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This paper describes the algorithm for deriving the total column ozone from spectral radiances and irradiances measured by the Ozone Monitoring Instrument (OMI) on the Earth Observing System Aura satellite. The algorithm is based on the differential optical absorption spectroscopy technique. The main characteristics of the algorithm as well as an error analysis are described. The algorithm has been successfully applied to the first available OMI data. First comparisons with ground-based instruments are very encouraging and clearly show the potential of the method.

We discuss the quality of the two available SCIAMACHY limb ozone profile products. They were retrieved with the University of Bremen IFE's algorithm version 1.61 (hereafter IFE), and the official ESA offline algorithm (hereafter OL) versions 2.4 and 2.5. The ozone profiles were compared to a suite of correlative measurements from ground-based lidar and microwave, sondes, SAGE II and SAGE III (Stratospheric Aerosol and Gas Experiment). To correct for the expected Envisat pointing errors, which have not been corrected implicitly in either of the algorithms, we applied a constant altitude shift of -1.5 km to the SCIAMACHY ozone profiles. The IFE ozone profile data between 16 and 40 km are biased low by 3-6%. The average difference profiles have a typical standard deviation of 10% between 20 and 35 km. We show that more than 20% of the SCIAMACHY official ESA offline (OL) ozone profiles version 2.4 and 2.5 have unrealistic ozone values, most of these are north of 15° S. The remaining OL profiles compare well to correlative instruments above 24 km. Between 20 and 24 km, they underestimate ozone by 15±5%.

The IFE-1.6 scientific data set of SCIAMACHY limb ozone profiles is validated for the period August–December 2002. The data set provides ozone profiles over an altitude range of 15–45 km. The main uncertainty in the profiles is the imprecise knowledge of the pointing of the instrument, leading to retrieved profiles that are shifted in altitude direction. To obtain a first order correction for the pointing error and the remaining uncertainties, the retrieved profiles are compared to their a-priori value and ozone sondes based on absolute distance and equivalent latitude criteria. A vertical shift of the satellite profiles with 2 km downward is found to be an appropriate correction for the data set studied. A total root-mean-square difference between limb profiles and sondes of 10–15% remains for the stratospheric ozone profile after application of the correction. Small biases are left above and below the ozone maximum at mid latitudes, where the vertical gradients in the retrieved product are in general too strong.

A large number of ozone profiles measured by using various methods (lidar, ozonesondes, microwave radiometer, and Stratospheric Aerosol and Gas Experiment II) over Lauder, New Zealand, between late 1994 and early 1998 are intercompared. These profiles are also used to validate a collocated Dobson spectrophotometer. Between March 1996 (August 1996 for sonde measurements) and January 1998, all instruments were operational and no instrument changes took place. The ozone number densities averaged over this period agreed within 5% in the 20- to 35-kin range. Between 12 and 20 kin, lidar and sonde results deviated by less than 8%, and lidar and SAGE II results deviated by less than 15%. The ozone column densities measured by the Dobson spectrophotometer agreed within 3% with the integrated ozone profiles. The various methods are discussed, and modifications are proposed. They comprise a decrease of the reported sonde altitudes of about 125 m (+50 m) to correct for the response time of the sonde's chemical solution, the use of more accurate molecular parameter values in the lidar algorithm, and a 2.5% decrease in SAGE II ozone densities. Improved agreement between the average ozone profiles to within 1.5% for lidar and sondes (20-35 kin) and within 2.5% for lidar and SAGE II (20-35 kin) is achieved. The Dobson results are found to be influenced by the annual cycle of the temperature profile through the altitude-averaged ozone absorption cross section, which has been assumed to be constant in the presented data but actually varies with an amplitude of 2% over Lauder.

Following a blind intercomparison of ozone profiling instruments in the Network for the Detection of Stratospheric Change at Lauder, New Zealand, revisions to the analyses were made resulting in a new data set. This paper compares the revised results from two differential absorption lidars (RIVM and GSFC), a microwave radiometer (Millitech/LaRC), and electrochemical concentration cell (ECC) balloon sondes (NIWA). In general, the results are substantially improved compared to the earlier blind intercomparison. The level of agreement was similar both for single profiles and for the campaign average profile and was approximately 5% for the lidars and the sondes over the altitude range from 15 to 42 km (32 km for sondes). The revised microwave data show a bias of 5–10% high in the region from 22 to 42 km. Starting at 42 km, the lidar errors increase significantly, and comparisons of the microwave results were not possible above this altitude.

Ground-based lidars have been used to detect and identify ground-state (v" =0) hydroxyl radicals (OH) in the mesosphere between about 75 and 85 km altitude. These lidars operate near 308 nm and OH is observed through laser-induced-fluorescence on the A 2∑ + -X 2II(0, 0) band. The results expose a valuable global set of nighttime OH observations, since existing long-term lidar data at several NDSC sites contain the (serendipitous) OH information. Results of lidar observations are presented from two mid-latitude sites, one in each hemisphere: Table Mountain (34°N), California, and Lauder (45°S), New Zealand. They show observations of a geometrically thin (∼3 km) nocturnal layer of OH near 80 km. For the Table Mountain observations, the derived values for the OH density at 80 km typically are 2 - 4 × 10 5 cm -3 which is in accordance with model predictions [Dodd et al., 1994]. The temporal behavior of the mesospheric OH signal, following sunset, that was found, supports previous model predictions [Allen et al., 1984] in a qualitative fashion.

[1] Satellite instruments are efficient detectors of air pollutants such as NO2. However, the interpretation of satellite retrievals is not a trivial matter. We describe a novel instrument, the RIVM NO2 mobile lidar, to measure tropospheric NO2 profiles for the interpretation and validation of satellite data. During the DANDELIONS campaign in 2006 we obtained an extensive collection of lidar NO2 profiles, coinciding with OMI and SCIAMACHY overpasses. On clear days and early mornings a comparison between lidar and in situ measurements showed excellent agreement. At other times the in situ monitors with molybdenum converters suffered from NOy interference. The lidar NO2 profiles indicated a well-mixed boundary layer, with high NO2 concentrations in the boundary layer and concentrations above not differing significantly from zero. The boundary layer concentrations spanned a wide range, which likely depends on the wind directions and on the intensity of local (rush hour) traffic which varies with the day of the week. Large diurnal differences were mainly driven by the height of the boundary layer, although direct photolysis or photochemical processes also contribute. Small-scale temporal and spatial variations in the NO2 concentrations of the order of 20–50% were measured, probably indicative of small-scale eddies. A preliminary comparison between satellite and lidar data shows that the satellite data tend to overestimate the amount of NO2 in the troposphere compared to the lidar data.

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. Copyright 2008 by the American Geophysical Union. U7 - Export Date: 2 August 2010 U7 - Source: Scopus U7 - Art. No.: D16S46

[1] This paper presents a comparison of NO 2 data measured with the Ozone Monitoring Instrument (OMI) on board the EOS-AURA satellite with ground-based direct-Sun Brewer measurement data. Since its deployment in July 2004, OMI has provided more than 2 years of daily high-resolution (∼13 x 24 km 2 at nadir) NO 2 vertical column density maps. We describe the retrieval, which includes an estimation of the stratospheric and tropospheric fraction of total NO 2 columns, the air mass factor (AMF) correction based on detected tropospheric NO 2 enhancements, and the generation of the gridded data product. We present a validation study of the gridded NO 2 data set using data from a Brewer MK3 double monochromator in direct-Sun mode located at NASA Goddard Space Flight Center in Greenbelt, Maryland, USA. Monthly averages of coinciding measurements correlate well (r = 0.9) but OMI data are about 25% lower than the Brewer measurement data (slope 0.75, intercept -0.38 x 10 15 molecules/cm 2 ). We present a detailed uncertainty analysis for both ground and satellite data and discuss the possible reasons for the observed differences.

[1] This paper is an overview of the validation of the total column ozone data products from the Ozone Monitoring Instrument (OMI) on board the NASA EOS-Aura satellite. OMI is an imaging UV/visible spectrometer that maps global ozone on a daily basis. There are two ozone products from OMI, one derived using the traditional TOMS retrieval algorithm and another derived using a Differential Optical Absorption Spectroscopy algorithm that is being developed to take advantage of the hyperspectral capabilities of OMI. Validation is primarily performed through comparison with a network of Dobson and Brewer ground stations and secondarily through campaigns conducted specifically to validate Aura. Comparison with an ensemble of 76 Northern Hemisphere ground stations shows that OMI-TOMS total column ozone averages 0.4% higher than the station average, with station-to-station standard deviation of ±0.6%. The comparison shows that the OMI-TOMS ozone was stable over the 2-year period with no evidence of drift relative to the ground network. The OMI-DOAS product is also stable but with a 1.1% offset and a seasonal variation of ±2%. During four aircraft validation campaigns using the NASA DC-8 and WB-57 aircraft, ozone above the aircraft was measured using an actinic flux instrument and compared with OMI ozone. These comparisons showed agreement within 2% over a broad range of latitude and viewing conditions. Only during the high-latitude flights did the OMI-DOAS ozone show the effects of a solar zenith angle dependent error.

[1] In this paper we present validation results of the total ozone column data products of the Ozone Monitoring Instrument (OMI) on board the NASA EOS-AURA satellite through comparisons with ground-based observations by Dobson and Brewer spectrophotometer instruments. Quality-controlled and archived total ozone column data from these ground-based instruments located at stations worldwide have been used to validate more than 2 a of total ozone column observations from OMI. There are two operationally available satellite total ozone column data products, based on the OMI-TOMS and the OMI-DOAS retrieval algorithms, respectively. Validation with ground-based data focused on global comparisons and seasonal dependence and the possible dependence on latitude and solar zenith angle. Our results show a globally averaged agreement of better than 1% for OMI-TOMS data and better than 2% for OMI-DOAS data with the ground-based observations. The OMI-TOMS data product is shown to be of high overall quality with no significant dependence on solar zenith angle or latitude. The OMI-DOAS data product shows no significant dependence on latitude except for the high latitudes of the Southern Hemisphere where it systematically overestimates the total ozone value. In addition a significant dependence on solar zenith angle is found between OMI-DOAS and ground-based data. Comparisons of satellite and ground-based data tend to show a marginal seasonal dependence even though it remains unclear whether this dependence originates from the ground-based or spaceborne observations.

We present a new algorithm for the near-real time retrieval – within 3 h of the actual satellite measurement – of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). The retrieval system is based on the combined retrieval-assimilation-modelling approach developed at KNMI for off-line tropospheric NO2 from the GOME and SCIAMACHY satellite instruments. We have adapted the off-line system such that the required a priori information ndash; profile shapes and stratospheric background NO2 ndash; is now immediately available upon arrival of the OMI NO2 slant columns and cloud data at KNMI. Slant column NO2 and cloud information arrives at KNMI typically within 80 min of actual OMI observations. Slant columns for NO2 are retrieved using differential optical absorption spectroscopy (DOAS) in the 405–465 nm range. Cloud fraction and cloud pressure are provided by a new cloud retrieval algorithm that uses the absorption of the O2–O2 collision complex near 477 nm. On-line availability of stratospheric slant columns and NO2 profiles is achieved by running the TM4 chemistry transport model (CTM) forward in time based on forecast ECMWF meteo and assimilated NO2 information from all previously observed orbits. OMI NO2 slant columns, after correction for spurious across-track variability, show a random error for individual pixels of approximately 0.7×1015molec.cm–2. As NO2 retrievals are very sensitive to clouds, we evaluated the consistency of cloud fraction and cloud pressure from the new O2–O2 (OMI) algorithm and from the Fast Retrieval Scheme for Cloud Observables (FRESCO). Cloud parameters from the O2–O2 (OMI) algorithm have similar frequency distributions as cloud parameters retrieved from FRESCO (SCIAMACHY) for August 2006. On average, OMI cloud fractions are higher by 0.011, and OMI cloud pressures exceed FRESCO cloud pressures by 60 hPa. As a consistency check, we intercompared OMI near-real time NO2 columns measured at 13:45 h local time to SCIAMACHY off-line NO2 columns measured at 10:00 h local time. In August 2006, both instruments observe very similar spatial patterns of tropospheric NO2 columns, and small differences for most locations on Earth where tropospheric NO2 columns are small. For regions that are strongly polluted, SCIAMACHY observes higher tropospheric NO2 columns than OMI.

This paper describes a new ozone column retrieval algorithm and its application to SCIAMACHY measurements. The TOSOMI algorithm is based on the Differential Optical Absorption Spectroscopy (DOAS) technique and implements several improvements over older algorithms. These improvements include aspects like (i) the explicit treatment of rotational Raman scattering, (ii) an improved air-mass factor formulation which is based on a simulation of the reflectivity spectrum and a subsequent DOAS fit of this simulated spectrum, (iii) the use of an improved ozone climatology and a column dependent air-mass factor, (iv) the use of daily varying ECMWF temperature profile analyses. The results of three validation exercises are reported. The TOSOMI columns are compared with an extensive set of ground-based observations (Brewer, Dobson) for the years 2003 and 2004. Secondly, a direct comparison for January–June 2003 with two new GOME retrievals, GDP Version 4 and TOGOMI, is presented. Third, data assimilation is used to study the dependence of the TOSOMI columns with retrieval parameters such as the viewing angle, cloud fraction and geographical location. These comparisons show a good consistency on the percent level between the GOME and SCIAMACHY algorithms. The present TOSOMI implementation (v0.32) shows an offset of about −1.5% with respect to ground-based observations and the GOME retrievals.

[1] Altitude profiles of ozone (O3) over Lauder (45°S, 170°E) performed using a lidar, ozonesondes, and the satellite-borne Stratospheric Aerosol and Gas Experiment (SAGE II) instrument are presented. These data form one of the few long-term sets of O3 profiles at a Southern Hemisphere location. In the 5 years of data presented, the dominant variation is the annual cycle, the phase and amplitude of which differ below and above 27.5 km. Superposed are irregular episodic variations, caused by various processes. The first process studied is stratosphere-troposphere exchange, characterized by dry and O3-rich air residing in the troposphere, which was found in 21% of the measurements. The second relates to the positioning of the higher polar vortex over Lauder, often in combination with the exchange of air between midlatitude and subtropical stratospheric regions. We present examples of this which were observed over Lauder during the 1997 winter. This winter was selected for further study because of the record-low O3 amounts measured. The third process is mixing of O3-depleted vortex air with midlatitude air after the vortex breakup. We present one example, which shows that a filament originating from the depleted Antarctic vortex significantly lowers O3 amounts over Lauder around 27 November 1997. There is thus a connection between Antarctic O3 depletion and later decrease of O3 amounts at a Southern Hemisphere midlatitude location, namely Lauder.

Record-low ozone (O3) column densities (with a minimum of 222 DU) were observed over the Lauder NDSC (Network for the Detection of Stratospheric Change) sta- tion (45S, 170E) in August 1997. Possible causes are ex- amined using height-resolved O3 measurements over Lauder, and high-resolution reverse trajectory maps ofO3 (initialised with Microwave Limb Sounder measurements) and of poten- tial vorticity. The analysis shows thatO3 poor air originated from two regions: Below the 550 K isentrope (22 km) sub- tropical air was observed, while between 600 and 1000 K (25 { 33.5 km) the polar vortex tilted over Lauder for sev- eral days. A rapid recovery of the O3 column density was observed later, due to an O3 rich polar vortex lament mov- ing over Lauder between 18 and 24 km, while simultaneously the O3 poor higher vortex moved away.

An intercomparison of ozone-profiling instruments, two differential absorption lidars, a microwave radiometer, electrochemical concentration sondes, and the SAGE II satellite instrument is presented. The ground-based instruments were located at the Network for the Detection of Stratospheric Change (NDSC) primary station at Lauder, New Zealand. The campaign, which took place between April 15 and 29, 1995, strictly followed the NDSC guidelines for a blind intercomparison. Agreement between the measurements was within 15% for single profiles and within 10% for the campaign average, in the region from 20 to 40 km altitude. Outside of this region the differences were greater but can generally be ascribed to the limits of a particular instrument.

Over one hundred ozone profiles have been measured by the RIVM lidar in Lauder, New Zealand. The ozone results have been validated during OPAL (Ozone Profiler Assessment at Lauder) and agree to the results of other participating instruments within about 10% in the blind data set, and about 5% in the revised data set (15 to 45 km region).

We review the standard nitrogen dioxide (NO2) data product (Version 1.0.), which is based on measurements made in the spectral region 415–465 nm by the Ozone Monitoring Instrument (OMI) on the NASA Earth Observing System-Aura satellite. A number of ground- and aircraft-based measurements have been used to validate the data product's three principal quantities: stratospheric, tropospheric, and total NO2 column densities under nearly or completely cloud-free conditions. The validation of OMI NO2 is complicated by a number of factors, the greatest of which is that the OMI observations effectively average the NO2 over its field of view (minimum 340 km2), while a ground-based instrument samples at a single point. The tropospheric NO2 field is often very inhomogeneous, varying significantly over tens to hundreds of meters, and ranges from 1016 cm−2 over urban and industrial areas. Because of OMI's areal averaging, when validation measurements are made near NO2 sources the OMI measurements are expected to underestimate the ground-based, and this is indeed seen. Further, we use several different instruments, both new and mature, which might give inconsistent NO2 amounts; the correlations between nearby instruments is 0.8–0.9. Finally, many of the validation data sets are quite small and span a very short length of time; this limits the statistical conclusions that can be drawn from them. Despite these factors, good agreement is generally seen between the OMI and ground-based measurements, with OMI stratospheric NO2 underestimated by about 14% and total and tropospheric columns underestimated by 15–30%. Typical correlations between OMI NO2 and ground-based measurements are generally >0.6.