The semianalytical cloud retrieval algorithm for SCIAMACHY II. The application to MERIS and SCIAMACHY data

International audienceThe SemiAnalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, we derive simultaneously cloud optical thickness (COT) and cloud top height (CTH), using SCIAMACHY measurements in the visible (442 nm, COT) and in the oxygen A-band (755?775 nm, CTH). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observes almost the same scene as SCIAMACHY. The same cloud algorithm is applied to both MERIS and SCIAMACHY data. In addition, we perform the vicarious calibration of SCIAMACHY at the wavelength 442 nm, using MERIS measurements at the same wavelength. Differences in the retrieved COT for the same cloud field obtained using MERIS and SCIAMACHY measurements are discussed

Synergetic aerosol retrieval from SCIAMACHY and AATSR onboard ENVISAT

International audienceThe synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary information of a radiometer and a spectrometer onboard one satellite platform to extract aerosol optical depth (AOD) and speciation (as choice from a representative set of pre-defined mixtures of water-soluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used to do accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique. In the second step the spectrometer is applied to choose the most plausible aerosol type through a least square fit of the measured spectrum with simulated spectra using the AOD and surface brightness retrieved in the first step. This method was developed and a first case study evaluation against few (15) multi-spectral ground-based AERONET sun photometer observations was conducted with a sensor pair (ATSR-2 and GOME) onboard ERS-2. However, due to instrumental limitations the coverage of SYNAER/ERS-2 and the AERONET network in 1997/98 is very sparse and thus only few coincidences with AERONET were found. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair a thorough evaluation of the synergetic methodology and its information content has been conducted, which led to significant improvements in the methodology: an update of the aerosol model, an improved cloud detection, and an enhanced dark field albedo characterization. This paper describes the information content analysis and these improvements in detail and presents first results of applying the SYNAER methodology to AATSR and SCIAMACHY

In-flight degradation correction of SCIAMACHY UV reflectances and Absorbing Aerosol Index

In this paper we study the close relationship between the radiometric calibration of a satellite instrument and the Absorbing Aerosol Index (AAI) derived from the observed Earth reflectance. Instrument degradation of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument in the ultraviolet wavelength range is examined by analyzing time series of global means of the AAI, making use of the experience that the global mean should be more or less constant when instrument degradation is absent. The analysis reveals the magnitude of the (scan angle dependent) instrument degradation of SCIAMACHY and also shows that currently available correction techniques are not able to correct the instrument degradation in a sufficient manner. We therefore develop and introduce a new method for degradation correction, which is based on the analysis of the time evolution of the global mean reflectance. Seasonal variations in the global mean reflectance, which mainly result from seasonal variations in scattering geometry and global cloud coverage, are separated from the time series in order to isolate the instrument degradation. Finally, we apply the derived reflectance correction factors to the SCIAMACHY reflectances and calculate the AAI to find that the effects of instrument degradation are reduced to within the 0.1 index point level. The derived AAI is also compared with the AAI based on other correction techniques. The proposed in-flight reflectance degradation correction method performs best in all aspects. © 2012 by the American Geophysical Union

Retrieval of aerosol optical thickness over snow and ice surfaces in the Arctic using Advanced Along Track Scanning Radiometer

Aerosols in the Arctic cause radiative forcing and a variety of climatic feedbacks, which affect climate of both local and global scales. In order to assess the state of the Arctic climate, information on the aerosol type and amount is needed. Harsh conditions and remoteness of the Arctic region result in very few ground based measurements of aerosol optical thickness. Remote sensing has the potential to provide the necessary temporal and spatial coverage. A non-trivial task of aerosol retrieval over a very bright surface is being solved within the thesis; the developed retrieval consists of cloud screening over snow and two types of aerosol retrieval over snow - in the visible and infrared spectral regions. A number of validation and case studies has been performed to assess the quality of the retrieval. The developed algorithm applies to the data of Advanced Along Track Scanning Radiometer and produces maps of aerosol optical thickness over snow and ice

Cloud retrieval from UV/VIS satellite instruments : (SCIAMACHY and GOME)

The detection of cloud parameters like cloud fraction and cloud top height from satellite is an important issue: 1.) for meteorology and the investigation of climate change and 2.) for the space-based analysis of tropospheric trace gases relevant to environmental and climatological issues. The Heidelberg Iterative Cloud Retrieval Utilities (HICRU) algorithm retrieves effective cloud fraction, cloud height and surface albedo. Reflectances from broad-band spectrometers (617-705nm) and spectral analysis (DOAS) of the O2-gamma-band around 630nm are used. The radiative transfer is included using the Monte-Carlo models TRACY II and McArtim. The algorithm is applied to SCIAMACHY on ENVISAT and GOME on ERS-2. The results are validated using lidar/radar measurements from the surface, intercomparisons with cloud retrievals for satellite instruments like MERIS and MODIS, climatological values from ISCCP and other SCIAMACHY/GOME cloud retrievals. The new algorithm and data products form an improvement to the results of existing algorithms and gives reliable results in particular for problematic areas like deserts and regions with seasonal cloud coverage, which often lead to problems for cloud algorithms

SCIAMACHY Level 1 data: calibration concept and in-flight calibration

The calibration of SCIAMACHY was thoroughly checked since the instrument was launched on-board ENVISAT in February 2002. While SCIAMACHY's functional performance is excellent since launch, a number of technical difficulties have appeared, that required adjustments to the calibration. The problems can be separated into three types: (1) Those caused by the instrument and/or platform environment. Among these are the high water content in the satellite structure and/or MLI layer. This results in the deposition of ice on the detectors in channels 7 and 8 which seriously affects the retrievals in the IR, mostly because of the continuous change of the slit function caused by scattering of the light through the ice layer. Additionally a light leak in channel 7 severely hampers any retrieval from this channel. (2) Problems due to errors in the on-ground calibration and/or data processing affecting for example the radiometric calibration. A new approach based on a mixture of onground and in-flight data is shortly described here. (3) Problems caused by principal limitations of the calibration concept, e.g. the possible appearance of spectral structures after the polarisation correction due to unavoidable errors in the determination of atmospheric polarisation. In this paper we give a complete overview of the calibration and problems that still have to be solved. We will also give an indication of the effect of calibration problems on retrievals where possible. Since the operational processing chain is currently being updated and no newly processed data are available at this point in time, for some calibration issues only a rough estimate of the effect on Level 2 products can be given. However, it is the intention of this paper to serve as a future reference for detailed studies into specific calibration issues

Assessing the Calibration Differences in the Reflective Solar Bands of Terra MODIS and Landsat-7 Enhanced Thematic Mapper Plus

Long-term data records obtained from Earth observing sensors depend not only onthe calibration accuracy of individual sensors but also on the consistency across instruments andplatforms. Hence, sensor calibration intercomparison plays a vital role for a better understandingof various science products. The Moderate Resolution Imaging Spectroradiometer (MODIS)and enhanced thematic mapper plus (ETM+) on the Terra and Landsat 7 platforms have operatedsuccessfully since their launch, collecting measurements in the reflective solar and infrared partsof the spectrum. Terra MODIS has employed a reflectance-based calibration since beginning itsmission. In the case of ETM+, a radiance-based calibration was employed until recent years,when a reflectance-based calibration was introduced. Being in the AM constellation with lessthan 30 min difference in overpass times, near-simultaneous Earth scene measurements can beeffectively used to assess the calibration differences between the spectrally matching bands ofthese two instruments. The pseudoinvariant calibration sites (PICS) in the North African desertare widely used for on-orbit calibration and validation of satellite sensors. Four PICS from thisregion have been employed to assess the multitemporal reflectance differences. Correction forbidirectional reflectance, spectral response function mismatch, and impacts of atmosphericwater-vapor have been incorporated to provide an assessment of the long-term stability ofeach spectral band and reflectance differences amongst them. Results indicate that the spectralbands of both instruments show a long-term stability to within 2% from 2000 to 2017. Thetop-of-atmosphere reflectances between the two instruments postcorrection agree to within 4%.Also included in this paper is a detailed discussion of various parameters contributing to theuncertainties of this cross-calibration. The techniques presented in this paper can be furtherextended to perform similar intercomparison between Landsat 8 Operational Land Imager, AquaMODIS, and Suomi-NPP VIIRS

The Applicability of Remote Sensing in the Field of Air Pollution

This report prepared by KNMI and JRC is the final result of a study on the applicability of remote sensing in the field of air pollution requested by the DG Environment. The objectives of this study were to: Have an assessment of presently available scientific information on the feasibility of utilising remote sensing techniques in the implementation of existing legislation, and describe opportunities for realistic streamlining of monitoring in air quality and emissions, based on greater use of remote sensing. Have recommendations for the next policy cycle on the use of remote sensing through development of appropriate provisions and new concepts, including, if appropriate, new environmental objectives, more suited to the use of remote sensing. Have guidance on how to effectively engage with GMES and other initiatives in the air policy field projects Satellite remote sensing of the troposphere is a rapidly developing field. Today several satellite sensors are in orbit that measure trace gases and aerosol properties relevant to air quality. Satellite remote sensing data have the following unique properties: Near-simultaneous view over a large area; Global coverage; Good spatial resolution. The properties of satellite data are highly complementary to ground-based in-situ networks, which provide detailed measurements at specific locations with a high temporal resolution. Although satellite data have distinct benefits, the interpretation is often less straightforward as compared to traditional in-situ measurements. Maps of air pollution measured from space are widespread in the scientific community as well as in the media, and have had a strong impact on the general public and the policy makers. The next step is to make use of satellite data in a quantitative way. Applications based solely on satellite data are foreseen, however an integrated approach using satellite data, ground-based data and models combined with data assimilation, will make the best use of the satellite remote-sensing potential, as well as of the synergy with ground-based observations.JRC.H.4-Transport and air qualit