子：
8.9
作者：
P. Chambon;Sara Q. Zhang;A. Hou;M. Zupanski;S. Cheung
通讯作者：
P. Chambon;Sara Q. Zhang;A. Hou;M. Zupanski;S. Cheung
DOI：
10.1002/2013jd020325
发表时间：
2013-12
期刊：
Journal of Geophysical Research: Atmospheres
影响因子：
--
作者：
N. Bormann;A. Fouilloux;W. Bell
通讯作者：
N. Bormann;A. Fouilloux;W. Bell