Scanning Imaging Absorption Spectrometer For Atmospheric Cartography Research Articles

Forecasts and assimilation experiments of the Antarctic ozone hole 2008

Abstract. The 2008 Antarctic ozone hole was one of the largest and most long-lived in recent years. Predictions of the ozone hole were made in near-real time (NRT) and hindcast mode with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The forecasts were carried out both with and without assimilation of satellite observations from multiple instruments to provide more realistic initial conditions. Three different chemistry schemes were applied for the description of stratospheric ozone chemistry: (i) a linearization of the ozone chemistry, (ii) the stratospheric chemical mechanism of the Model of Ozone and Related Chemical Tracers, version 3, (MOZART-3) and (iii) the relaxation to climatology as implemented in the Transport Model, version 5, (TM5). The IFS uses the latter two schemes by means of a two-way coupled system. Without assimilation, the forecasts showed model-specific shortcomings in predicting start time, extent and duration of the ozone hole. The assimilation of satellite observations from the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), the Solar Backscattering Ultraviolet radiometer (SBUV-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) led to a significant improvement of the forecasts when compared with total columns and vertical profiles from ozone sondes. The combined assimilation of observations from multiple instruments helped to overcome limitations of the ultraviolet (UV) sensors at low solar elevation over Antarctica. The assimilation of data from MLS was crucial to obtain a good agreement with the observed ozone profiles both in the polar stratosphere and troposphere. The ozone analyses by the three model configurations were very similar despite the different underlying chemistry schemes. Using ozone analyses as initial conditions had a very beneficial but variable effect on the predictability of the ozone hole over 15 days. The initialized forecasts with the MOZART-3 chemistry produced the best predictions of the increasing ozone hole whereas the linear scheme showed the best results during the ozonehole closure.

Retrieval of atmospheric CO2with enhanced accuracy and precision from SCIAMACHY: Validation with FTS measurements and comparison with model results

The Bremen Optimal Estimation differential optical absorption spectroscopy (DOAS) (BESD) algorithm for satellite based retrievals of XCO_2 (the column-average dry-air mole fraction of atmospheric CO_2) has been applied to Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) data. It uses measurements in the O_2-A absorption band to correct for scattering of undetected clouds and aerosols. Comparisons with precise and accurate ground-based Fourier transform spectrometer (FTS) measurements at four Total Carbon Column Observing Network (TCCON) sites have been used to quantify the quality of the new SCIAMACHY XCO_2 data set. Additionally, the results have been compared to NOAA's assimilation system CarbonTracker. The comparisons show that the new retrieval meets the expectations from earlier theoretical studies. We find no statistically significant regional XCO_2 biases between SCIAMACHY and the FTS instruments. However, the standard error of the systematic differences is in the range of 0.2 ppm and 0.8 ppm. The XCO_2 single-measurement precision of 2.5 ppm is similar to theoretical estimates driven by instrumental noise. There are no significant differences found for the year-to-year increase as well as for the average seasonal amplitude between SCIAMACHY XCO_2 and the collocated FTS measurements. Comparison of the year-to-year increase and also of the seasonal amplitude of CarbonTracker exhibit significant differences with the corresponding FTS values at Darwin. Here the differences between SCIAMACHY and CarbonTracker are larger than the standard error of the SCIAMACHY values. The difference of the seasonal amplitude exceeds the significance level of 2 standard errors. Therefore, our results suggest that SCIAMACHY may provide valuable additional information about XCO_2, at least in regions with a low density of in situ measurements.

A case study on the application of SCIAMACHY satellite methane measurements for regional studies: the Greater Area of the Eastern Mediterranean

Many studies have focused on geological formations, such as mud volcanoes, which abound in the Greater Area of the Eastern Mediterranean (GAEM; 25° N–50° N, 5° E–55° E). This geological source is thought to provide a significant portion of the global methane (CH4) emissions. However, studies in the GAEM have focused on specific locations rather than extensive areas, which has led to a gap in our understanding of the spatial and temporal variability of CH4 atmospheric mixing ratios. Here, we present characteristics of methane loading over land in the GAEM using dry air columnar data (XCH4) retrieved from SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) satellite measurements with the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) version 1.0 algorithm. We defined methane annual, seasonal and monthly spatial patterns over the area using 2003 and 2004 measurements. The annual mean XCH4 levels over the study area were estimated to be 1761 ± 27 ppb for 2003 and 1758 ± 26 ppb for 2004. A seasonal variability with a summer–autumn peak was observed for both 2003 and 2004, August being the month with the highest methane concentrations. The northeastern part of the area exhibits the highest XCH4 values while the high elevation regions defined by the triangle of eastern Turkey, the Persian Gulf and the Caspian Sea and the region of the eastern coast of the Red Sea exhibit the lowest levels. A latitudinal gradient was observed for the area during 2003 and 2004. A comparison of measured XCH4 levels above two of the world's most renowned mud volcano regions situated in the GAEM with anticipated methane columnar concentrations as modelled for eruption cases shows that no mud volcano eruptions were observed from SCIAMACHY during 2003 or 2004.

Analysis of spatial and temporal variations of carbon dioxide over China using SCIAMACHY satellite observations during 2003–2005

This study aims to assess CO2 levels in China, based on the dry air column-averaged mixing ratios of CO2 measured by the Scanning Imaging Absorption spectrometer for Atmospheric CartograpHY (SCIAMACHY) instrument on board ENVISAT and emission inventories. A land cover and statistical data set, the Regional emission inventory in Asia (REAS), was also used in this study. The results show that the spatial variations of the CO2 concentration in the whole of China are obvious, and with clear seasonal fluctuation during 2003–2005. The monthly averaged variability of CO2 over China fluctuates, with the peak occurring in April to May and the trough occurring in August to October. The largest peak-to-trough amplitude was about 16 ppm in this period. The spatial and temporal variations of CO2 had a strong correlation with anthropogenic CO2 emissions and regional terrestrial ecosystem, as well as local meteorological conditions. This paper illustrates that satellite data are promising for obtaining a comprehensive understanding of the variations of atmospheric CO2 concentrations and of CO2 emissions to the atmosphere.

Temporal variation of urban NO x concentration in India during the past decade as observed from space

Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) tropospheric NO2 retrievals (average during March–April–May 2003–2006) were used to locate the major urban sources of NO2 in India. To show that tropospheric NO2 measurements from satellites can provide useful information on day-to-day changes in urban NO2 concentration, we compared 2-year (October 2004–October 2006) records of surface air NO2 concentrations obtained at one of the measurement sites in Delhi to retrievals of tropospheric NO2 columns from Ozone Monitoring Instrument (OMI) observations. The quality of correlation between satellite observations at the urban scale and surface measurements (45%) provided confidence to investigate the temporal changes in the local emission over major urban locations. Combined Global Ozone Monitoring Experiment (GOME) and SCIAMACHY measurements for the period March 1996–December 2007 were used to compute the trends over the selected urban locations. A statistical analysis was applied to derive trends for this period over these locations. The time series of the monthly NO2 columns for these 11 years were fitted with a linear function superposed on an annual seasonal cycle. We found a statistically significant increase in tropospheric NO2 levels over the major urban cities in India. Notable urban locations of positive trends were found to be the cities where the urban population is growing rapidly.

Global column-averaged methane mixing ratios from 2003 to 2009 as derived from SCIAMACHY: Trends and variability

After a decade of stable or slightly decreasing global methane concentrations, ground-based in situ data show that CH_4 began increasing again in 2007 and that this increase continued through 2009. So far, space-based retrievals sensitive to the lower troposphere in the time period under consideration have not been available. Here we report a long-term data set of column-averaged methane mixing ratios retrieved from spectra of the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) instrument onboard Envisat. The retrieval quality after 2005 was severely affected by degrading detector pixels within the methane 2ν_3 absorption band. We identified the most crucial problems in SCIAMACHY detector degradation and overcame the problem by applying a strict pixel mask as well as a new dark current characterization. Even though retrieval precision after the end of 2005 is invariably degraded, consistent methane retrievals from 2003 through 2009 are now possible. Regional time series in the Sahara, Australia, tropical Africa, South America, and Asia show the methane increase in 2007–2009, but we cannot yet draw a firm conclusion concerning the origin of the increase. Tropical Africa even seems to exhibit a negative anomaly in 2006, but an impact from changes in SCIAMACHY detector degradation cannot be excluded yet. Over Assakrem, Algeria, we observed strong similarities between SCIAMACHY measurements and ground-based data in deseasonalized time series. We further show long-term SCIAMACHY xCH_4 averages at high spatial resolution that provide further insight into methane variations on regional scales. The Red Basin in China exhibits, on average, the highest methane abundance worldwide, while other localized features such as the Sudd wetlands in southern Sudan can also be identified in SCIAMACHY xCH_4 averages.

Global patterns in daytime cloud properties derived from GOME backscatter UV-VIS measurements

In this paper, we present an overview of the cloud property data set derived from 8 years of reflected solar ultraviolet-visible (UV-VIS) measurements taken by the global ozone monitoring experiment (GOME) instrument from April 1996 to June 2003. We consider four such properties: cloud amount, cloud-top pressure, cloud optical thickness and cloud type. Cloud amounts are generated from GOME broadband polarization data using data fusion techniques, while cloud-top height (pressure) and cloud-top albedo are retrieved from GOME backscatter measurements in the oxygen (O2) A-band via neural network inversion of simulated reflectances. Cloud optical thickness is derived as an additional parameter from the cloud-top albedo and radiative transfer model simulations, and cloud type is determined from the cloud-top pressure and optical thickness. We analyse global and seasonal patterns for these properties, looking at monthly means, standard deviations and the 8-year average values. We compare GOME results with the longer-period multisatellite international satellite cloud climatology project (ISCCP) D-series cloud climatology. The overall good agreement demonstrates that GOME provides accurate and complementary cloud information. Differences in cloud amount, cloud-top height and optical thickness values are due primarily to contrasting measurement strategies (GOME measures daytime-only UV-VIS backscatter, ISCCP is based on several day and night infrared satellite observations). We look forward to the extension of this UV-VIS cloud parameter series with the advent of more recent backscatter atmospheric composition instruments such as the scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) on-board the environmental satellite (ENVISAT) and the GOME-2 series on the MetOp platforms.

A long‐term stratospheric ozone data set from assimilation of satellite observations: High‐latitude ozone anomalies

A 29 year data set of stratospheric ozone from sequential assimilation of solar backscatter UV (SBUV) satellite ozone profile observations into a chemical transport model is introduced and validated against independent observations (satellite instruments and sondes). Our assimilated data set shows excellent agreement with ozone profile data from sonde measurements from high‐latitude observation sites on both hemispheres and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite observations, including during polar night when no SBUV observations are available. Although we only assimilate ozone profiles, total column ozone in the assimilated data set is in good agreement with independent satellite observations from the Global Ozone Monitoring Experiment (GOME), the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and the Total Ozone Mapping Spectrometer (TOMS). The data set can thus be viewed as a consistent long‐term data set closing the gaps in satellite observations in order to investigate high‐latitude ozone variability. We then use the assimilated data set to analyze the development and persistence of both high and low ozone anomalies in the Arctic stratosphere. Ozone anomalies typically develop in the 1000 K potential temperature (∼35 km) region and slowly descend from there, remaining visible for around 7 months. Anomalies in the stratospheric circulation, expressed by the Northern Hemisphere annular mode (NAM) index, show a large influence on ozone anomalies. Extreme phases of the NAM index (strong and weak vortex events) lead to the creation of distinctively shaped ozone anomalies, which first appear in the uppermost stratosphere and then rapidly cover the upper and middle stratosphere, from where they then slowly descend into the lowermost stratosphere within 5 months.

Global evaluation of SCIAMACHY and MOPITT carbon monoxide column differences for 2004–2005

This paper presents a detailed global comparison of Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) and Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) column measurements for the years 2004 and 2005. Qualitatively, spatiotemporal variations of SCIAMACHY and MOPITT are similar. Quantitative comparisons have been performed taking the effects of instrument noise errors, vertical sensitivities via the averaging kernel and a priori, different spatiotemporal sampling and clouds into account using simulated CO profiles from the TM4 model. SCIAMACHY and MOPITT CO columns are similar over tropical, subtropical, and Northern Hemisphere oceans as well as over boreal regions where SCIAMACHY and MOPITT agree to within 10% or 2 × 1017 molecules/cm2. The short‐wave infrared SCIAMACHY observations also provide information about lower tropospheric CO in Arctic and subarctic regions north of 60°N, where the MOPITT sensitivity is strongly reduced. South of 45°S, SCIAMACHY CO columns are 3–5 × 1017 molecules/cm2 smaller than MOPITT CO columns. Approximately 1.5 × 1017 molecules/cm2 (∼10%) of this difference is attributed to a bias in the SCIAMACHY CO columns, which is currently under investigation. The remaining difference is possibly related to MOPITT biases in this region. In the transition from oceans to dry desert regions, MOPITT CO total columns show a rapid increase of approximately 3 × 1017 molecules/cm2 (∼15%). While MOPITT and SCIAMACHY agree over oceans, MOPITT is approximately 5 × 1017 molecules/cm2 (∼25%) larger than SCIAMACHY results over dry land regions. The origin of this bias needs further investigation.

Modulations of the 27 day solar rotation signal in stratospheric ozone from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (2003–2008)

Here we investigate the modulating nature of the 27 day solar rotation forcing on stratospheric ozone using a new ozone profile data set from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY, 2003–2008). Continuous wavelet transform (CWT), fast Fourier transform (FFT), and cross correlations (CC) have been applied to SCIAMACHY ozone in the tropics (<20° latitude) between 20 and 60 km altitude. The maximum correlation between Mg II index and ozone is weaker during the maximum of solar cycle 23 (r = 0.38) than in the previous two solar cycles that have been investigated in earlier studies using different data sets. The magnitude of the ozone signal is highly time dependent and may vanish for several solar rotations even close to solar maximum conditions. The FFT analysis reveals, besides the 27 day signal, several frequencies close to 27 days. The ozone sensitivity (ozone change in percent per percent change in 205 nm solar flux) is on average about 0.2%/% above 30 km altitude and smaller by about a factor of 2 compared to earlier studies. For selected 3 month periods the sensitivity may rise beyond 0.6%/% in better agreement with earlier studies. The analysis of the 27 day solar forcing was also carried out with stratospheric temperatures from European Centre for Medium‐Range Weather Forecasts operational analysis. Although direct radiation effects on temperature are weak in the upper stratosphere, temperature signals with statistically significant periods in the 25–35 day range similar to ozone could be found with the applied methods.

Determination of the cloud fraction in the SCIAMACHY ground scene using MERIS spectral measurements

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) is a passive remote sensing spectrometer observing backscattered radiation from the atmosphere and the Earth's surface, in the wavelength range between 240 and 2380 nm. The instrument is onboard ENVironmental SATellite (ENVISAT) which was launched on 1 March 2002. The Medium Resolution Imaging Spectrometer (MERIS) is also one of the 10 instruments onboard the ENVISAT satellite. MERIS is a 68.5° field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). It obtains a global coverage of the Earth in three days. Its main objective is to measure sea colour and quantify ocean chlorophyll content and sediment, thus providing information on the ocean carbon cycle and thermal regime. It is also used to derive the cloud top height, aerosol and cloud optical thickness, and water vapour column. The ground spatial resolution of the instrument is 260 m × 290 m. This paper is aimed at determining the cloud fraction in SCIAMACHY pixels (typically, 30 km × 60 km ground scenes) using MERIS observations and number of thresholds for MERIS top-of-atmosphere reflectances and their ratios. Thresholds utilize the fact that clouds are bright white objects having similar reflectances in the blue and red. The MERIS cloud fraction has been derived for a number of SCIAMACHY states with area of 916 km × 400 km. The results are compared with correspondent cloud fractions obtained using SCIAMACHY polarization measurement devices (PMDs). Large differences are found between cloud fractions derived using SCIAMACHY and MERIS measurements. It is recommended to use highly spatially resolved MERIS observations instead of SCIAMACHY PMD measurements to retrieve cloud fractions in SCIAMACHY pixels. The improvements advised will enhance SCIAMACHY trace gas and cloud retrievals in the presence of broken cloud fields.

The GlobMODEL Demonstrator: Assimilation of New Satellite Products in an Operational Meteorological Center

As part of its Data User Element programme, the European Space Agency funded the GlobMODEL project which aimed at investigating the scientific, technical, and organizational issues associated with the use and exploitation of remotely-sensed observations, particularly from new sounders. A pilot study was performed as a ldquodemonstratorrdquo of the GlobMODEL idea, based on the use of new data, with a strong European heritage, not yet assimilated operationally. Two parallel assimilation experiments were performed, using either total column ozone or ozone profiles retrieved at the Royal Netherlands Meteorological Institute (KNMI) from the Ozone Monitoring Instrument (OMI). In both cases, the impact of assimilating OMI data in addition to the total ozone columns from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) on the European Centre for Medium Range Weather Forecasts (ECMWF) ozone analyses was assessed by means of independent measurements. We found that the impact of OMI total columns is mainly limited to the region between 20 and 80 hPa, and is particularly important at high latitudes in the Southern hemisphere where the stratospheric ozone transport and chemical depletion are generally difficult to model with accuracy. Furthermore, the assimilation experiments carried out in this work suggest that OMI DOAS (Differential Optical Absorption Spectroscopy) total ozone columns are on average larger than SCIAMACHY total columns by up to 3 DU, while OMI total columns derived from OMI ozone profiles are on average about 8 DU larger than SCIAMACHY total columns. At the same time, the demonstrator brought to light a number of issues related to the assimilation of atmospheric composition profiles, such as the shortcomings arising when the vertical resolution of the instrument is not properly accounted for in the assimilation. The GlobMODEL demonstrator accelerated scientific and operational utilization of new observations and its results prompted ECMWF to start the operational assimilation of OMI total column ozone data.

Assimilation of SCIAMACHY total column CO observations: Global and regional analysis of data impact

Carbon monoxide (CO) total column observations from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) on board Envisat‐1 are assimilated into the Global Modeling and Assimilation Office constituent assimilation system for the period 1 April to 20 December 2004. The impact of the assimilation on CO distribution is evaluated using independent surface flask observations from the National Oceanic and Atmospheric Administration (NOAA)/ESRL global cooperative air sampling network and Measurement of Ozone and Water Vapor by Airbus In‐Service Aircraft (MOZAIC) in situ CO profiles. Assimilation of SCIAMACHY data improves agreement of CO assimilation with both of these data sets on both global and regional scales compared to the free‐running model. Regional comparisons with MOZAIC profiles made in western Europe, the northeastern United States, and the Arabian Peninsula show improvements at all three locations in the free troposphere and into the boundary layer over Arabia and the northeastern United States. Comparisons with NOAA Earth System Research Laboratory data improve at about two thirds of the surface observation sites. The systematic model errors related to the uncertainty of CO surface sources and the chemistry of CO losses are investigated through experiments with increased surface CO emissions over the Arabian Peninsula and/or globally reduced hydroxyl radical (OH) concentrations. Both model changes decrease mean CO errors at all altitudes in comparison to MOZAIC data over Dubai and Abu Dhabi. In contrast, errors in the assimilated CO are reduced by the increased emissions for pressures ≥800 hPa and by the reduced OH for pressures ≤600 hPa. Our analysis suggests that CO emissions over Dubai in 2004 are more than double those in the 1998 emissions inventory.

Comparison of weekly cycle of NO2 satellite retrievals and NOx emission inventories for the continental United States

Spatially resolved weekly NO2 variations are obtained from 2003 to 2005 Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) tropospheric NO2 columns for three different types of regions: urban, rural, and rural‐point (rural with significant electricity generation unit (EGU) emissions). Regions are compared for magnitudes and weekly profiles. Rural regions do not show any weekly pattern, whereas urban areas show a distinct decrease on the weekends. Rural regions with EGUs show a slight decrease on Sundays. When compared with estimated mobile and stationary nitrogen oxides (NOx) emissions from the year 2004 for seven cities, the satellite data have greater variation during weekdays (Monday–Friday). Overall comparisons show that SCIAMACHY‐derived NO2 correlate well with estimated NOx emissions for urban and rural but less for rural‐point regions.

Detection of surface emission hot spots, trends, and seasonal cycle from satellite‐retrieved NO2 over India

Tropospheric NO2 concentrations derived from spaceborne measurements of Global Ozone Monitoring Experiment (GOME) on board ERS 2 and Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) on board Envisat, respectively, for the time period of 1996–2006 have been used to identify major NO2 emission hot spots, trends, and seasonal cycle over different regions of India. Emission hot spots are observed over the locations of thermal power plants and over major urban and industrial regions. A multifunctional regression model has been used to analyze the trends and seasonal cycle over these emission hot spots. Increasing trends of ∼1.65 ± 0.52% a−1 have been observed for NO2 over India. The fast growing industrial regions of Mumbai and Delhi show increasing trends of ∼2.1 ± 1.1 and ∼2.4 ± 1.2% a−1, respectively. Seasonal variations of tropospheric NO2 concentrations show a maximum during winter‐summer (December–May) and a minimum during the monsoon seasons (June–September). The observed seasonal cycle in satellite‐derived NO2 agrees well with the surface‐level observations of NOX.

The 2005 and 2006 DANDELIONS NO2 and aerosol intercomparison campaigns

Dutch Aerosol and Nitrogen Dioxide Experiments for Validation of OMI and SCIAMACHY (DANDELIONS) is a project that encompasses validation of spaceborne measurements of NO2 by the Ozone Monitoring Instrument (OMI) and Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and of aerosol by OMI and Advanced Along‐Track Scanning Radiometer (AATSR), using an extensive set of ground‐based and balloon measurements over the polluted area of the Netherlands. We present an extensive data set of ground‐based, balloon, and satellite data on NO2, aerosols, and ozone obtained from two campaigns within the project, held during May–June 2005 and September 2006. We have used these data for first validation of OMI NO2, and the data are available through the Aura Validation Data Center website for use in other validation efforts. In this paper we describe the available data, and the methods and instruments used, including the National Institute of Public Health and the Environment (RIVM) NO2 lidar. We show that NO2 from Multi‐Axis Differential Optical Absorption Spectroscopy (MAX‐DOAS) compares well with in situ measurements. We show that different MAX‐DOAS instruments, operating simultaneously during the campaign, give very similar results. We also provide unique information on the spatial homogeneity and the vertical and temporal variability of NO2, showing that during a number of days, the NO2 columns derived from measurements in different directions varied significantly, which implies that, under polluted conditions, measurements in one single azimuth direction are not always representative for the averaged field that the satellite observes. In addition, we show that there is good agreement between tropospheric NO2 from OMI and MAX‐DOAS, and also between total NO2 from OMI and direct‐sun observations. Observations of the aerosol optical thickness (AOT) show that values derived with three ground‐based instruments correspond well with each other, and with aerosol optical thicknesses observed by OMI.

Ground‐based validation of EOS‐Aura OMI NO2 vertical column data in the midlatitude mountain ranges of Tien Shan (Kyrgyzstan) and Alps (France)

Ground‐based UV‐visible instruments for NO2 vertical column measurements have been operating at Issyk‐Kul station, in Kyrgyzstan, and Observatoire de Haute‐Provence (OHP), in France, since 1983 and 1992, respectively. These measurements have already been used for validation of ERS‐2 Global Ozone Monitoring Experiment (GOME) and Envisat Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) NO2 column data. Building upon the successful missions of GOME and SCIAMACHY, the Ozone Monitoring Experiment (OMI) was launched by NASA onboard the EOS Aura satellite in July 2004. Here we present the results of recent comparisons between OMI NO2 operational data (standard product) and correlative ground‐based twilight measurements in midlatitudes, at Issyk‐Kul and OHP, in 2004–2006. The stratospheric NO2 columns, observed by OMI and our ground‐based instruments, have been corrected for NO2 diurnal change and normalized to local noon values using a photochemical box model. According to our comparison, OMI stratospheric NO2 columns underestimate ground‐based measurements by (0.3 ± 0.3) × 1015 molecules/cm2 and (0.7 ± 0.6) × 1015 molecules/cm2 at Issyk‐Kul and OHP, respectively. The effect of tropospheric pollution on the NO2 measurements in both regions of observations has been identified and discussed.

Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space

For the period 1996–2006, global distributions of tropospheric nitrogen dioxide (NO2) have been derived from radiances measured with the satellite instruments GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY). A statistical analysis is applied to derive trends and seasonal variability for this period on a global scale. The time series of the monthly NO2 columns for these ten years have been fitted with a linear function superposed on an annual seasonal cycle on a grid with a spatial resolution of 1° by 1°. We see significant reductions (up to 7% per year) in NO2 in Europe and parts of the eastern United States, and a strong increase in Asia, most particularly in China (up to 29% per year) but also in Iran and Russia. By comparing the data with the cloud information derived from the same satellite observations, the contribution of lightning to the total column of NO2 is estimated. The estimated NO2 from lightning is, especially in the tropics, in good agreement with lightning flash rate observations from space. The satellite observed seasonal variability of NO2 generally correlates well with independent observations and estimates of the seasonal cycle of specific NOx sources. Source categories considered are anthropogenic (fossil fuel and biofuel), biomass burning, soil emissions and lightning. Using the characteristics of the seasonal variability of these source categories, the dominant source of NOx emissions has been identified on a global scale and on a 1° by 1° grid.

Intercomparison of SCIAMACHY nitrogen dioxide observations, in situ measurements and air quality modeling results over Western Europe

The Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite spectrometer provides detailed information on the nitrogen dioxide (NO2) content in the planetary boundary layer. NO2 tropospheric column retrievals of SCIAMACHY and its predecessor Global Ozone Monitoring Experiment are characterized by errors of the order of 40%. We present here a new SCIAMACHY tropospheric retrieval data set for the year 2003. The cloud free satellite observations are compared to surface measurements and simulations over western Europe performed with the regional air‐quality model CHIMERE. The model has a resolution of 50 km similar to the satellite observations. For these comparisons, averaging kernels are applied to the collocated model profiles to remove the dependency of the comparison on a priori NO2 profile information used in the retrieval. The consistency of both SCIAMACHY and CHIMERE outputs over sites where surface measurements are available allows us to be confident in evaluation of the model over large areas not covered by surface observations. CHIMERE underestimates surface NO2 concentrations for urban and suburban stations which we mainly attribute to the low representativeness of point observations. No such bias is found for rural locations. The yearly average SCIAMACHY and CHIMERE spatial NO2 distributions show a high degree of quantitative agreement over rural and urban sites: a bias of 5% (relative to the retrievals) and a correlation coefficient of 0.87 (n = 2003). On a seasonal basis, biases are smaller than 20% and correlation coefficients are larger than 0.75. Spatial correlations between both the model and satellite columns and the European Monitoring and Evaluation Program (EMEP) emission inventory are high in summer (r = 0.74, n = 1779) and low in winter (r = 0.48, n = 1078), related to seasonal changes in lifetime and transport. On the other hand, CHIMERE and SCIAMACHY columns are mutually consistent in summer (r = 0.82) and in winter (r = 0.79). This shows that CHIMERE simulates the transport and chemical processes with a reasonable accuracy. The NO2 columns show a high daily variability. The daily NO2 pollution plumes observed by SCIAMACHY are often well described by CHIMERE both in extent and in location. This result demonstrates the capabilities of a satellite instrument such as SCIAMACHY to monitor the NO2 concentrations over large areas on a daily basis. It provides evidence that present and future satellite missions, in combination with CTM and surface data, will contribute to improve quantitative air quality analyses at a continental scale.

Intercomparison of ozone profile measurements from ASUR, SCIAMACHY, MIPAS, OSIRIS, and SMR

The airborne submillimeter radiometer (ASUR) was deployed onboard the Falcon research aircraft during the scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) validation and utilization experiment (SCIAVALUE) and the European polar stratospheric cloud and lee wave experiment (EuPLEx) campaigns. A large number of ozone profile measurements were performed over a latitude band spanning from 5°S to 80°N in September 2002 and February/March 2003 during the SCIAVALUE and around the northern polar latitudes in January/February 2003 during the EuPLEx. Both missions amassed an ample microwave ozone profile data set that is used to make quantitative comparisons with satellite measurements in order to assess the quality of the satellite retrievals. In this paper, the ASUR ozone profile measurements are compared with measurements from SCIAMACHY and Michelson interferometer for passive atmospheric sounding (MIPAS) on Environmental Satellite and optical spectrograph and infrared imager system (OSIRIS) and submillimeter radiometer (SMR) on the Odin satellite. The cross comparisons with the criterion that the ASUR measurements are performed within ±1000 km and ±6 hrs of the satellite observations show a good agreement with all the four satellite sensors. The differences in data values are the following: −4 to +8% for ASUR‐SCIAMACHY (operational product, v2.1), within ±15% for ASUR‐SCIAMACHY (scientific product, v1.62), up to +6% for ASUR‐MIPAS (operational product v4.61) and ASUR‐MIPAS (scientific product v1‐O3‐1), up to 17% for ASUR‐OSIRIS (v012), and −6 to 17% for ASUR‐SMR (v222) between the 20‐ and 40‐km altitude range depending on latitude. Thus, the intercomparisons provide important quantitative information about the quality of the satellite ozone profiles, which has to be considered when using the data for scientific analyses.