Land surface anomaly simulations and predictions with a climate model: an El Niño Southern Oscillation case study | Zendy

Debbie Putt | Zendy; Keith Haines | Zendy; R. J. Gurney | Zendy; Chunlei Liu | Zendy

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Land surface anomaly simulations and predictions with a climate model: an El Niño Southern Oscillation case study

Author(s) -

Debbie Putt,

Keith Haines,

R. J. Gurney,

Chunlei Liu

Publication year - 2008

Publication title -

philosophical transactions of the royal society a mathematical physical and engineering sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.074

H-Index - 169

eISSN - 1471-2962

pISSN - 1364-503X

DOI - 10.1098/rsta.2008.0182

Subject(s) - predictability , climatology , hadcm3 , anomaly (physics) , environmental science , data assimilation , climate model , snow , water content , atmosphere (unit) , atmospheric model , moisture , atmospheric sciences , climate change , meteorology , geology , general circulation model , gcm transcription factors , geography , oceanography , physics , geotechnical engineering , condensed matter physics , quantum mechanics

The ability of climate models to reproduce and predict land surface anomalies is an important but little-studied topic. In this study, an atmosphere and ocean assimilation scheme is used to determine whether HadCM3 can reproduce and predict snow water equivalent and soil moisture during the 1997-1998 El Niño Southern Oscillation event. Soil moisture is reproduced more successfully, though both snow and soil moisture show some predictability at 1- and 4-month lead times. This result suggests that land surface anomalies may be reasonably well initialized for climate model predictions and hydrological applications using atmospheric assimilation methods over a period of time.

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