C. Bertrand

Outgoing longwave flux estimation: improvement of angular modelling using spectral information

A radiance-to-flux conversion is needed to estimate radiative fluxes at the top of the atmosphere from directional measurements made by broadband (BB) radiometers on satellites. Such a conversion is known to be one of the major sources of error in the resulting instantaneous shortwave and longwave fluxes. This paper analyzes the possibility to improve the radiance-to-flux conversion for the longwave radiation when spectral information about the radiation is available through a set of narrow-band (NB) measurements. The study is based on a database of spectral radiance fields at the top of the atmosphere built using radiative transfer computation. The analysis of this database shows that there exists a certain degree of correlation between the angular and the spectral behaviors of the radiation field. According to the type and the accuracy of the spectral information, this correlation allows a 25–55% reduction of the error introduced by the radiance-to-flux conversion with respect to a simple model that uses only broadband information. The method discussed in this paper might be used when broadband radiometer and spectral imager data are available together like the combination of Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Radiometer Imager (SEVIRI) or the combination of CERES and MODIS.

Exploring a new method for the retrieval of urban thermophysical properties using thermal infrared remote sensing and deterministic modeling

[1] Increasingly, mesoscale meteorological and climate models are used to predict urban weather and climate. Yet, large uncertainties remain regarding values of some urban surface properties. In particular, information concerning urban values for thermal roughness length and thermal admittance is scarce. In this paper, we present a method to estimate values for thermal admittance in combination with an optimal scheme for thermal roughness length, based on METEOSAT-8/SEVIRI thermal infrared imagery in conjunction with a deterministic atmospheric model containing a simple urbanized land surface scheme. Given the spatial resolution of the SEVIRI sensor, the resulting parameter values are applicable at scales of the order of 5 km. As a study case we focused on the city of Paris, for the day of 29 June 2006. Land surface temperature was calculated from SEVIRI thermal radiances using a new split-window algorithm specifically designed to handle urban conditions, as described in Appendix A, including a correction for anisotropy effects. Land surface temperature was also calculated in an ensemble of simulations carried out with the ARPS mesoscale atmospheric model, combining different thermal roughness length parameterizations with a range of thermal admittance values. Particular care was taken to spatially match the simulated land surface temperature with the SEVIRI field of view, using the so-called point spread function of the latter. Using Bayesian inference, the best agreement between simulated and observed land surface temperature was obtained for the Zilitinkevich (1970) and Brutsaert (1975) thermal roughness length parameterizations, the latter with the coefficients obtained by Kanda et al. (2007). The retrieved thermal admittance values associated with either thermal roughness parameterization were, respectively, 1843 � 108 J m � 2 s � 1/2 K � 1 and 1926 � 115 J m � 2 s � 1/2 K � 1 .

Unfiltering of the Geostationary Earth Radiation Budget (GERB) Data. Part II: Longwave Radiation

Abstract The method used to estimate the unfiltered longwave broadband radiance from the filtered radiances measured by the Geostationary Earth Radiation Budget (GERB) instrument is presented. This unfiltering method is used to generate the first released edition of the GERB-2 dataset. This method involves a set of regressions between the unfiltering factor (i.e., the ratio of the unfiltered and filtered broadband radiances) and the narrowband observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. The regressions are theoretically derived from a large database of simulated spectral radiance curves obtained by radiative transfer computations. The generation of this database is fully described. Different sources of error that may affect the GERB unfiltering have been identified and the associated error magnitudes are assessed on the database. For most of the earth–atmosphere conditions, the error introduced during the unfiltering processes is well under 0.5% (RMS error of abo...

Estimation of the 2002 Mount Etna eruption cloud radiative forcing from Meteosat-7 data

Abstract On 27th October 2002, after 15 months of small activity, the Mount Etna located on the island of Sicily, Italy (37.73°N, 15.00°E) erupted undergoing one of its most vigorous eruptions in years. During a few days, Europes highest and most active volcano hurled lava and spewed significant amounts of ash and trace gases into the atmosphere. The smoke and ash plume originating from the volcano stretched from the Sicily to the north African coast. The plume from the volcano has been identified and tracked using half-hourly Meteosat-7 visible, infrared, and water vapor imagery in order to estimate the radiative forcing produced by the introduction of the volcanic cloud in a previously clear sky. Our results indicate that, while the volcanic cloud has introduced a well-discernable radiative perturbation, the magnitude of the shortwave volcanic forcing appears in the range of the one introduced by large clouds above the Mediterranean Sea. By contrast, the perturbation generated in the longwave spectrum at the top of the atmosphere is larger than the one introduced by large meteorological clouds.

Sensitivity to spatio-temporal resolution of satellite-derived daily surface solar irradiation

Solar radiation data are essential for many applications, and in particular for solar energy systems. Because ground-based measurements of solar radiation are usually scarce, several methods have been proposed to estimate the solar radiation incoming on a horizontal surface at ground level from satellite imagery. These satellite-based estimations can be used as such, or combined with ground-based measurements. Because the satellite data sets differ in spatial and temporal resolution, this study evaluates the sensitivity of the satellite-derived daily surface solar irradiation to the underlying space and time resolution. More precisely, three surface solar radiation data sets retrieved from the Meteosat Second Generation (MSG) satellites are compared against ground-based measurements. Additionally, the benefit of merging information from the ground-based measurements with satellite data is explored. The study finds that the accuracy of daily surface solar irradiation estimates increases by up to 10% by doubling the temporal resolution of the MSG data, while it is largely insensitive to spatial resolution. This suggests that future geostationary satellite missions might primarily improve temporal rather than spatial resolution.

Angular distribution models, anisotropic correction factors, and mixed clear-scene types: a sensitivity study

Because radiometers do not measure the earths outgoing flux directly, angular distribution models (ADMs) are used to invert measured radiances at the top of atmosphere (TOA) to flux. However, data used to build ADMs are generally not sorted for mixed scene types, and anisotropic correction factors for such scenes are not usually available. In the present study, we have analyzed shortwave (SW) flux values retrieved over nine areas representative of a junction between two different ADM scene types in the Meteosat-7 field of view. The Clouds and the Earths Radiant Energy System (CERES) broadband SW ADMs were used to perform the radiance-to-flux conversion. Because of the large anisotropy difference that can exist between ADMs, use of the ADM that corresponds to the scene type with the highest percent coverage over footprints containing a mixture of scene types generates instantaneous as well as systematic errors in the retrieved SW flux values. Nevertheless, in the absence of available mixed scene type ADMs, we show that the CERES on the Tropical Rainfall Measuring Mission satellite SW ADMs can be combined together to provide reliable mixed scene types anisotropic correction factors. The use of such anisotropic factors appears to be especially well suited along the coastline of continents.

Aerosol optical depth spatio-temporal characterization over the Canadian BOREAS domain

A complete set of Advanced Very High Resolution Radiometer (AVHRR) data (75 images) is used to retrieve aerosol optical depth (AOD) over dense vegetation and over lake water in the visible AVHRR channel. The present approach for remote sensing of aerosols from the National Oceanic and Atmospheric Administration (NOAA)-11 AVHRR sensor is based on the detection of atmospherically dominated signals over dark surface covers such as dense dark vegetation (DDV). Such targets were identified using the reflective portion of the middle-wave AVHRR channel 3 signal. When a fixed DDV surface reflectance is subtracted from the observed reflectance after correction for all other atmospheric effects, the remaining part, which is due to aerosols, is inverted to derive aerosol optical thickness using a look-up table (LUT) similar to that used in water surface inversion. The algorithm was applied to the daily afternoon NOAA-11 AVHRR (1 km×1 km) data acquired from the end of May to mid-August 1994 over the Canadian 1000 km×1000 km Boreal Ecosystem Atmosphere Study (BOREAS) domain. A validation analysis using five ground-based Sun photometers within the studied area shows the good performance of the retrieval algorithm. The approach allows detailed analysis of the AOD spatio-temporal behaviour at the regional scale useful for climate and transport model validation.

Angular distribution models anisotropic correction factors and sun glint: a sensitivity study

Because radiometers do not measure the Earths outgoing fluxes directly, angular distribution models (ADMs) are used to invert measured radiances at the top of atmosphere (TOA) to fluxes. In this study, we have investigated if the use of the newly developed clear ocean Clouds and the Earths Radiant Energy System (CERES) broadband short wave (SW) ADMs from the Tropical Rainfall Measuring Mission (TRMM) satellite will allow reliable estimation of the instantaneous reflected SW fluxes at the TOA when the measured radiances are contaminated by sun glint. Using SW fluxes estimations computed from Meteosat‐7 visible radiances as a surrogate of the forthcoming Geostationary Earth Radiation Budget SW fluxes, our results indicate that while CERES‐TRMM ADMs angular resolution presents an advance over the previously built Earth Radiation Budget Experiment (ERBE) ADMs, the angular resolution is still too coarse to suitably define anisotropic correction factors in the sunlight region. SW fluxes are overestimated in the strong sun glint region and underestimated in the surrounding regions. Nevertheless, we show that by combining the high temporal sampling of the sun glint regions afforded by the geostationary orbit of the instrument with information contained in the clear ocean wind‐speed‐dependent CERES‐TRMM ADMs, an improved estimation of the reflected SW flux at the TOA is possible by comparison to a simple ADM flux interpolation.

The GERB Edition 1 products SEVIRI scene identification

The first Geostationary Earth Radiation Budget (GERB) instrument was launched during the 2002 summer together with the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board of the Meteosat-8 satellite. This broadband radiometer aims to deliver near real-time estimates of the top of the atmosphere solar and thermal radiative fluxes at high temporal resolution thanks to the geostationary orbit. Such goal is achieved with the L20 GERB processing which generates these fluxes at several spatial resolutions from the directional filtered radiance measurements of the instrument. This processing consists of successive components, one of them being a radiance-to-flux conversion. Such conversion is carried out in the solar region by using the shortwave angular dependency models (ADMs) developed from the Tropical Rainfall Measuring Mission (TRMM) Clouds and the Earths Radiant Energy System (CERES) experiment. As these ADMs are stratisfed according to specific scene properties, the GERB ground segment will have to rely on a scene identification of SEVIRI data which allows us to select the proper ADM. In this paper, we will briefly justify and describe the implementation of a specific GERB scene identification for the offcial Edition 1 release of the L2 products. Preliminary comparisons between GERB and CERES scene identifications both applied to SEVIRI data will follow. Finally, we will suggest possible improvements based on limitations which could be found.

Evidence of azimuthal anisotropy for the thermal infrared radiation leaving the Earth's atmosphere

The analysis of one year of Cloud and the Earths Radiant Energy System (CERES) data from the Earth Observation System (EOS)-Terra satellite provides evidence that the longwave radiation escaping from the atmosphere exhibits significant variability according to the azimuthal angle of observation. A regional analysis of this variability shows that the anisotropy in azimuth is maximum over mountain and desert areas and under cloud-free conditions. A relative difference between north and south views of about 5% in annual average is observed over the Himalayan region in the 8-14 µm infrared (IR) window. The remote sensing community should be aware of this variability, in particular when analysing IR data provided by instruments on geostationary orbits. Indeed, in this case, the azimuthal anisotropy may lead to systematic overestimation of the outgoing longwave radiation and to biases on estimated quantities such as the surface temperature.