Potential of Mid-tropospheric Water Vapor Isotopes to Improve Large-Scale Circulation and Weather Predictability

被引:10
作者
Toride, Kinya [1 ,2 ]
Yoshimura, Kei [1 ,3 ]
Tada, Masataka [4 ]
Diekmann, Christopher [5 ]
Ertl, Benjamin [5 ,6 ]
Khosrawi, Farahnaz [5 ]
Schneider, Matthias [5 ]
机构
[1] Univ Tokyo, Inst Ind Sci, Chiba, Japan
[2] Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA
[3] Japan Aerospac Explorat Agcy, Earth Observat Res Ctr, Tokyo, Japan
[4] Japan Weather Assoc, Tokyo, Japan
[5] Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Karlsruhe, Germany
[6] Karlsruhe Inst Technol, Steinbuch Ctr Comp, Karlsruhe, Germany
关键词
data assimilation; IASI; water isotope; weather forecasting; ENSEMBLE DATA ASSIMILATION; KALMAN FILTER; MOISTURE; MODEL; CONVECTION;
D O I
10.1029/2020GL091698
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Recent satellite techniques have uncovered detailed tropospheric water vapor isotope patterns on a daily basis, yet the significance of water isotopes on weather forecasting has remained largely unknown. Here, we perform a proof-of-concept observing system simulation experiment to show that mid-tropospheric water isotopes observed by the Infrared Atmospheric Sounding Interferometer (IASI) can substantially improve weather forecasts through non-local impacts on the convective heating structure and large-scale circulation. Assimilating IASI isotopes can improve wind, humidity, and temperature fields by more than 10% at mid-troposphere compared to only assimilating conventional non-isotopic observations. These improvements are about two-thirds of assimilating simultaneous IASI water vapor observations. The improvements can be attributed more to thermodynamic (phase change) effects than dynamic (transport) effects of water isotopes. Furthermore, isotopic observations produce additional 3%-4% improvements to the fields constrained by the conventional observations and simultaneous IASI water vapor observations, demonstrating the unique characteristics of water isotopes.
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页数:10
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