Land surface albedo from MSG/SEVIRI: retrieval method, validation, and application for weather forecast

The European Meteorological Satellite Organization (EUMETSAT) maintains a number of decentralized processing centers dedicated to different scientific themes. The Portuguese Meteorological Institute hosts the Satellite Application Facility on Land Surface Analysis (LSA-SAF). The primary objective of the LSA-SAF is to provide added-value products for the meteorological and environmental science communities with main applications in the fields of climate modeling, environmental management, natural hazards management, and climate change detection. Since 2005 data from Meteosat Second Generation satellite are routinely processed in near real time by the LSA-SAF operational system in Lisbon. Presently, the delivered operational products comprise land surface albedo and temperature, shortwave and long-wave downwelling radiation fluxes, vegetation parameters and snow cover. After more than ten years (1999-2010) of research, development, and progressive operational activities, a summary of the surface albedo product characteristics and performances is presented. The relevance of LSA-SAF albedo product is analyzed through a weather forecast model (ALADIN) in order to account for the inter-annual spatial and temporal variability. Results clearly show a positive impact on the 12-hour forecast of 2m temperatures

Comparison of two methods for aerosol optical depth retrieval over North Africa from MSG/SEVIRI data

A comparison between the algorithm for Land Aerosol property and Bidirectional reflectance Inversion by Time Series technique (LABITS) and a daily estimation of aerosol optical depth (AOD) algorithm (AERUS-GEO) over land surface using MSG/SEVIRI data over North Africa is presented. To obtain indications about the quantitative performance of two AOD retrieval methods mentioned above, daily SEVIRI AOD values is considered with respect to those measured from the global aerosol-monitoring Aerosol Robotic Network (AERONET) data. The correlation coefficient (R2) between retrieved SEVIRI AOD at 650 nm from the AERUS-GEO algorithm and the AERONET Level 2.0 daily average AOD at 675 nm is 0.80 and root mean square error (RMSE) is 0.044, and R2 between retrieved AOD from the LABITS algorithm and AERONET AOD is 0.80 and RMSE is 0.037

Satellite remote sensing of aerosols using geostationary observations from MSG-SEVIRI

Aerosols play a fundamental role in physical and chemical processes affecting regional and global climate, and have adverse effects on human health. Although much progress has been made over the past decade in understanding aerosol-climate interactions, their impact still remains one of the largest sources of uncertainty in climate change assessment. The wide variety of aerosol sources and the short lifetime of aerosol particles cause highly variable aerosol fields in both space and time. Groundbased measurements can provide continuous data with high accuracy, but often they are valid for a limited area and are not available for remote areas. Satellite remote sensing appears therefore to be the most appropriate tool for monitoring the high variability of aerosol properties over large scales. Passive remote sensing of aerosol properties is based on the ability of aerosols to scatter and absorb solar radiation. Algorithms for aerosol retrieval from satellites are used to derive the aerosol optical depth (AOD), which is the aerosol extinction integrated over the entire atmospheric column. The aim of the work described in this thesis was to develop and validate a new algorithm for the retrieval of aerosol optical properties from geostationary observations with the SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) instrument onboard the MSG (Meteorological Second Generation) satellite. Every 15 minutes, MSG-SEVIRI captures a full scan of an Earth disk covering Europe and the whole African continent with a high spatial resolution. With such features MSG-SEVIRI offers the unique opportunity to explore transport of aerosols, and to study their impact on both air quality and climate. The SEVIRI Aerosol Retrieval Algorithm (SARA) presented in this thesis, estimates the AOD over sea and land surfaces using the three visible channels and one near-infrared channel of the instrument. Because only clear sky radiances can be used to derive aerosol information, a stand-alone cloud detection algorithm was developed to remove cloud contaminated pixels. The cloud mask was generated over Europe for different seasons, and it compared favorably with the results from other cloud detection algorithms - namely the cloud mask algorithm of Meteo-France for MSG-SEVIRI, and the MODIS (Moderate Resolution Imaging Spectroradiometer) algorithm. The aerosol information is extracted from cloud-free scenes using a method that minimizes the error between the measured and the simulated radiance. The signal observed at the satellite level results from the complex combination of the surface and the atmosphere contributions. The surface contribution is either parameterized (over sea), or based on a priori values (over land). The effects of atmospheric gases and aerosols on the radiance are simulated with the radiative transfer model DAK (Doubling-Adding-KNMI) for different atmospheric scenarios. The algorithm was applied for various case studies (i.e. forest fires, dust storm, anthropogenic pollution) over Europe, and the results were validated against groundbased measurements from the AERONET database, and evaluated by comparison with aerosol products derived from other space-borne instruments such as the Terra/- Aqua-MODIS sensors. In general, for retrievals over the ocean, AOD values as well as their diurnal variations are in good agreement with the observations made at AERONET coastal sites, and the spatial variations of the AOD obtained with the SARA algorithm are well correlated with the results derived from MODIS. Over land, the results presented should be considered as preliminary. They show reasonable agreement with AERONET and MODIS, however extra work is required to improve the accuracy of the retrievals based on the proposed metho

ESTIMATING LAND SURFACE ALBEDO FROM SATELLITE DATA

Land surface albedo, defined as the ratio of the surface reflected incoming and outgoing solar radiation, is one of the key geophysical variables controlling the surface radiation budget. Surface shortwave albedo is widely used to drive climate and hydrological models. During the last several decades, remotely sensed surface albedo products have been generated through satellite-acquired data. However, some problems exist in those products due to instrument measurement inaccuracies and the failure of current retrieving procedures, which have limited their applications. More significantly, it has been reported that some albedo products from different satellite sensors do not agree with each other and some even show the opposite long term trend regionally and globally. The emergence of some advanced sensors newly launched or planned in the near future will provide better capabilities for estimating land surface albedo with fine resolution spatially and/or temporally. Traditional methods for estimating the surface shortwave albedo from satellite data include three steps: first, the satellite observations are converted to surface directional reflectance using the atmospheric correction algorithms; second, the surface bidirectional reflectance distribution function (BRDF) models are inverted through the fitting of the surface reflectance composites; finally, the shortwave albedo is calculated from the BRDF through the angular and spectral integration. However, some problems exist in these algorithms, including: 1) "dark-object" based atmospheric correction methods which make it difficult to estimate albedo accurately over non-vegetated or sparsely vegetated area; 2) the long-time composite albedo products cannot satisfy the needs of weather forecasting or land surface modeling when rapid changes such as snow fall/melt, forest fire/clear-cut and crop harvesting occur; 3) the diurnal albedo signature cannot be estimated in the current algorithms due to the Lambertian approximation in some of the atmospheric correction algorithms; 4) prior knowledge has not been effectively incorporated in the current algorithms; and 5) current observation accumulation methods make it difficult to obtain sufficient observations when persistent clouds exist within the accumulation window. To address those issues and to improve the satellite surface albedo estimations, a method using an atmospheric radiative transfer procedure with surface bidirectional reflectance modeling will be applied to simultaneously retrieve land surface albedo and instantaneous aerosol optical depth (AOD). This study consists of three major components. The first focuses on the atmospheric radiative transfer procedure with surface reflectance modeling. Instead of executing atmospheric correction first and then fitting surface reflectance in the previous satellite albedo retrieving procedure, the atmospheric properties (e.g., AOD) and surface properties (e.g., BRDF) are estimated simultaneously to reduce the uncertainties produced in separating the entire radiative transfer process. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua are used to evaluate the performance of this albedo estimation algorithm. Good agreement is reached between the albedo estimates from the proposed algorithm and other validation datasets. The second part is to assess the effectiveness of the proposed algorithm, analyze the error sources, and further apply the algorithm on geostationary satellite - the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). Extensive validations on surface albedo estimations from MSG/SEVIRI observations are conducted based on the comparison with ground measurements and other satellite products. Diurnal changes and day-to-day changes in surface albedo are accurately captured by the proposed algorithm. The third part of this study is to develop a spatially and temporally complete, continuous, and consistent albedo maps through a data fusion method. Since the prior information (or climatology) of albedo/BRDF plays a vital role in controlling the retrieving accuracy in the optimization method, currently available multiple land surface albedo products will be integrated using the Multi-resolution Tree (MRT) models to mitigate problems such as data gaps, systematic bias or low information-noise ratio due to instrument failure, persistent clouds from the viewing direction and algorithm limitations. The major original contributions of this study are as follows: 1) this is the first algorithm for the simultaneous estimations of surface albedo/reflectance and instantaneous AOD by using the atmospheric radiative transfer with surface BRDF modeling for both polar-orbiting and geostationary satellite data; 2) a radiative transfer with surface BRDF models is used to derive surface albedo and directional reflectance from MODIS and SEVIRI observations respectively; 3) extensive validations are made on the comparison between the albedo and AOD retrievals, and the satellite products from other sensors; 4) the slightly modified algorithm has been adopted to be the operational algorithm of Advanced Baseline Imager (ABI) in the future Geostationary Operational Environmental Satellite-R Series (GOES-R) program for estimating land surface albedo; 5) a framework of using MRT is designed to integrate multiple satellite albedo products at different spatial scales to build the spatially and temporally complete, continuous, and consistent albedo maps as the prior knowledge in the retrieving procedure

Description and validation of an AOT product over land at the 0.6 μm channel of the SEVIRI sensor onboard MSG

The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to the provision of observations for climate monitoring and research. We use the data in visible and near infrared (NIR) channels to derive the aerosol optical thickness (AOT) over land. The algorithm is based on the assumption that the top of the atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-days time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models is used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and NIR spectral bands. <br><br> The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3 km at sub-satellite point, over the entire SEVIRI disk covering Europe, Africa and part of South America. The resulting AOT, a level 2 product at the native temporal and spatial SEVIRI resolutions, is presented and evaluated in this paper. <br><br> The AOT has been validated using ground based measurements from AErosol RObotic NETwork (AERONET), a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, <i>r</i> = 0.64, with a slight overestimate, bias = −0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both datasets show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of Moderate Resolution Imaging Spectroradiometer (MODIS) AOT level 3 product shows qualitative good agreement in the retrieved geographic patterns of AOT. <br><br> Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies. This paper presents a first evaluation and validation of the derived AOT over Europe in order to document the overall quality of a product that will be made publicly available to the users of the aforementioned research communities

Intercomparison of desert dust optical depth from satellite measurements

This work provides a comparison of satellite retrievalsof Saharan desert dust aerosol optical depth (AOD)during a strong dust event through March 2006. In this event,a large dust plume was transported over desert, vegetated,and ocean surfaces. The aim is to identify the differencesbetween current datasets. The satellite instruments consideredare AATSR, AIRS, MERIS, MISR, MODIS, OMI,POLDER, and SEVIRI. An interesting aspect is that the differentalgorithms make use of different instrument characteristicsto obtain retrievals over bright surfaces. These includemulti-angle approaches (MISR, AATSR), polarisationmeasurements (POLDER), single-view approaches using solarwavelengths (OMI, MODIS), and the thermal infraredspectral region (SEVIRI, AIRS). Differences between instruments,together with the comparison of different retrievalalgorithms applied to measurements from the same instrument,provide a unique insight into the performance andcharacteristics of the various techniques employed. As wellas the intercomparison between different satellite products,the AODs have also been compared to co-located AERONETdata. Despite the fact that the agreement between satellite andAERONET AODs is reasonably good for all of the datasets,there are significant differences between them when comparedto each other, especially over land. These differencesare partially due to differences in the algorithms, such as assumptionsabout aerosol model and surface properties. However,in this comparison of spatially and temporally averageddata, it is important to note that differences in sampling, relatedto the actual footprint of each instrument on the heterogeneousaerosol field, cloud identification and the qualitycontrol flags of each dataset can be an important issue

Suivi des flux d'énergie, d'eau et de carbone à la surface : apport de la télédétection et de la modélisation du rayonnement solaire absorbé par la végétation

It is known that a global 4% increase of land surface albedo (also called reflectivity) may result approximately in a decrease of 0.7°C in the Earth’s equilibrium temperature. Nowadays the surface properties (including albedo) are changing under climatic and human pressure. At the same time, there is a debate that divides the scientific community about the potential trends (increase or decrease) affecting the surface incoming solar radiation since mid-1980 (resulting of a decrease or increase of aerosol concentration in the atmosphere, respectively). The Earth is a complex system driven at the surface level by three cycles (energy, water, and carbon). These cycles are not insensitive to changes of surface reflectivity, incoming radiation, or aerosol properties. For example, some argue that the increase of diffuse radiation during the last decades would have led to an exceed of carbon uptake by the Earth’s vegetation of 9.3%. The main issue raised here is to assess the added value of the knowledge in absorbed solar radiation by the surface (combination of incoming solar radiation with surface albedo) and, especially, by the vegetation for the monitoring of energy, water and carbon fluxes.In this work, I have used satellite observations and modeled the radiative transfer theory in order to make dynamic mapping of solar radiation absorbed by the surface and through the vertical dimension of the vegetation. First, I quantified each uncertainty source affecting incoming solar radiation, surface albedo and the way radiation is split between horizontal and vertical heterogeneity. In a second step, I measured the added value of using this absorbed radiation mapping of the surface by satellite to estimate the energy and water fluxes at the surface. The resulting improved scores of weather forecast models in the short-range time scale suggested potential feedbacks at the climatic time scale over sensible areas such as the Sahel region. Another significant outcome is that the developments proposed to better characterize the vertical heterogeneity within the canopy led to an improvement of 15% of annual global terrestrial gross primary production (GPP). Moreover, this study has led to measure the impact of the lack of knowledge of spatial and temporal variability of aerosol properties (concentration and type). I have shown that the tracking of temporal changes of directional properties of reflectance allows me to retrieve to the amount of aerosols in the atmosphere as precisely as other widely used methods but with a higher frequency (5 times more) by using data from geostationary satellite. Finally, this study addresses some possibilities to better track temporal changes of properties of reflectivity of surface and aerosol of atmosphere, and to access to a better monitoring of biogeochemical cycles of the terrestrial biosphere.Au niveau global, il a été estimé qu’une augmentation de 4% de l’albédo (ou réflectivité) de la surface provoquerait une diminution de 0,7° de la température d’équilibre de la Terre. Or les propriétés des surfaces (dont l’albédo) changent sous la pression climatique et l’action de l’homme. Parallèlement à ce changement des propriétés de surface un débat divise la communauté scientifique sur une éventuelle diminution ou augmentation du rayonnement incident à la surface depuis le milieu des années 1980 (conséquence d’une augmentation ou diminution de la concentration d’aérosols dans l’atmosphère). La Terre est un système complexe piloté en sa surface par 3 cycles (énergie, eau et carbone). Ces cycles ne sont pas insensibles à ces changements de propriété de réflectivité de surface, de rayonnement solaire incident ou de concentration en aérosols. Certains avancent ainsi qu’une augmentation du rayonnement diffus durant les dernières décennies aurait déjà entraîné un excédent de captation de carbone par la végétation de 9.3%. La problématique ici soulevée est d’évaluer l’apport de la connaissance du flux solaire absorbé par la surface (combinaison du rayonnement solaire et de l’albédo de surface) et plus particulièrement par sa partie végétative pour le suivi des flux d’énergie, d’eau et de carbone. Dans ce travail, j’ai fait appel à l’observation satellitaire et à la modélisation du transfert radiatif pour cartographier la dynamique du rayonnement solaire absorbé par la surface et sur la verticale de la végétation. Dans un premier temps, chacune des sources d’incertitudes sur le rayonnement incident, sur l’albédo de surface mais aussi sur la répartition du rayonnement entre les hétérogénéités horizontales et verticales à la surface furent quantifiées. Puis tout en discutant l’effet de ces incertitudes, j’ai mesuré l’apport de l’utilisation de cette cartographie par satellite du rayonnement solaire absorbé pour estimer les flux d’énergie et d’eau en surface ; ce qui améliora les scores de prévision du temps à court terme et permis également de suggérer des rétroactions à l’échelle climatique sur des zones sensibles tel le Sahel. Aussi une correction de biais de 15% sur l’estimation de la production primaire brute de carbone à l’échelle planétaire démontra l’importance des développements réalisés afin de caractériser les hétérogénéités verticales dans le couvert. Finalement, ce travail m’a conduit à chiffrer l’impact de la méconnaissance des variabilités spatiales et temporelles des propriétés des aérosols (concentration et type). J’ai montré que le suivi au cours du temps des propriétés de directionalité de la réflectivité de surface (tel abordé dans la première partie de mon étude) pouvait aussi permettre de remonter à la quantité d’aérosol dans l’atmosphère. L’utilisation d’observations issues de satellite géostationnaire permet d’estimer la concentration en aérosol avec la même qualité mais avec une fréquence de détection plus élevée (x5 environ) que les méthodes classiques. Enfin, ce travail dresse des pistes pour améliorer la détection des changements des propriétés de réflectivité de surface et d’aérosols de l’atmosphère, et atteindre un suivi encore meilleur des cycles biogéochimiques de la biosphère terrestre

Temporal constraints on linear BRDF model parameters

Linear models of bidirectional reflectance distribution are useful tools for understanding the angular variability of surface reflectance as observed by medium-resolution sensors such as the Moderate Resolution Imaging Spectrometer. These models are operationally used to normalize data to common view and illumination geometries and to calculate integral quantities such as albedo. Currently, to compensate for noise in observed reflectance, these models are inverted against data collected during some temporal window for which the model parameters are assumed to be constant. Despite this, the retrieved parameters are often noisy for regions where sufficient observations are not available. This paper demonstrates the use of Lagrangian multipliers to allow arbitrarily large windows and, at the same time, produce individual parameter sets for each day even for regions where only sparse observations are available

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation

Implementation of a satellite-based prognostic daily surface albedo depending on soil wetness : impact study in SURFEX modelling platform over France

L'objectif de la thèse est de développer un albédo de surface journalier pronostique dans les modèles météorologiques et d’évaluer son impact pour le bilan d'énergie et l'hydrologie dans la plate-forme de modélisation SURFEX sur le domaine France. En premier lieu, un albédo climatologique est à ce jour considéré dans SURFEX. Il est analysé dans cette étude par rapport aux albédos quotidiens de SEVIRI et MODIS dont ce dernier est obtenu à partir d'une méthode originale que l'on valide. Ensuite, une méthode est développée pour obtenir des albédos du sol et de la végétation de façon séparée à la fois statiquement, donc sur une base climatologique, puis dynamiquement en s'appuyant sur plusieurs années de données du satellite MODIS. Une fois réglé l'albédo du sol journalier, il est recherché une calibration avec l'humidité du sol nu à l'aide des données du réseau de stations sol SMOSMANIA du sud-ouest de la France. Il est montré que l'on peut prédire l'évolution de l'albédo de surface, par comparaison avec les observations spatiales avec l'humidité seule dans la limite d'une végétation faiblement couvrante. Cet albédo simulé est complété par celui de la végétation seule à partir d'une paramétrisation simplifiée du code de transfert radiatif PROSAIL. L'approche théorique est validée avec les données du site de Majadas pour lequel on montre que l'on sait simuler le cycle d'évolution de l'albédo total avec prise en compte de la chlorophylle au niveau de la feuille. En dernier lieu, il a été réalisé une étude d'impact du nouveau albédo évolutif sur le bilan d'énergie et l'hydrologie dans SURFEX sur la France. Il est aussi mis en place une assimilation de l'albédo conjointement avec l'indice foliaire et l'humidité superficielle, ce qui a des effets positifs pour le cas des végétations qui ne sont pas trop denses. ABSTRACT : The main objective of the thesis is to develop a prognostic surface albedo of the visible spectrum and near infrared and assess its impact on the energy balance and hydrology in the modelling platform of SURFEX. First, a statistical approach has generated a global climate albedo product at 0.05 ° for bare soil and vegetation using multiple years 8 -day MODIS onboard TERRA and AQUA satellites heliosynchronous data. Then, an original method has been developed to reduce temporal resolution of MODIS 500m albedo to daily. The result is validated against in situ measurements as well as daily albedo from geostationary satellite MSG / SEVIRI Land SAF project after projection of MODIS. Then a method of separating albedo of bare soil and vegetation is applied to the datasets of the two satellite systems. Using a threshold of vegetation cover, a calibration of the albedo bare soil with measured soil moisture is derived from 2007 to 2010 for 12 SMOSMANIA stations over southwestern France. We derived a parameterization of the albedo of bare soil with moisture to make the climate changing albedo. The albedo and simulated happens to be very well correlated with observations from space, which helps to explain the albedo variations at very short notice. To change seasonally albedo, a simple parameterization of canopy albedo derived from detailed radiative transfer code PROSAIL is used. The variables are the albedo of the sheet, canopy geometry and chlorophyll content. In order to be sensitive to chlorophyll, the study is based on an albedo at 560 nm. The theoretical approach is validated with MODIS satellite data for the site Majadas (Spain). The next step is to conduct an impact study of this new predictive albedo on the energy balance and hydrology within SURFEX over France and highlighting effects on temperature. More preliminary restricted to a SMOSMANIA station, an assimilation scheme is developed for surface albedo together with the leaf area index LAI and surface moisture. This effects an improvement in the prescribed LAI at the beginning of crop growth