Preprints
https://doi.org/10.5194/gmd-2020-371
https://doi.org/10.5194/gmd-2020-371

Submitted as: model evaluation paper 02 Feb 2021

Submitted as: model evaluation paper | 02 Feb 2021

Review status: this preprint is currently under review for the journal GMD.

Surface representation impacts on turbulent heat fluxes in WRF (v.4.1.3)

Carlos Román-Cascón1,2, Marie Lothon2, Fabienne Lohou2, Oscar Hartogensis3, Jordi Vila-Guerau de Arellano3, David Pino4, Carlos Yagüe5, and Eric R. Pardyjak6 Carlos Román-Cascón et al.
  • 1Centre National d’Études Spatiales (CNES), 31400 Toulouse, France
  • 2Laboratorie d’Aerologie, CNRS, Université de Toulouse, 31400 Toulouse, France
  • 3Meteorology and Air Quality Section, Wageningen University, Wageningen, Netherlands
  • 4Department of Physics, Universitat Politècnica de Catalunya-BarcelonaTech, 08034 Barcelona, Spain
  • 5Departamento de Física de la Tierra y Astrofísica. Universidad Complutense de Madrid, 28040 Madrid, Spain
  • 6Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA

Abstract. The water and energy transfers at the interface between the Earth's surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface leads to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France, using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with four widely-used land-surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach, where 30-m sub-grid surface information was used to calculate the final grid fluxes, based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests, due to the large fluxes errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for the coniferous forest. The mosaic approach produced fluxes more similar to reality and served to improve, especially, the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model.

Carlos Román-Cascón et al.

Status: open (until 30 Mar 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2020-371', Wayne Angevine, 12 Feb 2021 reply

Carlos Román-Cascón et al.

Data sets

Data and scripts for GMD publication - Surface representation impacts on turbulent heat fluxes in WRF (v.4.1.3) Román-Cascón, Carlos, Lothon, Marie, Lohou, Fabienne, Hartogensis, Oscar, Vila-Guerau de Arellano, Jordi, Pino, David, Yagüe, Carlos, and Pardyjak, Eric R. https://doi.org/10.5281/zenodo.4449761

Carlos Román-Cascón et al.

Viewed

Total article views: 282 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
214 62 6 282 7 6
  • HTML: 214
  • PDF: 62
  • XML: 6
  • Total: 282
  • BibTeX: 7
  • EndNote: 6
Views and downloads (calculated since 02 Feb 2021)
Cumulative views and downloads (calculated since 02 Feb 2021)

Viewed (geographical distribution)

Total article views: 193 (including HTML, PDF, and XML) Thereof 193 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Mar 2021
Download
Short summary
The type of vegetation (or land cover) and its status influence the heat and water transfers between the surface and the air, affecting the processes that develop in the atmosphere at different (but connected) spatiotemporal scales. In this work, we investigate how these transfers are affected by the way the surface is represented in a widely used weather model. The results encourage including realistic high-resolution and updated land-cover databases in models to improve their predictions.