J. M. Krijger

SRON Netherlands Institute for Space Research

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Ilse Aben

SRON Netherlands Institute for Space Research

Stefan Noël

University of Bremen

H. Schrijver

SRON Netherlands Institute for Space Research

L. G. Tilstra

Royal Netherlands Meteorological Institute

Paul Tol

SRON Netherlands Institute for Space Research

Günter Lichtenberg

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Larysa Istomina

University of Bremen

Manfred Gottwald

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Ralph Snel

Netherlands Organisation for Applied Scientific Research

J. R. Acarreta

European Space Astronomy Centre

Cooperative Institutions

University of Bremen

SRON Netherlands Institute for Space Research

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Royal Netherlands Meteorological Institute

Nederlands Instituut Voor Zuivel Oonderzoek

European Space Research and Technology Centre

Royal Belgian Institute for Space Aeronomy

National Institute for Space Research

Utrecht University

University of Leicester

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SCIAMACHY Level1 data: Calibration concept and in-flight calibration

Günter Lichtenberg Q. Kleipool J. M. Krijger Gijs van Soest Richard M. van Hees

Abstract. This paper discusses the basic concept of the calibration of the SCIAMACHY instrument and remaining open issues. SCIAMACHY is a scanning Limb/Nadir spectrometer covering the wavelength range from 212 nm to 2386 nm. It was launched on-board ENVISAT in February 2002. In general the instrument performance is excellent: It performs as tested on ground and there is only very minor degradation in time. The only exception is the unexpected formation of water ice on the infrared channels 7 and 8 that attenuates the signal and a light leak in channel 7. Both effects will be discussed. In the paper we will explain all individual calibration steps needed to come to a wavelength calibrated spectrum of the Earth reflectance. Open points in the calibrations and latest improvements, such as the new radiometric calibration will also be treated.

SCIAMACHY

Nadir

Radiometric Calibration

10.5194/acpd-5-8925-2005

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Citations (62)

Development and Maintenance of SCIAMACHY operational ESA level 2 products: from Version 5 towards Version 6

H. Bovensmann Kai‐Uwe Eichmann Stefan Noël F. Wittrock Michael Buchwitz

Since the establishment of the SCIAMACHY Quality Working Group (SQWG) in a joint inter-agency ESA-DLRNSO effort in late 2006, the ESA operational Level 2 processor was significantly improved w.r.t. data quality and the product list was substantially enhanced by new parameters. The version 5 of the operational Level 2 product is now containing nadir total columns of O3, NO2, SO2, BrO, OClO (slant only), H2O, CO as well as the Absorbing Aerosol Index. In limb mode, stratospheric profiles of O3, NO2 and BrO as well as tropospheric cloud flags and top height information are available. The full mission reprocessing 2002-2012 of this product version 5.02 was finished in June 2012. In addition, the Quality Working Group started to prepare the next product version (Version 6). The new version will include for the nadir mode total columns of HCHO, CHOCHO, CH4, tropospheric columns of NO2 as well as an improved cloud identification over ice/snow and AAI. In limb mode main developments are the extension of the O3 profile to the mesosphere as well as an flag for mesospheric clouds.

SCIAMACHY

Nadir

Albedo (alchemy)

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Technical Note: The effect of sensor resolution on the number of cloud-free observations from space

Atmospheric chemistry and physics (2007)

J. M. Krijger Michiel van Weele Ilse Aben R. Frey

Abstract. Air quality and surface emission inversions are likely to be focal points for future satellite missions on atmospheric composition. Most important for these applications is sensitivity to the atmospheric composition in the lowest few kilometers of the troposphere. Reduced sensitivity by clouds needs to be minimized. In this study we have quantified the increase in number of useful footprints, i.e. footprints which are sufficient cloud-free, as a function of sensor resolution (footprint area). High resolution (1 km×1 km) MODIS TERRA cloud mask observations are aggregated to lower resolutions. Statistics for different thresholds on cloudiness are applied. For each month in 2004 four days of MODIS data are analyzed. Globally the fraction of cloud-free observations drops from 16% at 100 km2 resolution to only 3% at 10 000 km2 if not a single MODIS observation within a footprint is allowed to be cloudy. If up to 5% or 20% of a footprint is allowed to be cloudy, the fraction of cloud-free observations is 9% or 17%, respectively, at 10 000 km2 resolution. The probability of finding cloud-free observations for different sensor resolutions is also quantified as a function of geolocation and season, showing examples over Europe and northern South America (ITCZ).

Cloud fraction

Footprint

Geolocation

Cloud top

10.5194/acp-7-2881-2007

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Citations (87)

Application of QA4EO principles to SCIAMACHY Level 1 data

Günter Lichtenberg Sander Slijkhuis Manfred Gottwald Ralph Snel Nigel Fox

QA4EO seeks to improve interoperability of Earth observations made by different instruments. This is achieved through the establishment of the key principle that all data products should have associated with them a Quality indicator based on documented evidence of traceability to internationally agreed standards. QA4EO provides guidance on how best to follow and demonstrate this principle in a harmonious manner through a set of key guidelines. QA4EO makes clear that traceability for data products, starts with the on-ground calibration and goes up to derived products used in e.g. model and assimilation applications. The basis of all derived products are usually Level 1 data, which combine on-ground calibration with in-flight monitoring and calibration measurements. In the case of SCIAMACHY, the Level 1b data product comprises raw and geolocated data accompanied by all calibration parameters needed to generate the so-called Level 1c product with radiances as a function of wavelength. The mission concept includes frequent in-flight calibration and monitoring measurements. In this paper we discuss the application of QA4EO principles to operational Level 0-1 processing and the possibility to derive quality indicators from CEOS endorsed vicarious calibration sites (e.g. DOME-C campaign) for SCIAMACHY data.

Traceability

SCIAMACHY

Data Processing

Data set

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VERIFICATION OF SCIAMACHY'S POLARISATION CORRECTION OVER THE SAHARA DESERT

ESASP (2003)

L. G. Tilstra J. R. Acarreta J. M. Krijger P. Stammes

The justification for doing the work presented in this paper lies in the recent and disturbing rumours regarding the reflectivity of the current SCIAMACHY Level 1b product. The reflectivity was claimed to show an overall 20-percent loss in magnitude compared to GOME. We will show that the reported discrepancy in the reflectivity is indeed not a fictional one, but that it is certainly not caused by the failing polarisation correction. We also concentrate on the polarisation correction itself. Unfortunately, the current version of the polarisation correction algorithm is not reliable, and shows severe errors in the applied correction. 1 POLARISATION CORRECTION OF RADIANCES Light can be described by means of Stokes vectors

SCIAMACHY

Atmospheric correction

Stokes parameters

Desert (philosophy)

Systematic error

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Distinction between clouds and ice/snow covered surfaces in the identification of cloud-free observations using SCIAMACHY PMDs

Atmospheric chemistry and physics (2005)

J. M. Krijger Ilse Aben H. Schrijver

Abstract. SCIAMACHY on ENVISAT allows measurement of different trace gases including those most abundant in the troposphere (e.g. CO2, NO2, CH4, BrO, SO2). However, clouds in the observed scenes can severely hinder the observation of tropospheric gases. Several cloud detection algorithms have been developed for GOME on ERS-2 which can be applied to SCIAMACHY. The GOME cloud algorithms, however, suffer from the inadequacy of not being able to distinguish between clouds and ice/snow covered surfaces because GOME only covers the UV, VIS and part of the NIR wavelength range (240-790 nm). As a result these areas are always flagged as clouded, and therefore often not used. Here a method is presented which uses the SCIAMACHY measurements in the wavelength range between 450 nm and 1.6 µm to make a distinction between clouds and ice/snow covered surfaces. The algorithm is developed using collocated MODIS observations. The algorithm presented here is specifically developed to identify cloud-free SCIAMACHY observations. The SCIAMACHY Polarisation Measurement Devices (PMDs) are used for this purpose because they provide higher spatial resolution compared to the main spectrometer measurements.

SCIAMACHY

10.5194/acp-5-2729-2005

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Citations (57)

Mirror contamination in space I: mirror modelling

Atmospheric measurement techniques (2014)

J. M. Krijger R. Snel Gerard van Harten Jeroen Rietjens Ilse Aben

Abstract. We present a comprehensive model that can be employed to describe and correct for degradation of (scan) mirrors and diffusers in satellite instruments that suffer from changing optical Ultraviolet to visible (UV–VIS) properties during their operational lifetime. As trend studies become more important, so does the importance of understanding and correcting for this degradation. This is the case not only with respect to the transmission of the optical components, but also with respect to wavelength, polarisation, or scan-angle effects. Our hypothesis is that mirrors in flight suffer from the deposition of a thin absorbing layer of contaminant, which slowly builds up over time. We describe this with the Mueller matrix formalism and Fresnel equations for thin multi-layer contamination films. Special care is taken to avoid the confusion often present in earlier publications concerning the Mueller matrix calculus with out-of-plane reflections. The method can be applied to any UV–VIS satellite instrument. We illustrate and verify our approach to the optical behaviour of the multiple scan mirrors of SCIAMACHY (onboard ENVISAT).

Confusion

Mueller calculus

Ultraviolet

10.5194/amt-7-3387-2014

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Citations (21)

CURRENT STATUS OF SCIAMACHY POLARISATION MEASUREMENTS

ESA Special Publication (2003)

J. M. Krijger L. G. Tilstra

The measured signals by SCIAMACHY are corrected by a Polarisation Correction Algorithm to transform the signals to those that would have been measured for unpolarised light. This is achieved by transforming the signals of seven broadband Polarisation Measurement Devices onboard SCIAMACHY to the fractional Stokes parameters Q and U and interpolating them across the whole wavelength range of SCIAMACHY. At the moment of this report the fractional Stokes parameters Q and U as determined by the data-processor show unphysical values, except for the two Polarisation Measurement Devices at the shortest wavelength, as shown by a comparison with GOME polarisation measurements.

SCIAMACHY

Stokes parameters

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Citations (5)

Potential of the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor for the monitoring of terrestrial chlorophyll fluorescence

Atmospheric measurement techniques (2015)

Luis Guanter Ilse Aben Paul Tol J. M. Krijger André Hollstein

Abstract. Global monitoring of sun-induced chlorophyll fluorescence (SIF) is improving our knowledge about the photosynthetic functioning of terrestrial ecosystems. The feasibility of SIF retrievals from spaceborne atmospheric spectrometers has been demonstrated by a number of studies in the last years. In this work, we investigate the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite mission for SIF retrieval. TROPOMI will sample the 675–775 nm spectral window with a spectral resolution of 0.5 nm and a pixel size of 7 km × 7 km. We use an extensive set of simulated TROPOMI data in order to assess the uncertainty of single SIF retrievals and subsequent spatio-temporal composites. Our results illustrate the enormous improvement in SIF monitoring achievable with TROPOMI with respect to comparable spectrometers currently in-flight, such as the Global Ozone Monitoring Experiment-2 (GOME-2) instrument. We find that TROPOMI can reduce global uncertainties in SIF mapping by more than a factor of 2 with respect to GOME-2, which comes together with an approximately 5-fold improvement in spatial sampling. Finally, we discuss the potential of TROPOMI to map other important vegetation parameters at a global scale with moderate spatial resolution and short revisit time. Those include leaf photosynthetic pigments and proxies for canopy structure, which will complement SIF retrievals for a self-contained description of vegetation condition and functioning.

Imaging spectrometer

Tropospheric ozone

Spectral resolution

10.5194/amt-8-1337-2015

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Citations (175)

Improved identification of clouds and ice/snow covered surfaces in SCIAMACHY observations

Atmospheric measurement techniques (2011)

J. M. Krijger Paul Tol Larysa Istomina Cornelia Schlundt H. Schrijver

Abstract. In the ultra-violet, visible and near infra-red wavelength range the presence of clouds can strongly affect the satellite-based passive remote sensing observation of constituents in the troposphere, because clouds effectively shield the lower part of the atmosphere. Therefore, cloud detection algorithms are of crucial importance in satellite remote sensing. However, the detection of clouds over snow/ice surfaces is particularly difficult in the visible wavelengths as both clouds an snow/ice are both white and highly reflective. The SCIAMACHY Polarisation Measurement Devices (PMD) Identification of Clouds and Ice/snow method (SPICI) uses the SCIAMACHY measurements in the wavelength range between 450 nm and 1.6 μm to make a distinction between clouds and ice/snow covered surfaces, specifically developed to identify cloud-free SCIAMACHY observations. For this purpose the on-board SCIAMACHY PMDs are used because they provide higher spatial resolution compared to the main spectrometer measurements. In this paper we expand on the original SPICI algorithm (Krijger et al., 2005a) to also adequately detect clouds over snow-covered forests which is inherently difficult because of the similar spectral characteristics. Furthermore the SCIAMACHY measurements suffer from degradation with time. This must be corrected for adequate performance of SPICI over the full SCIAMACHY time range. Such a correction is described here. Finally the performance of the new SPICI algorithm is compared with various other datasets, such as from FRESCO, MICROS and AATSR, focusing on the algorithm improvements.

SCIAMACHY

10.5194/amt-4-2213-2011

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Citations (14)