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Seasonal variation of surface energy balance over two Sahelian surfaces

โœ Scribed by Verhoef, A.; Allen, S.J.; Lloyd, C.R.


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
147 KB
Volume
19
Category
Article
ISSN
0899-8418

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โœฆ Synopsis


The seasonal variation of the surface energy balance (SEB) (net radiation, soil heat flux, and sensible and latent heat fluxes) for a savanna and an open natural forest (tiger-bush) located in the Sahel is presented. Daily averages of these four fluxes were obtained using standard micrometeorological instruments/methods (radiometry, soil heat flux plates and the eddy correlation technique). Because sensible and latent heat flux data were not available during the dry season (and occasionally missing during the wet season), estimates from a simple linear equation, which relates sensible heat flux to the difference between surface and air temperature, were used instead. This produced a practically continuous time series of the surface energy balance for a period of over 1 year. Net radiation over both surfaces appeared to be very similar, varying roughly between 75 W m -2 (dry winter months) and 175 W m -2 (wet summer months) on a daily basis. During the winter months, soil heat flux had maximum values of about -8 W m -2 , while maximum values during the summer were approximately +8 W m -2 . Sensible heat flux varied between approximately 20 W m -2 (wet season) and 100 W m -2 (end of dry season) with generally slightly higher values for the savanna than for the tiger-bush, especially during the dry autumn and winter months. During the wet season, evaporation reached values of 100-150 W m -2 . Both surfaces were predicted to exhibit some evaporation during the dry season; approximately 5-10 W m -2 for the savanna and approximately 20 W m -2 for the tiger-bush. The course of these fluxes is supported by secondary observations such as rooting depth and greenness of the vegetation, indicating that this method may be a useful tool if gaps in long-term time series exist. The information presented will be useful as verification data for climate modelling and can be used as ground truth data for remote sensing.


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