Land surface model parameter optimisation using in situ flux data : Comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia and USCCC. We acknowledge the financial support to the eddy covariance data harmonisation provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Universiteì Laval, Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California – Berkeley and the University of Virginia.Peer reviewedPublisher PD

Contribution à la caractérisation de sites sableux : signature spectro-directionnelle, distribution en taille et minéralogie extraites d'échantillons de sables

International audienceThe characterization of sands detailed in this paper has been performed in order to support the in-flight radiometric performance assessment of space-borne optical sensors over so-called Pseudo-Invariant Calibration Sites (PICS). Although the physical properties of PICS surface are fairly stable in time, the signal measured from space varies with the illumination and the viewing geometries. Thus there is a need to characterize the spectro-directional properties of PICS. This can be done, at a broad scale, thanks to multi-spectral multi-directional space-borne sensors such as the POLDER instrument (with old data). However, interpolating or extrapolating the spectro-directional reflectances measured from space to spectral bands of another sensor is not straightforward. The hyperspectral characterization of sand samples collected within or nearby PICS can contribute to a solution. In this context, a set of 31 sand samples was compiled. The BiConical Reflectance Factor (BCRF) was measured between 0.4 and 2.5 µm, over a quarter hemisphere when the amount of sand in the sample was large enough and for only a single fixed angular configuration for small samples. These optical measurements were complemented by grain size distribution measurements and mineralogical analysis and compiled together with previously published measurements in the so-called PICSAND database, freely available on line.La caractérisation des sables détaillée dans cet article a été faite en soutien à l'estimation en vol des performances radiométriques des capteurs optiques spatiaux à partir des sites appelés PICS pour Pseudo-Invariant Calibration Sites. Bien que les propriétés physiques des PICS soient relativement stables dans le temps, le signal mesuré depuis l'espace varie en fonction des géométries d'illumination et d'observation. De ce fait, il est nécessaire de caractériser les propriétés spectro-directionnelles des PICS. Ceci peut être fait, à une grande échelle, à partir de capteurs spatiaux multi-spectraux et multi-directionnels tels que le capteur POLDER (avec des données anciennes). Cependant, l'interpolation ou l'extrapolation des réflectances spectro-directionnelles obtenues depuis l'espace aux bandes spectrales d'un autre capteur est délicate. La caractérisation hyperspectrale d'échantillons de sable issus de PICS ou de leur voisinage peut participer à une solution. Dans ce contexte, 31 échantillons de sable ont été collectés. Le Facteur de Reflectance BiConique (BCRF) a été mesuré entre 0,4 et 2,5 µm, pour une demi-hémisphère lorsque la quantité de sable était suffisante, et pour une seule géométrie pour les échantillons plus petits. Ces mesures optiques ont été complétées par des mesures de distribution en taille et par une analyse minéralogique, et mises dans une base de données appelée PICSAND avec d'autres mesures publiées dans la littérature. Cette base de donnée est en libre accès en ligne

Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model

Aim: The mechanisms of plant trait adaptation and acclimation are still poorly understood and, consequently, lack a consistent representation in terrestrial biosphere models (TBMs). Despite the increasing availability of geo‐referenced trait observations, current databases are still insufficient to cover all vegetation types and environmental conditions. In parallel, the growing number of continuous eddy‐covariance observations of energy and CO2 fluxes has enabled modellers to optimize TBMs with these data. Past attempts to optimize TBM parameters mostly focused on model performance, overlooking the ecological properties of ecosystems. The aim of this study was to assess the ecological consistency of optimized trait‐related parameters while improving the model performances for gross primary productivity (GPP) at sites. Location: Worldwide. Time period: 1992–2012. Major taxa studied: Trees and C3 grasses. Methods: We optimized parameters of the ORCHIDEE model against 371 site‐years of GPP estimates from the FLUXNET network, and we looked at global covariation among parameters and with climate. Results: The optimized parameter values were shown to be consistent with leaf‐scale traits, in particular, with well‐known trade‐offs observed at the leaf level, echoing the leaf economic spectrum theory. Results showed a marked sensitivity of trait‐related parameters to local bioclimatic variables and reproduced the observed relationships between traits and climate. Main conclusions: Our approach validates some biological processes implemented in the model and enables us to study ecological properties of vegetation at the canopy level, in addition to some traits that are difficult to observe experimentally. This study stresses the need for: (a) implementing explicit trade‐offs and acclimation processes in TBMs; (b) improving the representation of processes to avoid model‐specific parameterization; and (c) performing systematic measurements of traits at FLUXNET sites in order to gather information on plant ecophysiology and plant diversity, together with micro‐meteorological conditions

Variability of biome reflectance directional signatures as seen by POLDER

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Normalization of the directional effects in NOAA–AVHRR reflectance measurements for an improved monitoring of vegetation cycles

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Comparison of four radiative transfer models to simulate plant canopies reflectance: Direct and inverse mode

International audienceFour one-dimensional radiative transfer models are compared in direct and inverse modes. These models are combinations of the PROSPECT leaf optical properties model and the SAIL, IAPI, KUUSK, and NADI canopy reflectance models. To evaluate their ability to estimate canopy biophysical parameters, inversions were first performed on synthetic reflectance spectra (10 wavelengths in the visible and near infrared). The simulated spectral and directional reflectances showed good agreement among the four models. A 1997 airborne experiment in the USA was used to test their performance on real data. This experiment gathered a unique data set composed primarily of 200 reflectance spectra acquired over corn (Zea mays L.) and soybean (Glycine max) fields, and the corresponding ground truth (chlorophyll a+b content and leaf area index). Only the first three models, which ran fast enough to allow the processing of a large data set, were actually inverted by iterative optimization techniques. Inversions were conducted in successive stages where the number of retrieved parameters was reduced. No significant difference can be observed between the three models. Globally, the leaf mesophyll structure parameter (N) and leaf dry matter content (Cm) couldn't be estimated. The chlorophyll content (Cab), the leaf area index (LAI), and the mean leaf inclination angle (θl) yielded better results, although the latter wasn't validated due to missing ground data. Assuming that model inversion by iterative optimization techniques is a promising method to extract information on plant canopies, the SAIL and KUUSK models, which perform well in terms of accuracy and running time, proved to be good candidates for remote sensing application in ecology or agriculture (precision farming)

Design and analysis of numerical experiments to compare four canopy reflectance models

International audienceA method designed to study the relative effects of the input parameters of any model has been investigated with canopy reflectance (CR) models. Traditionally, sensitivity analyses are performed by changing one input parameter at a time. Such an approach is limited because it lacks strategy. A promising alternative is in the use of design of experiments, a statistical method that allows defining a structured and restricted number of simulations for which all input parameters vary simultaneously. This approach is especially helpful in multidimensional parameter spaces. It is demonstrated using four 1D radiative transfer models that are compared in direct mode. These models are combinations of the PROSPECT leaf optical properties model with the four CR models, SAIL (Scattering and Arbitrarily Inclined Leaves), KUUSK, IAPI, and NADI (New Advanced DIscrete model). The sensitivity studies were conducted in the visible/near-infrared on the following parameters: the leaf structure (N), the chlorophyll-a and -b content (Cab), the leaf area index (LAI), the mean leaf inclination angle (ql), the hot spot (sl), and the soil brightness (asoil). We compared simulated reflectances for a given set of measurement geometries and two wavebands of the POLDER (Polarization and Directionality of the Earth’s Reflectances) spaceborne instrument. The relative effects of the biophysical parameters are assessed as well as their contribution to reflectance, allowing us to rank the most influential ones. Their interactions were also studied from the perspective of improving inversion procedures. Globally, the four models agree well in terms of computed reflectances and parameter effects, nevertheless with some discrepancies due to the implementation of different leaf angle distribution (LAD) functions