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In David et al (2021), we introduced a neural network (NN) approach for estimating the column-averaged dry air mole fraction of CO2 (XCO2) and the surface pressure from the reflected solar spectra acquired by the OCO-2 instrument. The results indicated great potential for the technique as the comparison against both model estimates and independent TCCON measurements showed an accuracy and precision similar or better than that of the operational ACOS (NASA’s Atmospheric CO2 Observations from Space retrievals – ACOS) algorithm. Yet, subsequent analysis showed that the neural network estimate often mimics the training dataset and is unable to retrieve small scale features such as CO2 plumes from industrial sites. Importantly, we found that, with the same inputs as those used to estimate XCO2 and surface pressure, the NN technique is able to estimate latitude and date with unexpected skill, i.e. with an error whose standard deviation is only 7° and 61 days, respectively. The information about the date mainly comes from the weak CO2 band, that is influenced by the well-mixed and increasing concentrations of CO2 in the stratosphere. The availability of such information in the measured spectrum may therefore allow the NN to exploit it rather than the direct CO2 imprint in the spectrum, to estimate XCO2. Thus, our first version of the NN performed well mostly because the XCO2 fields used for the training were remarkably accurate, but it did not bring any added value. Further to this analysis, we designed a second version of the NN, excluding the weak CO2 band from the input. This new version has a different behaviour as it does retrieve XCO2 enhancements downwind of emission hotspots, i.e. a feature that is not in the training dataset. The comparison against the reference Total Carbon Column Observing Network (TCCON) and the surface-air-sample-driven inversion of the Copernicus Atmosphere Monitoring Service (CAMS) remains very good, as in the first version of the NN. In addition, the difference with the CAMS model (also called innovation in a data assimilation context) for NASA Atmospheric CO2 Observations from Space (ACOS) and the NN estimates are significantly correlated. These results confirm the potential of the NN approach for an operational processing of satellite observations aiming at the monitoring of CO2 concentrations and fluxes.

The Polarization and Directionality of Earth Reflectances (POLDER) instrument provides unique cloud droplet radius (CDR) and effective variance (EV) observations for the analysis of clouds on the global scale. However, the cloud droplet size distribution estimated using the conventional POLDER algorithm is limited by its coarse spatial resolution (150 km) and insufficient information for large droplets (CDR > 15 μm). In this study, we proposed an improved primary cloudbow retrieval (PCR) algorithm to estimate CDR and EV from POLDER. Simulated retrievals based on a radiative transfer model indicate that primary cloudbow measurements are sensitive to large droplets (CDR > 15 μm) and enable the retrieval to be applied at a higher spatial resolution; therefore, we employ POLDER polarized measurements from both primary and supernumerary cloudbow regions in the PCR algorithm. Retrieval cases using POLDER measurements reveal that the PCR algorithm is robust when the cloud fields are homogeneous. When the cloud field is heterogeneous, the estimation of CDR is sensitive to the scattering angle ranges as well as the grid size, with uncertainty

An increasingly-large number of cities have designed ambitious climate mitigation plans to contribute to national GHG emission reduction objectives, typically starting with city-scale accountability of their direct and indirect fossil fuel emissions (Self Reported Inventories). Several concepts of spaceborne instruments providing high resolution 2D view of CO2 total column concentrations (XCO2) have been developed to monitor the CO2 anthropogenic emissions. Those images target mainly the CO2 atmospheric plumes from cities and large power plants, expecting that their study may quantify the emissions of those sources. However, there is still a need to develop and asses estimation methods which could process a large number of images in a robust way for such quantifications.In this study, we evaluate the ability to quantify CO2 urban emissions from XCO2 2D images by conducting sensitivity experiments with synthetic images over the Paris area during the winter 2019/2020. Synthetic data were simulated using state-of-the-art mesoscale model simulations at 1km resolution coupled to a high-resolution inventory, all validated against in situ CO2 tower measurements. We compared multiple direct flux calculation methods as described in various studies including Source Pixel, Integrated Mass Enhancement and Cross-sectional methods [Varon et al.,2018], further examined with various configurations, in addition to several formulations of Gaussian plume inversion techniques. These methods are computationally affordable compared to mesoscale inversions based on Eulerian or Lagrangian models, hence able to process rapidly a large amount of data over various cities in the future.We quantified the uncertainties and accuracy for these methods using different combinations of assumptions to i) identify the plume from the city, ii) to determine the corresponding background concentrations from natural and anthropogenic sources outside the city, and iii) to estimate the effective wind speed and direction of the plume. From this large ensemble of approaches and configurations, we identified the most robust methods and parametrizations with their corresponding precisions under various meteorological conditions and specifications of the XCO2 images (esp. spatial resolution and measurement errors).Starting with ideal cases without measurement noise and with perfectly known transport, we further increase the complexity of the experiments towards more realistic conditions in order to quantify the impact of the various sources of uncertainties (i.e. measurement errors, uncertainties in background conditions, uncertain plume detection, transport uncertainties). We show that most methods have to be adapted to handle the spatial extent of the targeted sources and that their performance are good in near steady state conditions. The source pixel method seems to be the less suited for extended source estimation. However, the final uncertainty is mainly driven by the pre-processing steps (background, plume limits and effective wind estimations).

We use a global transport model and satellite retrievals of the carbon dioxide (CO2) column average to explore the impact of CO2 emissions reductions that occurred during the economic downturn at the start of the Covid‐19 pandemic. The changes in the column averages are substantial in a few places of the model global grid, but the induced gradients are most often less than the random errors of the retrievals. The current necessity to restrict the quality‐assured column retrievals to almost cloud‐free areas appears to be a major obstacle in identifying changes in CO2 emissions. Indeed, large changes have occurred in the presence of clouds and, in places that were cloud‐free in 2020, the comparison with previous years is hampered by different cloud conditions during these years. We therefore recommend to favor all‐weather CO2 monitoring systems, at least in situ, to support international efforts to reduce emissions., Key Points Covid‐19 impacted the CO2 column mostly in the vicinity of a few emission locations that changed over time.These places have not been well observed by the OCO‐2 satellite because of frequent or persistent cloud conditions.To support the Paris Agreement on climate, priority should be given on the development of all‐weather carbon‐monitoring systems.

The Polarization and Directionality of Earth Reflectances (POLDER) instrument provides unique cloud droplet radius (CDR) and effective variance (EV) observations for the analysis of clouds on the global scale. However, the cloud droplet size distribution estimated using the conventional POLDER algorithm (Breon et al, 2005) is limited by its coarse spatial resolution (150 km) and insufficient information for large droplets (CDR>15 µm). In this study, we proposed an improved primary cloudbow retrieval (PCR) algorithm to estimate CDR and EV from POLDER. Simulated retrievals based on a radiative transfer model indicate that primary cloudbow measurements are sensitive to large droplets (CDR>15 µm) and enable the retrieval to be applied at a higher spatial resolution; therefore, we employ POLDER polarized measurements from both primary and supernumerary cloudbow regions in the PCR algorithm. Retrieval cases using POLDER measurements reveal that the PCR algorithm is robust when the cloud fields are homogeneous. When the cloud field is heterogeneous, the estimation of CDR is sensitive to the scattering angle ranges as well as the grid size, with uncertainty less than 1 µm. In addition, a spatial resolution of 40-60 km is suitable for the PCR algorithm based on the relationship between the retrieval grid size and the total successful retrievals. Further comparisons between the PCR retrievals and operational products are conducted on the global scale using POLDER measurements for February, May, August and November 2008, revealing that PCR retrievals agree well with operational products on the global scale as CDR

Although less mediatized than deforestation or climate change, biological invasions remain problematic for the conservation of many ecosystems and the maintenance of various socio-economical activities.Understanding the way invasive non-native species spread in their introduced range is enabling a better apprehension of their impacts, the possibility to predict their expansion, and the development of better management strategies. A problem is that a species invasion dynamics are actually composed of a hierarchy of processes occurring simultaneously at various spatiotemporal scales and which are controlled by drivers that are time- or context-dependent. To gain more profound insights into these dynamics, one has to study the patterns they create and their underlying processes at all relevant scales.Occurring on the five continents and highly invasive on at least two of them, Asian knotweeds (Reynoutria spp.) are acknowledged as being among the most invasive species in the world. Gifted with a large environmental tolerance and high abilities for vegetative multiplication, these giant herbaceous plants can quickly form large clonal monocultures that exclude the other plant species, modify biogeochemical cycles, and affect various anthropic activities. Target of management campaigns for decades, knotweeds display an insolent resilience to the great despair of many stakeholders. Despite having been extensively studied, many aspects of their dynamics are still elusive. Consequently, in this thesis, we have tried to highlight what the drivers of the spatiotemporal dynamics of knotweeds across scales are, and how their management could benefit from a better understanding of these dynamics?To answer these questions, we first focused our attention on the clonal dynamics of knotweeds and on their variations when they experience differing conditions in terms of light availability and disturbance (repeated mowing). We have shown that although shade or mowing affects the vigour and the development of clones, it does not prevent their establishment or their growth. In fact, knotweeds seem able to adopt different growth strategies to cope with environmental heterogeneity, suggesting some management avenues. In a second study, we tried to identify the drivers that controlled the expansion of knotweed stands along an elevational gradient. If we showed that the lateral expansion of stands is mostly constrained by their size (and thus, possibly their age) and the vicinity of roads and rivers, we also brought evidences that knotweeds could have the potential to invade mountain regions. Then, to help for the acquisition of large-scale datasets on knotweeds’ distribution, we developed a procedure to accurately detect and map knotweeds using satellite or drone imagery. Our results were quite encouraging and could be useful to both the basic research and to the detection of newly invaded areas, enabling earlier control operations and more efficient management.Finally, we tried to draw a full picture of the current knowledge on the invasion dynamics of knotweeds by reviewing the literature on the movement of these plants across spatial and temporal scales, to discuss and expand the reach of the insights gained in the various chapters of this thesis.; Bien moins médiatisées que la déforestation ou le changement climatique, les invasions biologiques n’en demeurent pas moins problématiques pour la conservation de nombreux écosystèmes ou le bon déroulement de nombreuses activités socio-économiques.Comprendre la façon dont les espèces exotiques envahissantes s’étendent dans les différents milieux qu’elles colonisent c’est permettre à la fois de mieux appréhender leurs impacts, de pouvoir de prédire leur expansion, et de trouver les endroits stratégiques où agir pour contrer ou atténuer les effets indésirables de ces espèces. Le problème est que dynamiques d’invasions d’une espèce regroupent en fait une hiérarchie de processus se produisant simultanément à différentes échelles spatiotemporelles et qui sont contrôlés par des facteurs qui changent en fonction du temps et du contexte d’invasion. Pour acquérir une compréhension profonde de ces dynamiques, il faut donc étudier leurs manifestations et leurs causes aux diverses échelles spatiales et temporelles auxquelles elles se produisent.Présentes sur les cinq continents et très envahissante sur au moins deux, les renouées asiatiques (Reynoutria spp.) sont reconnues comme faisant partie des espèces les plus invasives de la planète. Dotées d’une grande tolérance environnementale et d’importantes capacités de multiplication végétatives, ces plantes herbacées géantes peuvent former rapidement de grandes monocultures clonales qui excluent les autres espèces végétales, modifient les cycles biogéochimiques des zones envahies et perturbent diverses activités anthropiques. Cibles de campagnes de gestion depuis des décennies, elles affichent cependant une résilience insolente qui désespère de nombreux gestionnaires. Bien que très étudiées, de nombreux détails concernant leurs dynamiques nous échappent toujours. Dans ce travail de thèse, nous avons donc cherché à identifier quels sont les facteurs qui contrôlent les dynamiques spatiotemporelles des renouées à différentes échelles, et comment une meilleure compréhension de ces dynamiques clés pourrait profiter à leur gestion ?Pour ce faire, nous nous sommes donc d’abord intéressés à leur dynamiques clonales et à leurs variations en fonction de différentes conditions de stress (ombrage) ou de perturbation (fauchage répétée). Nous avons montré que si les renouées sont bien affectées par des conditions stressantes ou perturbées, cela ne les empêche ni de s’établir, ni de croître. En fait, les renouées semblent pouvoir adopter différentes stratégies de croissance pour pallier ces contraintes, soulevant différentes questions liées à la gestion. Dans une deuxième étude, nous avons cherché quels étaient les variables qui expliquaient l’expansion des taches de renouées le long d’un gradient altitudinal. Si nous avons montré que les dynamiques d’expansion des taches étaient principalement contrôlées par leur taille (et donc potentiellement leur âge) ainsi que par la proximité de routes et de rivières, nous avons également apporté des indices qui suggèrent que les renouées pourraient être potentiellement capables d’envahir les montagnes. Ensuite, pour tenter d’aider à résoudre le problème de l’acquisition des données de distribution des renouées à large échelle, nous avons développé une méthode pour détecter et cartographier les populations de renouées à partir d’images satellites et issues de drones. Notre méthode a montré des résultats encourageants et celle-ci pourrait être utile à l’étude des invasions ainsi qu’à la détection des nouveaux foyers d’invasion pour une gestion plus précoce et efficace des renouées.Enfin, nous avons tenté de dresser un portrait global de la compréhension actuelle des dynamiques d’invasion des renouées en réalisant, en guise de discussion, une grande revue de littérature sur les mouvements de ces plantes à travers les échelles spatiales et temporelles et en y intégrant les apports des autres travaux de cette thèse.

International audience; In-flight assessment of the radiometric performances of space-borne instruments can be achieved by means of vicarious calibration over Pseudo-Invariant Calibration Sites (PICS). PICS are chosen for the high temporal stability of their surface optical properties combined with a high spatial homogeneity. A first list of the main desert PIC sites was identified 20 years ago for the calibration of medium/coarse spatial resolution instruments in the solar spectral range (400–2500 nm). They are located in the Saharan desert and in the Arabian Peninsula. Six of them have since been endorsed by the CEOS/WGCV/IVOS as reference Calibration/Validation test sites. In this study, we have revisited the list of desert PIC sites at the global scale with the aim of (1) assessing if these twenty PICS are still “optimal”, in terms of temporal stability and spatial uniformity, and using up-to-date multi-spectral remote sensing data, and (2) identifying new calibration sites distributed over other areas of the world. We verified that the original sites remain very relevant, although alternate locations in their close vicinity have slightly better characteristics. We proposed four additional targets with similar characteristics, some of which may offer easier logistical access. In order to support radiative transfer simulations of satellite sensor measurements over the sites, we assessed the abilities of several semi-empirical models to reproduce the spectro-directional signatures of six IVOS sites and the four new candidate sites, and we derived climatologies of the main atmospheric properties (trace gas column load and aerosol optical depth).

The linear kernel-driven RossThick-LiSparseReciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was originally developed from the simplified scenarios of continuous and discrete vegetation canopies, and has been widely used to fit multiangle observations of vegetation-soil systems of the land surface in many fields. Although this model was not developed explicitly for snow surfaces, it can capture the geometric-optical effect caused by the shadowing of rugged or undulating snow surfaces. However, in this study, this model has been further developed to better characterize the scattering properties of snow surface, which can also exhibit strongly forward-scattering behavior. This study proposes a new snow kernel to characterize the reflectance anisotropy of pure snow based on the asymptotic radiative transfer (ART) model that assumes snow can be modeled as a semi-infinite, plane-parallel, weakly absorbing light scattering layer. This new snow kernel adopts a correction term with a free parameter α to correct the analytic form of the ART model that has been reported to underestimate observed snow reflectance in the forward-scattering direction in the principal plane (PP), particularly in cases of a large viewing zenith angle (>60°). This snow kernel has now been implemented in the kernel-driven RTLSR BRDF model framework in conjunction with two additional kernels (i.e., the volumetric scattering kernel and geometric-optical scattering kernel) and is validated using observed and simulated multiangle data from three data sources. Pure snow targets were selected from the extensive archive of the Polarization and Directionality of the Earth's Reflectance (POLDER) BRDF data. Antarctic snow field measurements, which were taken from the top of a 32-m-tall tower at Dome C Station and include 6336 spectral bidirectional reflectance factors (BRFs), were also utilized. Finally, a set of simulated BRFs, generated by a hybrid scattering snow model that combines the geometric optics with vector radiative transfer theory, were used to further assess the proposed method. We first retrieve the value of the free parameter α for a comprehensive analysis using single multiangle snow data with a sufficient BRDF sampling. Then, we determine the optimally fixed value of the α parameter as prior information for potential users. The new snow kernel method is shown to be quite accurate, presenting a high correlation coefficient (R2 = ~0.9) and a negligible bias between the modeled BRFs and the various snow BRDF validation data. The finding demonstrates that this snow kernel provides an improved potential compared to that of the original kernel-driven model framework for a pure snow surface in many applications, particularly those involving the global water cycle and radiation budget, where snow cover plays an important role.

International audience; The semi-empirical, kernel-driven, linear RossThick-LiSparseReciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is used to generate the routine MODIS BRDF/Albedo product due to its global applicability and the underlying physics. A challenge of this model in regard to surface reflectance anisotropy effects comes from its underestimation of the directional reflectance signatures near the Sun illumination direction; also known as the hotspot effect. In this study, a method has been developed for improving the ability of the RTLSR model to simulate the magnitude and width of the hotspot effect. The method corrects the volumetric scattering component of the RTLSR model using an exponential approximation of a physical hotspot kernel, which recreates the hotspot magnitude and width using two free parameters (C1 and C2, respectively). The approach allows one to reconstruct, with reasonable accuracy, the hotspot effect by adjusting or using the prior values of these two hotspot variables. Our results demonstrate that: (1) significant improvements in capturing hotspot effect can be made to this method by using the inverted hotspot parameters; (2) the reciprocal nature allow this method to be more adaptive for simulating the hotspot height and width with high accuracy, especially in cases where hotspot signatures are available; and (3) while the new approach is consistent with the heritage RTLSR model inversion used to estimate intrinsic narrowband and broadband albedos, it presents some differences for vegetation clumping index (CI) retrievals. With the hotspot-related model parameters determined a priori, this method offers improved performance for various ecological remote sensing applications; including the estimation of canopy structure parameters.

The authors wish to make the following corrections to this paper [...]

Multiangle remote sensing plays a central role in the development of algorithms for the retrieval of various surface biophysical parameters that are influenced by the reflectance anisotropy. Surface reflectance anisotropy is characterized by the Bidirectional Reflectance Distribution Function (BRDF). Within the past decade, space-borne multiangle observations acquired by the MODerate resolution Imaging Spectroradiometer (MODIS) sensor (which has a gridded spatial resolution of 500 m) and by the POLarization and Directionality of Earth Reflectances (POLDER) sensor (which has a spatial resolution of 6 × 7 km) have been used for a wide variety of global applications. However, it is necessary to fully understand the variability inherent in the surface BRDF information as retrieved from MODIS and POLDER at these two spatial resolutions to optimize their use. In this study, we make use of extensive POLDER Bidirectional Reflectance Factors (BRFs) selected from the entire archive of the POLDER BRDF database and standard MODIS BRDF parameter products (MCD43A1, Collection V005) that were geolocated within the same spatial extents as the POLDER data. The variability in surface BRDF is characterized by investigation of three BRDF model parameters as retrieved from MODIS and POLDER and a comprehensive index indicating the variations in the primary dome-bowl BRDF patterns (the anisotropic flat index (AFX)). The principal information content contained in these BRDF data is characterized by the general BRDF shapes (the BRDF archetypes) that account for >90% of the total variance in these BRDF data. A hotspot-revised BRDF model is used directly on top of the retrieved model BRDF parameters to capture the hotspot effect associated with these BRDF parameters. The main findings of this study show that the variability in surface BRDF, as extracted from the MODIS and POLDER datasets, shares six reciprocal BRDF archetypes. However, the 500-m MODIS BRDF data can uniquely capture some additional extreme BRDF shapes mainly due to the data's finer pixel scales. These original findings are very important, because subsequent albedo retrievals can be significantly impacted by the use of BRDFs of different resolutions. This study provides evidence concerning the influence of spatial resolution on angular variation patterns of optical reflectance as retrieved from the MODIS and POLDER BRDF products.

This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on observing system simulation experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50 % uncertainty on the hourly or sectorial emissions, and with ∼ 25 % uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6 h mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular, the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it.

International audience; The MODIS instruments have been flying onboard the Terra and Aqua platforms and have acquired Earth observation data since early 2000 and mid 2002, respectively. After atmospheric correction, the collected data allows the monitoring of the land cover dynamics. Here, we describe a data processing scheme to generate Earth reflectance and emissivity time series at a sub-kilometer spatial resolution and with a period of 8 days. The data processing scheme removes residual cloud and aerosol contamination in the MODIS products, applies directional correction, and fills the gaps resulting from persistent cloud cover. The resulting database, referred to FondsDeSol, offers a significant improvement with respect to the first version proposed in (Gonzalez et al., 2010), and covers a period of ten years against only one year for the first version. The first motivation of the database is to improve the estimation of at sensor radiances for the design of future sensor in the optical domain. Nevertheless, such database opens the way to new research topics like land surface dynamics, land cover changes, and inter-annual variations due to climate perturbations.; Les instruments MODIS volent sur les plateformes TERRA et AQUA et acquièrent des données d'observation de la Terre depuis début 2000 et mi-2002 respectivement. Après correction atmosphérique, les données collectées permettent le suivi de la dynamique de l'occupation des sols. Dans ce papier, nous décrivons le traitement des données permettant la génération de séries temporelles de réflectances et d'émissivités de la surface à une résolution spatiale sub-kilométrique et avec une période de 8 jours. Au cours du traitement des données, les nuages et la contamination par les aérosols résiduels sont éliminés des produits MODIS, une correction directionnelle est appliquée et les trous résultants d'une couverture nuageuse persistante sont comblés. La base de données FondsDeSol ainsi obtenue offre une amélioration significative au regard de la première version proposée dans (Gonzalez et al. 2010), et couvre une période de 10 ans au lieu de 1 ans pour la première version. La première motivation de cette nouvelle base est d'améliorer l'estimation des luminances pour aider au développement de nouveaux capteurs optiques. Néanmoins, une telle base de données ouvre la voie à de nouveaux sujets de recherche en dynamique de la surface, pour l'étude du changement dans l'occupation des sols ou des variations inter-annuelles dues aux perturbations climatiques.

An inter-comparison study of the aerosol optical thickness (AOT) at 0.55 μm retrieved using different satellite instruments and algorithms based on the analysis of backscattered solar light is presented for a single scene over central Europe on October 13th, 2005. For the first time comparisons have been performed for as many as six instruments on multiple satellite platforms. Ten different algorithms are briefly discussed and inter-compared. It was found that on the scale of a single pixel there can be large differences in AOT retrieved over land using different retrieval techniques and instruments. However, these differences are not as pronounced for the average AOT over land. For instance, the average AOT at 0.55 μm for the area 7–12E, 49–53N was equal to 0.14 for MISR, NASA MODIS and POLDER algorithms. It is smaller by 0.01 for the ESA MERIS aerosol product and larger by 0.04 for the MERIS BAER algorithm. AOT as derived using AATSR gives on average larger values as compared to all other instruments, while SCIAMACHY retrievals underestimate the aerosol loading. These discrepancies are explained by uncertainties

Understanding the spatial dynamics of invasive alien plants is a growing concern for many scientists and land managers hoping to effectively tackle invasions or mitigate their impacts. Consequently, there is an urgent need for the development of efficient tools for large scale mapping of invasive plant populations and the monitoring of colonization fronts. Remote sensing using very high resolution satellite and Unmanned Aerial Vehicle (UAV) imagery is increasingly considered for such purposes. Here, we assessed the potential of several single- and multi-date indices derived from satellite and UAV imagery (i.e., UAV-generated Canopy Height Models—CHMs; and Bi-Temporal Band Ratios—BTBRs) for the detection and mapping of the highly problematic Asian knotweeds (Fallopia japonica; Fallopia × bohemica) in two different landscapes (i.e., open vs. highly heterogeneous areas). The idea was to develop a simple classification procedure using the Random Forest classifier in eCognition, usable in various contexts and requiring little training to be used by non-experts. We also rationalized errors of omission by applying simple “buffer” boundaries around knotweed predictions to know if heterogeneity across multi-date images could lead to unfairly harsh accuracy assessment and, therefore, ill-advised decisions. Although our “crisp” satellite results were rather average, our UAV classifications achieved high detection accuracies. Multi-date spectral indices and CHMs consistently improved classification results of both datasets. To the best of our knowledge, it was the first time that UAV-generated CHMs were used to map invasive plants and their use substantially facilitated knotweed detection in heterogeneous vegetation contexts. Additionally, the “buffer” boundary results showed detection rates often exceeding 90–95% for both satellite and UAV images, suggesting that classical accuracy assessments were overly conservative. Considering these results, it seems that knotweed can be satisfactorily mapped and monitored via remote sensing with moderate time and money investment but that the choice of the most appropriate method will depend on the landscape context and the spatial scale of the invaded area.

The PARASOL instrument provides polarization measurements of the Earth's reflectance. Data processing of these measurements leads to a large and representative dataset of Bidirectional Polarization Distribution Functions (BPDF) for a wide range of surface cover. All surfaces show a similar pattern of the polarized reflectances, with very little polarization at backscattering and a general increase with the phase angle. The largest polarized reflectances are observed facing the sun, with large sun and view angles and amount to 0.02–0.04 depending on the surface type. Simple BPDF models available in the literature predict the correct order of magnitude as well as the main features of its directional signatures. However, these models also show significant biases for some viewing geometries. We propose a new model for the BPDF of natural surfaces, based on theoretical development as well as empirical fit to the PARASOL measurements. This linear model with only one free parameter allows a similar fit to the measurements as a previously published one (Nadal and Breon, 1999), non-linear with two parameters. Because the BPDF of natural surfaces appears to vary very little, a fixed model (i.e. with a priori biome-specific values for the parameter) is defined and may be sufficient for most applications.

In a previous paper, we described a procedure to correct the directional effects in AVHRR reflectance time series. The corrected measurements show much less high frequency variability than their original counterparts, which makes them suitable to study vegetation dynamics. The time series are used here to estimate the start and ending dates of the growing season for 18 years from 1982 to 1999. We focus on the interannual variations of these phenological parameters. A database of in situ phenology observations is used to quantify the accuracy of the satellite-based estimates. Although based on a limited sampling of the Northern mid and high latitudes, the comparison indicates that i) the satellite phenological product contains meaningful information on interannual onset anomalies; ii) there is a higher degree of consistency over regions covered by Broadleaf Forests, Grasses and cereal Crops than over those covered by Needleleaf Forests or Savannas; and iii) the satellite phenological product is of lower quality in regions with mountainous terrain. In favorable conditions, interannual variations of the onset are captured with an accuracy of a few days. As this satellite-derived product captures the interannual onset variability at ground-truth sites, we confidently use it to larger scales studies. Mapped at a continental scale, the onset anomalies show coherent patterns at the regional (≈ 1000 km) scale for the mid and high latitudes of the Northern hemisphere, which is consistent with a meteorological forcing. In the tropics, there is larger spatial heterogeneity, which suggests more complex controls of the phenology. The relation between vegetation phenology and climate is further investigated over Europe by comparing the variability of the satellite-derived vegetation onset and that of the winter North Atlantic Oscillation index, at a fine spatial scale. The strong correlations observed confirm that this climate forcing parameter explains most of the onset variability over a large fraction of Northern Europe (earlier onsets for positive winter NAO), with lower impact towards the south and opposite effects around the Mediterranean basin. The NAO has a predictive character as the January–February NAO index is strongly correlated with the vegetation onset that occurs around April in Northern Europe.

The directional variation of land surface reflectance generates an apparent noise in the time series acquired from satellites with variable observation geometries, which can be corrected through appropriate modeling of the bidirectional reflectance distribution function (BRDF). In a previous paper, we described and validated the VJB method that estimates a target BRDF shape and corrects for directional effects and yet retains the high temporal resolution of the measurement. Here, we analyze its potential to measure the BRDF of targets at the 0.5-km resolution of Moderate Resolution Imaging Spectroradiometer (MODIS). The description of the BRDF in the NASA MCD43A1 product shows very large temporal variations that are unrealistic. However, the reflectance time series, normalized to a standard observation geometry using this modeling, have a similar quality as those derived using VJB. Conversely, the MCD43A1 modeled reflectances for a nonstandard geometry are unrealistically variable. These results indicate that the standard BRDF model inversion used to derive the MCD43A1 product is underconstrained due to the limited directional sampling of the 16-day composite period. The apparent noise in the corrected reflectance time series is significantly larger than the one obtained at lower spatial resolution, and is very much a function of the spatial heterogeneity of the area surrounding the target. These results strongly indicate that the multitemporal MODIS measurement at high spatial resolution (0.5 km) is affected by a change in the effective resolution for off-nadir observation and by inaccurate registration. The resulting noise in the measurements precludes an accurate measurement of the BRDF at such a scale.

The PHYSAT method, which enables identification of four different phytoplankton groups from their impact on the normalized water-leaving radiance (nLw) spectra, is applied to coincident in situ measurements of both chlorophyll a concentration (Chl a ) and nLw. Observations show that measurements acquired in waters dominated by haptophytes, diatoms and Synechococcus-like cyanobacteria have optical properties that deviate significantly from the mean OC4V4 bio-optical model, which is currently used as the standard for global ocean color processing. A specific OC4v4-like relationship, i.e., Chl a as a 4th-order polynomial of the “maximum band ratio”, was fitted for each dominant phytoplankton group identified by PHYSAT. The resulting OC4-SD bio-optical model thus starts from a classification of the dominant phytoplankton group, followed by a species-dependent estimate of Chl a . It has been applied to global daily SEAWIFS data of the year 2001. Monthly mean maps of Chl a derived from OC4-SD or OC4v4 show large regional differences that can reach 50% at high latitudes. The new algorithm leads to lower concentrations in regions where the standard model retrievals are known to be too high, such as the Mediterranean Sea. Conversely, higher concentrations are retrieved in regions dominated by diatom blooms, such as the northern North Atlantic in summer, where previous studies have demonstrated a low bias in standard SEAWIFS Chl a .

International audience; The polarization measurements achieved by the POLDER instrument on ADEOS-! are used for the remote sensing of aerosols over land surfaces. The key advantage of using polarized observations is their ability to systematically correct for the ground contribution, whereas the classical approach using natural light fails. The estimation of land surface polarizing properties from POLDER has been examined in a previous paper. Here we consider how the optical thickness 30 and ,•ngstr6m exponent a of aerosols are derived from the polarized light backscattered by the particles. The inversion scheme is detailed, and illustrative results are presented. Maps of the retrieved optical thickness allow for detection of large aerosol features, and in the case of small aerosols, the $0 and a retrievals are consistent with correlative ground-based measurements. However, because polarized light stems mainly from small particles, the results are biased for aerosol distributions containing coarser modes of particles. To overcome this limitation, an aerosol index defined as the product AI = •0a is proposed. Theoretical analysis and comparison with ground-based measurements suggest that AI is approximately the same when using •0, and a is related to the entire aerosol size distribution or derived from the polarized light originating from the small polarizing particles alone. This invariance is specially assessed by testing the continuity of AI across coastlines, given the unbiased properties of aerosol retrieval over ocean. Although reducing the information concerning the aerosols, this single parameter allows a link between the POLDER aerosol surveys over land and ocean. POLDER aerosol index global maps enable the monitoring of major aerosol sources over continental areas.

The Meteosat geostationary satellites carry a filtered radiometer channel centered at 6.2 μm for the measurement of upper tropospheric humidity. The operational calibration is derived from radiative transfer calculations applied to radiosonde measurements; large fluctuations in the calibration have been noticed. Here, we apply another method based on collocations with NOAA/High-Resolution Infrared Radiometer Sounder (HIRS) channel 12. Radiative transfer calculations show that Meteosat measurements can be accurately predicted from HIRS channel 12 brightness temperatures. In addition, the HIRS instrument has onboard calibration of the complete optics, which makes it suitable as a reference for the calibration of other spaceborne radiometers. Application of the method to 3 years of Meteosat-5 data shows calibration fluctuations significantly smaller than those provided by the operational method. This result indicates that the short-term stability of the instrument calibration is much better than 5%, the variability given by the operational calibration. The proposed calibration coefficient is smaller by about 10–15%, which results in equivalent brightness temperatures biased by about 3–4 K and 35–50% relative error on the upper tropospheric humidity. Hypotheses of the causes for such large differences between the two calibration procedure results are proposed.

International audience; Spaceborne instruments such as POLDER (polarization and directionality of Earth's reflectances) provide multidirectional estimates of the surface reflectance (after atmospheric correction). A better description of the surface cover is needed for an improvement in climate modeling. This paper describes how the inversion of a three-parameter bidirectional model from the measurements yields some variables of interest such as the surface albedo, the leaf area index, the fraction of vegetation, and the daily integrated photosynthetically active radiation absorption. Airborne measurements of POLDER were made during the HAPEX-Sahel experiment over various surface types and for different atmospheric conditions. These measurements together with some "ground truth" allow a validation of the proposed method. The reflectance bidirectional signature of the Sahelian landscape shows some classical features such as a general increase toward backscattering and the hot spot phenomenon. The bidirectional model allows an accurate representation of the observed signatures. However, a large range of angular measurements is necessary to constrain the model inversion and to decrease the uncertainty in the three-parameter retrieval. The surface variables derived from these three parameters are found to be in agreement with the in situ measurements. Obviously, a validation on other landscapes with a higher vegetation coverage is now needed. The technique described in this paper will be applied to the spaceborne POLDER data sets.

Surface reflectance time series measured from space borne instruments, such as the MODIS sensor, show an apparent high-frequency noise that limits their information content. A major contributor to this noise is the directional effect as the target reflectance varies with the observation geometry. The operational MODIS processing inverts the parameters of a BRDF model which are provided in the so-called MCD43C2 product with a frequency of (8 days)− 1. Recently, Vermote et al. (2009) suggested an alternative BRDF inversion method. A major assumption is that the BRDF model shape (i.e. the BRDF normalized by its overall amplitude) varies little throughout the year so that the two model parameters are linear functions of the NDVI. Consequently, a given target BRDF shape is described by four parameters (slope and intercept for the two NDVI-dependent parameters) rather than 2 parameters that change for each 8 days period. This method imposes additional constrain for the surface BRDF inversion. In this paper, we evaluate the performance of these two approaches for the correction of surface reflectance time series. We work at the 0.05° (≈ 5 km) resolution of the CMG grid and analyze a representative set of + 100 targets selected on the basis of the location of AERONET sites. The performance is quantified by the high-frequency noise in the corrected time series. We demonstrate that the performances of the two approaches are very similar. This result demonstrates that a simple four-parameter NDVI-scaled model performs as well as a more complex model with many more degrees of freedom. Besides, the four-parameter model, which is inverted on a given year, can be applied to the measurements of other years with a similar level of performance. Finally, a single “averaged” model can be applied to any target with a performance that is only slightly reduced compared to what is achieved with a model derived through a full inversion of the multi-temporal data. The proposed four-parameter BRDF model permits the reduction of noise in the reflectance time series by a factor of the order of three in the red and four in the near infrared. After correction, the reflectance time series are very clean, with an apparent noise that is ≈ 0.005 in the red band and 0.01 in the near infrared. The quality of the BRDF correction makes it possible to use the individual reflectance time-series at high temporal resolution, rather than indices based on their ratio, and thus retain more information about the vegetation dynamics.

This paper introduces the new Polarization and Directionality of the Earth's Reflectances (POLDER) instrument. The spaceborne POLDER sensor, which is selected to fly aboard the Japanese ADEOS satellite scheduled for launch in early 1996, has nearly completed phase C of its development at the Centre National d'Etudes Spatiales, the French space agency. To prepare for the 1996 space mission, airborne prototypes are being tested and evaluated in the framework of various measurement campaigns. The POLDER sensor is designed to collect global observations of polarized and directional solar radiation reflected by the Earth-atmosphere system for climate and global change studies. Aboard the ADEOS platform, the POLDER mission will provide near-daily coverage of the Earth at 6/spl times/7 km/sup 2/ resolution. The POLDER system will offer unprecedented opportunities to observe biophysical parameters over the oceans and land surfaces. The sensor's unique features, when compared to current and planned spaceborne instruments, include its ability to: 1) measure polarized reflectance in the visible and near-infrared spectral regions; 2) observe Earth target reflectance from 12 directions during a single satellite pass; and 3) operate in two dynamic modes in order to achieve both high signal to noise ratio and wide dynamic range. Six of POLDER's eight channels are optimized for observing atmospheric aerosols, clouds, ocean color, and land surfaces. The other two are centered on the H/sub 2/O and O/sub 2/ absorption bands for retrieving atmospheric water vapor amount and cloud top altitude, respectively. POLDER data will be subject to the high calibration standards defined by the POLDER mission team, with absolute calibration accuracies of 2% for the shorter wavelength channels (/spl lambda//spl les/565 nm) and 3% for the longer wavelengths. A 1% accuracy is the goal for the intercalibration between the spectral channels. The POLDER instrument aboard ADEOS will contribute significantly to climate-related research on aerosol cycling, cloud-radiation interactions, the Earth radiation budget, ocean primary productivity, and continental biosphere dynamics. POLDER mission's scientific objectives will be to: 1) map atmospheric aerosols, including their sources and transport, and study their influence on the Earth radiation budget; 2) assess cloud properties, namely their height, phase and type; 3) estimate total integrated water vapor amount; 4) improve Earth radiation budget estimates; 5) estimate chlorophyll-like pigment content in the ocean surface layer and its role in the carbon cycle; and 6) characterize land surface properties and vegetation cover. >

The aerosol remote sensing from space has started in the 1980's using observations provided by geostationary satellites or by polar orbiting platforms not specifically designed for observing aerosols. As a result, the number of retrieved parameters was limited and retrievals in the visible restricted over ocean. Over land, because of the important surface contribution, the aerosol detection was performed in the UV (or in the dark blue) where most of the earth surfaces are dark enough but with overlap of multiple aerosols parameters, content, altitude and absorption. Instruments dedicated to aerosol monitoring are recently available and the POLDER instrument on board the PARASOL mission is one of them. By measuring the wavelength, angular and polarization properties of the radiance at the top of the atmosphere, in coordination with the other A-Train instruments, PARASOL can better quantify aerosol optical depths (AOD) and improve the derivation of the radiative and physical properties. The instrument, the inversion schemes and the list of aerosol parameters are described. Examples of retrieved aerosol parameters are provided as well as innovative approaches and further inversion techniques.

The POLDER (POLarization and Directionality of the Earth's Reflectances) instrument provides polarized reflectance measurements that can be used to distinguish atmospheric and surface contributions to reflectance. Polarized reflectance measurements can then be used for an accurate aerosol estimation over land. The POLDER instrument was flown for the first time on 17 June 1990 over the “La Crau” site, in southern France and the results are present in this article. The POLDER instrument is scheduled for launch in 1995 on the Japanese ADEOS (ADvanced Earth Observing System) platform. Surface based atmospheric optic measurements (spectral optical thickness, sky radiance) are used to estimate the aerosol refractive index and size distribution. The corresponding aerosol model is then used in a radiative transfer model to simulate POLDER polarized measurements. The correlation between the observations and the simulations is good for the 550 nm and 650 nm wavelengths, but the simulation is biased for the 850 nm wavelength. These results indicate that, compared with the atmospheric contribution to the polarized reflectance, the surface contribution can be neglected at shorter wavelengths, but not so in near infrared wavelengths. The POLDER instrument allows multidirectional reflectance measurements. A surface target bidirectional reflectance, therefore, can be sampled at various viewing angles. In this article, we investigate the angular variations of the surface reflectance of various surface covers. The main observed variations are: i) a limb brightening; ii) a larger reflectance in the backscattering direction; iii) a local maximum in the forward direction for the shorter wavelengths, indicating specular reflection by the leaves. A very simple empirical model is proposed to quantify the main reflectance angular variations.

In a companion article, an analytical model for the cloud-free atmosphere/ocean system directional reflectance is developed. In this article, the model is inverted against airborne POLDER directional and spectral measurements acquired during its first oceanic campaign. After an interband calibration of the measurements on the sun glitter reflectance, the model fits the observations with a 1.2% relative accuracy. The aerosol optical thickness and the Angstrom coefficient retrieved by the inversion procedure agree very well with surface measurements. The spectral ocean reflectance accuracy is not sufficient, however, to retrieve the chlorophyll pigment concentration. The directional specular reflectance is used to derive the wave slope distribution, which leads to the wind speed and direction. These parameters agree very well with surface observations. If this finding is confirmed during forthcoming campaigns, spaceborn POLDER measurements could then be used for a global oceanic retrieval of wind speed and direction. The analytical model accurately reproduces all spectral and angular reflectance variations observed with POLDER. These include a large reflectance asymmetry with respect to the principal plane associated with the anisotropic wave slope distribution.

We show that the Polarization and Directionality of the Earth's Reflectances (POLDER)/ADEOS two-dimensional imaging concept permits measurement of the innermost few degrees of the hot spot (the enhancement of land surface reflectance when Sun and view directions coincide) with an angular resolution of approximately 0.3@. The analysis approach assumes that the hot-spot characteristics (amplitude, width) are homogeneous over regions of about 50 km in extent. Examples of the hot spot in red and near-infrared bands are shown. The five hot spot examples presented show a variation of less than a factor of two in both amplitude and width, despite sampling a wide variety of land cover including grassland, woodland and dense eucalypt forest. POLDER offers the potential for the first systematic global mapping of hot-spot characteristics, and hence a possible new source of quantitative information on vegetation structure.

Despite their primary contribution to climate change, there are still large uncertainties on the sources and sinks of the main greenhouse gases: carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). A better knowledge of these sources is necessary to understand the processes that control them and therefore to predict their variations. Indeed, large feedbacks between climate change and greenhouse gas fluxes are expected during the 21st century. Sources and sinks of these gases generate spatial and temporal gradients that can be measured either in situ or from space. One can then estimate the surface fluxes, either positive or negative, from concentration measurements through a so-called atmospheric inversion. Surface measurements are currently used to estimate the fluxes at continental scales. The high density of spaceborne observations allows potentially a much higher resolution. Several remote sensing techniques can be used to measure atmospheric concentration of greenhouse gases. These techniques have motivated the development of spaceborne instruments, some of them already in space and others under development. However, the accuracy of the current estimates is still not sufficient to improve our knowledge on the greenhouse gases sources and sinks. Rapid improvements are expected during the forthcoming years with a strong implication of the scientific community and the launch of dedicated instruments, optimized for the measurement of CO2 and CH4 concentrations.

International audience; We present a method for simultaneously retrieving aerosol and surface parameters from ground-based and satellite observations collocated in space and time. We show that a combination of down and up-looking observations provides sufficient measurement constraints for characterizing both aerosol and surface properties with minimal assumptions. In order to employ this concept in AERONET processing, the standard inverse algorithm [Dubovik, O. & King, M. D. (2000), A flexible inversion algorithm for retrieval of aerosol optical properties from sun and sky radiance measurements. Journal of Geophysical Research, 105, 20673–20696] has been modified to retrieve surface reflectance in addition to aerosol parameters when co-incident satellite measurements are available.The method was applied to observations of smoke and desert dust over the Mongu (Zambia) and Solar Village (Saudi Arabia) AERONET sites respectively. The AERONET data were complemented by available observations from the MISR, MODIS, and POLDER-2 satellite sensors. The retrieved bidirectional reflectance factor (BRF) and surface albedo comparison shows good agreement between results obtained using observations from different satellites. The robustness of the method is tested by analyzing surface albedo time series retrieved during periods of high aerosol optical depth variability and low seasonal changes in surface reflectance. The analysis shows that the performance of retrieval algorithm is stable under different aerosol loadings. It is shown that much of the observed surface albedo temporal variability could be attributed mostly to the combined uncertainty in satellite radiometric calibration and aerosol vertical distribution for Mongu and to differences in satellite angular sampling on different days for Solar Village. The sensitivity of surface retrievals to assumptions on aerosol vertical distribution and aerosol particle shape are analyzed. It is found that the maximum error in retrieved surface albedo at 0.44 μm is 0.035 for aerosol optical depth 0.85 at 0.44 μm. For aerosol optical depths lower than ∼ 0.7 the error in retrieved surface albedo is less than 0.02. Analysis of particle shape assumptions on surface retrievals showed that aerosol particle non-sphericity significantly affects the angular shape of BRF, but not the surface albedo. Finally, the sensitivity of AERONET aerosol retrievals to uncertainty in assumed surface reflectance is analyzed by comparing aerosol retrievals obtained with different surface assumptions. It is found that the uncertainty in surface reflectance model employed in the version 1 AERONET operational algorithm is larger than was previously assumed in [Dubovik, O., Smirnov, A., Holben, B. N., King, M. D., Kaufman, Y. J., Eck, T. F., & Slutsker, I. (2000), Accuracy assessment of aerosol optical properties retrieved from AERONET sun and sky radiance measurements. Journal of Geophysical Research, 105, 9791–9806] and may have more significant effect on the retrieved aerosol properties than was documented in that work. In particular, larger errors were encountered for the real part of the refractive index (∼ 0.05–0.07 increase) and maximum of the particle size distribution (∼ 20% decrease) retrievals for the Mongu case, when the aerosol optical depth was relatively small (∼ 0.4 at 0.44 μm). The retrieved single scattering albedo uncertainties were within the error bars (0.03) estimated in [Dubovik, O., Smirnov, A., Holben, B. N., King, M. D., Kaufman, Y. J., Eck, T. F., & Slutsker, I. (2000), Accuracy assessment of aerosol optical properties retrieved from AERONET sun and sky radiance measurements. Journal of Geophysical Research, 105, 9791–9806], with the exception of the 0.44 μm retrievals for the desert dust case when they increased by ∼ 0.09 and 0.07 for low and high aerosol loadings respectively.

A method for simultaneously retrieving aerosol and surface parameters from ground based and satellite observations collocated in space and time is presented. The improvements in aerosol and surface reflectance characterization are discussed.

This paper describes a correction of directional effects in AVHRR reflectance time series. The method relies on a priori directional signatures, in the red and near infrared, for various surface covers. The reflectance normalization is applied to the historical Pathfinder AVHRR Land (PAL) data set acquired between 1981 and 1999. The high frequency variability in the reflectance time series, which is interpreted as a noise due to varying observation geometry and directional effects, is reduced by a factor greater than 1.7 for most vegetated surfaces. For the analysis of the vegetation annual cycle and its inter-annual variations, we recommend the use of the Difference Vegetation Index (DVI), following a prior correction of the directional effects, instead of the commonly used NDVI. Indeed, DVI appears more robust than NDVI to noise resulting from atmospheric perturbations, which makes it a good candidate for long-term ecological surveys and climate change studies.

International audience Properly handling satellite data to constrain the inversion of CO2 sources and sinks at the Earth surface is a challenge motivated by the limitations of the current surface observation network. In this paper we present a Bayesian inference scheme to tackle this issue. It is based on the same theoretical principles as most inversions of the flask network but uses a variational formulation rather than a pure matrix-based one in order to cope with the large amount of satellite data. The minimization algorithm iteratively computes the optimum solution to the inference problem as well as an estimation of its error characteristics and some quantitative measures of the observation information content. A global climate model, guided by analyzed winds, provides information about the atmospheric transport to the inversion scheme. A surface flux climatology regularizes the inference problem. This new system has been applied to 1 year's worth of retrievals of vertically integrated CO2 concentrations from the Television Infrared Observation Satellite Operational Vertical Sounder (TOVS). Consistent with a recent study that identified regional biases in the TOVS retrievals, the inferred fluxes are not useful for biogeochemical analyses. In addition to the detrimental impact of these biases, we find a sensitivity of the results to the formulation of the prior uncertainty and to the accuracy of the transport model. Notwithstanding these difficulties, four-dimensional inversion schemes of the type presented here could form the basis of multisensor data assimilation systems for the estimation of the surface fluxes of key atmospheric compounds.

Reflectance measurements acquired with the spaceborne POLDER instrument are used to analyze the variability of land surface directional signatures as a function of vegetation cover type. The reflectance directional signatures are quantified by the three parameters of a modified version of the Ross–Li reflectance model. The variability of the estimated parameters with respect to the seven MODIS biome classes was found to be higher within the classes than between classes, with the exception of the desert targets that show more isotropic reflectances. A limited number of standard BRDFs (typically 5 in the red and near infrared) capture most of the variability of the directional reflectance measurements, supporting the idea that different land surfaces have similar directional signatures. Over vegetation targets, they are characterized by a strong increase toward backscattering and much smaller variations in forward directions. The results express the diversity in structural situations within a given biome class and indicate that, at the resolution of the POLDER sensor, i.e. a few kilometers, the BRDF contains little information on the dominant vegetation type. We show that standard directional signatures may be used to correct the reflectance measurements for directional effects with an RMS error on the order of 0.011 in the red and 0.015 in the near infrared.

International audience; Cloud droplet effective radius (CDR) can be estimated from the spectral signature of cloud reflectance. The technique has been applied to measurements of the Advanced Very High Resolution Radiometer instrument and more recently to the Moderate Resolution Imaging Spectroradiometer (MODIS). Another technique relies on the directional signature of the polarized reflectance and has been applied to observations from Polarization and Directionality of the Earth's Reflectances (POLDER) onboard Advanced Earth Observation Satellite (ADEOS). Although the latter technique requires very specific conditions, we argue that, when applicable, it is very accurate. A large fraction of successful POLDER estimates are derived from measurements over stratocumulus cloud fields. During portions of 2003, POLDER and MODIS acquired near coincident observations. The data can then be used for an evaluation of the two CDR products. The two datasets are highly correlated over the oceans albeit with a MODIS high bias of about 2 μm. The correlation breaks down when POLDER retrieves small droplets (less than 7 μm), which occurs over most land surfaces as well as polluted oceanic areas. We discuss the possible causes for biases and errors. Although differences in the two CDR estimates are expected because of the differences in the spatial scale and vertical weighting function, we did not find a fully satisfactory explanation for the bias and lack of correlation over land surfaces. It seems, however, that the spatial variability as seen by MODIS is larger than that deduced from POLDER measurements, in particular over land surfaces.

The Orbiting Carbon Observatory (OCO) mission will make the first global, space-based measurements of atmospheric carbon dioxide (CO 2 ) with the precision, resolution, and coverage needed to characterize CO 2 sources and sinks on regional scales. The measurement approach and instrument specifications were determined through an analysis of existing carbon cycle data and a series of observing system simulation experiments. During its 2-year mission, OCO will fly in a 1:15 PM sun-synchronous orbit with a 16-day ground-track repeat time, just ahead of the EOS Aqua platform. It will carry a single instrument that incorporates three bore-sighted high-resolution spectrometers designed to measure reflected sunlight in the 0.76-μm O 2 A-band and in the CO 2 bands at 1.61 and 2.06 μm. Soundings recorded in these three bands will be used to retrieve the column-averaged CO 2 dry air mole fraction (X CO2 ). A comprehensive validation program was included in the mission to ensure that the space-based X CO2 measurements have precisions of ∼0.3% (1 ppm) on regional scales. OCO measurements will be used in global synthesis inversion and data assimilation models to quantify CO 2 sources and sinks. While OCO will have a nominal lifetime of only 2 years, it will serve as a pathfinder for future long-term CO 2 monitoring missions. © 2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Multidirectional observation from the spaceborne POLDER (Polarization and Directionality of the Earth Reflectance) instrument makes it possible to measure the bidirectional reflectance of a large variety of Earth targets. A careful selection of cloud-free measurements with a large directional coverage lead to about 22,000 sets of measured Bidirectional Reflectance Distribution Functions (BRDFs). This data set is used to evaluate the ability of analytical models to reproduce the observed directional signatures. Among those evaluated, the best models appear to be the three-parameter linear Ross–Li model, and the nonlinear Rahman–Pinty–Verstraete (RPV) model. On the other hand, all models fail to accurately reproduce the sharp reflectance increase (hot spot) close to the backscattering direction. Based on physical considerations, we suggest a modification of the Ross–Li model, without adding a free parameter, to account for the complex radiative transfer within the canopy that leads to the hot spot signature. The modified linear model performs better than all others, including the RPV nonlinear model. Although the correction modifies the retrieved directional signature parameters, it does not change significantly the surface albedo estimates.

International audience; Polarization and directionality of the Earth's reflectances (POLDER) is a multispectral imaging radiometer-polarimeter with a wide field-of-view, a moderate spatial resolution, and a multi-angle viewing capability. It functioned nominally aboard ADEOS1 from November 1996 to June 1997. When the satellite passes over a target, POLDER allows to observe it under up to 14 different viewing directions and in several narrow spectral bands of the visible and near-infrared spectrum (443-910 nm). This new type of multi-angle instruments offers new opportunity for deriving cloud parameters at global scale. The aim of this short overview paper is to point out the main contributions of such an instrument for cloud study through its original instrumental capabilities (multidirectionality, multipolarization, and multispectrality). This is mainly illustrated by using ADEOS 1-POLDER derived cloud parameters which are operationally processed by CNES and are available since the beginning of 1999.

Currently two polar orbiting satellite instruments measure CO2 concentrations in the Earth's atmosphere, while other missions are planned for the coming years. In the future such instruments might become powerful tools for monitoring changes in the atmospheric CO2 abundance and to improve our quantitative understanding of the leading processes controlling this. At the moment, however, we are still in an exploratory phase where first experiences are collected and promising new space-based measurement concepts are investigated. This study assesses the potential of some of these concepts to improve CO2 source and sink estimates obtained from inverse modelling. For this purpose the performance of existing and planned satellite instruments is quantified by synthetic simulations of their ability to reduce the uncertainty of the current source and sink estimates in comparison with the existing ground-based network of sampling sites. Our high resolution inversion of sources and sinks (at 8º x 10º allows us to investigate the variation of instrument performance in space and time and at various temporal and spatial scales. The results of our synthetic tests clearly indicate that the satellite performance increases with increasing sensitivity of the instrument to CO2 near the Earth's surface, favoring the near infra-red technique. Thermal infrared instruments, on the contrary, reach a better global coverage, because the performance in the near infrared is reduced over the oceans owing to a low surface albedo. Near infra-red sounders can compensate for this by measuring in sun-glint, which will allow accurate measurements over the oceans, at the cost, however, of a lower measurement density. Overall, the sun-glint pointing near infrared instrument is the most promising concept of those tested. We show that the ability of satellite instruments to resolve fluxes at smaller temporal and spatial scales is also related to surface sensitivity. All the satellite instruments performed relatively well over the continents resulting mainly from the larger prior flux uncertainties over land than over the oceans. In addition, the surface networks are rather sparse over land increasing the additional benefit of satellite measurements there. Globally, rather challenging satellite instrument precisions are needed to compete with the surface network (about 1 ppmv for weekly and 8° × 10° averaged SCIAMACHY columns). Regionally, however, these requirements relax considerably, increasing to 5 ppmv for SCIAMACHY over tropical continents. This points not only to an interesting research area using SCIAMACHY data, but also to the fact that satellite requirements should not be quantified by only a single number. The applicability of our synthetic results to real satellite instruments is limited by rather crude representations of instrument and data retrieval related uncertainties. This should receive high priority in future work.

For better knowledge of the carbon cycle, there is a need for spaceborne measurements of atmospheric CO2 concentration. Because the gradients are relatively small, the accuracy requirements are better than 1%. We analyze the feasibility of a CO2-weighted-column estimate, using the differential absorption technique, from high-resolution spectroscopic measurements in the 1.6- and 2-microm CO2 absorption bands. Several sources of uncertainty that can be neglected for other gases with less stringent accuracy requirements need to be assessed. We attempt a quantification of errors due to the radiometric noise, uncertainties in the temperature, humidity and surface pressure uncertainty, spectroscopic coefficients, and atmospheric scattering. Atmospheric scattering is the major source of error [5 parts per 10 (ppm) for a subvisual cirrus cloud with an assumed optical thickness of 0.03], and additional research is needed to properly assess the accuracy of correction methods. Spectroscopic data are currently a major source of uncertainty but can be improved with specific ground-based sunphotometry measurements. The other sources of error amount to several ppm, which is less than, but close to, the accuracy requirements. Fortunately, these errors are mostly random and will therefore be reduced by proper averaging.

Analyses the anisotropic properties of Sahelian vegetation as seen by POLDER in the framework of the 1992 HAPEX-Sahel experiment. The backscattering effect is the main perturbation of the surface albedo measurement. A model is used to firstly correct this effect and further generates reflectance data sets in Sun-view geometries where relationships have been established between vegetation indices and land-surface key-parameters such as the fraction of vegetation, the LAI and the f/sub APAR/.

The hot spot is an enhancement in the optical reflectance of land surfaces at view directions close to the antisolar (exact backscatter) direction. The two-dimensional imaging capability of POLDER on ADEOS has previously been exploited to measure the hot spot on homogeneous land surfaces from space with an angular resolution of 0.3/spl deg/, by using the variation in view direction with spatial position across a single image frame. This paper extends that approach to inhomogeneous areas by estimating the non-hot-spot component of the reflectance from views of the scene at directions far from the hot spot direction. The technique is robust enough to be applied to essentially any POLDER image in which the hot spot falls on cloud-free land. On a single orbit down eastern Australia, the half-width of the hot spot at 670 nm has the rather restricted range of 1/spl deg/-2/spl deg/ despite sampling a broad range of land cover types.

International audience; The POLDER (POlarization and Directionality of the Earth's Reflectances) instrument, developed by the French Space Agency (CNES) has flown on board the ADEOS-1/NASDA platform from November 1996 until June 1997. The sensor has a wide field of view (2400km swath) for collecting global daily data and has multi-angle viewing capability. It measures the solar radiation reflected by the Earth in eight spectral bands. For three of these bands (0.443, 0.670 and 0.865 μm), measurements include the polarization ratio by the use of 3 polarizers. This measurement strategy provides unique information on aerosols, clouds and surfaces.

Global map of aerosol parameters (optical thickness, Angstrom exponent, and refractive index) are derived from the POLDER instrument on board the ADEOS-1 platform. This paper focuses on aerosol optical thickness and Angstrom exponent retrievals that are based on visible and near infrared back scattering measurements. Assessment of the retrieval quality is achieved by means of comparison with AERONET sunphotometer data. The results show that the POLDER measurements can be used to distinguish several aerosol types from their Angstrom coefficients, in addition to a precise estimate of the aerosol optical thickness.

The POLDER instrument on board ADEOS provides the first opportunity to apply the two-channel ratio technique in the near infrared to retrieve atmospheric water vapor content at the global scale. Over land, POLDER estimates compare well with radiosonde measurements, with a 3.1-kg m/sup -2/ rms error. There is a clear negative bias of a few kg m/sup -2/ however. This bias can be explained by the spectral variation of the target reflectance between the two bands used for the estimate. Over ocean, POLDER estimates compare very well with either radiosonde measurements (6.9 kg m/sup -2/ rms error) or SSM/I estimates (4.2 kg m/sup -2/ rms error). A mapped POLDER product shows a good overall similarity with ECMWF analyzed field, with smaller synoptic structures in the POLDER field. An example of the monthly product is presented.

POLDER is a CNES instrument on-board ADEOS polar orbiting satellite, which was successfully launched in August 1996. In November 1996, POLDER entered its nominal acquisition phase and functioned perfectly until ADEOS early end of service in June 1997. POLDER is a multispectral imaging radiometer/polarimeter designed to collect global and repetitive observations of the solar radiation reflected by the Earth/atmosphere system, with a wide field of view (2400 km) and a moderate geometric resolution (6 km). The instrument concept is based on telecentric optics, on a rotating wheel carrying 15 spectral filters and polarizers, and on a bidimensional CCD detector array. In addition to the classical measurement and mapping characteristics of a narrow-band imaging radiometer, POLDER has a unique ability to measure polarized reflectances using three polarizers (for three of its eight spectral bands, 443 to 910 nm), and to observe target reflectances from 13 different viewing directions during a single satellite pass. One of POLDER original features is that its in-flight radiometrical calibration does not rely on any on-board device. Many calibration methods using well-characterized calibration targets have been developed to achieve a very high calibration accuracy. This paper presents the various methods involved in the absolute in-flight calibration plan and the results obtained during the calibration phase of the instrument: absolute calibration over molecular scattering, inter-band calibration over sunglint and clouds, inter-calibration with OCTS, water vapor channels calibration over sunglint using meteorological analysis. A brief description of the algorithm and of the performances of each method is given.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.