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Comparing tropical precipitation simulated by the Met Office NWP and climate models with satellite observations

Liu, C., Allan, R. P. ORCID: https://orcid.org/0000-0003-0264-9447, Brooks, M. and Milton, S. (2014) Comparing tropical precipitation simulated by the Met Office NWP and climate models with satellite observations. Journal of Applied Meteorology and Climatology, 53 (1). pp. 200-214. ISSN 1558-8424

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To link to this item DOI: 10.1175/JAMC-D-13-082.1

Abstract/Summary

Forecasts of precipitation and water vapor made by the Met Office global numerical weather prediction (NWP) model are evaluated using products from satellite observations by the Special Sensor Microwave Imager/Sounder (SSMIS) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) for June–September 2011, with a focus on tropical areas (308S–308N). Consistent with previous studies, the predicted diurnal cycle of precipitation peaks too early (by ;3 h) and the amplitude is too strong over both tropical ocean and land regions. Most of the wet and dry precipitation biases, particularly those over land, can be explained by the diurnal-cycle discrepancies. An overall wet bias over the equatorial Pacific and Indian Oceans and a dry bias over the western Pacific warmpool and India are linked with similar biases in the climate model, which shares common parameterizations with the NWP version. Whereas precipitation biases develop within hours in the NWP model, underestimates in water vapor (which are assimilated by the NWP model) evolve over the first few days of the forecast. The NWP simulations are able to capture observed daily-to-intraseasonal variability in water vapor and precipitation, including fluctuations associated with tropical cyclones.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary Research Centres (IDRCs) > Walker Institute
Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:36247
Publisher:American Meteorological Society

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