Abstract
Earth systems models require gridded land surface properties to compute fluxes of water, energy, and carbon within the landscape and to the atmosphere. However, most parameter sets contain time-invariant properties despite their known variability. Here we present new MODerate Resolution Imaging Spectroradiometer (MODIS)-based land surface parameters (MOD-LSP) formatted for the Variable Infiltration Capacity (VIC) hydrologic model that account for seasonal and interannual variability and longer-term change over the continental United States, Mexico, and southern Canada at 0.0625° spatial resolution and monthly temporal resolution. MOD-LSP improves over previously-available parameter sets via: (1) land cover maps of higher native spatial resolution; (2) multiple versions corresponding to the land cover of years 1992, 2001, and 2011; (3) spatially-explicit mean annual cycles of land surface properties, including leaf area index, canopy fraction, and albedo, derived from 17 years of observations; and (4) additional 17-year time series of these properties. The MOD-LSP parameters are useful as inputs to the VIC model, as an example land surface scheme, to assess the hydrologic impacts of land cover change from interannual to decadal scales; and as stand-alone datasets characterizing the temporal variability of these properties as a function of land cover class.
Highlights
Background & SummaryHydrologic and earth system models require specification of gridded land surface properties such as land cover type, leaf area index (LAI), and albedo to simulate the land surface response to meteorological forcings over watershed to global scales, typically at resolutions of less than 10 km
For studies at regional to global scales, the effort required to process the large data volume of remote sensing datasets can discourage the updating of these parameters, in some cases leading to the use of land surface parameters that represent time periods outside of the period of simulation
Prior Variable Infiltration Capacity (VIC) parameters over the United States[11,12,13], Mexico[14], and North America[15] share several limitations: (1) they were derived from a coarse-resolution land cover map, based on Advanced Very High-Resolution Radiometer (AVHRR) imagery from the early 1990s7; (2) the annual cycle of monthly LAI values was derived by spatially interpolating a sparse (
Summary
Hydrologic and earth system models require specification of gridded land surface properties such as land cover type, leaf area index (LAI), and albedo to simulate the land surface response to meteorological forcings over watershed to global scales, typically at resolutions of less than 10 km For those properties that can be measured from space, remote sensing products have been useful in providing gridded values at high resolution with global coverage[1,2,3,4,5,6,7]. Included; (2) the long-term mean annual cycles of phenology variables have been derived from 17 years (2000–2016) of 8- and 16-day MODIS products using all available pixels, yielding spatially explicit and statistically representative estimates for each land cover class in each grid cell; (3) phenology values have been provided for urban areas; and (4) to account for interannual variability in phenology, monthly time series of phenology spanning the period 2000–2016 have been generated as an optional set of vegetative forcings for the VIC model
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