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. 2023 Apr 27;4(3):134-145.
doi: 10.1002/pei3.10107. eCollection 2023 Jun.

Simulating the impact of varying vegetation on West African monsoon surface fluxes using a regional convection-permitting model

Adama Bamba  1   2   3 , Kouakou Kouadio  1   2 , N'Datchoh E Toure  1   2 , Lawrence Jackson  4 , John Marsham  4 , Alex Roberts  4 , Masaru Yoshioka  4 , Sandrine Anquetin  5 , Arona Diedhiou  2   3   5
Affiliations

Simulating the impact of varying vegetation on West African monsoon surface fluxes using a regional convection-permitting model

Adama Bamba et al. Plant Environ Interact. .

Abstract

This study assessed the sensitivity of the West African climate to varying vegetation fractions. The assessment of a such relationship is critical in understanding the interactions between land surface and atmosphere. Two sets of convection-permitting simulations from the UK Met Office Unified Model at 12 km horizontal resolution covering the monsoon period May-September (MJJAS) were used, one with fixed vegetation fraction (MF-V) and the other with time-varying vegetation fraction (MV-V). Vegetation fractions are based on MODIS retrievals between May and September. We focused on three climatic zones over West Africa: Guinea Coast, Sudanian Sahel, and the Sahel while investigating heat fluxes, temperature, and evapotranspiration. Results reveal that latent heat fluxes are the most strongly affected by vegetation fraction over the Sahelian and Sudanian regions while sensible heat fluxes are more impacted over the Guinea Coast and Sudanian Sahel. Also, in MV-V simulation there is an increase in evapotranspiration mainly over the Sahel and some specific areas in Guinea Coast from June to September. Moreover, it is noticed that high near-surface temperature is associated with a weak vegetation fraction, especially during May and June. Finally, varying vegetation seems to improve the simulation of surface energy fluxes and in turn impact on climate parameters. This suggests that climate modelers should prioritize the use of varying vegetation options to improve the representation of the West African climate system.

Keywords: convection‐permitting; evapotranspiration; heat fluxes; precipitation; seasonal vegetation.

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Conflict of interest statement

The authors declare they have no conflict of interest.

Figures

FIGURE 1
FIGURE 1
West Africa map showing the study area with the three selected climatic zones: Guinea Coast (GC), Sudanian zone (SD), and Sahel zone (SL). Vegetation fraction from MODIS observations is shown on a scale from 0 to 1.
FIGURE 2
FIGURE 2
Spatial distribution of monthly difference (MV‐V minus MF‐V) in vegetation fraction (a–e) and the vegetation fraction averaged over West Africa with the red dot line showing MJJAS mean vegetation fraction (f).
FIGURE 3
FIGURE 3
Monthly variation of the surface heat fluxes (latent and sensible heat) of fixed vegetation and variable vegetation experiment/simulation in w m−2 over (a) the Sahel, (b) Sudanian, and (c) Guinea coast.
FIGURE 4
FIGURE 4
Difference (%) in latent heat flux (a) and sensible heat flux (b) over Guinea Coast (GC), Sudanian (SD), and Sahel (SL) between the simulations using MV‐V and MF‐V.
FIGURE 5
FIGURE 5
Difference between the monthly mean diurnal cycles of the MV‐V and MF‐V simulations of surface LH flux (dashed lines) in w m−2 and surface SH flux (Solid lines) in w m−2 over Sahel (SL), Sudanian Sahel (SD), and Guinea Coast (GC) regions, for each month from May to September.
FIGURE 6
FIGURE 6
Monthly variation in temperature (in percentage) difference between MV‐V and MF‐V; and its latitudinal distribution averaged over longitudes 5W‐5E. GC, Guinea coast; SD, Sudanian; SL, Sahel.
FIGURE 7
FIGURE 7
Spatial distribution of variations in surface temperature over West Africa averaged from May to September; black dots represent the areas with significant variations at p‐value of 10%.
FIGURE 8
FIGURE 8
Spatial distribution of variations in evaporative fraction over West Africa averaged from May to September; black dots represent the areas with significant variations at p‐value of 10%.
See this image and copyright information in PMC

References

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