Note that these results here are tentative and preliminary.
Global land surface remote sensing by MODIS provides predictor variables at a high spatial resolution (e.g. 1km), but at a coarser temporal resolution (e.g. 8-daily) and only for the lifetime of MODIS (2000-present). Meteorological conditions likely provide additional information on the variability of carbon and energy fluxes that are not captured by remotely sensed surface properties alone. Utilizing meteorological predictor variables measured at FLUXNET sites requires gridded meteorological data products to produce the global flux products. Those are available for a longer time period at a finer temporal resolution (sub-daily to daily), but usually at a coarser spatial resolution (0.5° to 1°). Because gridded meteorological data are uncertain, using them in the upscaling introduces additional uncertainties in global flux products.
Mean annual GPP from FLUXCOM-RS ensemble (gC m-2 yr-1).
Uncertainty in mean annual GPP from FLUXCOM-RS ensemble (gC m-2 yr-1).
RGB composite of sensible heat (H), latent heat (LE), and evaporative fraction (LE/Rn). Bar charts on right: Mean seasonal cycle of LE and H along a North-South transect from boreal – temperate – mediterranean – subtropical – tropical – arid. Bottom: mean annual Rn, LE, and H for the Iberian peninsula.