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- W2884329524 abstract "Abstract. Canopy structural and leaf photosynthesis parameterizations such as maximum carboxylation capacity (Vcmax), slope of the Ball–Berry stomatal conductance model (BBslope) and leaf area index (LAI) are crucial for modeling plant physiological processes and canopy radiative transfer. These parameters are large sources of uncertainty in predictions of carbon and water fluxes. In this study, we develop an optimal moving window nonlinear Bayesian inversion framework to use the Soil Canopy Observation Photochemistry and Energy fluxes (SCOPE) model for constraining Vcmax, BBslope and LAI with observations of coupled carbon and energy fluxes and spectral reflectance from satellites. We adapted SCOPE to follow the biochemical implementation of the Community Land Model and applied the inversion framework for parameter retrievals of plant species that have both the C3 and C4 photosynthetic pathways across three ecosystems. We present comparative analysis of parameter retrievals using observations of (i) gross primary productivity (GPP) and latent energy (LE) fluxes and (ii) improvement in results when using flux observations along with reflectance. Our results demonstrate the applicability of the approach in terms of capturing the seasonal variability and posterior error reduction (40 %–90 %) of key ecosystem parameters. The optimized parameters capture the diurnal and seasonal variability in the GPP and LE fluxes well when compared to flux tower observations (0.95>R2>0.79). This study thus demonstrates the feasibility of parameter inversions using SCOPE, which can be easily adapted to incorporate additional data sources such as spectrally resolved reflectance and fluorescence and thermal emissions." @default.
- W2884329524 created "2018-08-03" @default.
- W2884329524 creator A5010988798 @default.
- W2884329524 creator A5011092289 @default.
- W2884329524 creator A5055655717 @default.
- W2884329524 creator A5069783783 @default.
- W2884329524 creator A5075397242 @default.
- W2884329524 date "2019-01-11" @default.
- W2884329524 modified "2023-10-16" @default.
- W2884329524 title "Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes" @default.
- W2884329524 cites W1209269186 @default.
- W2884329524 cites W1480922037 @default.
- W2884329524 cites W1490443704 @default.
- W2884329524 cites W1491964615 @default.
- W2884329524 cites W1568528618 @default.
- W2884329524 cites W1590396946 @default.
- W2884329524 cites W1721472034 @default.
- W2884329524 cites W1965122835 @default.
- W2884329524 cites W1966523582 @default.
- W2884329524 cites W1966715855 @default.
- W2884329524 cites W1969939898 @default.
- W2884329524 cites W1970527729 @default.
- W2884329524 cites W1980901385 @default.
- W2884329524 cites W1988144647 @default.
- W2884329524 cites W1992821384 @default.
- W2884329524 cites W2003997831 @default.
- W2884329524 cites W2010784770 @default.
- W2884329524 cites W2018330599 @default.
- W2884329524 cites W2019623635 @default.
- W2884329524 cites W2029074727 @default.
- W2884329524 cites W2035962295 @default.
- W2884329524 cites W2038781720 @default.
- W2884329524 cites W2046857879 @default.
- W2884329524 cites W2047242451 @default.
- W2884329524 cites W2050648603 @default.
- W2884329524 cites W2055842947 @default.
- W2884329524 cites W2059501000 @default.
- W2884329524 cites W2070774092 @default.
- W2884329524 cites W2072490792 @default.
- W2884329524 cites W2075041338 @default.
- W2884329524 cites W2077896114 @default.
- W2884329524 cites W2082249472 @default.
- W2884329524 cites W2082780896 @default.
- W2884329524 cites W2087070363 @default.
- W2884329524 cites W2091141016 @default.
- W2884329524 cites W2093009240 @default.
- W2884329524 cites W2096018221 @default.
- W2884329524 cites W2096466966 @default.
- W2884329524 cites W2098682573 @default.
- W2884329524 cites W2098845299 @default.
- W2884329524 cites W2100174116 @default.
- W2884329524 cites W2101010747 @default.
- W2884329524 cites W2101695001 @default.
- W2884329524 cites W2103218141 @default.
- W2884329524 cites W2116291451 @default.
- W2884329524 cites W2116751232 @default.
- W2884329524 cites W2121983269 @default.
- W2884329524 cites W2123134406 @default.
- W2884329524 cites W2127132651 @default.
- W2884329524 cites W2128993529 @default.
- W2884329524 cites W2134093193 @default.
- W2884329524 cites W2134289299 @default.
- W2884329524 cites W2134307851 @default.
- W2884329524 cites W2139780323 @default.
- W2884329524 cites W2143076990 @default.
- W2884329524 cites W2143494625 @default.
- W2884329524 cites W2144653885 @default.
- W2884329524 cites W2145780057 @default.
- W2884329524 cites W2145998172 @default.
- W2884329524 cites W2151328940 @default.
- W2884329524 cites W2155212656 @default.
- W2884329524 cites W2160482092 @default.
- W2884329524 cites W2161783224 @default.
- W2884329524 cites W2163004831 @default.
- W2884329524 cites W2163738952 @default.
- W2884329524 cites W2165628866 @default.
- W2884329524 cites W2166134628 @default.
- W2884329524 cites W2179250365 @default.
- W2884329524 cites W2181150263 @default.
- W2884329524 cites W2183882374 @default.
- W2884329524 cites W2256578114 @default.
- W2884329524 cites W2312515306 @default.
- W2884329524 cites W2316929704 @default.
- W2884329524 cites W2317425714 @default.
- W2884329524 cites W2325025062 @default.
- W2884329524 cites W2338049369 @default.
- W2884329524 cites W2434551657 @default.
- W2884329524 cites W2548423966 @default.
- W2884329524 cites W2557651103 @default.
- W2884329524 cites W2558380412 @default.
- W2884329524 cites W2746142786 @default.
- W2884329524 cites W2760848730 @default.
- W2884329524 cites W3088859894 @default.
- W2884329524 cites W4240733927 @default.
- W2884329524 cites W4242124975 @default.
- W2884329524 doi "https://doi.org/10.5194/bg-16-77-2019" @default.
- W2884329524 hasPublicationYear "2019" @default.
- W2884329524 type Work @default.