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Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain

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  • Igor Gómez

    (Department of Applied Physics, Faculty of Sciences, University of Alicante, 03690 Alicante, Spain
    Multidisciplinary Institute for Environmental Studies (MIES) “Ramón Margalef”, University of Alicante, 03690 Alicante, Spain)

  • Sergio Molina

    (Department of Applied Physics, Faculty of Sciences, University of Alicante, 03690 Alicante, Spain
    Multidisciplinary Institute for Environmental Studies (MIES) “Ramón Margalef”, University of Alicante, 03690 Alicante, Spain)

  • Juan José Galiana-Merino

    (Department of Physics, Systems Engineering and Signal Theory, University of Alicante, 03690 Alicante, Spain
    University Institute of Physics Applied to Sciences and Technologies, University of Alicante, 03690 Alicante, Spain)

  • María José Estrela

    (Department of Geography, Faculty of Geography and History, University of Valencia, 46010 Valencia, Spain)

  • Vicente Caselles

    (Earth Physics and Thermodynamics Department, Faculty of Physics, University of Valencia, 46100 Valencia, Spain)

Abstract

The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partitioning at the land surface in short-time scale simulations. Aside from in situ observations, we use the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor to assess the Land Surface Temperature (LST) field simulated by WRF. Regarding multiple options in Noah-MP, WRF has been configured using three distinct soil moisture factors to control stomatal resistance ( β factor) available in Noah-MP (Noah, CLM, and SSiB-types), two canopy stomatal resistance (Ball–Berry and Jarvis), and two options for surface layer drag coefficients (Monin–Obukhov and Chen97 scheme). Considering the β factor schemes, CLM and SSiB-type β factors simulate very low values of the latent heat flux while increasing the sensible heat flux. This result has been obtained independently of the canopy stomatal resistance scheme used. Additionally, the surface skin temperature simulated by Noah-MP is colder than that obtained by the original Noah LSM. This result is also highlighted when the simulated surface skin temperature is compared to the MSG-SEVIRI LST product. The largest differences between the satellite data and the mesoscale simulations are produced using the Noah-MP configurations run with the Monin–Obukhov parameterization for surface layer drag coefficients. In contrast, the Chen97 scheme shows larger surface skin temperatures than Monin–Obukhov, but at the expense of a decrease in the simulated sensible heat fluxes. In this regard, the ground heat flux and the net radiation play a key role in the simulation results.

Suggested Citation

  • Igor Gómez & Sergio Molina & Juan José Galiana-Merino & María José Estrela & Vicente Caselles, 2021. "Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain," Sustainability, MDPI, vol. 13(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11399-:d:657320
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    References listed on IDEAS

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    1. Jiayang Li & Xinqi Zheng & Chunxiao Zhang & Youmin Chen, 2018. "Impact of Land-Use and Land-Cover Change on Meteorology in the Beijing–Tianjin–Hebei Region from 1990 to 2010," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
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    4. Prashant K. Srivastava & Dawei Han & Aradhana Yaduvanshi & George P. Petropoulos & Sudhir Kumar Singh & Rajesh Kumar Mall & Rajendra Prasad, 2017. "Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation," Sustainability, MDPI, vol. 9(11), pages 1-17, October.
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