Abstract

To understand surface energy exchange processes over the semiarid regions in West Africa, numerical simulations of surface energy and water balances were carried out using a one-dimensional multilayer atmosphere-SOil-VEGetation (SOLVEG) model for selected days of the dry and rainy seasons over a savanna grassland ecosystem in Sumbrungu in the Upper East region of Ghana. The measured Bowen ratio was used to partition the residual energy into the observed sensible heat flux (H) and latent heat flux (LE) in order to investigate the impact of the surface energy closure on model performance. The results showed that the model overall reproduced the diurnal changes in the observed energy fluxes, especially the net radiation (Rn), compared to half-hourly eddy covariance flux measurements, for the study periods. The performance measure in terms of the correlation coefficient (R), centred root mean square error (RMSE), and normalized standard deviation (σ) between the simulated H and LE and their corresponding uncorrected observed values ranged between R = 0.63–0.99 and 0.83–0.94, RMSE = 0.88–1.25 and 0.88–1.92, and σ = 0.95–2.23 and 0.13–2.82 for the dry and rainy periods respectively, indicating a moderate to good model performance. The partitioning of H and LE by SOLVEG was generally in agreement with the observations during the dry period but showed clear discrepancies during the rainy period, particularly after rainfall events. Further sensitivity tests over longer simulation periods (e.g., 1 year) are required to improve model performance and to investigate seasonal exchanges of surface energy fluxes over the West African Savanna ecosystems in more details.

Highlights

  • Land surface models (LSMs) have a role in partitioning the energy influx of net radiation into sensible and latent heat fluxes in atmospheric models [1]

  • The results revealed that the model was able to simulate the surface energy fluxes such as net radiation, sensible heat flux, and latent heat flux during the wet period

  • The results show that best matches of the simulated and observed variables are obtained for Rn during the period

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Summary

Introduction

Land surface models (LSMs) have a role in partitioning the energy influx of net radiation into sensible and latent heat fluxes in atmospheric models [1]. Since these partitioned energy fluxes influence the development of the boundary layer, cloud formation, weather, and climate [2], their accurate representation in LSMs is required for weather and climate simulations [3, 4]. It was not sensitive to the changes in the roughness length for momentum on both seasonal and daily bases This fact was attributed to the coefficient that related transpiration and evaporation to the atmosphere [7, 8]

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