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

Khadija Arjdal aInternational Water Research Institute, College for Sustainable Agriculture and Environmental Science, Mohammed VI Polytechnic University, Benguerir, Morocco
bLaboratoire de Météorologie Dynamique–IPSL, Sorbonne Université/CNRS/École Normale Supérieure–PSL Université/École Polytechnique–Institut Polytechnique de Paris, Paris, France

Search for other papers by Khadija Arjdal in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0002-2790-3790
,
Étienne Vignon bLaboratoire de Météorologie Dynamique–IPSL, Sorbonne Université/CNRS/École Normale Supérieure–PSL Université/École Polytechnique–Institut Polytechnique de Paris, Paris, France

Search for other papers by Étienne Vignon in
Current site
Google Scholar
PubMed
Close
,
Fatima Driouech aInternational Water Research Institute, College for Sustainable Agriculture and Environmental Science, Mohammed VI Polytechnic University, Benguerir, Morocco

Search for other papers by Fatima Driouech in
Current site
Google Scholar
PubMed
Close
,
Frédérique Chéruy bLaboratoire de Météorologie Dynamique–IPSL, Sorbonne Université/CNRS/École Normale Supérieure–PSL Université/École Polytechnique–Institut Polytechnique de Paris, Paris, France

Search for other papers by Frédérique Chéruy in
Current site
Google Scholar
PubMed
Close
,
Salah Er-Raki cCenter for Remote Sensing Applications, College for Sustainable Agriculture and Environmental Science, Mohammed VI Polytechnic University, Benguerir, Morocco
dLaboratoire 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

Search for other papers by Salah Er-Raki in
Current site
Google Scholar
PubMed
Close
,
Adriana Sima bLaboratoire de Météorologie Dynamique–IPSL, Sorbonne Université/CNRS/École Normale Supérieure–PSL Université/École Polytechnique–Institut Polytechnique de Paris, Paris, France

Search for other papers by Adriana Sima in
Current site
Google Scholar
PubMed
Close
,
Abdelghani Chehbouni aInternational Water Research Institute, College for Sustainable Agriculture and Environmental Science, Mohammed VI Polytechnic University, Benguerir, Morocco

Search for other papers by Abdelghani Chehbouni in
Current site
Google Scholar
PubMed
Close
, and
Philippe Drobinski bLaboratoire de Météorologie Dynamique–IPSL, Sorbonne Université/CNRS/École Normale Supérieure–PSL Université/École Polytechnique–Institut Polytechnique de Paris, Paris, France

Search for other papers by Philippe Drobinski in
Current site
Google Scholar
PubMed
Close
Restricted access

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.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Khadija Arjdal, khadija.arjdal@um6p.ma

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.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Khadija Arjdal, khadija.arjdal@um6p.ma

Supplementary Materials

    • Supplemental Materials (PDF 1.1306 MB)
Save
  • Ait El Mekki, O., and N.-E. Laftouhi, 2016: Combination of a geographical information system and remote sensing data to map groundwater recharge potential in arid to semi-arid areas: The Haouz Plain, Morocco. Earth Sci. Inf., 9, 465479, https://doi.org/10.1007/s12145-016-0268-0.

    • Search Google Scholar
    • Export Citation
  • Aït‐Mesbah, S., J. L. Dufresne, F. Cheruy, and F. Hourdin, 2015: The role of thermal inertia in the representation of mean and diurnal range of surface temperature in semiarid and arid regions. Geophys. Res. Lett., 42, 75727580, https://doi.org/10.1002/2015GL065553.

    • Search Google Scholar
    • Export Citation
  • Ali, E., W. Cramer, J. Carnicer, E. Georgopoulou, N. J. M. Hilmi, G. Le Cozannet, and P. Lionello, 2022: Mediterranean region. Climate Change 2022: Impacts, Adaptation and Vulnerability, H.-O. Pörtner et al., Eds., Cambridge University Press, 2233–2272, https://doi.org/10.1017/9781009325844.021.

  • Arboleda-Obando, P. F., A. Ducharne, Z. Yin, and P. Ciais, 2024: Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2. Geosci. Model Dev., https://doi.org/10.5194/egusphere-2023-1323, in press.

    • Search Google Scholar
    • Export Citation
  • Arjdal, K., F. Driouech, É. Vignon, F. Chéruy, R. Manzanas, P. Drobinski, A. Chehbouni, and A. Idelkadi, 2023: Future of land surface water availability over the Mediterranean basin and North Africa: Analysis and synthesis from the CMIP6 exercise. Atmos. Sci. Lett., 24, e1180, https://doi.org/10.1002/asl.1180.

    • Search Google Scholar
    • Export Citation
  • Balhane, S., F. Driouech, O. Chafki, R. Manzanas, A. Chehbouni, and W. Moufouma-Okia, 2022: Changes in mean and extreme temperature and precipitation events from different weighted multi-model ensembles over the northern half of Morocco. Climate Dyn., 58, 389404, https://doi.org/10.1007/s00382-021-05910-w.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., 2007: Coupling of water vapor convergence, clouds, precipitation, and land-surface processes. J. Geophys. Res., 112, D10108, https://doi.org/10.1029/2006JD008191.

    • Search Google Scholar
    • Export Citation
  • Born, K., A. H. Fink, and H. Paeth, 2008: Dry and wet periods in the northwestern Maghreb for present day and future climate conditions. Meteor. Z., 17, 533551, https://doi.org/10.1127/0941-2948/2008/0313.

    • Search Google Scholar
    • Export Citation
  • Born, K., A. H. Fink, and P. Knippertz, 2010: Meteorological processes influencing the weather and climate of Morocco. Impacts of Global Change on the Hydrological Cycle in West and Northwest Africa, P. Seth, M. Christoph, and B. Diekkrüger, Eds., Springer, 150–163.

  • Botta, A., N. Viovy, P. Ciais, P. Friedlingstein, and P. Monfray, 2000: A global prognostic scheme of leaf onset using satellite data. Global Change Biol., 6, 709725, https://doi.org/10.1046/j.1365-2486.2000.00362.x.

    • Search Google Scholar
    • Export Citation
  • Boucher, O., and Coauthors, 2020: Presentation and evaluation of the IPSL-CM6A-LR climate model. J. Adv. Model. Earth Syst., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010.

    • Search Google Scholar
    • Export Citation
  • Cavicchia, L., and Coauthors, 2018: Mediterranean extreme precipitation: A multi-model assessment. Climate Dyn., 51, 901913, https://doi.org/10.1007/s00382-016-3245-x.

    • Search Google Scholar
    • Export Citation
  • Chehbouni, A., and Coauthors, 2008: An integrated modelling and remote sensing approach for hydrological study in arid and semi‐arid regions: The SUDMED Programme. Int. J. Remote Sens., 29, 51615181, https://doi.org/10.1080/01431160802036417.

    • Search Google Scholar
    • Export Citation
  • Cherif, S., and Coauthors, 2020: Drivers of change. Climate and Environmental Change in the Mediterranean Basin—Current Situation and Risks for the Future: First Mediterranean Assessment Report, W. Cramer, J. Guiot, and K. Marini, Eds., Union for the Mediterranean, Plan Bleu, UNEP/MAP, 59–180.

  • Cheruy, F., A. Campoy, J.-C. Dupont, A. Ducharne, F. Hourdin, M. Haeffelin, M. Chiriaco, and A. Idelkadi, 2013: Combined influence of atmospheric physics and soil hydrology on the simulated meteorology at the SIRTA atmospheric observatory. Climate Dyn., 40, 22512269, https://doi.org/10.1007/s00382-012-1469-y.

    • Search Google Scholar
    • Export Citation
  • Cheruy, F., J. L. Dufresne, S. Aït Mesbah, J. Y. Grandpeix, and F. Wang, 2017: Role of soil thermal inertia in surface temperature and soil moisture-temperature feedback. J. Adv. Model. Earth Syst., 9, 29062919, https://doi.org/10.1002/2017MS001036.

    • Search Google Scholar
    • Export Citation
  • Cheruy, F., and Coauthors, 2020: Improved near‐surface continental climate in IPSL‐CM6A‐LR by combined evolutions of atmospheric and land surface physics. J. Adv. Model. Earth Syst., 12, e2019MS002005, https://doi.org/10.1029/2019MS002005.

    • Search Google Scholar
    • Export Citation
  • Coindreau, O., F. Hourdin, M. Haeffelin, A. Mathieu, and C. Rio, 2007: Assessment of physical parameterizations using a global climate model with stretchable grid and nudging. Mon. Wea. Rev., 135, 14741489, https://doi.org/10.1175/MWR3338.1.

    • Search Google Scholar
    • Export Citation
  • Cornes, R. C., G. van der Schrier, E. J. M. van den Besselaar, and P. D. Jones, 2018: An ensemble version of the E-OBS temperature and precipitation data sets. J. Geophys. Res. Atmos., 123, 93919409, https://doi.org/10.1029/2017JD028200.

    • Search Google Scholar
    • Export Citation
  • de Rosnay, P., 2003: Integrated parameterization of irrigation in the land surface model ORCHIDEE. Validation over Indian Peninsula. Geophys. Res. Lett., 30, 1986, https://doi.org/10.1029/2003GL018024.

    • Search Google Scholar
    • Export Citation
  • Diallo, F. B., F. Hourdin, C. Rio, A.-K. Traore, L. Mellul, F. Guichard, and L. Kergoat, 2017: The surface energy budget computed at the grid-scale of a climate model challenged by station data in West Africa. J. Adv. Model. Earth Syst., 9, 27102738, https://doi.org/10.1002/2017MS001081.

    • Search Google Scholar
    • Export Citation
  • Diffenbaugh, N. S., and F. Giorgi, 2012: Climate change hotspots in the CMIP5 global climate model ensemble. Climatic Change, 114, 813822, https://doi.org/10.1007/s10584-012-0570-x.

    • Search Google Scholar
    • Export Citation
  • Douville, H., and Coauthors, 2021: Water cycle changes. Climate Change 2021: The Physical Science Basis, V. Masson-Delmotte et al., Eds., Cambridge University Press, 1055–1210, https://doi.org/10.1017/9781009157896.010.

  • Driouech, F., 2010: Distribution des précipitations hivernales sur le Maroc dans le cadre d’un changement climatique: Descente d’échelle et incertitudes. Ph.D. thesis, Université de Toulouse, Institut National Polytechnique de Toulouse, 164 pp.

  • Driouech, F., M. Déqué, and A. Mokssit, 2009: Numerical simulation of the probability distribution function of precipitation over Morocco. Climate Dyn., 32, 10551063, https://doi.org/10.1007/s00382-008-0430-6.

    • Search Google Scholar
    • Export Citation
  • Driouech, F., K. ElRhaz, W. Moufouma-Okia, K. Arjdal, and S. Balhane, 2020: Assessing future changes of climate extreme events in the CORDEX-MENA region using regional climate model ALADIN-climate. Earth Syst. Environ., 4, 477492, https://doi.org/10.1007/s41748-020-00169-3.

    • Search Google Scholar
    • Export Citation
  • Drobinski, P., and Coauthors, 2018: Scaling precipitation extremes with temperature in the Mediterranean: Past climate assessment and projection in anthropogenic scenarios. Climate Dyn., 51, 12371257, https://doi.org/10.1007/s00382-016-3083-x.

    • Search Google Scholar
    • Export Citation
  • Drobinski, P., N. Da Silva, S. Bastin, S. Mailler, C. Muller, B. Ahrens, O. B. Christensen, and P. Lionello, 2020: How warmer and drier will the Mediterranean region be at the end of the twenty-first century? Reg. Environ. Change, 20, 78, https://doi.org/10.1007/s10113-020-01659-w.

    • Search Google Scholar
    • Export Citation
  • Ducoudré, N. I., K. Laval, and A. Perrier, 1993: SECHIBA, a new set of parameterizations of the hydrologic exchanges at the land–atmosphere interface within the LMD atmospheric general circulation model. J. Climate, 6, 248273, https://doi.org/10.1175/1520-0442(1993)006<0248:SANSOP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Er-Raki, S., A. Chehbouni, N. Guemouria, B. Duchemin, J. Ezzahar, and R. Hadria, 2007: Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region. Agric. Water Manage., 87, 4154, https://doi.org/10.1016/j.agwat.2006.02.004.

    • Search Google Scholar
    • Export Citation
  • Er-Raki, S., A. Chehbouni, S. Khabba, V. Simonneaux, L. Jarlan, A. Ouldbba, J. C. Rodriguez, and R. Allen, 2010: Assessment of reference evapotranspiration methods in semi-arid regions: Can weather forecast data be used as alternate of ground meteorological parameters? J. Arid Environ., 74, 15871596, https://doi.org/10.1016/j.jaridenv.2010.07.002.

    • Search Google Scholar
    • Export Citation
  • Ezzahar, J., A. Chehbouni, J. C. B. Hoedjes, S. Er-Raki, A. Chehbouni, G. Boulet, J.-M. Bonnefond, and H. A. R. De Bruin, 2007: The use of the scintillation technique for monitoring seasonal water consumption of olive orchards in a semi-arid region. Agric. Water Manage., 89, 173184, https://doi.org/10.1016/j.agwat.2006.12.015.

    • Search Google Scholar
    • Export Citation
  • Fesquet, C., P. Drobinski, C. Barthlott, and T. Dubos, 2009: Impact of terrain heterogeneity on near-surface turbulence structure. Atmos. Res., 94, 254269, https://doi.org/10.1016/j.atmosres.2009.06.003.

    • Search Google Scholar
    • Export Citation
  • Fink, A. H., M. Christoph, K. Born, T. Brücher, K. Piecha, S. Phole, O. Schulz, and V. Ermert, 2010: Climate. Impacts of Global Change on the Hydrological Cycle in West and Northwest Africa, P. Speth, M. Christoph, and B. Diekkrüger, Eds., Springer, 54–58.

  • Foken, T., 2008: Micrometeorology. 2nd ed. Springer, 308 pp.

  • Garratt, J. R., and B. B. Hicks, 1973: Momentum, heat and water vapour transfer to and from natural and artificial surfaces. Quart. J. Roy. Meteor. Soc., 99, 680687, https://doi.org/10.1002/qj.49709942209.

    • Search Google Scholar
    • Export Citation
  • Gutiérrez, J. M., and Coauthors, 2021: Atlas. Climate Change 2021: The Physical Science Basis, V. Masson-Delmotte et al., Eds., Cambridge University Press, 1927–2058, https://doi.org/10.1017/9781009157896.021.

  • Harbouze, R., J.-P. Pellissier, J.-P. Rolland, and W. Khechimi, 2019: Rapport de synthèse sur l’agriculture au Maroc (Recherche). CIHEAM-IAMM, 104 pp., https://hal.science/hal-02137637/document.

  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

    • Search Google Scholar
    • Export Citation
  • Hourdin, F., F. Couvreux, and L. Menut, 2002: Parameterization of the dry convective boundary layer based on a mass flux representation of thermals. J. Atmos. Sci., 59, 11051123, https://doi.org/10.1175/1520-0469(2002)059<1105:POTDCB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2013: Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model. Climate Dyn., 40, 21672192, https://doi.org/10.1007/s00382-012-1411-3.

    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2015: Parameterization of convective transport in the boundary layer and its impact on the representation of the diurnal cycle of wind and dust emissions. Atmos. Chem. Phys., 15, 67756788, https://doi.org/10.5194/acp-15-6775-2015.

    • Search Google Scholar
    • Export Citation
  • Hourdin, F., A. Jam, C. Rio, F. Couvreux, I. Sandu, M. Lefebvre, F. Brient, and A. Idelkadi, 2019: Unified parameterization of convective boundary layer transport and clouds with the thermal plume model. J. Adv. Model. Earth Syst., 11, 29102933, https://doi.org/10.1029/2019MS001666.

    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2020: LMDZ6A: The atmospheric component of the IPSL climate model with improved and better tuned physics. J. Adv. Model. Earth Syst., 12, e2019MS001892, https://doi.org/10.1029/2019MS001892.

    • Search Google Scholar
    • Export Citation
  • Jam, A., F. Hourdin, C. Rio, and F. Couvreux, 2013: Resolved versus parametrized boundary-layer plumes. Part III: Derivation of a statistical scheme for cumulus clouds. Bound.-Layer Meteor., 147, 421441, https://doi.org/10.1007/s10546-012-9789-3.

    • Search Google Scholar
    • Export Citation
  • Khabba, S., and Coauthors, 2013: The SudMed Program and the Joint International Laboratory TREMA: A decade of water transfer study in the soil-plant-atmosphere system over irrigated crops in semi-arid area. Procedia Environ. Sci., 19, 524533, https://doi.org/10.1016/j.proenv.2013.06.059.

    • Search Google Scholar
    • Export Citation
  • Kharrou, M. H., S. Er-Raki, A. Chehbouni, B. Duchemin, V. Simonneaux, M. LePage, L. Ouzine, and L. Jarlan, 2011: Water use efficiency and yield of winter wheat under different irrigation regimes in a semi-arid region. Agric. Sci., 2, 273282, https://doi.org/10.4236/as.2011.23036.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Realistic initialization of land surface states: Impacts on subseasonal forecast skill. J. Hydrometeor., 5, 10491063, https://doi.org/10.1175/JHM-387.1.

    • Search Google Scholar
    • Export Citation
  • Lurton, T., and Coauthors, 2020: Implementation of the CMIP6 forcing data in the IPSL‐CM6A‐LR model. J. Adv. Model. Earth Syst., 12, e2019MS001940, https://doi.org/10.1029/2019MS001940.

    • Search Google Scholar
    • Export Citation
  • Marchane, A., Y. Tramblay, L. Hanich, D. Ruelland, and L. Jarlan, 2017: Climate change impacts on surface water resources in the Rheraya catchment (High Atlas, Morocco). Hydrol. Sci. J., 62, 979995, https://doi.org/10.1080/02626667.2017.1283042.

    • Search Google Scholar
    • Export Citation
  • Massman, W. J., 1999: A model study of kBH−1 for vegetated surfaces using ‘localized near-field’ Lagrangian theory. J. Hydrol., 223, 2743, https://doi.org/10.1016/S0022-1694(99)00104-3.

    • Search Google Scholar
    • Export Citation
  • Meddi, M. M., A. A. Assani, and H. Meddi, 2010: Temporal variability of annual rainfall in the Macta and Tafna catchments, northwestern Algeria. Water Resour. Manage., 24, 38173833, https://doi.org/10.1007/s11269-010-9635-7.

    • Search Google Scholar
    • Export Citation
  • Mizuochi, H., and Coauthors, 2021: Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model. Hydrol. Earth Syst. Sci., 25, 21992221, https://doi.org/10.5194/hess-25-2199-2021.

    • Search Google Scholar
    • Export Citation
  • Monin, A., and A. Obukhov, 1954: Basic laws of turbulent mixing in the atmosphere near the ground. Tr. Akad. Nauk SSSR Geophiz. Inst., 151, 163187.

    • Search Google Scholar
    • Export Citation
  • Nassah, H., S. Er-Raki, S. Khabba, Y. Fakir, F. Raibi, O. Merlin, and B. Mougenot, 2018: Evaluation and analysis of deep percolation losses of drip irrigated citrus crops under non-saline and saline conditions in a semi-arid area. Biosyst. Eng., 165, 1024, https://doi.org/10.1016/j.biosystemseng.2017.10.017.

    • Search Google Scholar
    • Export Citation
  • Raymond, F., A. Ullmann, P. Camberlin, P. Drobinski, and C. C. Smith, 2016: Extreme dry spell detection and climatology over the Mediterranean Basin during the wet season. Geophys. Res. Lett., 43, 71967204, https://doi.org/10.1002/2016GL069758.

    • Search Google Scholar
    • Export Citation
  • Raymond, F., P. Drobinski, A. Ullmann, and P. Camberlin, 2018a: Extreme dry spells over the Mediterranean Basin during the wet season: Assessment of HyMeX/Med-CORDEX regional climate simulations (1979–2009). Int. J. Climatol., 38, 30903105, https://doi.org/10.1002/joc.5487.

    • Search Google Scholar
    • Export Citation
  • Raymond, F., A. Ullmann, P. Camberlin, B. Oueslati, and P. Drobinski, 2018b: Atmospheric conditions and weather regimes associated with extreme winter dry spells over the Mediterranean basin. Climate Dyn., 50, 44374453, https://doi.org/10.1007/s00382-017-3884-6.

    • Search Google Scholar
    • Export Citation
  • Raymond, F., A. Ullmann, Y. Tramblay, P. Drobinski, and P. Camberlin, 2019: Evolution of Mediterranean extreme dry spells during the wet season under climate change. Reg. Environ. Change, 19, 23392351, https://doi.org/10.1007/s10113-019-01526-3.

    • Search Google Scholar
    • Export Citation
  • Rio, C., F. Hourdin, F. Couvreux, and A. Jam, 2010: Resolved versus parametrized boundary-layer plumes. Part II: Continuous formulations of mixing rates for mass-flux schemes. Bound.-Layer Meteor., 135, 469483, https://doi.org/10.1007/s10546-010-9478-z.

    • Search Google Scholar
    • Export Citation
  • Rio, C., and Coauthors, 2013: Control of deep convection by sub-cloud lifting processes: The ALP closure in the LMDZ5B general circulation model. Climate Dyn., 40, 22712292, https://doi.org/10.1007/s00382-012-1506-x.

    • Search Google Scholar
    • Export Citation
  • Rochetin, N., J.-Y. Grandpeix, C. Rio, and F. Couvreux, 2014: Deep convection triggering by boundary layer thermals. Part II: Stochastic triggering parameterization for the LMDZ GCM. J. Atmos. Sci., 71, 515538, https://doi.org/10.1175/JAS-D-12-0337.1.

    • Search Google Scholar
    • Export Citation
  • Sadourny, R., and K. Laval, 1984: January and July performance of the LMD general circulation model. New Perspectives in Climate Modelling, A. Berger and C. Nicolis, Eds., Elsevier, 173–198.

  • Sandu, I., A. Beljaars, G. Balsamo, and A. Ghelli, 2012: Revision of the surface roughness length table. ECMWF Newsletter, No. 130, ECMWF, Reading, United Kingdom, 8–9, https://www.ecmwf.int/en/elibrary/78202-newsletter-no-130-winter-201112.

  • Santanello, J. A., and Coauthors, 2018: Land–atmosphere interactions: The LoCo perspective. Bull. Amer. Meteor. Soc., 99, 12531272, https://doi.org/10.1175/BAMS-D-17-0001.1.

    • Search Google Scholar
    • Export Citation
  • Saouabe, T., K. A. Naceur, E. M. El Khalki, A. Hadri, and M. E. Saidi, 2022: GPM-IMERG product: A new way to assess the climate change impact on water resources in a Moroccan semi-arid basin. J. Water Climate Change, 13, 25592576, https://doi.org/10.2166/wcc.2022.403.

    • Search Google Scholar
    • Export Citation
  • Schilling, J., K. P. Freier, E. Hertig, and J. Scheffran, 2012: Climate change, vulnerability and adaptation in North Africa with focus on Morocco. Agric. Ecosyst. Environ., 156, 1226, https://doi.org/10.1016/j.agee.2012.04.021.

    • Search Google Scholar
    • Export Citation
  • Schilling, J., E. Hertig, Y. Tramblay, and J. Scheffran, 2020: Climate change vulnerability, water resources and social implications in North Africa. Reg. Environ. Change, 20, 15, https://doi.org/10.1007/s10113-020-01597-7.

    • Search Google Scholar
    • Export Citation
  • Su, Z., T. Schmugge, W. P. Kustas, and W. J. Massman, 2001: An evaluation of two models for estimation of the roughness height for heat transfer between the land surface and the atmosphere. J. Appl. Meteor., 40, 19331951, https://doi.org/10.1175/1520-0450(2001)040<1933:AEOTMF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tramblay, Y., W. Badi, F. Driouech, S. El Adlouni, L. Neppel, and E. Servat, 2012: Climate change impacts on extreme precipitation in Morocco. Global Planet. Change, 82–83, 104114, https://doi.org/10.1016/j.gloplacha.2011.12.002.

    • Search Google Scholar
    • Export Citation
  • Tramblay, Y., D. Ruelland, S. Somot, R. Bouaicha, and E. Servat, 2013: High-resolution Med-CORDEX regional climate model simulations for hydrological impact studies: A first evaluation of the ALADIN-Climate model in Morocco. Hydrol. Earth Syst. Sci., 17, 37213739, https://doi.org/10.5194/hess-17-3721-2013.

    • Search Google Scholar
    • Export Citation
  • Vafeidis, A. T., and Coauthors, 2020: Managing future risks and building socio-ecological resilience in the Mediterranean. Climate and Environmental Change in the Mediterranean Basin—Current Situation and Risks for the Future. First Mediterranean Assessment Report, W. Cramer, J. Guiot, and K. Marini, Eds., Union for the Mediterranean, Plan Bleu, UNEP/MAP, 539–588, https;//doi.org/10.5281/zenodo.7101119.

  • Vicente-Serrano, S. M., and Coauthors, 2014: Evidence of increasing drought severity caused by temperature rise in southern Europe. Environ. Res. Lett., 9, 044001, https://doi.org/10.1088/1748-9326/9/4/044001.

    • Search Google Scholar
    • Export Citation
  • Vignon, E., F. Hourdin, C. Genthon, H. Gallée, E. Bazile, M.-P. Lefebvre, J.-B. Madeleine, and B. J. H. Van de Wiel, 2017: Antarctic boundary layer parametrization in a general circulation model: 1-D simulations facing summer observations at Dome C. J. Geophys. Res. Atmos., 122, 68186843, https://doi.org/10.1002/2017JD026802.

    • Search Google Scholar
    • Export Citation
  • Vignon, E., F. Hourdin, C. Genthon, B. J. H. Van de Wiel, H. Gallée, J. Madeleine, and J. Beaumet, 2018: Modeling the dynamics of the atmospheric boundary layer over the Antarctic Plateau with a general circulation model. J. Adv. Model. Earth Syst., 10, 98125, https://doi.org/10.1002/2017MS001184.

    • Search Google Scholar
    • Export Citation
  • Wang, F., A. Ducharne, F. Cheruy, M.-H. Lo, and J.-Y. Grandpeix, 2018: Impact of a shallow groundwater table on the global water cycle in the IPSL land–atmosphere coupled model. Climate Dyn., 50, 35053522, https://doi.org/10.1007/s00382-017-3820-9.

    • Search Google Scholar
    • Export Citation
  • Yamada, T., 1983: Simulations of nocturnal drainage flows by a q2 l turbulence closure model. J. Atmos. Sci., 40, 91106, https://doi.org/10.1175/1520-0469(1983)040<0091:SONDFB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zkhiri, W., Y. Tramblay, L. Hanich, L. Jarlan, and D. Ruelland, 2019: Spatiotemporal characterization of current and future droughts in the High Atlas basins (Morocco). Theor. Appl. Climatol., 135, 593605, https://doi.org/10.1007/s00704-018-2388-6.

    • Search Google Scholar
    • Export Citation
  • Zobler, L., 1986: A world soil file for global climate modeling. NASA Tech. Memo. 87802, 32 pp.

All Time Past Year Past 30 Days
Abstract Views 414 414 75
Full Text Views 146 146 36
PDF Downloads 167 167 44