Does More Accurate Land Cover Information Improve Earth System Models? An Example of the West African Monsoon.
Hartley, Andrew1; Parker, Douglas2; Garcia-Carreras, Luis2; Defourny, Pierre3; Brockmann, Carsten4; Bontemps, Sophie3
1Met Office Hadley Centre, UNITED KINGDOM; 2Leeds University, UNITED KINGDOM; 3Universite Catholique du Louvain, BELGIUM; 4Brockmann Consult, GERMANY
The land surface interacts with the atmosphere through the exchange of energy, water and minerals. These interactions often occur over relatively small areas and the strength of the relationship can vary according to the diurnal cycle. In some cases, such as during the West African monsoon, these small scale processes can have a large impact on the regional climatology. In West Africa, observational studies have shown that soil moisture conditions and vegetation type can affect the initiation and development of mesoscale convective systems, contributing up to 70% of total annual precipitation in parts of the Sahel. However, in this region, most General Circulation Models (GCMs) lack the spatial resolution, or process parameterisation, to simulate these processes well, and consequently climate change projections are highly uncertain. Here, we use a high resolution nested suite of the Met Office Unified Model to assess the effects of a new land cover dataset on local scale precipitation in West Africa. Two separate model experiments were run, firstly using plant functional types (PFTs) derived from the IGBP DISCOVER land cover dataset, and secondly using PFTs derived from the new ESA Land Cover Climate Change Initiative (LC_CCI). Both model simulations were nested at 60km, 24km and 4km spatial resolutions, with the 4km model allowing explicit convection. Results were analysed to show how different land cover datasets affect local and regional scale precipitation patterns.