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Climate services are largely supported by satellite Climate Data Records (CDRs). This paper demonstrates how CDR development and uptake benefit from simulations. We identify three classes of application. Using global reanalyses and an offline radiance simulator, we provide three examples for each application class. The first application is to validate assumptions. Hereto we establish the order of channels in the U.S. Defense Meteorological Satellite Program (DMSP) Special Sensor H (SSH) data record, rescued from oblivion thanks to inter-agency collaboration. We then show the value of applying advanced quality controls to geostationary European (Meteosat) and Japanese (Himawari) images. We also investigate the corrections applied during reprocessing of DMSP Special Sensor Microwave Temperature sounder (SSM/T-1) data. The second application is to assess the coherence between and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI-1) flown on Soviet satellites before 1980. We also explore the coherence of the impact of two major volcanic eruptions between Advanced Very High Resolution Radiometer (AVHRR) and the High-resolution Infrared Radiation Sounder (HIRS) data. Finally, we investigate how advanced bias correction can help improve coherence between reanalysis and Nimbus-3 Medium-Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform CDR users about particular quality aspects. Hereto we show, with the Nimbus-7 Scanning Multichannel Microwave Radiometer (SSMR), the Meteosat Second Generation imager, and the DMSP Special Sensor Microwave Water Vapor Profiler (SSM/T-2), how simulations bring information that should help to make a better-informed use of the corresponding CDR.

Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy budget and it is for this reason an essential variable in climate studies. Instruments on geostationary satellites provide suitable observations allowing long-term monitoring of surface albedo from space. In 2012, EUMETSAT published Release 1 of the Meteosat Surface Albedo (MSA) data record. The main limitation effecting the quality of this release was non-removed clouds by the incorporated cloud screening procedure that caused too high albedo values, in particular for regions with permanent cloud coverage. For the generation of Release 2, the MSA algorithm has been replaced with the Geostationary Surface Albedo (GSA) one, able to process imagery from any geostationary imager. The GSA algorithm exploits a new, improved, cloud mask allowing better cloud screening, and thus fixing the major limitation of Release 1. Furthermore, the data record has an extended temporal and spatial coverage compared to the previous release. Both Black-Sky Albedo (BSA) and White-Sky Albedo (WSA) are estimated, together with their associated uncertainties. A direct comparison between Release 1 and Release 2 clearly shows that the quality of the retrieval improved significantly with the new cloud mask. For Release 2 the decadal trend is less than 1% over stable desert sites. The validation against Moderate Resolution Imaging Spectroradiometer (MODIS) and the Southern African Regional Science Initiative (SAFARI) surface albedo shows a good agreement for bright desert sites and a slightly worse agreement for urban and rain forest locations. In conclusion, compared with MSA Release 1, GSA Release 2 provides the users with a significantly more longer time range, reliable and robust surface albedo data record.

A new intercalibration method for two polar-orbiting satellite instruments or two instrument constellations’ Fundamental Climate Data Records (FCDRs) is presented. It is based on statistical fitting of reflectance data from the two instruments covering the same area during the same period, but not simultaneously. A Deming regression with iterative weights is used. The accuracy of the intercalibration method itself was better than 0.5% for the Moderate Resolution Imaging Spectroradiometer (MODIS) versus MODIS and Advanced Very High Resolution Radiometer (AVHRR) versus AVHRR test data sets. The intercalibration of an AVHRR FCDR generated by NOAA versus a combined MODIS Terra and Aqua data set of red and near-infrared (NIR) channels was carried out and showed a difference in the reflectance values of about 2% (red) and 6% (NIR). The presented intercalibration method can be used for checking the calibration of two instruments or FCDRs in all viewing angles used separately.

Validating the accuracy and long-term stability of terrestrial satellite data products necessitates a network of reference sites. This paper documents a global database of more than 2000 sites globally which have been characterized in terms of their spatial heterogeneity. The work was motivated by the need for potential validation sites for geostationary surface albedo data products, but the resulting database is useful also for other applications. The database (SAVS 1.0) is publicly available through the EUMETSAT website (http://savs.eumetsat.int/, doi:10.15770/EUM_SEC_CLM_1001). Sites can be filtered according to different criteria, providing a flexible way to identify potential validation sites for further studies and a traceable approach to characterize the heterogeneity of these reference sites. The present paper describes the detailed information on the generation of the SAVS 1.0 database and its characteristics.

Climate has been recognized to have direct and indirect impact on society and economy, both in the long term and daily life. The challenge of understanding the climate system, with its variability and changes, is enormous and requires a joint long-term international commitment from research and governmental institutions. An important international body to coordinate worldwide climate monitoring efforts is the World Meteorological Organization (WMO). The Global Climate Observing System (GCOS) has the mission to provide coordination and the requirements for global observations and essential climate variables (ECVs) to monitor climate changes. The WMO-led activity on Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) is responding to these requirements by ensuring a continuous and sustained generation of climate data records (CDRs) from satellite data in compliance with the principles and guidelines of GCOS. SCOPE-CM represents a new partnership between operational space agencies to coordinate the generation of CDRs. To this end, pilot projects for different ECVs, such as surface albedo, cloud properties, water vapor, atmospheric motion winds, and upper-tropospheric humidity, have been initiated. The coordinated activity on land surface albedo involves the operational meteorological satellite agencies in Europe [European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], in Japan [the Japan Meteorological Agency (JMA)], and in the United States [National Oceanic and Atmospheric Administration (NOAA)]. This paper presents the first results toward the generation of a unique land surface albedo CDR, involving five different geostationary satellite positions and approximately three decades of data starting in the 1980s, and combining close to 30 different satellite instruments.

Satellite-based retrievals offer the most cost-effective way to comprehensively map the surface albedo of the Earth, a key variable for understanding the dynamics of radiative energy interactions in the atmosphere-surface system. Surface albedo retrievals have commonly been designed separately for each different spaceborne optical imager. Here, we introduce a novel type of processing framework that combines the data from two polar-orbiting optical imager families, the Advanced Very High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). The goal of the paper is to demonstrate that multisensor albedo retrievals can provide a significant reduction in the sampling time required for a robust and comprehensive surface albedo retrieval, without a major degradation in retrieval accuracy, as compared to state-of-the-art single-sensor retrievals. We evaluated the multisensor retrievals against reference in situ albedo measurements and compare them with existing datasets. The results show that global land surface albedo retrievals with a sampling period of 10 days can offer near-complete spatial coverage, with a retrieval bias mostly comparable to existing single sensor datasets, except for bright surfaces (deserts and snow) where the retrieval framework shows degraded performance because of atmospheric correction design compromises. A level difference is found between the single sensor datasets and the demonstrator developed here, pointing towards a need for further work in the atmospheric correction, particularly over bright surfaces, and inter-sensor radiance homogenization. The introduced framework is expandable to include other sensors in the future.

The devastating drought in the Sahel during the 70s and the 80s is among the most undisputed and largest recent climate event recognized by the research community. This dramatic climate event has generated numerous sensitivity analyses on land-atmosphere feedback mechanisms with contradicting conclusions on surface albedo response to precipitation changes. Recent improvements in the calibration and quantitative exploitation of archived Meteosat data for the retrieval of surface albedo have permitted to compare surface albedo of 1884, the driest year of the 80s, with year 2003 which had similar precipitation rate than conditions prevailing prior to the 80s drought. This analysis reveals detailed information on the geographical extension and magnitude of the surface albedo increase during from the 80s drought. A mean zonal increase in broadband surface albedo of about 0.06 between 1984 and 2003 has been estimated from the analysis of Meteosat observations. Regions particularly affected by the 1980s drought are essentially located into a narrow band of about 2° width along 16°N running from 18°W up to 20°E. Within this geographical area, surface albedo changes are not homogeneous and largest differences might locally exceed 0.15 whereas other places remained almost unaffected. The variety of previously published results might be explained by these important spatial variations observed around 16°N.

Operational weather geostationary satellites have acquired data for more than two decades and offer thus the possibility to generate long time series of Essential Climate Variables like surface albedo as suggested by GCOS. This paper investigates the possibility to generate consistent global, to the exception of the polar regions, surface broadband albedo product from these satellites. In this context, the paper addresses two specific issues. Firstly, the spatial consistency of surface albedo derived from five different geostationary satellites is examined in detail. Secondly, this product is compared with the equivalent MODIS one to define the temporal consistency between surface albedo derived with old geostationary instruments and technologically advanced radiometers like MODIS. The analysis of the surface albedo products has revealed a good agreement between the products derived from the various geostationary satellites. Comparison of this global product with the one routinely derived from MODIS shows that on the average, the mean relative difference between these two data sets agree within 10%. These first encouraging results open therefore a new avenue for the exploitation of the archived data for the generation of long time series, covering the last 25 years or so, of global surface albedo from geostationary weather satellites.

The purpose of this paper is to present the results of the evaluation of the Meteosat Surface Albedo (MSA) product, including the effects due to instrument changes and associated calibration uncertainties. To this end, observations acquired by two adjacent geostationary spacecrafts, Meteosat-7 and Meteosat-5 have been processed with the MSA algorithm. These satellites are located, respectively, at 0° and 63° East. Data acquired by these two instruments overlap over a large area encompassing most of Africa and the Arabian peninsula. The consistency of the surface anisotropy retrieval is evaluated through a reconstruction of the Meteosat-5 (-7) observations with the Meteosat-7 (-5) surface anisotropy characterization. Some differences slightly higher than the calibration accuracy have been found. This effect has no significant impact on the albedo retrieval which indicates that MSA is a reliable algorithm to produce albedo datasets.

Surface albedo has been identified as an important parameter for understanding and quantifying the Earth's radiation budget. EUMETSAT generated the Meteosat Surface Albedo (MSA) Climate Data Record (CDR) currently comprising up to 24 years (1982–2006) of continuous surface albedo coverage for large areas of the Earth. This CDR has been created within the Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) framework. The long-term consistency of the MSA CDR is high and meets the Global Climate Observing System (GCOS) stability requirements for desert reference sites. The limitation in quality due to non-removed clouds by the embedded cloud screening procedure is the most relevant weakness in the retrieval process. A twofold strategy is applied to efficiently improve the cloud detection and removal. The first step consists of the application of a robust and reliable cloud mask, taking advantage of the information contained in the measurements of the infrared and visible bands. Due to the limited information available from old radiometers, some clouds can still remain undetected. A second step relies on a post-processing analysis of the albedo seasonal variation together with the usage of a background albedo map in order to detect and screen out such outliers. The usage of a reliable cloud mask has a double effect. It enhances the number of high-quality retrievals for tropical forest areas sensed under low view angles and removes the most frequently unrealistic retrievals on similar surfaces sensed under high view angles. As expected, the usage of a cloud mask has a negligible impact on desert areas where clear conditions dominate. The exploitation of the albedo seasonal variation for cloud removal has good potentialities but it needs to be carefully addressed. Nevertheless it is shown that the inclusion of cloud masking and removal strategy is a key point for the generation of the next MSA CDR release.

Comparison of surface albedos derived from spaceborne radiometers with different spectral bands requires, first of all, the conversion of these quantities into common spectral intervals. This letter proposes a spectral conversion method specifically dedicated to surface albedo derived in a large-band instrument such as the solar channel onboard the Meteosat first-generation radiometer. This new method accounts for the retrieval algorithm assumptions and radiometer spectral limitations that might have an impact on the retrieved surface albedo in such a large band. It is also shown that the proposed approach has no impact when surface albedo is derived in narrow bands and confirms the results of previously published spectral conversion methods.

New satellite instruments have been delivering a wealth of information regarding land surface albedo. This basic quantity describes what fraction of solar radiation is reflected from the earth’s surface. However, its concept and measurements have some ambiguity resulting from its dependence on the incidence angles of both the direct and diffuse solar radiation. At any time of day, a surface receives direct radiation in the direction of the sun, and diffuse radiation from the various other directions in which it may have been scattered by air molecules, aerosols, and cloud droplets. This contribution proposes a complete description of the distribution of incident radiation with angles, and the implications in terms of surface albedo are given in a mathematical form, which is suitable for climate models that require evaluating surface albedo many times. The different definitions of observed albedos are explained in terms of the coupling between surface and atmospheric scattering properties. The analytical development in this paper relates the various quantities that are retrieved from orbiting platforms to what is needed by an atmospheric model. It provides a physically simple and practical approach to evaluation of land surface albedo values at any condition of sun illumination irrespective of the current range of surface anisotropic conditions and atmospheric aerosol load. The numerical differences between the various definitions of albedo for a set of typical atmospheric and surface scattering conditions are illustrated through numerical computation.

[1] An original method, based on optimal estimation, was presented in a part one of this paper for the joint retrieval of the mean daily total column aerosol optical depth and the surface Bidirectional Reflectance Factor (BRF) from the daily accumulated Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI) observations in the solar channels. The objective of this paper is to evaluate the benefits of the proposed approach and to document the limits of the algorithm assumptions in the context of its implementation in an operational ground segment. A twofold approach is followed. In a first step, by looking at the posterior correlation error matrix the capability of the so-called Land Daily Aerosol (LDA) algorithm to decouple the surface-atmosphere signal is analyzed. In particular, the impact of the prior information is investigated in detail. In a second step, the results of the algorithm are compared with independent data sets of aerosol optical depth and surface reflectance. In this phase, the accuracy of the algorithm is evaluated against ground observations from the AERONET network. LDA is shown to be in good agreement with these data, especially when the prior update mechanism is activated. Comparisons with the MODIS surface product showed that the bihemispherical reflectance derived from the LDA products is consistent with the equivalent MODIS white-sky albedo. Aerosol spatial distributions are comparable in terms of geographical location and intensity, in particular for aerosol episodes with a limited daily variation.

[1] An original method is presented in this paper for the joint retrieval of the mean daily total column aerosol optical depth and surface BRF from the daily accumulated Meteosat Second Generation–Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI) observations inthe solar channels. The proposedalgorithm is basedon the optimalestimation (OE) theory, a one-dimensional variational retrieval scheme that seeks an optimal balance between information that can be derived from the observations, and the one that is derived from prior knowledge of the system. The forward radiative transfer model explicitly accounts for the surface anisotropy and its coupling with the atmosphere. The low rate of change in the surface reflectance is used to derive the prior information on the surface state variables. The reliable estimation of the measurement system error is one of the most critical aspects of the OE method as it strongly determines the likelihood of the solution. An important effort in the proposed method has thus been dedicated to this issue, where the actual radiometric performances of SEVIRI are dynamically taken into account.

Passive spaceborne imagers observe radiation that has interacted both with the atmosphere and the surface. Interactions with the atmosphere include gaseous absorption and scattering by molecules and particulate matter or aerosols. Their characterization from remote sensing observations relies essentially on their capacity to modify differently the amount of radiation observed as a function of the wavelength, the viewing directions or the polarization. One of the major issues when retrieving tropospheric aerosol properties using spaceborne imager observations is to discriminate the contribution of the observed signal reflected by the surface from the one scattered and absorbed by the aerosols. In particular, it is crucial when the retrieval occurs above land surfaces which might be responsible for a non-negligible part of the total signal. Conceptually, this is equivalent to solving a radiative system composed of minimum two layers, where the upper layers includes aerosols and the bottom ones represents the soil/vegetation strata. This problem is further complicated by the intrinsic anisotropic radiative behavior of natural surfaces and its coupling with atmospheric radiative processes. An increase in aerosol optical thickness is responsible for an increase of the fraction of diffuse sky radiation which, in turn, smooths the effects of surface anisotropy.

A full description of the end-to-end L2 prototype processor for the meteosat third generation hyperspectral sounder (MTG-IRS), including background physical principles, and the numerical implementation, input data, pre-processing steps, accuracy, efficiency, output data is proposed.

Using the principle of reciprocity, observations acquired by the SEVIRI radiometer on-board the Meteosat Second Generation satellites provide multi-angular and multi-spectral measurements that can be used for retrieving information on both the atmospheric aerosol load, and the Earth surface. The purpose of the presented new Land Daily Aerosol algorithm developed at EUMETSAT is to derive simultaneously the mean daily tropospheric aerosol load and the land surface properties from the SEVIRI observations. The algorithm is based on the Optimal Estimation theory. The aerosol load is calculated through the optical depth parameter, for various classes of aerosols over land surfaces, and is inferred from the inversion of a forward radiative transfer model against daily-accumulated observations in the 0.6, 0.8 and 1.6 SEVIRI bands. These daily time series provide the angular sampling used to discriminate the radiative effects that result from the surface anisotropy, from those caused by the aerosol scattering. Results of comparisons with AERONET data are presented to validate the modelling approach and the algorithm that resolves the inversion problem. The retrieval error is analysed, together with the effects on the retrieval quality of updating in time the prior information.

[1] The radiative impact of burn scars from biomass is investigated. Changes in surface albedo derived from satellite observations over the African continent are used as a first order indication of this impact. Because the direct radiative effect of aerosols from biomass burning is dependent on the underlying surface albedo, we investigate the interaction of the direct radiative effect due to biomass burning aerosols with the change in surface reflection due to the burn scars. The radiative effect of reduced surface albedo from burn scars is estimated to be close to 0.1 Wm−2 over a region covering the African continent.

[1] Monitoring and understanding climate changes of the Earth require the generation of long-term and consistent global data set from observations. In this context, geostationary satellite observations could play a significant role thanks to the long duration of the missions and the corresponding archives. In particular, their frequent acquisition cycle throughout the day can be used to document the surface anisotropy and therefore surface albedo. This paper investigates the possibility to generate a consistent surface albedo maps from two adjacent geostationary satellites, namely Meteosat-5 and -7. The analysis relies on the comparison of albedo values derived over the common observed area. These values agree favorably between the two spacecrafts.

The Sahel is a narrow region in West Africa, lying between the Sahara desert at 18°N and savannah and equatorial forest at about 15°N. The climate and atmospheric dynamics of this region are determined by the West African monsoon resulting from the alternating southwesterly and northwesterly winds, corresponding to a north-south migration of the Intertropical convergence Zone (ITCZ). during the northward shift of the ITCZ, rainfall occurs over Sahel during a short but intense wet season, between late June and mid-September, which induces fast vegetation growth. The dry season that follows this rainy period produces a rapid drying the vegetation.