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Volume 8, issue 10 | Copyright

Special issue: The SimSphere Land Biosphere Model

Geosci. Model Dev., 8, 3257-3284, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 16 Oct 2015

Methods for assessment of models | 16 Oct 2015

Quantifying the prediction accuracy of a 1-D SVAT model at a range of ecosystems in the USA and Australia: evidence towards its use as a tool to study Earth's system interactions

G. P. Petropoulos1, M. R. North1, G. Ireland1, P. K. Srivastava2,3,4, and D. V. Rendall1 G. P. Petropoulos et al.
  • 1Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, SY23 3DB, UK
  • 2Hydrological Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 3Earth System Science Interdisciplinary Center, University of Maryland, Maryland, USA
  • 4Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India

Abstract. This paper describes the validation of the SimSphere SVAT (Soil–Vegetation–Atmosphere Transfer) model conducted at a range of US and Australian ecosystem types. Specific focus was given to examining the models' ability in predicting shortwave incoming solar radiation (Rg), net radiation (Rnet), latent heat (LE), sensible heat (H), air temperature at 1.3 m (Tair 1.3 m) and air temperature at 50 m (Tair 50 m). Model predictions were compared against corresponding in situ measurements acquired for a total of 72 selected days of the year 2011 obtained from eight sites belonging to the AmeriFlux (USA) and OzFlux (Australia) monitoring networks. Selected sites were representative of a variety of environmental, biome and climatic conditions, to allow for the inclusion of contrasting conditions in the model evaluation.

Overall, results showed a good agreement between the model predictions and the in situ measurements, particularly so for the Rg, Rnet, Tair 1.3 m and Tair 50 m parameters. The simulated Rg parameter exhibited a root mean square deviation (RMSD) within 25 % of the observed fluxes for 58 of the 72 selected days, whereas an RMSD within ~ 24 % of the observed fluxes was reported for the Rnet parameter for all days of study (RMSD = 58.69 W m−2). A systematic underestimation of Rg and Rnet (mean bias error (MBE) = −19.48 and −16.46 W m−2) was also found. Simulations for the Tair 1.3 m and Tair 50 m showed good agreement with the in situ observations, exhibiting RMSDs of 3.23 and 3.77 °C (within ~ 15 and ~ 18 % of the observed) for all days of analysis, respectively. Comparable, yet slightly less satisfactory simulation accuracies were exhibited for the H and LE parameters (RMSDs = 38.47 and 55.06 W m−2, ~ 34 and ~ 28 % of the observed). Highest simulation accuracies were obtained for the open woodland savannah and mulga woodland sites for most of the compared parameters. The Nash–Sutcliffe efficiency index for all parameters ranges from 0.720 to 0.998, suggesting a very good model representation of the observations.

To our knowledge, this study presents the most detailed evaluation of SimSphere done so far, and the first validation of it conducted in Australian ecosystem types. Findings are important and timely, given the expanding use of the model both as an educational and research tool today. This includes ongoing research by different space agencies examining its synergistic use with Earth observation data towards the development of global operational products.

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The performance of the SimSphere SVAT model was comprehensively validated against in situ measurements from selected US and Australian sites of the FLUXNET monitoring network for 2011. The results obtained confirmed the correspondence of the model structure to the real conditions for which it was parameterised, evidencing its ability to reproduce outputs akin to the in situ reference data.To our knowledge this is the first comprehensive validation of SimSphere for Australia and the USA.
The performance of the SimSphere SVAT model was comprehensively validated against in situ...