A regional climate model simulation over West Africa: parameterization tests and analysis of land-surface fields View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2010-07

AUTHORS

M. Domínguez, M. A. Gaertner, P. de Rosnay, T. Losada

ABSTRACT

The West African Monsoon has been simulated with the regional climate model PROMES, coupled to the land-surface model ORCHIDEE and nested in ECMWF analysis, within AMMA-EU project. Three different runs are presented to address the influence of changes in two parameterizations (moist convection and radiation) on the simulated West African Monsoon. Another aim of the study is to get an insight into the relationship of simulated precipitation and 2-m temperature with land-surface fluxes. To this effect, data from the AMMA land-surface model intercomparison project (ALMIP) have been used. In ALMIP, offline simulations have been made using the same land-surface model than in the coupled simulation presented here, which makes ALMIP data particularly relevant for the present study, as it enables us to analyse the simulated soil and land-surface fields. The simulation of the monsoon depends clearly on the two analysed parameterizations. The inclusion of shallow convection parametrization affects the intensity of the simulated monsoon precipitation and modifies some dynamical aspects of the monsoon. The use of a fractional cloud-cover parameterization and a more complex radiation scheme is important for better reproducing the amplitude of the latitudinal displacement of the precipitation band. This is associated to an improved simulation of the surface temperature field and the easterly jets. However, the parameterization changes do not affect the timing of the main rainy and break periods of the monsoon. A better representation of downward solar radiation is associated with a smaller bias in the surface heat fluxes. The comparison with ALMIP land-surface and soil fields shows that precipitation and temperature biases in the regional climate model simulation are associated to certain biases in land-surface fluxes. The biases in soil moisture seem to be driven by atmospheric biases as they are strongly affected by the parameterization changes in atmospheric processes. More... »

PAGES

249-265

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00382-010-0769-3

DOI

http://dx.doi.org/10.1007/s00382-010-0769-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015183881


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47 schema:description The West African Monsoon has been simulated with the regional climate model PROMES, coupled to the land-surface model ORCHIDEE and nested in ECMWF analysis, within AMMA-EU project. Three different runs are presented to address the influence of changes in two parameterizations (moist convection and radiation) on the simulated West African Monsoon. Another aim of the study is to get an insight into the relationship of simulated precipitation and 2-m temperature with land-surface fluxes. To this effect, data from the AMMA land-surface model intercomparison project (ALMIP) have been used. In ALMIP, offline simulations have been made using the same land-surface model than in the coupled simulation presented here, which makes ALMIP data particularly relevant for the present study, as it enables us to analyse the simulated soil and land-surface fields. The simulation of the monsoon depends clearly on the two analysed parameterizations. The inclusion of shallow convection parametrization affects the intensity of the simulated monsoon precipitation and modifies some dynamical aspects of the monsoon. The use of a fractional cloud-cover parameterization and a more complex radiation scheme is important for better reproducing the amplitude of the latitudinal displacement of the precipitation band. This is associated to an improved simulation of the surface temperature field and the easterly jets. However, the parameterization changes do not affect the timing of the main rainy and break periods of the monsoon. A better representation of downward solar radiation is associated with a smaller bias in the surface heat fluxes. The comparison with ALMIP land-surface and soil fields shows that precipitation and temperature biases in the regional climate model simulation are associated to certain biases in land-surface fluxes. The biases in soil moisture seem to be driven by atmospheric biases as they are strongly affected by the parameterization changes in atmospheric processes.
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