Preliminary signs of the initiation of deep convection by GNSS

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 %

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

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

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

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

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

International audienceThis 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 CH2O 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 O4 collision complex centred near 360 nm. The air mass factors are determined from scattering weights generated using radiative transfer calculation taking into account the cloud fraction, the cloud height and the ground albedo. Vertical profile shapes of CH2O 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 CH2O datasets over the major emission regions

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

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

Trends of tropical tropospheric ozone from 20 years of European satellite measurements and perspectives for the Sentinel-5 Precursor

In preparation of the TROPOMI/S5P launch in early 2017, a tropospheric ozone retrieval based on the convective cloud differential method was developed. For intensive tests we applied the algorithm to the total ozone columns and cloud data of the satellite instruments GOME, SCIAMACHY, OMI, GOME-2A and GOME-2B. Thereby a time series of 20 years (1995–2015) of tropospheric column ozone was generated. To have a consistent total ozone data set for all sensors, one common retrieval algorithm, namely GODFITv3, was applied and the L1 reflectances were also soft calibrated. The total ozone columns and the cloud data were input into the tropospheric ozone retrieval. However, the tropical tropospheric column ozone (TCO) for the individual instruments still showed small differences and, therefore, we harmonised the data set. For this purpose, a multilinear function was fitted to the averaged difference between SCIAMACHY's TCO and those from the other sensors. The original TCO was corrected by the fitted offset. GOME-2B data were corrected relative to the harmonised data from OMI and GOME-2A. The harmonisation leads to a better agreement between the different instruments. Also, a direct comparison of the TCO in the overlapping periods proves that GOME-2A agrees much better with SCIAMACHY after the harmonisation. The improvements for OMI were small. Based on the harmonised observations, we created a merged data product, containing the TCO from July 1995 to December 2015. A first application of this 20-year record is a trend analysis. The tropical trend is 0.7 ± 0.12 DU decade−1. Regionally the trends reach up to 1.8 DU decade−1 like on the African Atlantic coast, while over the western Pacific the tropospheric ozone declined over the last 20 years with up to 0.8 DU decade−1. The tropical tropospheric data record will be extended in the future with the TROPOMI/S5P data, where the TCO is part of the operational products

Equations for solar tracking

Direct Sun light absorption by trace gases can be used to quantify them and investigate atmospheric chemistry. In such experiments, the main optical apparatus is often a grating or a Fourier transform spectrometer. A solar tracker based on motorized rotating mirrors is also needed to direct the light along the spectrometer axis, correcting for the apparent rotation of the Sun. Calculating the Sun azimuth and altitude for a given time and location can be achieved with high accuracy but different sources of angular offsets appear in practice when positioning the mirrors. A feedback on the motors, using a light position sensor closed to the spectrometer is almost always needed. This paper aims to gather the main geometrical formulas necessary for the use of a widely used kind of solar tracker, based on two 45{\deg} mirrors in altazimuthal set-up with a light sensor on the spectrometer, and to illustrate them with a tracker developed for atmospheric research by our group.Comment: 14 pages, 7 figures. Second version of the paper as published in Sensors. Main correction: a rotation matrix converted to a reflection matrix. Main addition: a discussion on how the control theory applies to this kind of tracking syte

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

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

Geophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura

The main aim of the paper is to assess the consistency of five years of Global Ozone Monitoring Experiment-2/Metop-A [GOME-2] total ozone columns and the long-term total ozone satellite monitoring database already in existence through an extensive inter-comparison and validation exercise using as reference Brewer and Dobson ground-based measurements. The behaviour of the GOME-2 measurements is being weighed against that of GOME (1995–2011), Ozone Monitoring Experiment [OMI] (since 2004) and the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY [SCIAMACHY] (since 2002) total ozone column products. Over the background truth of the ground-based measurements, the total ozone columns are inter-evaluated using a suite of established validation techniques; the GOME-2 time series follow the same patterns as those observed by the other satellite sensors. In particular, on average, GOME-2 data underestimate GOME data by about 0.80%, and underestimate SCIAMACHY data by 0.37% with no seasonal dependence of the differences between GOME-2, GOME and SCIAMACHY. The latter is expected since the three datasets are based on similar DOAS algorithms. This underestimation of GOME-2 is within the uncertainty of the reference data used in the comparisons. Compared to the OMI sensor, on average GOME-2 data underestimate OMI_DOAS (collection 3) data by 1.28%, without any significant seasonal dependence of the differences between them. The lack of seasonality might be expected since both the GOME data processor [GDP] 4.4 and OMI_DOAS are DOAS-type algorithms and both consider the variability of the stratospheric temperatures in their retrievals. Compared to the OMI_TOMS (collection 3) data, no bias was found. We hence conclude that the GOME-2 total ozone columns are well suitable to continue the long-term global total ozone record with the accuracy needed for climate monitoring studies

Global observations of tropospheric BrO columns using GOME-2 satellite data

Measurements from the GOME-2 satellite instrument have been analyzed for tropospheric BrO using a residual technique that combines measured BrO columns and estimates of the stratospheric BrO content from a climatological approach driven by O<sub>3</sub> and NO<sub>2</sub> observations. Comparisons between the GOME-2 results and BrO vertical columns derived from correlative ground-based and SCIAMACHY nadir observations, present a good level of consistency. We show that the adopted technique enables separation of stratospheric and tropospheric fractions of the measured total BrO columns and allows quantitative study of the BrO plumes in polar regions. While some satellite observed plumes of enhanced BrO can be explained by stratospheric descending air, we show that most BrO hotspots are of tropospheric origin, although they are often associated to regions with low tropopause heights as well. Elaborating on simulations using the <i>p</i>-TOMCAT tropospheric chemical transport model, this result is found to be consistent with the mechanism of bromine release through sea salt aerosols production during blowing snow events. No definitive conclusion can be drawn however on the importance of blowing snow sources in comparison to other bromine release mechanisms. Outside polar regions, evidence is provided for a global tropospheric BrO background with column of 1–3 × 10<sup>13</sup> molec cm<sup>−2</sup>, consistent with previous estimates