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At least 19 records

Nimbus-7 total ozone algorithm

The total ozone algorithm used for the processing of Nimbus-4 BUV measurements is modified to account for off-nadir viewing of the Total Ozone Mapping Spectrometer onboard Nimbus-7 satellite. TOMS is a cross-track scanning instrument with a 50 x 50-km field of view, increasing to 150 x 150 km at the extreme off-nadir angle of 51 deg and six spectral bands in the 310-380-nm region. Consideration is given to the determination of the pressure at the reflecting surface and profile selection scheme at very high solar zenith angles. The algorithm is also applicable to the Solar Backscattered UV Experiment aboard the same satellite. The modifications provide for a better cloud height, snow correction, and improved retrievals near the terminator.

Bhartia, P. K.↗

Highlights of TOMS Version 9 Total Ozone Algorithm

The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side benefit of this algorithm is that it is considerably simpler than the present algorithm that uses a database of 1512 profiles to retrieve total ozone. These profiles are tedious to construct and modify. Though conceptually similar to the SBUV V8 algorithm that was developed about a decade ago, the SBUV and TOMS V9 algorithms differ in detail. The TOMS algorithm uses 3 wavelengths to retrieve the profile while the SBUV algorithm uses 6-9 wavelengths, so TOMS provides less profile information. However both algorithms have comparable total ozone information and TOMS V9 can be easily adapted to use additional wavelengths from instruments like GOME, OMI and OMPS to provide better profile information at smaller SZAs. The other significant difference between the two algorithms is that while the SBUV algorithm has been optimized for deriving monthly zonal means by making an appropriate choice of the a priori error covariance matrix, the TOMS algorithm has been optimized for tracking short-term variability using month and latitude dependent covariance matrices.

Bhartia, Pawan↗

New Total Ozone Algorithm for Application to the Total Ozone Mapping Spectrometer

The Total Ozone Mapping Spectrometer (TOMS) series comprises four instruments providing a total of 25 years of daily global stratospheric ozone data over the sunlit portion of the Earth. A new retrieval algorithm has been developed for TOMS, designated Version 8. The algorithm is based on differential absorption across a pair of wavelength channels chosen close together to minimize the impact of wavelength dependent forward modeling errors. Version 8 enhancements include correction for the presence of tropospheric aerosols and sun glint from water surfaces, a better treatment of variability due to tropospheric ozone and temperature dependence, and an improved forward model, particularly in regions of persistent snow and ice. Among other things, the Version 8 enhancements have reduced latitudinal dependence seen previously in TOMS - Dobson comparisons, predominantly in the Southern Hemisphere's summer, when the tropospheric ozone, temperature, and snow/ice corrections are additive. The basic components of the algorithm and its impact on derived total ozone will be discussed.

Wellemeyer, C.↗

Description and Sensitivity Analysis of the SOLSE/LORE-2 and SAGE III Limb Scattering Ozone Retrieval Algorithms

The SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments are scheduled for reflight on Space Shuttle flight STS-107 in July 2002. In addition, the SAGE III (Stratospheric Aerosol and Gas Experiment) instrument will begin to make limb scattering measurements during Spring 2002. The optimal estimation technique is used to analyze visible and ultraviolet limb scattered radiances and produce a retrieved ozone profile. The algorithm used to analyze data from the initial flight of the SOLSE/LORE instruments (on Space Shuttle flight STS-87 in November 1997) forms the basis of the current algorithms, with expansion to take advantage of the increased multispectral information provided by SOLSE/LORE-2 and SAGE III. We also present detailed sensitivity analysis for these ozone retrieval algorithms. The primary source of ozone retrieval error is tangent height misregistration (i.e., instrument pointing error), which is relevant throughout the altitude range of interest, and can produce retrieval errors on the order of 10-20 percent due to a tangent height registration error of 0.5 km at the tangent point. Other significant sources of error are sensitivity to stratospheric aerosol and sensitivity to error in the a priori ozone estimate (given assumed instrument signal-to-noise = 200). These can produce errors up to 10 percent for the ozone retrieval at altitudes less than 20 km, but produce little error above that level.

Loughman, R.↗

Comparison of trend analyses for Umkehr data using new and previous inversion algorithms

Ozone vertical profile Umkehr data for layers 3-9 obtained from 12 stations, using both previous and new inversion algorithms, were analyzed for trends. The trends estimated for the Umkehr data from the two algorithms were compared using two data periods, 1968-1991 and 1977-1991. Both nonseasonal and seasonal trend models were fitted. The overall annual trends are found to be significantly negative, of the order of -5% per decade, for layers 7 and 8 using both inversion algorithms. The largest negative trends occur in these layers under the new algorithm, whereas in the previous algorithm the most negative trend occurs in layer 9. The trend estimates, both annual and seasonal, are substantially different between the two algorithms mainly for layers 3, 4, and 9, where trends from the new algorithm data are about 2% per decade less negative, with less appreciable differences in layers 7 and 8. The trend results from the two data periods are similar, except for layer 3 where trends become more negative, by about -2% per decade, for 1977-1991.

Reinsel, Gregory C.↗

The Updated Umkehr Ozone Retrieval Algorithm and its Validation against Satellite Data

Improvements to the Umkehr ozone profile retrieval algorithm have been developed and are now being evaluated. The updated algorithm is able to simulate observations more accurately and provides data output that is easier to analyze. Among the new diagnostic capabilities that the updated algorithm provides is the averaging kernel (AK) method. The AK approach allows studying how the algorithm responds when a small perturbation is made in a particular layer of the atmosphere [Rodgers 1976, 1990]. We will use the AK method to define precisely what Umkehr should measure given a set of profiles measured by other platforms. This method allows us to compare trends and offsets in data more accurately than it has been done in the past. The updated Umkehr retrievals will be validated against SAGE II ozone profiles as well as SSBUV ozone profile data. We will discuss possible reasons for offset between data and differences in derived ozone profile trends. Considerable variability of the ozone profile within the 10-degree latitude envelope creates noise in the SAGE matching dataset and makes comparisons difficult. To eliminate this problem, the SAGE and Umkehr data had been previously de-seasonalized by subtracting the latitude/season dependent ozone climatology. However, the remaining noise in the ozone residuals was still considerably high for trend analysis and was attributed to longitude variability of SAGE sampling. The new ozone climatology (Labow, NASA) that has longitude dependent ozone variability will be used to minimize contribution of sampling noise in comparisons of satellite and ground station. The comparison of zenith-sky radiances (Umkehr N-value measurements) synthesized for a given set of SAGE profiles will be used to determine whether SAGE-derived N-values agree with the Umkehr-measured N-values. The instrumental effects will be discussed. Both the Umkehr data and SAGE II measurements will be analyzed for their information about ozone variability and loss and recovery rates at the mid- and upper (40 km) levels. The updated long-term Umkehr dataset can be used to provide high quality information for identifying signs of ozone recovery. The long Umkehr historical record can provide additional information for separating the dynamic and chemical mechanisms of depletion, and can help the community better understand climate change effects.

Petropavlovskikh, I.↗

Information content of ozone retrieval algorithms

The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.

Rodgers, C.↗

Improving Total Column Ozone Retrievals by Using Cloud Pressures Derived from Raman Scattering in the UV

The higher spectral resolution, coverage, and sampling of the Aura satellite ozone monitoring instrument (OMI), as compared with the total ozone mapping spectrometer (TOMS) should allow for improved ozone retrievals, including estimates of tropospheric ozone. By default, the TOMS-like OMI total column ozone algorithm uses climatological cloud-top pressures based on infrared (IR) measurements to estimate the column ozone below the clouds. Alternatively, cloud pressure can be retrieved using atmospheric rotational Raman scattering with OMI. The retrieved cloud pressures should be more consistent with assumptions made in the total ozone algorithm. Here, we use data from the global ozone monitoring experiment (GOME) to estimate total ozone using both the IR-climatological and retrieved cloud pressures. The exceed approximately 15 DU. Use of the UV cloud pressure retrievals leads to a smoother distribution of ozone along a satellite track by reducing small spatial irregularities presumably caused by errors in the climatological cloud pressures.

Vasilkov, A.↗

Optimized Umkehr Profile Algorithm for Ozone Trend Analyses

The long-term record of Umkehr measurements from four NOAA Dobson spectrophotometers was reprocessed after updates to the instrument calibration procedures. In addition, a new data quality-control tool was developed for the Dobson automation software (WinDobson). This paper presents a comparison of Dobson Umkehr ozone profiles from NOAA ozone network stations (Boulder, OHP, MLO, Lauder) against several satellite records, including Aura Microwave Limb Sounder (MLS; ver. 4.2), and combined SBUV and OMPS records (NASA AGG and NOAA COH). A subset of satellite data is selected to match Dobson Umkehr observations at each station spatially (distance less than 200 km) and temporally (within 24 hours). Umkehr Averaging Kernels (AKs) are applied to vertically smooth all overpass satellite profiles prior to comparisons. The station Umkehr record consists of several instrumental records, which have different optical characterizations, and thus instrument-specific stray light contributes to the data processing errors and creates step changes in the record. This work evaluates the overall quality of Umkehr long-term measurements at NOAA ground-based stations and assesses the impact of the instrumental changes on the stability of the Umkehr ozone profile record. This paper describes a method designed to correct biases and discontinuities in the retrieved Umkehr profile that originate from the Dobson calibration process, repair, or optical realignment of the instrument. The M2GMI and GMI CTM ozone profile model output matched to station location and date of observation is used to evaluate instrumental step changes in the Umkehr record. Homogenization of the Umkehr record and discussion of the apparent stray light error in retrieved ozone profiles are the focus of this paper. Homogenization of ground-based records is of great importance for studies of long-term ozone trends and climate change.

Umkehr↗

Climatology 2011: An MLS and Sonde Derived Ozone Climatology for Satellite Retrieval Algorithms

The ozone climatology used as the a priori for the version 8 Solar Backscatter Ultraviolet (SBUV) retrieval algorithms has been updated. The Microwave Limb Sounder (MLS) instrument on Aura has excellent latitude coverage and measures ozone daily from the upper troposphere to the lower mesosphere. The new climatology consists of monthly average ozone profiles for ten degree latitude zones covering pressure altitudes from 0 to 65 km. The climatology was formed by combining data from Aura MLS (2004-2010) with data from balloon sondes (1988-2010). Ozone below 8 km (below 12 km at high latitudes) is based on balloons sondes, while ozone above 16 km (21 km at high latitudes) is based on MLS measurements. Sonde and MLS data are blended in the transition region. Ozone accuracy in the upper troposphere is greatly improved because of the near uniform coverage by Aura MLS, while the addition of a large number of balloon sonde measurements improves the accuracy in the lower troposphere, in the tropics and southern hemisphere in particular. The addition of MLS data also improves the accuracy of climatology in the upper stratosphere and lower mesosphere. The revised climatology has been used for the latest reprocessing of SBUV and TOMS satellite ozone data.

McPeters, Richard D.↗

Algorithm for vertical ozone profile determination for the Nimbus-4 BUV data set

A description is provided of the algorithm used by the Ozone Processing Team at NASA to process seven years of Backscatter Ultraviolet (BUV) ozone profile data. The algorithm is a modification of the original retrieval algorithm developed by Mateer (1972) to process some of the early data from the BUV experiment. Principal changes made are in the first guess selection scheme, the use of all wavelengths in the inversion, and the weighting of the various wavelengths according to the errors in the radiance estimation. It is found that the described BUV ozone profile algorithm is an extremely efficient algorithm for retrieving large amounts of satellite data. The algorithm makes full use of all the available information from the measured radiances including the longer wavelength radiances which previously had not been used.

Bhartia, P. K.↗

Ozone and Aerosol Retrieval from Backscattered Ultraviolet Radiation

In this presentation we will discuss the techniques to estimate total column ozone and aerosol absorption optical depth from the measurements of backscattered ultraviolet (buv) radiation. The total ozone algorithm has been used to create a unique record of the ozone layer, spanning more than 3 decades, from a series of instruments (BUV, SBUV, TOMS, SBUV/2) flown on NASA, NOAA, Japanese and Russian satellites. We will discuss how this algorithm can be considered a generalization of the well-known Dobson/Brewer technique that has been used to process data from ground-based instruments for many decades, and how it differs from the DOAS techniques that have been used to estimate vertical column densities of a host of trace gases from data collected by GOME and SCIAMACHY instruments. The BUV aerosol algorithm is most suitable for the detection of UV absorbing aerosols (smoke, desert dust, volcanic ash) and is the only technique that can detect aerosols embedded in clouds. This algorithm has been used to create a quarter century record of aerosol absorption optical depth using the BUV data collected by a series of TOMS instruments. We will also discuss how the data from the OM1 instrument launched on July 15,2004 will be combined with data from MODIS and CALIPSO lidar data to enhance the accuracy and information content of satellite-derived aerosol measurements. The OM1 and MODIS instruments are currently flying on EOS Aura and EOS Aqua satellites respectively, part of a constellation of satellites called the "A-train". The CALIPSO satellite is expected to join this constellation in mid 2005.

Bhartia, Pawan K.↗

Ozone and Aerosol Retrieval from Backscattered Ultraviolet Radiation

In this presentation we will discuss the techniques to estimate total column ozone and aerosol absorption optical depth from the measurements of back scattered ultraviolet (buv) radiation. The total ozone algorithm has been used to create a unique record of the ozone layer, spanning more than 3 decades, from a series of instruments (BUV, SBUV, TOMS, SBUV/2) flown on NASA, NOAA, Japanese and Russian satellites. We will discuss how this algorithm can be considered a generalization of the well-known Dobson/Brewer technique that has been used to process data from ground-based instruments for many decades, and how it differs from the DOAS techniques that have been used to estimate vertical column densities of a host of trace gases from data collected by GOME and SCIAMACHY instruments. The buv aerosol algorithm is most suitable for the detection of UV absorbing aerosols (smoke, desert dust, volcanic ash) and is the only technique that can detect aerosols embedded in clouds. This algorithm has been used to create a quarter century record of aerosol absorption optical depth using the buv data collected by a series of TOMS instruments. We will also discuss how the data from the OMI instrument launched on July 15, 2004 will be combined with data from MODIS and CALIPSO lidar data to enhance the accuracy and information content of satellite-derived aerosol measurements. The OMI and MODIS instruments are currently flying on EOS Aura and EOS Aqua satellites respectively, part of a constellation of satellites called the "A-train".

Bhartia, Pawan K.↗

GOME Total Ozone and Calibration Error Derived Usign Version 8 TOMS Algorithm

The Global Ozone Monitoring Experiment (GOME) is a hyper-spectral satellite instrument measuring the ultraviolet backscatter at relatively high spectral resolution. GOME radiances have been slit averaged to emulate measurements of the Total Ozone Mapping Spectrometer (TOMS) made at discrete wavelengths and processed using the new TOMS Version 8 Ozone Algorithm. Compared to Differential Optical Absorption Spectroscopy (DOAS) techniques based on local structure in the Huggins Bands, the TOMS uses differential absorption between a pair of wavelengths including the local stiucture as well as the background continuum. This makes the TOMS Algorithm more sensitive to ozone, but it also makes the algorithm more sensitive to instrument calibration errors. While calibration adjustments are not needed for the fitting techniques like the DOAS employed in GOME algorithms, some adjustment is necessary when applying the TOMS Algorithm to GOME. Using spectral discrimination at near ultraviolet wavelength channels unabsorbed by ozone, the GOME wavelength dependent calibration drift is estimated and then checked using pair justification. In addition, the day one calibration offset is estimated based on the residuals of the Version 8 TOMS Algorithm. The estimated drift in the 2b detector of GOME is small through the first four years and then increases rapidly to +5% in normalized radiance at 331 nm relative to 385 nm by mid 2000. The lb detector appears to be quite well behaved throughout this time period.

Gleason, J.↗

Profile shape dependence in backscattered ultraviolet satellite retrievals of total ozone

Total ozone operational algorithms use climatological mean ozone profiles. When the actual ozone profiles have significantly different shapes versus the climatology and the solar zenith angles are large, retrieved total ozone will have an error. Recalibrated SBUV profiles are used to estimate this error. Preliminary results suggest that, on the average, the change and variation in significant profiles shapes can to a large degree be estimated by the SBUV derived profiles. Preliminary results suggest the average error in the report algorithm ozone trend (trend in reported ozone) from profile shape is relatively small during the north hemisphere winter (less than 2 percent) for solar zenith angles less than 82 degrees (for 60 degrees North Latitude).

Taylor, S. L.↗

Can One Satellite Data Set Validation Another? Validation of Envisat SCIAMACHY Data by Comparisons with NOAA-16 SBUV/2 and ERS-2 GOME

Validation of satellite data remains a high priority for the construction of climate data sets. Traditionally ground based measurements have provided the primary comparison data for validation. For some atmospheric parameters such as ozone, a thoroughly validated satellite data record can be used to validate a new instrument s data product in addition to using ground based data. Comparing validated data with new satellite data has several advantages; availability of much more data, which will improve precision, larger geographical coverage, and the footprints are closer in size, which removes uncertainty due to different observed atmospheric volumes. To demonstrate the applicability and some limitations of this technique, observations from the newly launched SCIAMACHY instrument were compared with the NOM-16 SBW/2 and ERS-2 GOME instruments. The SBW/2 data had all ready undergone validation by comparing to the total ozone ground network. Overall the SCIAMACHY data were found to low by 3% with respect to satellite data and 1% low with respect to ground station data. There appears to be seasonal and or solar zenith angle dependences in the comparisons with SBW/2 where differences increase with higher solar zenith angles. It is known that accuracies in both satellite and ground based total ozone algorithms decrease at high solar zenith angles. There is a strong need for more accurate measurement from and the ground under these conditions. At the present time SCIAMACHY data are limited and longer data set with more coverage in both hemispheres is needed to unravel the cause of these differences.

Hilsenrath, E.↗