###### Abstract  
We present the first comparison between new fAPAR and LAI products derived from the GlobAlbedo dataset and the widely-used MODIS fAPAR and LAI products. The GlobAlbedo-derived products are produced using a 1D two-stream radiative transfer (RT) scheme designed explicitly for global parameter retrieval from albedo, with consistency between RT model assumptions and observations, as well as with typical large-scale land surface model RT schemes. The approach does not require biome-specific structural assumptions (e.g., cover, clumping, understory), unlike more detailed 3D RT model approaches. GlobAlbedo-derived values of fAPAR and LAI are compared with MODIS values over 2002-2011 at multiple flux tower sites within selected biomes, over \(1200\times 1200\) km regions and globally. GlobAlbedo-derived fAPAR and LAI values are temporally more stable than the MODIS values due to the smoothness of the underlying albedo, derived via optimal estimation (assimilation) using an a priori estimate of albedo derived from an albedo \"climatology\" (composited multi-year albedo observations). Parameters agree closely in timing but with GlobAlbedo values consistently lower than MODIS, particularly for LAI. Larger differences occur in winter (when values are lower) and in the Southern hemisphere. Globally, we find that: GlobAlbedo-derived fAPAR is \(\sim\)0.9-1.01 \(\times\) MODIS fAPAR with an intercept of \(\sim\)0.03; GlobAlbedo-derived LAI is \(\sim\)0.6 \(\times\) MODIS LAI with an intercept of \(\sim\)0.2. Differences arise due to the RT model assumptions underlying the products, meaning care is required in interpreting either set of values, particularly when comparing to fine-scale ground-based estimates. We present global transformations between GlobAlbedo-derived and MODIS products. fAPAR; LAI; albedo; radiative transfer; vegetation; MODIS; GlobAlbedo +
Footnote †: journal: remote sensing  
0000-0002-4800-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-0000-00000-00000-00000-00000-0  
scales are also a requirement for improved land surface models (LSMs) [1]. Vegetation structure and amount is widely-characterized by the canopy leaf area index (LAI); radiometric properties of vegetation (absorption in particular) are related to the fraction of absorbed photosynthetically active radiation (fAPAR). LAI encapsulates the amount of vegetation available for radiation absorption, while fAPAR describes the efficiency of absorption. As a result, a wide range of approaches has been developed to estimate these properties from satellite observations of reflected radiation [2; 3]. These approaches range from the purely empirical, exploiting relationships between fAPAR and LAI and easily estimated spectral indices such as normalised vegetation index (NDVI) [4], to physically-based radiative transfer (RT) models that describe reflected solar radiation as a function of LAI and fAPAR [5; 6]. Key advantages of the physically-based approach are that it is quantitative and allows for attribution of changes in the observed signal to changes in the surface properties. Just as importantly, the uncertainty in the resulting parameter estimates can be characterized explicitly (although this is not always done in practice). Physically-based RT model retrievals underpin the most widely-used LAI and fAPAR estimates, such as those derived from the NASA MODIS instruments [7; 8]. Here, we describe the properties of a new LAI and fAPAR product, derived from estimates of broadband albedo rather than spectral reflectance using an optimal model-observation framework. The underlying albedo data were developed for the European Space Agency (ESA) GlobAlbedo project [9]. The LAI and fAPAR products have been derived from GlobAlbedo products as part of the ESA Water Cycle Observation Multi-mission Strategy--EvapoTranspiration (WACMOS-II) project, to provide inputs into large-scale models of terrestrial evapotranspiration [10].