On the added value of improving the spatial representation and seasonal variations of vegetation cover in land surface models for simulated land surface temperature
- 1Instituto Dom Luiz, IDL, Faculty of Sciences, University of Lisbon, 1749-016-Lisbon, Portugal
- 2CNRM UMR 3589, Météo-France/CNRS, Toulouse, France
- 3ECMWF, Reading, UK
Earth observations were used to evaluate and improve the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models - the European Center for Medium Range Weather Forecasting (ECMWF) Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL) and the Méteo-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 HTESSEL over Iberia is affected by a large cold bias during summer months when compared against the Satellite Application Facility Land Surface Analysis (LSA-SAF), reaching magnitude larger than 10ºC 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 had such a cold bias. This was due to the better representation of vegetation coverage 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 HTESSEL 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 vegetation includes a clumping approach to introduce seasonality to the vegetation coverage. The results show significant added value, removing the daily maximum LST summer cold bias completely while never reducing the accuracy over all seasons and hours of the day.
This work has important implications: First, LST is a key variable in surface-atmosphere energy and water exchanges and, thus, its accurate representation in earth system models is very important. Second, HTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis, hence systematic errors are propagated into these products. Indeed, we show that the summer daily maximum LST cold bias over Iberia in HTESSEL is present in the widely used ECMWF fifth generation reanalysis (ERA5) and fourth generation reanalysis (ERA-Interim). Finally, our results provide hints into the interaction between vegetation land-atmosphere exchanges, highlight the consistent relevance of the vegetation cover and seasonality in representing land surface temperature in both models, and how earth observations play a critical role for constraining and improving weather and climate simulations.
How to cite: Nogueira, M., Albergel, C., Boussetta, S., Johanssen, F., and Dutra, E.: On the added value of improving the spatial representation and seasonal variations of vegetation cover in land surface models for simulated land surface temperature, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18110, https://doi.org/10.5194/egusphere-egu2020-18110, 2020