Modeling Land–Atmosphere Interactions over Semiarid Plains in Morocco: In-Depth Assessment of GCM Stretched-Grid Simulations Using In Situ Data

Author:

Arjdal Khadija12ORCID,Vignon Étienne2,Driouech Fatima1,Chéruy Frédérique2,Er-Raki Salah34,Sima Adriana2,Chehbouni Abdelghani1,Drobinski Philippe2

Affiliation:

1. a International Water Research Institute, College for Sustainable Agriculture and Environmental Science, Mohammed VI Polytechnic University, Benguerir, Morocco

2. b Laboratoire de Météorologie Dynamique–IPSL, Sorbonne Université/CNRS/École Normale Supérieure–PSL Université/École Polytechnique–Institut Polytechnique de Paris, Paris, France

3. c Center for Remote Sensing Applications, College for Sustainable Agriculture and Environmental Science, Mohammed VI Polytechnic University, Benguerir, Morocco

4. d Laboratoire des Procédés pour l’Energie Durable et l’Environnement/AgroBiotech Center, Département de Physique Appliquée, Faculté des Sciences et Techniques, Université Cadi Ayyad, Marrakech, Morocco

Abstract

Abstract Land surface–atmosphere interactions are a key component of climate modeling. They are particularly critical to understand and anticipate the climate and the water resources over the semiarid and arid North African regions. This study uses in situ observations to assess the ability of the IPSL-CM global climate model to simulate the land–atmosphere interactions over the Moroccan semiarid plains. A specific configuration with a grid refinement over the Haouz Plain, near Marrakech, and nudging outside Morocco has been performed to properly assess the model’s performances. To ensure reliable model–observation comparisons despite the fact that station measurements are not representative of a mesh-size area, we carried out experiments with adapted vegetation properties. Results show that the CMIP6 version of the model’s physics represents the near-surface climate over the Haouz Plain reasonably well. Nonetheless, the simulation exhibits a nocturnal warm bias, and the wind speed is overestimated in tree-covered meshes and underestimated in the wheat-covered region. Further sensitivity experiments reveal that LAI-dependent parameterization of roughness length leads to a strong surface wind drag and to underestimated land surface atmosphere thermal coupling. Setting the roughness heights to the observed values improves the wind speed and, to a lesser extent, the nocturnal temperature. A low bias in latent heat flux and soil moisture coinciding with a pronounced diurnal warm bias at the surface is still present in our simulations. Including a first-order irrigation parameterization yields more realistic simulated evapotranspiration flux and daytime skin surface temperatures. This result raises the importance of accounting for the irrigation process in present and future climate simulations over Moroccan agricultural areas.

Funder

Laboratoire de Météorologie Dynamique

Publisher

American Meteorological Society

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