Simple process-led algorithms for simulating habitats (SPLASH v.1.0): Robust indices of radiation, evapotranspiration and plant-available moisture
Geoscientific Model Development
© Author(s) 2017. CC Attribution 3.0 License.
© Author(s) 2017.Bioclimatic indices for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios depend on estimates of surface fluxes and other quantities, such as radiation, evapotranspiration and soil moisture, for which direct observations are sparse. These quantities can be derived indirectly from meteorological variables, such as near-surface air temperature, precipitation and cloudiness. Here we present a consolidated set of simple process-led algorithms for simulating habitats (SPLASH) allowing robust approximations of key quantities at ecologically relevant timescales. We specify equations, derivations, simplifications, and assumptions for the estimation of daily and monthly quantities of top-of-the-atmosphere solar radiation, net surface radiation, photosynthetic photon flux density, evapotranspiration (potential, equilibrium, and actual), condensation, soil moisture, and runoff, based on analysis of their relationship to fundamental climatic drivers. The climatic drivers include a minimum of three meteorological inputs: precipitation, air temperature, and fraction of bright sunshine hours. Indices, such as the moisture index, the climatic water deficit, and the Priestley-Taylor coefficient, are also defined. The SPLASH code is transcribed in C++, FORTRAN, Python, and R. A total of 1 year of results are presented at the local and global scales to exemplify the spatiotemporal patterns of daily and monthly model outputs along with comparisons to other model results.
This work was primarily funded by Imperial College London as a part of the AXA Chair Programme on Biosphere and Climate Impacts. It is a contribution to the Imperial College initiative on Grand Challenges in Ecosystems and the Environment, and the Ecosystem Modelling And Scaling Infrastructure (eMAST) facility of the Australian Terrestrial Ecosystem Research Network (TERN). TERN is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS). BDS funded by the Swiss National Science Foundation (SNF) and the European Commission’s 7th Framework Programme, under grant agreement number 282672, EMBRACE project. WC contributes to the Labex OT-Med (no. ANR-11-LABX-0061) funded by the French government through the A MIDEX project (no. ANR-11-IDEX-0001-02). AGS has been supported by a Natural Environment Research Council grant (NERC grant number NE/I012915/1). VIC simulations utilized the Janus supercomputer, which is supported by the National Science Foundation (award number CNS-0821794) and the University of Colorado Boulder. The Janus supercomputer is a joint effort of the University of Colorado Boulder, the University of Colorado Denver, and the National Center for Atmospheric Research. CERES EBAF data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. CPC soil moisture data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at http://www.esrl.noaa.gov/psd/.
This is the final version of the article. Available from Copernicus Publications via the DOI in this record.
Vol. 10, Iss. 2, pp. 689 - 708