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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2020-49
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-49
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 13 Mar 2020

Submitted as: model evaluation paper | 13 Mar 2020

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This preprint is currently under review for the journal GMD.

Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia

Miguel Nogueira1, Clément Albergel2, Souhail Boussetta3, Frederico Johannsen1, Isabel F Trigo4, Sofia L Ermida4, João P A Martins4, and Emanuel Dutra1 Miguel Nogueira et al.
  • 1Instituto Dom Luiz, IDL, Faculty of Sciences, University of Lisbon, 1749-016 Lisbon, Portugal
  • 2CNRM, Université de Toulouse, Meteo-France, CNRS, Toulouse, France
  • 3ECMWF, Reading, UK
  • 4Instituto Português do Mar e da Atmosfera, 1749-077 Lisboa, Portugal

Abstract. Earth observations were used to evaluate the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium Range Weather Forecasting (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modelling platform (SURFEX-ISBA) for the 2004–2015 period. The results show that the daily maximum LST simulated by CHTESSEL over Iberia is affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 °C over wide portions of central and southwestern Iberia. This error is shown to be tightly linked to a misrepresentation of the vegetation cover. In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) Leaf Area Index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also includes a clumping approach that introduces seasonality to the vegetation cover. The results show significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guide the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface-atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve model’s representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis, hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we show that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth generation reanalysis (ERA5). Finally, our results provide hints into the interaction between vegetation land-atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrates the added value in using multiple earth observation products for constraining and improving weather and climate simulations.

Miguel Nogueira et al.

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Miguel Nogueira et al.

Data sets

Simulation results from SURFEX and CHTESSEL M. Nogueira, C. Albergel, S. Boussetta, F. Johannsen, I. F. Trigo, S. L. Ermida, J. P. A. Martins, and E. Dutra https://doi.org/10.5281/zenodo.3701230

Model code and software

SURFEX v8.1 M. Nogueira, C. Albergel, S. Boussetta, F. Johannsen, I. F. Trigo, S. L. Ermida, J. P. A. Martins, and E. Dutra https://doi.org/10.5281/zenodo.3701230

Miguel Nogueira et al.

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Latest update: 28 Mar 2020
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Short summary
We used earth observations to evaluate and improve the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX Land Surface Models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction of daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
We used earth observations to evaluate and improve the representation of Land Surface...
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