| Registro completo |
| Provedor de dados: |
OceanDocs
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| País: |
Belgium
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| Título: |
The Role of the Land Surface Background State in Climate Predictability
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| Autores: |
Dirmeyer, P.A.
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| Data: |
2005-07-26
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| Ano: |
2002
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| Palavras-chave: |
Atmosphere-ocean system
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| Resumo: |
Skill in ensemble-mean dynamical seasonal climate hindcasts with a coupled land-atmosphere model and specified observed sea surface temperature is compared to that for long multi-decade integrations of the same model where the initial conditions are far removed from the seasons of validation. The evaluations are performed for surface temperature and compared among all seasons. Skill is found to be higher in the seasonal simulations than the multi-decadal integrations except during boreal winter. The higher skill is prominent even beyond the first month when the direct influence of the atmospheric initial state elevates model skill. Skill is generally found to be lowest during the winter season for the dynamical seasonal forecasts, equal to that of the long integrations, which show some of the highest skill during winter. The reason for the differences in skill during the non-winter months is attributed to the severe climate drift in the long simulations, manifest through errors in downward fluxes of water and energy over land and evident in soil wetness. The drift presses the land surface to extreme dry or wet states over much of the globe, into a range where there is little sensitivity of evaporation to fluctuations in soil moisture. Thus, the land-atmosphere feedback is suppressed, which appears to lessen the model’s ability to respond correctly over land to remote ocean temperature anomalies.
Center for Ocean-Land-Atmosphere Studies
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| Tipo: |
Journal Contribution
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| Idioma: |
Inglês
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| Identificador: |
Journal of Hydrometeorology, 4(3), p. 599-610
1525-755X
http://hdl.handle.net/1834/500
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| Editor: |
American Meteorological Society
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| Relação: |
doi: 10.1175/1525-7541(2003)004<0599:TROTLS>2.0.CO;2
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| Formato: |
503454 bytes
application/pdf
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