256 research outputs found
Three years of greenhouse gas column-averaged dry air mole fractions retrieved from satellite – Part 2: Methane
Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 µm absorption band), CH4 (1.66 µm) and oxygen (O2 A-band at 0.76 µm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCH4 data set. The XCO2 data set is discussed in a separate paper (Part 1). For 2003 we present detailed comparisons with the TM5 model which has been optimally matched to highly accurate but sparse methane surface observations. After accounting for a systematic low bias of ~2% agreement with TM5 is typically within 1–2%. We investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from NOAA's CO2 assimilation system CarbonTracker. We show that the CO2 corrected and uncorrected XCH4 spatio-temporal pattern are very similar but that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with previous studies (e.g., Frankenberg et al., 2005b) we find higher methane over the tropics compared to the model. We show that tropical methane is also higher when normalizing the CH4 columns with retrieved O2 columns instead of CO2. In consistency with recent results of Frankenberg et al. (2008b) it is shown that the magnitude of the retrieved tropical methane is sensitive to the choice of the spectroscopic line parameters of water vapour. Concerning inter-annual variability we find similar methane spatio-temporal pattern for 2003 and 2004. For 2005 the retrieved methane shows significantly higher variability compared to the two previous years, most likely due to somewhat larger noise of the spectral measurement
Global distribution of ship tracks from one year of AATSRdata
The perturbation of a cloud layer by ship-generated aerosol changes the cloud reflectivity and is identified by elongated structures in satellite images, known as ship tracks. As ship tracks indicate a pollution of the clean marine environment and also affect the radiation budget below and above the cloud, it is important to investigate their radiative and climate impact. In this study we use satellite data to examine the effects of ship tracks on a particular scene as well as on
the global scale. The cloud optical and microphysical properties are derived using a semi-analytical retrieval technique combined with a look-up-table approach. Within the ship tracks a significant change in the droplet number concentration, the effective radius and the optical thickness are found
compared to the unaffected cloud. The resulting cloud properties are used to calculate the radiation budget below and above the cloud. Local impacts are shown for a selected scene from MODIS on Terra. The mean reflectance at top of atmosphere (TOA) is increased by 40.8 Wm-2. For a particular scene chosen close to the West Coast of North America on 10th February 2003, ship emissions increase the backscattered solar radiation at TOA by 2.0Wm-2, corresponding to a negative radiative forcing (RF). A global distribution of ship tracks derived from one year of AATSR data shows high spatial and temporal variability with highest occurrence of ship tracks westward of North America and the southwest coast of Africa, but small RF on the global scale
Validation of SCIAMACHY AMC-DOAS water vapour columns
International audienceA first validation of water vapour total column amounts derived from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) in the visible spectral region has been performed. For this purpose, SCIAMACHY water vapour data have been determined for the year 2003 using an extended version of the Differential Optical Absorption Spectroscopy (DOAS) method, called Air Mass Corrected (AMC-DOAS). The SCIAMACHY results are compared with corresponding water vapour measurements by the Special Sensor Microwave Imager (SSM/I) and with model data from the European Centre for Medium-Range Weather Forecasts (ECMWF). In confirmation of previous results it could be shown that SCIAMACHY derived water vapour columns are typically slightly lower than both SSM/I and ECMWF data, especially over ocean areas. However, these deviations are much smaller than the observed scatter of the data which is caused by the different temporal and spatial sampling and resolution of the data sets. For example, the overall difference with ECMWF data is only -0.05 g/cm2 whereas the typical scatter is in the order of 0.5 g/cm2. Both values show almost no variation over the year. In addition, first monthly means of SCIAMACHY water vapour data have been computed. The quality of these monthly means is currently limited by the availability of calibrated SCIAMACHY spectra. Nevertheless, first comparisons with ECMWF data show that SCIAMACHY (and similar instruments) are able to provide a new independent global water vapour data set
Three years of global carbon monoxide from SCIAMACHY: comparison with MOPITT and first results related to the detection of enhanced CO over cities
Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and climate. SCIAMACHY on ENVISAT is currently the only satellite instrument that can measure the vertical column of CO with nearly equal sensitivity at all altitudes down to the Earth's surface because of its near-infrared nadir observations of reflected solar radiation. Here we present three years' (2003–2005) of SCIAMACHY CO columns consistently retrieved with the latest version of our retrieval algorithm (WFMDv0.6). We describe the retrieval method and discuss the multi-year global CO data set focusing on a comparison with the operational CO column data product of MOPITT. We found reasonable to good agreement (~20%) with MOPITT, with the best agreement for 2004. We present detailed results for various regions (Europe, Middle East, India, China) and discuss to what extent enhanced levels of CO can be detected over populated areas including individual cities. The expected CO signal from cities is close to or even below the detection limit of individual measurements. We show that cities can be identified when averaging long time series
Preliminary results of GOME-2 water vapour retrievals and first applications in polar regions
International audienceGlobal total water vapour columns have been derived from measurements of the Global Ozone Monitoring Experiment 2 (GOME-2) on MetOp. For this purpose, the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) method has been adapted, having previously been applied successfully to GOME (on ERS-2) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY, on ENVISAT) data. Comparisons between the derived GOME-2 and SCIAMACHY water vapour columns show a good overall agreement. This gives confidence that the temporal series of water vapour columns from GOME-type instruments (GOME/ERS-2, SCIAMACHY/ENVISAT), which began in 1995, is successfully continued by the MetOp instrumentation until at least 2020. The enhanced temporal and spatial resolution of GOME-2 enables the analysis of diurnal variations in the polar regions. This is especially important because atmospheric data sources in the polar regions are generally sparse. As an exemplary application, daily water vapour total columns over the polar research station Ny Ålesund (78°55'19" N/11°56'33" E) are investigated. At this latitude GOME-2 yields about six data points during daylight hours at varying local times. From these data diurnal variations of water vapour have been successfully retrieved
Retrieval of global water vapour columns from GOME-2 and first applications in polar regions
International audienceGlobal total water vapour columns have been derived from measurements of the Global Ozone Monitoring Experiment 2 (GOME-2) on MetOp. For this purpose, the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) method has been adapted, which has already been applied successfully to GOME (on ERS-2) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY, on ENVISAT) data. Comparisons between the derived GOME-2 and SCIAMACHY water vapour columns show a good overall agreement. This gives confidence that the time series of water vapour columns from GOME-type instruments which started in 1995 can be continued by the MetOp instrumentation until at least 2020. The enhanced temporal and spatial resolution of GOME-2 enables the analysis of short-term variations particularly in the polar regions. This is especially important since atmospheric data sources in the polar regions are generally sparse. As an exemplary application, daily water vapour concentrations over the polar research station Ny Ålesund (78°55'19" N/11°56'33" E) are investigated. At this latitude GOME-2 gives about six data points during daylight hours at varying local times. The results of this study show that it is possible to derive information about the diurnal variability of water vapour in polar regions from GOME-2 measurements
Analysis of global water vapour trends from satellite measurements in the visible spectral range
International audienceGlobal water vapour total column amounts have been retrieved from spectral data provided by the Global Ozone Monitoring Experiment (GOME) flying on ERS-2, which was launched in April 1995, and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT launched in March 2002. For this purpose the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) approach has been used. The combination of the data from both instruments provides us with a long-term global data set spanning more than 11 years with the potential of extension up to 2020 by GOME-2 data, on Metop. Using linear and non-linear methods from time series analysis and standard statistics the trends of H2O contents and their errors have been calculated. In this study, factors affecting the trend such as the length of the time series, the magnitude of the variability of the noise, and the autocorrelation of the noise are investigated. Special emphasis has been placed on the calculation of the statistical significance of the observed trends, which reveal significant local changes of water vapour columns distributed over the whole globe. <br
Three Years of Greenhouse Gas Column-Averaged Dry Air Mole Fractions Retrieved from Satellite - Part 2: Methane
Abstract. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases.
SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003-2005) of SCIAMACHY nearinfrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58µm absorption band),
CH4 (1.66µm) and oxygen (O2 A-band at 0.76µm) using the scientific retrieval algorithm WFM-DOAS.We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (1 min per orbit, corresponding to 6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better
cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 Aband.
Here we focus on a discussion of the XCH4 data set. The XCO2 data set is discussed in a separate paper (Part 1). For 2003 we present detailed comparisons with the TM5 model which has been optimally matched to highly accurate but sparse methane surface observations. After accounting for a systematic low bias of 2% agreement with TM5 is typically within 1¿2%. We investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from NOAA¿s CO2 assimilation system CarbonTracker. We show that the CO2 corrected and uncorrected XCH4 spatio-temporal pattern are very similar but that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with previous studies (e.g., Frankenberg et al., 2005b) we find higher methane over the tropics compared to the model. We show that tropical methane is also higher when normalizing the CH4 columns with retrieved O2 columns instead of CO2. In consistency with recent results of Frankenberg et al. (2008b) it is shown that the magnitude of the retrieved tropical methane is sensitive to the choice of the spectroscopic line parameters of water vapour. Concerning inter-annual
variability we find similar methane spatio-temporal pattern for 2003 and 2004. For 2005 the retrieved methane shows significantly higher variability compared to the two previous years, most likely due to somewhat larger noise of the spectral measurements.JRC.H.2-Air and Climat
First direct observation of the atmospheric CO2 year-to-year increase from space
The reliable prediction of future atmospheric CO<sub>2</sub> concentrations and associated global climate change requires an adequate understanding of the CO<sub>2</sub> sources and sinks. The sparseness of the existing surface measurement network limits current knowledge about the global distribution of CO<sub>2</sub> surface fluxes. The retrieval of CO<sub>2</sub> total vertical columns from satellite observations is predicted to improve this situation. Such an application however requires very high accuracy and precision. We report on retrievals of the column-averaged CO<sub>2</sub> dry air mole fraction, denoted XCO<sub>2</sub>, from the near-infrared nadir spectral radiance and solar irradiance measurements of the SCIAMACHY satellite instrument between 2003 and 2005. We focus on northern hemispheric large scale CO<sub>2</sub> features such as the CO<sub>2</sub> seasonal cycle and show - for the first time - that the atmospheric annual increase of CO<sub>2</sub> can be directly observed using satellite measurements of the CO<sub>2</sub> total column. The satellite retrievals are compared with global XCO<sub>2</sub> obtained from NOAA's CO<sub>2</sub> assimilation system CarbonTracker taking into account the spatio-temporal sampling and altitude sensitivity of the satellite data. We show that the measured CO<sub>2</sub> year-to-year increase agrees within about 1 ppm/year with CarbonTracker. We also show that the latitude dependent amplitude of the northern hemispheric CO<sub>2</sub> seasonal cycle agrees with CarbonTracker within about 2 ppm with the retrieved amplitude being systematically larger. The analysis demonstrates that it is possible using satellite measurements of the CO<sub>2</sub> total column to retrieve information on the atmospheric CO<sub>2</sub> on the level of a few parts per million
Global carbon monoxide as retrieved from SCIAMACHY by WFM-DOAS
First results concerning the retrieval of tropospheric carbon monoxide (CO) from satellite solar backscatter radiance measurements in the near-infrared spectral region (~2.3µm) are presented. The Weighting Function Modified (WFM) DOAS retrieval algorithm has been used to retrieve vertical columns of CO from SCIAMACHY/ENVISAT nadir spectra. We present detailed results for three days from the time periode January to October 2003 selected to have good overlap with the daytime CO measurements of MOPITT onboard EOS Terra. Because the WFM-DOAS Version 0.4 CO columns presented in this paper are scaled by a constant factor of 0.5 to compensate for an obvious overestimation we focus on the variability of the retrieved columns rather than on their absolute values. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are detectable with single overpass SCIAMACHY data. Globally, the SCIAMACHY CO columns are in reasonable agreement with the Version 3 CO column data product of MOPITT. For example, for measurements over land, where the quality of the data is typically better than over ocean due to higher surface reflectivity, the standard deviation of the difference with respect to MOPITT is in the range 0.4-0.6x10<sup>18</sup> molecules/cm<sup>2</sup> and the linear correlation coefficient is between 0.4 and 0.7. The level of agreement between the data of both sensors depends on time and location but is typically within 30% for most latitudes. In the southern hemisphere outside Antarctica SCIAMACHY tends to give systematically higher values than MOPITT. More studies are needed to find out what the reasons for the observed differences with respect to MOPITT are and how the algorithm can be modified to improve the quality of the CO columns as retrieved from SCIAMACHY
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