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

Toride, Kinya; Yoshimura, Kei; Tada, Masataka; Diekmann, Christopher; Ertl, Benjamin; Khosrawi, Farahnaz; Schneider, Matthias

Abstract:
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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Verlagsausgabe §
DOI: 10.5445/IR/1000130903
Veröffentlicht am 26.03.2021
Originalveröffentlichung
DOI: 10.1029/2020GL091698
Scopus
Zitationen: 1
Dimensions
Zitationen: 3
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Universität Karlsruhe (TH) – Interfakultative Einrichtungen (Interfakultative Einrichtungen)
KIT-Zentrum Klima und Umwelt (ZKU)
Steinbuch Centre for Computing (SCC)
Universität Karlsruhe (TH) – Zentrale Einrichtungen (Zentrale Einrichtungen)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 16.03.2021
Sprache Englisch
Identifikator ISSN: 0094-8276, 1944-8007
KITopen-ID: 1000130903
HGF-Programm 12.11.13 (POF IV, LK 01) Long-term trends of global atmospheric composition
Weitere HGF-Programme 46.21.01 (POF IV, LK 01) Domain-Specific Simulation & SDLs and Research Groups
Erschienen in Geophysical Research Letters
Verlag John Wiley and Sons
Band 48
Heft 5
Seiten Art.Nr.e2020GL091698
Vorab online veröffentlicht am 19.02.2021
Schlagwörter data assimilation; IASI; water isotope; weather forecasting
Nachgewiesen in Dimensions
Scopus
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