SEVIRI Data Research Articles

Estimating hourly variation in photosynthetically active radiation across the UK using MSG SEVIRI data

The amount of photosynthetically active radiation (PAR) reaching the Earth's surface is a key input variable in most gross primary productivity models. However, poor representation of PAR due to large pixel size or limited temporal sampling is one of the main sources of uncertainty in such models. This paper presents a method to estimate PAR at up to 1 km spatial resolution at a regional to global scale. The method uses broadband radiance data (400–1100nm) and per-pixel estimates of relative cloud cover from a geostationary satellite to estimate the amount of PAR reaching the Earth's surface at high spatial and temporal resolution (1–2 km and hourly). The method was validated using data from 54 pyranometers located at sites across the UK. Hourly averaged PAR over the range 400–1400 μmol m−2 s−1 was estimated with a mean bias error = 5.01 μmol m−2 s−1 (R2 = 0.87), providing a source of accurate data for high resolution models of gross primary productivity.

A parameterization of SEVIRI and MODIS daily surface albedo with soil moisture: Calibration and validation over southwestern France

In climate models, it is important to simulate the partitioning of the surface albedo into soil and vegetation albedo components because these latter address different processes that are time-scale dependent. Vegetation albedo primarily varies along with the growing season while soil albedo shows day-to-day variations caused by rainfall events. In this study, the objective is to disentangle soil albedo from surface albedo within the visible (VIS) and near infrared (NIR) spectral bands of MODIS and SEVIRI sensors in order to yield a calibration with surface soil moisture (SSM). In a first step, we derive global static maps of soil and vegetation albedos from MODIS products at the resolution of 0.05° over a 4-year period. In a second step, we estimate a daily MODIS white-sky albedo (WSA) by combining 8-day BRDF and TERRA/AQUA reflectance values for each orbit pass. These MODIS products are then projected on the SEVIRI grid of 4km for further comparison. Then, a physical method is presented to get a daily soil albedo from both MODIS and SEVIRI data. Good correlations are obtained between satellite time series for 2007 and 2008 of retrieved soil albedo and in situ SSM measurements at the 12 SMOSMANIA stations located in southwestern France. A function of an exponential type between albedo and SSM, as supported by the theory, could be verified. As in the VIS domain, the goodness of fit r2 is about 0.42 and 0.54 for Lahas and Condom, respectively. The Chi-Square test indicates that the relationship is significant with p-value <0.01. Finally, it is shown that most anomalies of soil albedo correlate with anomalies of soil wetness, which yields crucial importance for studying the energy budget.

Combining model and geostationary satellite data to reconstruct hourly SST field over the Mediterranean Sea

This work focuses on the reconstruction of Sea Surface Temperature (SST) diurnal cycle through combination of numerical model analyses and geostationary satellite measurements. The approach takes advantage of geostationary satellite observations as the diurnal signal source to produce gap-free optimally interpolated (OI) hourly SST fields using model analyses as first-guess. The resulting SST anomaly field (satellite-model) is free, or nearly free, of any diurnal cycle, thus allowing one to interpolate SST anomalies using satellite data acquired at different times of the day.The method is applied to reconstruct the hourly Mediterranean SST field during summer 2011 using SEVIRI data and Mediterranean Forecasting System analyses. A synthetic cloud reconstruction experiment demonstrated that the OI SST method is able to reconstruct an unbiased SST field with a RMS=0.16°C with respect to SEVIRI observations. The OI interpolation estimate, the model first guess and the SEVIRI data are evaluated using drifter and mooring measurements. Special attention is devoted to the analysis of diurnal warming (DW) events that are particularly frequent in the Mediterranean Sea. The model reproduces quite well the Mediterranean SST diurnal cycle, except for the DW events. Due to the thickness of the model surface layer, the amplitude of the model diurnal cycle is often less intense than the corresponding SEVIRI and drifter observations. The Diurnal OI SST (DOISST) field, resulting from the blending of model and SEVIRI data via optimal interpolation, reproduces well the diurnal cycle including extreme DW events. The evaluation of DOISST products against drifter measurements results in a mean bias of −0.07°C and a RMS of 0.56°C over interpolated pixels. These values are very close to the corresponding statistical parameters estimated from SEVIRI data (bias=−0.16°C, RMS=0.47°C). Results also confirm that part of the mean bias between temperature measured by moorings at 1m depth and the satellite observations can be ascribed to the different nature of the measurements (bulk versus skin).

Synergy between polar-orbiting and geostationary sensors: Remote sensing of the ocean at high spatial and high temporal resolution

Ocean colour sensors have been capturing the state of the world's oceans for over a decade. They are typically installed on polar-orbiting satellites and cover the entire earth every 1 to 2days. This temporal resolution is insufficient to observe oceanic processes occurring at a higher frequency, especially when taking cloud cover into account. Data from geostationary platforms can be obtained with a much better temporal resolution (images every 15 or 60min), and thus are useful to study those processes. We show that by synergistically combining marine reflectance data from SEVIRI, a geostationary sensor, and MODIS Aqua, a polar orbiter, the resulting product is an improvement over both data sources. The synergy approach takes the reflectance from MODIS, with high quality and high spatial resolution, and modulates this over the day by the temporal variability of the SEVIRI reflectance, normalized to the SEVIRI reflectance at the time of MODIS overpass. The temporal frequency of the synergy product is much better than that of MODIS, and by using the latter's high quality data, the limited spatial and radiometric resolution of SEVIRI is enhanced. As the SEVIRI data is limited to a single broad red band (560–710nm), the applications of the synergy product are limited to parameters that can be derived from this band, such as suspended particulate matter (SPM), turbidity (T) and the diffuse attenuation of photosynthetically available radiation (Kpar) in turbid waters. A geostationary ocean colour sensor over Europe will provide invaluable data concerning our marine environment. The cost of increasing the spatial resolution of a geostationary sensor is very high, and this study illustrates that a lower resolution geostationary ocean colour sensor combined with a high resolution polar orbiting sensor, can provide a high frequency synergetic product with high spatial resolution.

Thermal insights into the dynamics of Nyiragongo lava lake from ground and satellite measurements

AbstractWe present new insights into the short‐ and long‐term thermal activity of the Nyiragongo lava lake by ground‐based and satellite infrared thermal imagery recorded in the first half of 2012. This is the very first time in which FLIR camera and SEVIRI data have been compared at this volcano. Maximum temperatures recorded at the molten lava were of ~1180 K, whereas the lake skin remained always below ~734 K in areas far from the upwelling zone and below ~843 K in those proximal to the source region. Ground‐based imagery yielded mean radiative power values between ~0.80 and 1.10 GW. Consistently, satellite observations showed similar mean values of 1.10 GW. Overall the thermal activity of the lava lake was quite variable along the three days of field measurements at both daily and intradaily scale. SEVIRI radiative power values retrieved for the January–June 2012 period revealed fluctuations within the same variability range suggesting that no significant changes of the lava lake area had occurred over the six months. Comparison with previous radiative power estimates showed that our data well agree with the general increasing trend recorded since the reappearance of the lava lake after the last flank eruption in 2002.

Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG

The ultimate objective of this paper is the estimation of rainfall over an area in Algeria using data from the SEVIRI radiometer (Spinning Enhanced Visible and Infrared Imager). To achieve this aim, we use a new Convective/Stratiform Rain Area Delineation Technique (CS-RADT). The satellite rainfall retrieval technique is based on various spectral parameters of SEVIRI that express microphysical and optical cloud properties. It uses a multispectral thresholding technique to distinguish between stratiform and convective clouds. This technique (CS-RADT) is applied to the complex situation of the Mediterranean climate of this region. The tests have been conducted during the rainy seasons of 2006/2007 and 2010/2011 where stratiform and convective precipitation is recorded. The developed scheme (CS-RADT) is calibrated by instantaneous meteorological radar data to determine thresholds, and then rain rates are assigned to each cloud type by using radar and rain gauge data. These calibration data are collocated with SEVIRI data in time and space.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

Abstract. Volcanic ash cloud-top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3–4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Validation of the Prototype System for Wildfire Hotspot Detection and Monitoring ofthe African Sub-Sahara Region:A Case Study of the Horn of Africa Region

Validation of the Prototype System for Wildfire Hotspot Detection and Monitoring of the African Sub-Sahara Region:A Case Study of the Horn of Africa Region The Italian Space Agency (ASI) recently installed a prototype system for hotspot detection and monitoring (FIRE) at its Broglio Space Centre (ASI/BSC) facility in Malindi (Kenya). FIRE has been developed at ASI Space Geodesy Centre (Matera, Italy) to monitor hotspots in the Mediterranean Regions and successively adapted to monitor hotspots in Sub-Saharan Africa. The FIRE system implements a processing chain that routinely receives Meteosat Second Generation (MSG) data through the EUMECAST Channel and extracts and transforms the SEVIRI data into geocoded reflectance, radiance and brightness temperature images. The Temperature images at 3.9 μm and 10.8 μm are used to detect the local thermal anomalies (hotspot). The time delay between the MSG data acquisition and the hotspot detection by the FIRE system is about 30 min.

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

Abstract. In this paper a new technique for the detection of fog and low stratus in 1 km resolution from MSG SEVIRI data is presented. The method relies on the pan-sharpening of 3 km narrow-band channels using the 1 km high-resolution visible (HRV) channel. As solar and thermal channels had to be sharpened for the technique, a new approach based on an existing pan-sharpening method was developed using local regressions. A fog and low stratus detection scheme originally developed for 3 km SEVIRI data was used as the basis to derive 1 km resolution fog and low stratus masks from the sharpened channels. The sharpened channels and the fog and low stratus masks based on them were evaluated visually and by various statistical measures. The sharpened channels deviate only slightly from reference images regarding their pixel values as well as spatial features. The 1 km fog and low stratus masks are therefore deemed of high quality. They contain many details, especially where fog is restricted by complex terrain in its extent, that cannot be detected in the 3 km resolution.

Retrieval of aerosol optical depth over land based on a time series technique using MSG/SEVIRI data

Abstract. A novel approach for the joint retrieval of aerosol optical depth (AOD) and aerosol type, using Meteosat Second Generation – Spinning Enhanced Visible and Infrared Imagers (MSG/SEVIRI) observations in two solar channels, is presented. The retrieval is based on a Time Series (TS) technique, which makes use of the two visible bands at 0.6 μm and 0.8 μm in three orderly scan times (15 min interval between two scans) to retrieve the AOD over land. Using the radiative transfer equation for plane-parallel atmosphere, two coupled differential equations for the upward and downward fluxes are derived. The boundary conditions for the upward and downward fluxes at the top and at the bottom of the atmosphere are used in these equations to provide an analytic solution for the AOD. To derive these fluxes, the aerosol single scattering albedo (SSA) and asymmetry factor are required to provide a solution. These are provided from a set of six pre-defined aerosol types with the SSA and asymmetry factor. We assume one aerosol type for a grid of 1°×1° and the surface reflectance changes little between two subsequent observations. A k-ratio approach is used in the inversion to find the best solution of atmospheric properties and surface reflectance. The k-ratio approach assumes that the surface reflectance is little influenced by aerosol scattering at 1.6 μm and therefore the ratio of surface reflectances in the solar band for two subsequent observations can be well-approximated by the ratio of the reflectances at 1.6 μm. A further assumption is that the surface reflectance varies only slightly over a period of 30 min. The algorithm makes use of numerical minimisation routines to obtain the optimal solution of atmospheric properties and surface reflectance by selection of the most suitable aerosol type from pre-defined sets. A detailed analysis of the retrieval results shows that it is suitable for AOD retrieval over land from SEVIRI data. Six AErosol RObotic NETwork (AERONET) sites with different surface types are used for detailed analysis and 42 other AERONET sites are used for validation. From 445 collocations representing stable and homogeneous aerosol type, we find that &gt;75% of the MSG-retrieved AOD at 0.6 and 0.8 μm values compare favourably with AERONET observed AOD values, within an error envelope of ± 0.05 ± 0.15 τ and a high correlation coefficient (R&gt;0.86). The AOD datasets derived using the TS method with SEVIRI data is also compared with collocated AOD products derived from NASA TERRA and AQUA MODIS (The Moderate-resolution Imaging Spectroradiometer) data using the Dark Dense Vegetation (DDV) method and the Deep Blue algorithms. Using the TS method, the AOD could be retrieved for more pixels than with the NASA Deep Blue algorithm. This method is potentially also useful for surface reflectance retrieval using SEVIRI observations. The current paper focuses on AOD retrieval and analysis, and the analysis and validation of reflectance will be given in a following paper.

An emergent strategy for volcano hazard assessment: From thermal satellite monitoring to lava flow modeling

Spaceborne remote sensing techniques and numerical simulations have been combined in a web-GIS framework (LAV@HAZARD) to evaluate lava flow hazard in real time. By using the HOTSAT satellite thermal monitoring system to estimate time-varying TADR (time averaged discharge rate) and the MAGFLOW physics-based model to simulate lava flow paths, the LAV@HAZARD platform allows timely definition of parameters and maps essential for hazard assessment, including the propagation time of lava flows and the maximum run-out distance. We used LAV@HAZARD during the 2008–2009 lava flow-forming eruption at Mt Etna (Sicily, Italy). We measured the temporal variation in thermal emission (up to four times per hour) during the entire duration of the eruption using SEVIRI and MODIS data. The time-series of radiative power allowed us to identify six diverse thermal phases each related to different dynamic volcanic processes and associated with different TADRs and lava flow emplacement conditions. Satellite-derived estimates of lava discharge rates were computed and integrated for the whole period of the eruption (almost 14months), showing that a lava volume of between 32 and 61million cubic meters was erupted of which about 2/3 was emplaced during the first 4months. These time-varying discharge rates were then used to drive MAGFLOW simulations to chart the spread of lava as a function of time. TADRs were sufficiently low (<30m3/s) that no lava flows were capable of flowing any great distance so that they did not pose a hazard to vulnerable (agricultural and urban) areas on the flanks of Etna.

Wildfire Detection and Tracking over Greece Using MSG‑SEVIRI Satellite Data

Greece is a high risk Mediterranean country with respect to wildfires. This risk has been increasing under the impact of climate change, and in summer 2007 approximately 200,000 ha of vegetated land were burnt. The SEVIRI sensor, on board the Meteosat Second Generation (MSG) geostationary satellite, is the only spaceborne sensor providing five and 15-minute observations of Europe in 12 spectral channels, including a short-wave infrared band sensitive to fire radiative temperature. In August 2007, when the bulk of the destructive wildfires started in Greece, the receiving station, operated by the Institute for Space Applications and Remote Sensing, provided us with a time series of MSG-SEVIRI images. These images were processed in order to test the reliability of a real‑time detection and tracking system and its complementarity to conventional means provided by the Fire Brigade. EUMETSAT’s Active Fire Monitoring (FIR) image processing algorithm for fire detection and monitoring was applied to SEVIRI data, then fine-tuned according to Greek conditions, and evaluated. Alarm announcements from the Fire Brigade’s archives were used as ground truthing data in order to assess detection reliability and system performance. During the examined period, MSG-SEVIRI data successfully detected 82% of the fire events in Greek territory with less than 1% false alarms.

Mapping daily evapotranspiration and dryness index in the East African highlands using MODIS and SEVIRI data

Abstract. Routine information on regional evapotranspiration (ET) and dryness index is essential for agricultural water management, drought monitoring, and studies of water cycle and climate. However, this information is not currently available for the East Africa highlands. The main purpose of this study is to develop (1) a new methodology that produces spatially gridded daily ET estimates on a (near) real-time basis exclusively from satellite data, and (2) a new dryness index that depends only on satellite data and weather forecast data. The methodology that calculates daily actual ET involves combining data from two sensors (MODIS and SEVIRI) onboard two kinds of platforms (Terra – polar orbit satellite and MSG – geostationary orbit satellite). The methodology is applied to the East African highlands, and results are compared to eddy covariance measurements at one site. Results show that the methodology produces ET estimates that accurately reproduce the daily fluctuation in ET but tends to underestimate ET on the average. It is concluded that the synergistic use of the polar-orbiting MODIS data and the geostationary-orbiting SEVIRI data has potential to produce reliable daily ET, but further research is needed to improve the accuracy of the results. This study also proposes an operational new dryness index that can be calculated from the satellite-based daily actual ET estimates and daily reference ET estimates based on SEVIRI data and weather forecast air temperature. Comparison of this index against ground measurements of daily actual ET at one site indicates that the new dryness index can be used for drought monitoring.

Ground-based observations for the validation of contrails and cirrus detection in satellite imagery

Abstract. Contrails and additional cirrus clouds caused by air traffic have a potential warming effect due to their optical properties and their location in the upper troposphere. The effect of contrails is directly related to their coverage and optical properties, which both can be derived from satellite observations. However, considerable local and global uncertainties remain, as detection limits and efficiency are still unknown. A six months time series of the occurrence of high-level clouds and contrails was analysed visually using an all-sky camera situated at Oberpfaffenhofen (Southern Germany). It shows a contrail occurrence of 21% (fraction of time with visible contrails during one hour) which is nearly constant over daytime and a cirrus occurrence that increases from 27% in the morning to 48% in the evening, suggesting a possible influence of air traffic or, more probably, convective cloud formation. Furthermore, we compared selected all-sky camera images with data of the satellite instruments NOAA/AVHRR and MSG/SEVIRI. As expected, the fraction of contrails visible and detectable in satellite images depends strongly on their width. Of the contrails observed with the all-sky camera of 1–5 km width 60–65% are visually detectable in AVHRR data while only 17% are identified by an automated contrail detection algorithm (CDA). This means that the automated CDA detects approx. 28% of the contrails which are identified by visual inspection in AVHRR data alone. As far as SEVIRI is concerned, visual inspection yields 48% of the contrails of 1–5 km width, the CDA 19%. That means 40% of all contrails visually identifiable in SEVIRI data are found by the automated algorithm. As far as cirrus detection using SEVIRI data is concerned, an automated algorithm tends to overestimate cirrus occurrence but correctly measures cirrus changes during the day compared to visual inspection.

Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data

In order to obtain high quality data, the correction of atmospheric perturbations acting upon land surface reflectance measurements recorded by a space-based sensor is an important topic within remote sensing. For many years the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model and the Simplified Method for Atmospheric Correction (SMAC) codes have been used for this atmospheric correction, but previous studies have shown that in a number of situations the quality of correction provided by the SMAC is low. This paper describes a method designed to improve the quality of the SMAC atmospheric correction algorithm through a slight increase in its computational complexity. Data gathered from the SEVIRI aboard Meteosat Second Generation (MSG) is used to validate the additions to SMAC, both by comparison to simulated data corrected using the highly accurate 6S method and by comparison to in-situ and 6S corrected SEVIRI data gathered for two field sites in Africa. The additions to the SMAC are found to greatly increase the quality of atmospheric correction performed, as well as broaden the range of atmospheric conditions under which the SMAC can be applied. When examining the Normalised Difference Vegetation Index (NDVI), the relative difference between SMAC and in-situ values decreases by 1.5% with the improvements in place. Similarly, the mean relative difference between SMAC and 6S reflectance values decreases by a mean of 13, 14.5 and 8.5% for Channels 1, 2 and 3 respectively. Furthermore, the processing speed of the SMAC is found to remain largely unaffected, with only a small increase in the time taken to process a full SEVIRI scene. Whilst the method described within this paper is only applicable to SEVIRI data, a similar approach can be applied to other data sources than SEVIRI, and should result in a similar accuracy improvement no matter which instrument supplies the original data.

The TAMORA algorithm: satellite rainfall estimates over West Africa using multi-spectral SEVIRI data

Abstract. A multi-spectral rainfall estimation algorithm has been developed for the Sahel region of West Africa with the purpose of producing accumulated rainfall estimates for drought monitoring and food security. Radar data were used to calibrate multi-channel SEVIRI data from MSG, and a probability of rainfall at several different rain-rates was established for each combination of SEVIRI radiances. Radar calibrations from both Europe (the SatPrecip algorithm) and Niger (TAMORA algorithm) were used. 10 day estimates were accumulated from SatPrecip and TAMORA and compared with kriged gauge data and TAMSAT satellite rainfall estimates over West Africa. SatPrecip was found to produce large overestimates for the region, probably because of its non-local calibration. TAMORA was negatively biased for areas of West Africa with relatively high rainfall, but its skill was comparable to TAMSAT for the low-rainfall region climatologically similar to its calibration area around Niamey. These results confirm the high importance of local calibration for satellite-derived rainfall estimates. As TAMORA shows no improvement in skill over TAMSAT for dekadal estimates, the extra cloud-microphysical information provided by multi-spectral data may not be useful in determining rainfall accumulations at a ten day timescale. Work is ongoing to determine whether it shows improved accuracy at shorter timescales.

Derivation of land surface temperature using measurements of IR radiances from geostationary meteorological satellites

Considered is a new method of remote derivation of the land surface temperature (LST) Ts using data of nonsimultaneous measurements of the SEVIRI/Meteosat-9 instrument in channels of transparency windows of 10.5–12.5 μm in the case of the cloudiness absence in the field of instrument. The method is the combination of two well-known algorithms of the subject processing of satellite data. It enables to derive Ts without the involvement of data on the values of the land emissivity at sounding stations. Experiments on the processing of SEVIRI actual data of some autumn days of 2008, as well as a comparison of the results with independent satellite estimations of Ts, confirm the operability and efficiency of the proposed method. The possibility of detailed description of the diurnal course of LST on the basis of SEVIRI data using the proposed method of Ts estimation is analyzed.

A new IR technique for monitoring low cloud properties using geostationary satellite data

AbstractA new technique of using satellite infrared radiance data for retrieving cloud properties is developed and applied to SEVIRI data, which is based on direct radiative transfer calculations, not on the emissivity approximation as used by other satellite IR only techniques. Instantaneous atmospheric profiles are used in the new technique for improving the accuracy of retrievals. Comparison of the retrieved results with coincident observations of CloudSat and CALIPSO shows excellent agreement for low clouds. This study shows that, using only IR radiances, the single layer assumption would significantly underestimate cloud optical depth when multilayered cloud system is presented. Copyright © 2009 Royal Meteorological Society

Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments

Some applications, e.g. from traffic or energy management, require air temperature data in high spatial and temporal resolution at two metres height above the ground ( T 2 m ), sometimes in near-real-time. Thus, a parameterization based on boundary layer physical principles was developed that determines the air temperature from remote sensing data (SEVIRI data aboard the MSG and MODIS data aboard Terra and Aqua satellites). The method consists of two parts. First, a downscaling procedure from the SEVIRI pixel resolution of several kilometres to a one kilometre spatial resolution is performed using a regression analysis between the land surface temperature ( LST) and the normalized differential vegetation index ( NDVI) acquired by the MODIS instrument. Second, the lapse rate between the LST and T 2 m is removed using an empirical parameterization that requires albedo, down-welling surface short-wave flux, relief characteristics and NDVI data. The method was successfully tested for Slovenia, the French region Franche-Comté and southern Germany for the period from May to December 2005, indicating that the parameterization is valid for Central Europe. This parameterization results in a root mean square deviation RMSD of 2.0 K during the daytime with a bias of −0.01 K and a correlation coefficient of 0.95. This is promising, especially considering the high temporal (30 min) and spatial resolution (1000 m) of the results.

Diurnal evolution of cloud base heights in convective cloud fields from MSG/SEVIRI data

Abstract. This study shows that it is possible to retrieve the temporal evolution of cloud base heights in convective broken cloud fields from data of the SEVIRI instrument onboard the geostationary satellite Meteosat-9. Presented and discussed are time dependent base heights with a temporal resolution of 15 min from morning to afternoon. Cloud base heights retrieved from SEVIRI data are also compared with independent measurements of a ceilometer, with condensation levels calculated from radiosonde data and with base heights obtained from an application of the method to NOAA/AVHRR data. The validation has been performed for three days in the year 2007 and for seven test areas distributed over Germany and neighbouring countries. The standard deviations of the absolute differences between cloud base heights from Meteosat-9 and radiosonde measurements as well as between NOAA/AVHRR and Meteosat-9 results are both of the order of ±290 m. The correlation coefficient is 0.53 for the comparison of satellite with radiosonde measurements and 0.78 for the intercomparison of the satellite measurements. Furthermore, it is shown that the method retrieves the temporal evolution of cloud base heights in very good agreement with time dependent ceilometer measurements.