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Intraseasonal scale ensemble forecasts of precipitation and evapotranspiration for the Madeira River basin using different physical parameterizations.

Authors :
Gomes, Weslley de Brito
Satyamurty, Prakki
Correia, Francis Wagner Silva
Chou, Sin Chan
Vergasta, Leonardo Alves
de Arruda Lyra, André
Source :
Atmospheric Research. Jun2022, Vol. 270, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

Eta Regional Model of CPTEC-INPE is used to obtain intraseasonal (30-day) 8-member ensemble forecasts over the Madeira River basin for the period 2002–2012. The initial and boundary conditions are taken from Atmospheric General Circulation Global Model in six members and from Global Coupled Ocean-Atmosphere Model in two members. The intraseasonal forecasts produced by dynamic downscaling with Eta Regional model ensemble have satisfactory skill. The skill of the ensemble mean is better than the individual members up to 15-days lead time forecasts. The ensemble mean reproduces the seasonal cycle and spatial distribution of the hydrological variables. Members with the relaxation technique of Betts-Miller-Janjic produced better results. The forecasts by the members that used Kain-Fritsch scheme presented larger deviations from observations. Substantial improvements in skill are obtained through bias correction. This is the first work to attempt dynamic downscaling over the Madeira Basin in the intraseasonal time scale for a period of 10 years. The ensemble downscaled products have potential to be fed into surface hydrological models for forecasting droughts and floods and related hydrological variables over the basin. • RCM-Eta satisfactorily reproduces the seasonal variability of hydroclimatic variables. • The ocean-atmosphere coupled model is unable to improve the forecast quality. • Bias correction improves the intra-seasonal forecasts substantially. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01698095
Volume :
270
Database :
Academic Search Index
Journal :
Atmospheric Research
Publication Type :
Academic Journal
Accession number :
155653496
Full Text :
https://doi.org/10.1016/j.atmosres.2022.106086