335 research outputs found

    CEOS Intercalibration of Ground-Based Spectrometers and Lidars: First Progress Report

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    This document reports on activities and achievements obtained during the first part of the ESA CEOS Intercalibration project. The period covered extends from March 2009 until December 2009.This document is the first progress report of the CEOS Intercalibration of Ground-Based Spectrometers and Lidars project. It summarizes activities performed and results achieved within each team

    Preliminary signs of the initiation of deep convection by GNSS

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    This study reports on the exploitation of GNSS (Global Navigation Satellite System) and a new potential application for weather forecasts and nowcasting. We focus on GPS observations (post-processing with a time resolution of 5 and 15 min and fast calculations with a time resolution of 5 min) and try to establish typical configurations of the water vapour field which characterise convective systems and particularly which supply precursors of their initiation are associated with deep convection. We show the critical role of GNSS horizontal gradients of the water vapour content to detect small scale structures of the troposphere (i. e. convective cells), and then we present our strategy to obtain typical water vapour configurations by GNSS called "H2O alert". These alerts are based on a dry/wet contrast taking place during a 30 min time window before the initiation of a convective system. GNSS observations have been assessed for the rainfall event of 28-29 June 2005 using data from the Belgian dense network (baseline from 5 to 30 km). To validate our GNSS H2O alerts, we use the detection of precipitation by C-band weather radar and thermal infrared radiance (cloud top temperature) of the 10.8-micrometers channel [Ch09] of SEVIRI instrument on Meteosat Second Generation. Using post-processed measurements, our H2O alerts obtain a score of about 80 %. Final and ultra-rapid IGS (International GNSS Service) orbits have been tested and show equivalent results. Fast calculations (less than 10 min) have been processed for 29 June 2005 with a time resolution of 5 min. The mean bias (and standard deviation) between fast and reference post-processed ZTD (zenith total delay) and gradients are, respectively, 0.002 (+/- 0.008) m and 0.001 (+/- 0.004) m. The score obtained for the H2O alerts generated by fast calculations is 65 %

    CEOS Intercalibration of Ground-Based Spectrometers and Lidars: Contract Change Notice 2012-2013: Final Report

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    This document is the final report of the Intercalibration of ground-based spectrometers and Lidars - Extension 2012-2013. It summarizes the activities performed in the period from November 2012 until December 2013 and the main results obtained

    Twelve years of global observations of formaldehyde in the troposphere using GOME and SCIAMACHY sensors

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    This work presents global tropospheric formaldehyde columns retrieved from near-UV radiance measurements performed by the GOME instrument onboard ERS-2 since 1995, and by SCIAMACHY, in operation on ENVISAT since the end of 2002. A special effort has been made to ensure the coherence and quality of the CH<sub>2</sub>O dataset covering the period 1996–2007. Optimised DOAS settings are proposed in order to reduce the impact of two important sources of error in the derivation of slant columns, namely, the polarisation anomaly affecting the SCIAMACHY spectra around 350 nm, and a major absorption band of the O<sub>4</sub> collision complex centred near 360 nm. The air mass factors are determined from scattering weights generated using radiative transfer calculations taking into account the cloud fraction, the cloud height and the ground albedo. Vertical profile shapes of CH<sub>2</sub>O are provided by the global CTM IMAGES based on an up-to-date representation of emissions, atmospheric transport and photochemistry. A comprehensive error analysis is presented. This includes errors on the slant columns retrieval and errors on the air mass factors which are mainly due to uncertainties in the a priori profile and in the cloud properties. The major features of the retrieved formaldehyde column distribution are discussed and compared with previous CH<sub>2</sub>O datasets over the major emission regions

    Characterisation of vertical BrO distribution during events of enhanced tropospheric BrO in Antarctica, from combined remote and in-situ measurements

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    Tropospheric BrO was measured by a ground-based remote-sensing spectrometer at Halley in Antarctica in spring 2007, and BrO was measured by satellite-borne remote-sensing spectrometers using similar spectral regions and similar Differential Optical Absorption Spectroscopy (DOAS) analyses. Near-surface BrO was simultaneously measured in situ at Halley by Chemical Ionisation Mass Spectrometer (CIMS), and in an earlier year near-surface BrO was measured at Halley over a long path by a ground-based DOAS spectrometer. During enhancement episodes, total amounts of tropospheric BrO from the ground-based remote-sensor were similar to those from space, but if we assume that the BrO was confined to the mixed layer they were very much larger than values measured by either near-surface technique. This large apparent discrepancy can be resolved if substantial amounts of BrO were in the free troposphere during most enhancement episodes. Amounts observed by the ground-based remote sensor at different elevation angles, and their formal inversions to vertical profiles, demonstrate that much of the BrO was indeed often in the free troposphere. This is consistent with the ~5 day lifetime of Bry and with the enhanced BrO observed during some Antarctic blizzards

    Evaluating the performance of pyrogenic and biogenic emission inventories against one decade of space-based formaldehyde columns

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    A new one-decade (1997–2006) dataset of formaldehyde (HCHO) columns retrieved from GOME and SCIAMACHY is compared with HCHO columns simulated by an updated version of the IMAGES global chemical transport model. This model version includes an optimized chemical scheme with respect to HCHO production, where the short-term and final HCHO yields from pyrogenically emitted non-methane volatile organic compounds (NMVOCs) are estimated from the Master Chemical Mechanism (MCM) and an explicit speciation profile of pyrogenic emissions. The model is driven by the Global Fire Emissions Database (GFED) version 1 or 2 for biomass burning, whereas biogenic emissions are provided either by the Global Emissions Inventory Activity (GEIA), or by a newly developed inventory based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) algorithms driven by meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF). The comparisons focus on tropical ecosystems, North America and China, which experience strong biogenic and biomass burning NMVOC emissions reflected in the enhanced measured HCHO columns. These comparisons aim at testing the ability of the model to reproduce the observed features of the HCHO distribution on the global scale and at providing a first assessment of the performance of the current emission inventories. The high correlation coefficients (<i>r</i>>0.7) between the observed and simulated columns over most regions indicate a good consistency between the model, the implemented inventories and the HCHO dataset. The use of the MEGAN-ECMWF inventory improves the model/data agreement in almost all regions, but biases persist over parts of Africa and Australia. Although neither GFED version is consistent with the data over all regions, a better agreement is achieved over Indonesia and Southern Africa when GFEDv2 is used, but GFEDv1 succeeds better in getting the correct seasonal patterns and intensities of the fire episodes over the Amazon basin, as reflected in the significantly higher correlations calculated in this region. Although the uncertainties in the HCHO retrievals, especially over fire scenes, can be quite large, this study provides a first assessment about whether the improved methodologies and input data implemented in GFEDv2 and MEGAN-ECMWF lead to better results in the comparisons of modelled with observed HCHO column measurements

    Satellite-based detection of volcanic sulphur dioxide from recent eruptions in Central and South America

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    Volcanic eruptions can emit large amounts of rock fragments and fine particles (ash) into the atmosphere, as well as several gases, including sulphur dioxide (SO<sub>2</sub>). These ejecta and emissions are a major natural hazard, not only to the local population, but also to the infrastructure in the vicinity of volcanoes and to aviation. Here, we describe a methodology to retrieve quantitative information about volcanic SO<sub>2</sub> plumes from satellite-borne measurements in the UV/Visible spectral range. The combination of a satellite-based SO<sub>2</sub> detection scheme and a state-of-the-art 3D trajectory model enables us to confirm the volcanic origin of trace gas signals and to estimate the plume height and the effective emission height. This is demonstrated by case-studies for four selected volcanic eruptions in South and Central America, using the GOME, SCIAMACHY and GOME-2 instruments

    Global emissions of non-methane hydrocarbons deduced from SCIAMACHY formaldehyde columns through 2003-2006

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    Formaldehyde columns retrieved from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography/Chemistry (SCIAMACHY) instrument onboard ENVISAT satellite through 2003 to 2006 are used as top-down constraints to derive updated global biogenic and biomass burning flux estimates for the non-methane volatile organic compounds (NMVOCs) precursors of formaldehyde. Our interest is centered over regions experiencing strong emissions, and hence exhibiting a high signal-to-noise ratio and lower measurement uncertainties. The formaldehyde dataset used in this study has been recently made available to the community and complements the long record of formaldehyde measurements from the Global Ozone Monitoring Experiment (GOME). We use the IMAGESv2 global chemistry-transport model driven by the Global Fire Emissions Database (GFED) version 1 or 2 for biomass burning, and from the newly developed MEGAN-ECMWF isoprene emission database. The adjoint of the model is implemented in a grid-based framework within which emission fluxes are derived at the model resolution, together with a differentiation of the sources in a grid cell. Two inversion studies are conducted using either the GFEDv1 or GFEDv2 as a priori for the pyrogenic fluxes. Although on the global scale the inferred emissions from the two categories exhibit only weak deviations from the corresponding a priori estimates, the regional updates often present large departures from their a priori values. The posterior isoprene emissions over North America, amounting to about 34 Tg C/yr, are estimated to be on average by 25% lower than the a priori over 2003–2006, whereas a strong increase (55%) is deduced over the south African continent, the optimized emission being estimated at 57 Tg C/yr. Over Indonesia the biogenic emissions appear to be overestimated by 20–30%, whereas over Indochina and the Amazon basin during the wet season the a priori inventory captures both the seasonality and the magnitude of the observed columns. Although neither biomass burning inventory seems to be consistent with the data over all regions, pyrogenic estimates inferred from the two inversions are reasonably similar, despite their a priori deviations. A number of sensitivity experiments are conducted in order to assess the impact of uncertainties related to the inversion setup and the chemical mechanism. Whereas changes in the background error covariance matrix have only a limited impact on the posterior fluxes, the use of an alternative isoprene mechanism characterized by lower HCHO yields (the GEOS-Chem mechanism) increases the posterior isoprene source estimate by 11% over northern America, and by up to 40% in tropical regions

    CEOS Intercalibration of Ground-Based Spectrometers and Lidars: Final Report

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    The ESA CEOS Intercalibration project concentrated on important calibration activities addressing three key components of the ground-based network ground-truthing capacity in Europe, namely the Dobson/Brewer network of ozone spectrophotometers, the aerosol lidar EARLINET network and the UV-Vis MAXDOAS technique for air quality remote-sensing. This document summarizes activities and achievements during the third part of the ESA CEOS Intercalibration project. The period covered by this report extends from February 2012 until October 2012

    Global long-term monitoring of the ozone layer - a prerequisite for predictions

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    Although the Montreal Protocol now controls the production and emission of ozone depleting substances, the timing of ozone recovery is unclear. There are many other factors affecting the ozone layer, in particular climate change is expected to modify the speed of re-creation of the ozone layer. Therefore, long-term observations are needed to monitor the further evolution of the stratospheric ozone layer. Measurements from satellite instruments provide global coverage and are supplementary to selective ground-based observations. The combination of data derived from different space-borne instruments is needed to produce homogeneous and consistent long-term data records. They are required for robust investigations including trend analysis. For the first time global total ozone columns from three European satellite sensors GOME (ERS-2), SCIAMACHY (ENVISAT), and GOME-2 (METOP-A) are combined and added up to a continuous time series starting in June 1995. On the one hand it is important to monitor the consequences of the Montreal Protocol and its amendments; on the other hand multi-year observations provide the basis for the evaluation of numerical models describing atmospheric processes, which are also used for prognostic studies to assess the future development. This paper gives some examples of how to use satellite data products to evaluate model results with respective data derived from observations, and to disclose the abilities and deficiencies of atmospheric models. In particular, multi-year mean values derived from the Chemistry-Climate Model E39C-A are used to check climatological values and the respective standard deviations
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