Estimation of the aerosol radiative forcing at ground level, over land, and in cloudless atmosphere, from METEOSAT-7 observation: method and first results

International audienceA new method is proposed to estimate the spatial and temporal variability of the solar radiative flux reaching the surface (DSSF) over land, as well as the Aerosol Radiative Forcing (ARF), in cloud-free atmosphere. The objective of global applications of the method is fulfilled by using the visible broadband of METEOSAT-7 satellite which scans Europe and Africa on a half-hourly basis. The method relies on a selection of best correspondence between METEOSAT-7 radiance and DSSF computed with a radiative transfer code. The validation of DSSF is performed comparing retrievals with ground-based measurements acquired in two contrasted environments, i.e. an urban site near Paris and a continental background site in South East of France. The study is concentrated on aerosol episodes occurring around the 2003 summer heat wave, providing 42 cases of comparison for variable solar zenith angle (from 59° to 69°), variable aerosol type (biomass burning emissions and urban pollution), and variable aerosol optical thickness (a factor 6). The method reproduces measurements of DSSF within an accuracy assessment of 20 Wm-2 (5% in relative) in 70% of the cases, and within 40 Wm-2 in 90% of the cases. Considering aerosol is the main contributor in changing the measured radiance at the top of the atmosphere, DSSF temporal variability is assumed to be caused only by aerosols, and consequently the ARF at ground level and over land is also retrieved: ARF is computed as the difference between DSSF and a parameterised aerosol-free reference level. Retrievals are linearly correlated with the ground-based measurements of the aerosol optical thickness (AOT): sensitivity is included between 120 and 160 Wm-2 per unity of AOT at 440 nm. AOT being an instantaneous measure indicative of the aerosol columnar amount, we therefore prove the feasibility to infer instantaneous aerosol radiative impact at the ground level over land with METEOSAT-7 visible channel

Daily estimates of the tropospheric aerosol optical thickness over land surface from MSG geostationary observations

The paper presents an innovative method to derive aerosol optical thickness (AOT) on a continental scale, using MSG observation. The approach consists in taking into account the high temporal resolution of the observing system, in order to discriminate between surface and aerosol effects. A suitably extended semi-empirical BRDF model is applied, combined with a recursive scheme. The method is not instrument-specific (can be adapted to instruments onboard polar satellites) and was tested with MSG/SEVIRI data over mid-latitude and African regions. The aerosol optical thickness estimates are compared to AERONET ground measurements and to the corresponding MODIS product over land. The method appears very promising for tracking anthropogenic emissions in the troposphere and also for estimating dust events over bright surfaces. The high spatial and temporal resolution of the estimate is appropriate to investigate the dependence of AOT on the density of urbanization and potentially on motor vehicle traffic. Finally, this study suggests that this approach is appropriate for multi-sensor data fusion, for the simultaneous retrieval of surface albedo and aerosol optical thickness, and to generate these products in near-real time with a very high generation frequency

Classification of African ecosystems at 1 km resolution using multiannual SPOT/VEGETATION data and a hybrid clustering approach

Ecosystems classification is the process of allocating vegetation types into groups so that individuals in the same class are similar according to their physiological and phonological characteristics to another one. Over large areas, the only suitable technique to obtain frequent and repetitive data acquisitions over such large areas is the use of observations recorded by sensors of moderate resolution. In order to minimize the role of the analyst and to improve the accuracy of the results, innovative and efficient approaches for the classification of ecosystems continue to appear in the literature. This research developed and implemented a new hybrid unsupervised classification approach to derive ecosystems using multi-annual time series by combining hierarchical and partitioning clustering principles. The latter approach is applied on 8-years time series (2000-2007) of 10-day composite Normalized Difference Vegetation Index (NDVI) recorded by SPOT/VEGETATION. After the first segmentation of the mainland in ecoregions using the Fast Fourier Transform (FFT), successive k-nearest neighbor (k-NN) clustering enhance the discrimination of ecosystems and yields to the production of a new ecosystem map for the African continent. The nomenclature relied on the Land Cover Classification System (LCCS) of the Food and Agricultural Organization (FAO). On the basis of validated continental, a pixel-by-pixel analysis is conducted to assess the accuracy of the new classification. The hybrid clustering facilitates the identification/labeling process and the obtained results which should provide key information needed for management/monitoring of natural resources, biodiversity conservation and biogeochemical studies may also deserve vegetation cover modeling at regional and local scal

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

Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

International audienceA CO2-responsive land surface model (the ISBAA- gs model of M´et´eo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale

Monitoring of water and carbon fluxes using a land data assimilation system: a case study for southwestern France

International audienceA Land Data Assimilation System (LDAS) able to ingest surface soil moisture (SSM) and Leaf Area Index (LAI) observations is tested at local scale to increase prediction accuracy for water and carbon fluxes. The ISBAA-gs Land Surface Model (LSM) is used together with LAI and the soil water content observations of a grassland at the SMOSREX experimental site in southwestern France for a seven-year period (2001-2007). Three configurations corresponding to contrasted model errors are considered: (1) best case (BC) simulation with locally observed atmospheric variables and model parameters, and locally observed SSM and LAI used in the assimilation, (2) same as (1) but with the precipitation forcing set to zero, (3) real case (RC)simulation with atmospheric variables and model parameters derived from regional atmospheric analyses and from climatological soil and vegetation properties, respectively. In configuration (3) two SSM time series are considered: the observed SSM using Thetaprobes, and SSM derived from the LEWIS L-band radiometer located 15m above the ground. Performance of the LDAS is examined in the three configurations described above with either one variable (either SSM or LAI) or two variables (both SSM and LAI) assimilated. The joint assimilation of SSM and LAI has a positive impact on the carbon, water, and heat fluxes. It represents a greater impact than assimilating one variable (either LAI or SSM). Moreover, the LDAS is able to counterbalance large errors in the precipitation forcing given as input to the model