Engineering topics

Bhartia, Pawan K.

Publications and source records attributed to Bhartia, Pawan K..

At least 37 records · Page 2

NASA NTRS2014

OMPS Limb Profiler Instrument Performance Assessment

Following the successful launch of the Ozone Mapping and Profiler Suite (OMPS) aboard the Suomi National Polar-orbiting Partnership (SNPP) spacecraft, the NASA OMPS Limb team began an evaluation of instrument and data product performance. The focus of this paper is the instrument performance in relation to the original design criteria. Performance that is closer to expectations increases the likelihood that limb scatter measurements by SNPP OMPS and successor instruments can form the basis for accurate long-term monitoring of ozone vertical profiles. The team finds that the Limb instrument operates mostly as designed and basic performance meets or exceeds the original design criteria. Internally scattered stray light and sensor pointing knowledge are two design challenges with the potential to seriously degrade performance. A thorough prelaunch characterization of stray light supports software corrections that are accurate to within 1% in radiances up to 60 km for the wavelengths used in deriving ozone. Residual stray light errors at 1000nm, which is useful in retrievals of stratospheric aerosols, currently exceed 10%. Height registration errors in the range of 1 km to 2 km have been observed that cannot be fully explained by known error sources. An unexpected thermal sensitivity of the sensor also causes wavelengths and pointing to shift each orbit in the northern hemisphere. Spectral shifts of as much as 0.5nm in the ultraviolet and 5 nm in the visible, and up to 0.3 km shifts in registered height, must be corrected in ground processing.

ozone↗

NASA NTRS2013

A Fast and Sensitive New Satellite SO2 Retrieval Algorithm based on Principal Component Analysis: Application to the Ozone Monitoring Instrument

We describe a new algorithm to retrieve SO2 from satellite-measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO2 Jacobians calculated with a radiative transfer model to directly estimate SO2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5-340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing longterm, consistent SO2 records for air quality and climate research.

Principal component analysis↗

NASA NTRS2013

Interpreting SBUV Smoothing Errors: an Example Using the Quasi-biennial Oscillation

The Solar Backscattered Ultraviolet (SBUV) observing system consists of a series of instruments that have been measuring both total ozone and the ozone profile since 1970. SBUV measures the profile in the upper stratosphere with a resolution that is adequate to resolve most of the important features of that region. In the lower stratosphere the limited vertical resolution of the SBUV system means that there are components of the profile variability that SBUV cannot measure. The smoothing error, as defined in the optimal estimation retrieval method, describes the components of the profile variability that the SBUV observing system cannot measure. In this paper we provide a simple visual interpretation of the SBUV smoothing error by comparing SBUV ozone anomalies in the lower tropical stratosphere associated with the quasi-biennial oscillation (QBO) to anomalies obtained from the Aura Microwave Limb Sounder (MLS). We describe a methodology for estimating the SBUV smoothing error for monthly zonal mean (mzm) profiles. We construct covariance matrices that describe the statistics of the inter-annual ozone variability using a 6 yr record of Aura MLS and ozonesonde data. We find that the smoothing error is of the order of 1percent between 10 and 1 hPa, increasing up to 15-20 percent in the troposphere and up to 5 percent in the mesosphere. The smoothing error for total ozone columns is small, mostly less than 0.5 percent. We demonstrate that by merging the partial ozone columns from several layers in the lower stratosphere/troposphere into one thick layer, we can minimize the smoothing error. We recommend using the following layer combinations to reduce the smoothing error to about 1 percent: surface to 25 hPa (16 hPa) outside (inside) of the narrow equatorial zone 20 S-20 N.

ozone profile retrievals↗

NASA NTRS2012

The Re-Analysis of Ozone Profile Data from a 41-Year Series of SBUV Instruments

In this study we present the validation of ozone profiles from a number of Solar Back Scattered Ultra Violet (SBUV) and SBUV/2 instruments that were recently reprocessed using an updated (Version 8.6) algorithm. The SBUV dataset provides the longest available record of global ozone profiles, spanning a 41-year period from 1970 to 2011 (except a 5-year gap in the 1970s) and includes ozone profile records obtained from the Nimbus-4 BUV and Nimbus-7 SBUV instruments, and a series of SBUV(/2) instruments launched on NOAA operational satellites (NOAA 09, 11, 14, 16, 17, 18, 19). Although modifications in instrument design were made in the evolution from the BUV instrument to the modern SBUV(/2) model, the basic principles of the measurement technique and retrieval algorithm remain the same. The long term SBUV data record allows us to create a consistent, calibrated dataset of ozone profiles that can be used for climate studies and trend analyses. In particular, we focus on estimating the various sources of error in the SBUV profile ozone retrievals using independent observations and analysis of the algorithm itself. For the first time we include in the metadata a quantitative estimate of the smoothing error, defined as the error due to profile variability that the SBUV observing system cannot inherently measure. The magnitude of the smoothing error varies with altitude, latitude, season and solar zenith angle. Between 10 and 1 hPa the smoothing errors for the SBUV monthly zonal mean retrievals are of the order of 1 %, but start to increase above and below this layer. The largest smoothing errors, as large as 15-20%, were detected in in the troposphere. The SBUV averaging kernels, provided with the ozone profiles in version 8.6, help to eliminate the smoothing effect when comparing the SBUV profiles with high vertical resolution measurements, and make it convenient to use the SBUV ozone profiles for data assimilation and model validation purposes. The smoothing error can also be minimized by combining layers of data, and we will discuss recommendations for this approach as well. The SBUV ozone profiles have been intensively validated against satellite profile measurements obtained from the Microwave Limb Sounders (MLS) (on board the UARS and AURA satellites), Stratospheric Aerosol and Gas Experiment (SAGE) and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Also, we compare coincident and collocated SBUV ozone retrievals with observations made by ground-based instruments, such as microwave spectrometers, lidars, Umkehr instruments and balloon-borne ozonosondes. Finally, we compare the SBUV ozone profiles with output from the NASA GSFC GEOS-CCM model. In the stratosphere between 25 and 1 hPa the mean biases and standard deviations are within 5% for monthly mean ozone profiles. Above and below this layer the vertical resolution of the SBUV algorithm decreases and the effects of vertical smoothing should be taken into account. Though the SBUV algorithm has a coarser vertical resolution in the lower stratosphere and troposphere, it is capable of precisely estimating the integrated ozone column between the surface and 25 hPa. The time series of the tropospheric - lower stratospheric ozone column derived from SBUV agrees within 5% with the corresponding values observed by an ensemble of ozone sonde stations in North Hemisphere. Drift of the ozone time series obtained from each SBUV(/2) instrument relative to ground based and satellite measurements are evaluated and some features of individual SBUV(l2) instruments are discussed. In addition to evaluating individual instruments against independent observations, we also focus on the instrument to instrument consistency in the series. Overall, Version 8.6 ozone profiles obtained from two different SBUV(l2) instruments compare within a couple of percent during overlap periods and are consistently varying in time, with some exceptions. Some of the noted discrepancies might bssociated with ozone diurnal variations, since the difference in the local time of the observations for a pair of SBUV(l2) instruments could be several hours. Other issues include the potential short-term drift in measurements as the instrument orbit drifts, and measurements are obtained at high solar zenith angles (>85 ). Based on the results of the validation, a consistent, calibrated dataset of SBUV ozone profiles has been created based on internal calibration only.

Kramarova, Natalya↗

NASA NTRS2012

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.↗

NASA NTRS2012

Retrieval of Aerosol Absorption Properties from Satellite Observations

The Angstrom Absorption Exponent (AAE) is a parameter commonly used to characterize the wavelength-dependence of aerosol absorption optical depth (AAOD). It is closely related to aerosol composition. Black carbon (BC) containing aerosols yield AAE values near unity whereas Organic carbon (OC) aerosol particles are associated with values larger than 2. Even larger AAE values have been reported for desert dust aerosol particles. Knowledge of spectral AAOD is necessary for the calculation of direct radiative forcing effect of aerosols and for inferring aerosol composition. We have developed a satellitebased method of determining the spectral AAOD of absorbing aerosols. The technique uses multi-spectral measurements of upwelling radiation from scenes where absorbing aerosols lie above clouds as indicated by the UV Aerosol Index. For those conditions, the satellite measurement can be explained, using an approximations of Beer's Law (BL), as the upwelling reflectance at the cloud top attenuated by the absorption effects of the overlying aerosol layer. The upwelling reflectance at the cloud-top in an aerosol-free atmospheric column is mainly a function of cloud optical depth (COD). In the proposed method of AAE derivation, the first step is determining COD which is retrieved using a previously developed color-ratio based approach. In the second step, corrections for molecular scattering effects are applied to both the observed ad the calculated cloud reflectance terms, and the spectral AAOD is then derived by an inversion of the BL approximation. The proposed technique will be discussed in detail and application results making use of OMI multi-spectral measurements in the UV-Vis. will be presented.

Torres, Omar↗

NASA NTRS2010

Direct Retrieval of Sulfur Dioxide Amount and Altitude from Spaceborne Hyperspectral UV Measurements: Theory and Application

We describe the physical processes by which a vertically localized absorber perturbs the top-of-atmosphere solar backscattered ultraviolet (UV) radiance. The distinct spectral responses to perturbations of an absorber in its column amount and layer altitude provide the basis for a practical satellite retrieval technique, the Extended Iterative Spectral Fitting (EISF) algorithm, for the simultaneous retrieval of these quantities of a SO2 plume. In addition, the EISF retrieval provides an improved UV aerosol index for quantifying the spectral contrast of apparent scene reflectance at the bottom of atmosphere bounded by the surface and/or cloud; hence it can be used for detection of the presence or absence of UV absorbing aerosols. We study the performance and characterize the uncertainties of the EISF algorithm using synthetic backscattered UV radiances, retrievals from which can be compared with those used in the simulation. Our findings indicate that the presence of aerosols (both absorbing and nonabsorbing) does not cause large errors in EISF retrievals under most observing conditions when they are located below the SO2 plume. The EISF retrievals assuming a homogeneous field of view can provide accurate column amounts for inhomogeneous scenes, but they always underestimate the plume altitudes. The EISF algorithm reduces systematic errors present in existing linear retrieval algorithms that use prescribed SO2 plume heights. Applying the EISF algorithm to Ozone Monitoring Instrument satellite observations of the recent Kasatochi volcanic eruption, we demonstrate the successful retrieval of effective plume altitude of volcanic SO2, and we also show the improvement in accuracy in the corresponding SO2 columns.

Yang, Kau↗

NASA NTRS2010

Highlights from 10 Years of NASA/KNMI/FMI Collaboration on UV Remote Sensing from Space

The first joint meeting between NASA, KNMI and FMI scientists was held on 13 & 14 June, 2000, almost exactly 10 years ago. NASA had recently selected 14 US scientists to work on instrument calibration, science algorithms, and validation activities related to the Ozone Monitoring Instrument (OMI) that we being built by collaboration between the Netherlands and Finland for flight on NASA's EOS Aura satellite. The progress on this project had been remarkable for a space based instrument. Only two years before this meeting my colleague Ernest Hilsenrath and I had visited Netherlands at the invitation of Fokker Space to persuade KNMI management to collaborate with NASA on this mission. And only 4 years after the first science meeting was held OMI was lunched on the Aura spacecraft. Next month will be the 6 th anniversary of this launch and very successful operation of OMI. All this was possible because of the leadership from Dr. Hennie Kelder and KNMI management who in 1998 saw the opportunity for Netherlands in the mission and stepped up to the challenge by creating a young and talented team of scientists at KNMI under the leadership of Dr. Pieterenel Levelt. This vision has now put Netherlands as the leading country in the world in monitoring air quality from space. Recent selection of TROPOMI by ESA attests to the success of this vision. I will present some selected highlights of our very successful collaboration on this project over the past 10 years.

Bhartia, Pawan K.↗

NASA NTRS2010

Highlights from 40 Years of Satellite UV Measurements

This year we are celebrating the 40th anniversary of the launch of the Backscatter Ultraviolet (BUV) instrument on NASA's Nimbus-4 satellite. The purpose of this instrument was to demonstrate the capability to measure total column ozone and its vertical distribution from space. The success of this instrument led to about a dozen instruments of this type on various NASA and NOAA satellites. These instruments used a single photomultiplier tube (PMT) that restricted the measurements to 6-12 discrete wavelengths in the 250-380 nm range. With the availability of solid-state detector arrays in the past decade it has been possible to make similar measurements but with hyperspectral (contiguous in wavelength) sampling and enhanced spectral resolution. This has allowed global mapping of several weakly-absorbing trace gases including S0 2, NO2, BrO, HCHO, and CIIOCHO. Since these measurements are affected by clouds and aerosols, a great deal of effort has gone into understanding their effect on ultraviolet radiation- both upwelling and downwelling. The downwelling UV radiation is chemically and biologically active and has both negative (genetic damage, air pollution) and positive (production of vitamin D and OH radical) environmental effects. I will discuss how the interaction of Rayleigh-scattered UV radiation with clouds and aerosols produce a variety of interesting effects that are leading to new methods of remote sensing of their properties. The UV measurements can greatly enhance the information that one derives from more traditional methods that use infrared and visible part of the solar spectrum.

Bhartia, Pawan K.↗

NASA NTRS2009

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

Vasilkov, Alexander↗

NASA NTRS2008

Validation of SO2 Retrievals from the Ozone Monitoring Instrument over NE China

The Dutch-Finnish Ozone Monitoring Instrument (OMI) launched on the NASA Aura satellite in July 2004 offers unprecedented spatial resolution, coupled with contiguous daily global coverage, for space-based UV measurements of sulfur dioxide (SO2). We present a first validation of the OMI SO2 data with in situ aircraft measurements in NE China in April 2005. The study demonstrates that OMI can distinguish between background SO2 conditions and heavy pollution on a daily basis. The noise (expressed as the standard deviation,sigma) is approximately 1.5 DU (Dobson units; 1 DU = 2.69 10 (exp 16) molecules/cm (exp 2)) for instantaneous field of view boundary layer (PBL) SO2 data. Temporal and spatial averaging can reduce the noise to sigma approximetly 0.3 DU over a remote region of the South Pacific; the long-term average over this remote location was within 0.1 DU of zero. Under polluted conditions collection 2 OMI data are higher than aircraft measurements by a factor of two. Improved calibrations of the radiance and irradiance data (collection 3) result in better agreement with aircraft measurements on polluted days. The air mass corrected collection 3 data still show positive bias and sensitivity to UV absorbing aerosols. The difference between the in situ data and the OMI SO2 measurements within 30 km of the aircraft profiles was about 1 DU, equivalent to approximately 5 ppb from 0 to 3000 m altitude. Quantifying the SO2 and aerosol profiles and spectral dependence of aerosol absorption between 310 and 330 nm are critical for an accurate estimate of SO2 from satellite UV measurements.

Krotkov, Nickolay A.↗

NASA NTRS2008

Air Quality Study Using Satellites - Current Capability and Future Plans

Satellite instruments have had great success in monitoring the stratospheric ozone and in understanding the processes that control its daily to decadal scale variations. This field is now reaching its zenith with a number of satellite instruments from the US, Europe and Canada capping several decades of active research in this field. The primary public policy imperative of this research was to make reliable prediction of increases in biologically active surface UV radiation due to human activity. By contrast retrieval from satellite data of atmospheric constituents and photo-chemically active radiation that affect air quality is a new and growing field that is presenting us with unique challenges in measurement and data interpretation. A key distinction compared to stratospheric sensors is the greatly enhanced role of clouds, aerosols, and surfaces (CAS) in determining the quality and quantity of useful data that is available for air quality research. In our presentation we will use data from several sensors that are currently flying on the A-train satellite constellation, including OMI, MODIS, CLOUDSAT, and CALIPSO, to highlight that CAS can have both positive and negative effects on the information content of satellite measurements. This is in sharp contrast to other fields of remote sensing where CAS are usually considered an interference except in those cases when they are the primary subject of study. Our analysis has revealed that in the reflected wavelengths one often sees much further down into the atmosphere, through most cirrus, than one does in the emitted wavelengths. The lower level clouds provide a nice background against which one can track long-range transport of trace gases and aerosols. In addition, differences in trace gas columns estimated over cloudy and adjacent clear pixels can be used to measure boundary layer trace gases. However, in order to take full advantage of these features it will be necessary to greatly advance our understanding of how CAS affect the radiation at wavelengths that are used to derive the atmospheric constituents that affect air quality as well as the radiation that controls the photolysis of chemically active trace gases. We will discuss how we are using these new insights to design future satellite missions to study air quality.

Bhartia, Pawan K.↗

NASA NTRS2006

Remote sensing of tropospheric constituents by OMI on the EOS Aura satellite

The Ozone Monitoring Instrument (OMI) was launched on NASA's EOS Aura satellite in July 2004. This instrument was built in the Netherlands with collaboration with Finland. The science data products are being developed jointly by scientists from the three countries. OMI is the first instrument to combine the high spatial resolution daily global mapping capability of TOMS with high spectral resolution measurements necessary for retrieving a number of trace gases of relevance to atmospheric chemistry, using techniques pioneered by GOME. In this talk I will show what our planet looks like at UV wavelengths and what these data can tell us about the effects of human activities on global air quality and climate.

Bhartia, Pawan K.↗

NASA NTRS2005

Development of Long-term Datasets from Satellite BUV Instruments: The "Soft" Calibration Approach

The first BUV instrument was launched in April 1970 on NASA's Nimbus4 satellite. More than a dozen instruments, broadly based on the same principle, but using very different technologies, have been launched in the last 35 years on NASA, NOAA, Japanese and European satellites. In this paper we describe the basic principles of the "soft" calibration approach that we have successfully applied to the data from many of these instruments to produce a consistent long-term record of total ozone, ozone profile and aerosols. This approach is based on using accurate radiative transfer models and assumed/known properties of the atmosphere in ultraviolet to derive calibration parameters. Although the accuracy of the results inevitably depends upon how well the assumed atmospheric properties are known, the technique has several built-in cross- checks that improve the robustness of the method. To develop further confidence in the data the soft calibration technique can be combined with data collected from few well- calibrated ground-based instruments. We will use examples from past and present BUV instruments to show how the method works.

Bhartia, Pawan K.↗

NASA NTRS2004

Assimilation of SBUV Version 8 Radiances into the GEOS Ozone DAS

In operational weather forecasting, the assimilation of brightness temperatures from satellite sounders, instead of assimilation of 1D-retrievals has become increasingly common practice over the last two decades. Compared to these systems, assimilation of trace gases is still at a relatively early stage of development, and efforts to directly assimilate radiances instead of retrieved products have just begun a few years ago, partially because it requires much more computation power due to the employment of a radiative transport forward model (FM). This paper will focus on a method to assimilate SBUV/2 radiances (albedos) into the Global Earth Observation System Ozone Data Assimilation Scheme (GEOS-03DAS). While SBUV-type instruments cannot compete with newer sensors in terms of spectral and horizontal resolution, they feature a continuous data record back to 1978, which makes them very valuable for trend studies. Assimilation can help spreading their ground coverage over the whole globe, as has been previously demonstrated with the GEOS-03DAS using SBUV Version 6 ozone profiles. Now, the DAS has been updated to use the newly released SBUV Version 8 data. We will compare pre]lmlnarv results of SBUV radiance assimilation with the assimilation of retrieved ozone profiles, discuss methods to deal with the increased computational load, and try to assess the error characteristics and future potential of the new approach.

Mueller, Martin D.↗

NASA NTRS2004

Highlights of the Version 8 SBUV and TOMS Datasets Released at this Symposium

Last October was the 25th anniversary of the launch of the SBUV and TOMS instruments on NASA's Nimbus-7 satellite. Total Ozone and ozone profile datasets produced by these and following instruments have produced a quarter century long record. Over time we have released several versions of these datasets to incorporate advances in UV radiative transfer, inverse modeling, and instrument characterization. In this meeting we are releasing datasets produced from the version 8 algorithms. They replace the previous versions (V6 SBUV, and V7 TOMS) released about a decade ago. About a dozen companion papers in this meeting provide details of the new algorithms and intercomparison of the new data with external data. In this paper we present key features of the new algorithm, and discuss how the new results differ from those released previously. We show that the new datasets have better internal consistency and also agree better with external datasets. A key feature of the V8 SBUV algorithm is that the climatology has no influence on inter-annual variability and trends; it only affects the mean values and, to a limited extent, the seasonal dependence. By contrast, climatology does have some influence on TOMS total O3 trends, particularly at large solar zenith angles. For this reason, and also because TOMS record has gaps, md EP/TOMS is suffering from data quality problems, we recommend using SBUV total ozone data for applications where the high spatial resolution of TOMS is not essential.

Bhartia, Pawan K.↗

NASA NTRS2004

A Long Data Record (1979-2003) of Stratospheric Ozone Derived from TOMS Cloud Slicing: Comparison with SAGE and Implications for Ozone Recovery

It is generally recognized that Stratospheric Aerosols and Gas Experiment (SAGE) stratospheric ozone data have become a standard long-record reference field for comparison with other stratospheric ozone measurements. This study demonstrates that stratospheric column ozone (SCO) derived from total ozone mapping spectrometer (TOMS) Cloud Slicing may be used to supplement SAGE data as a stand-alone long- record reference field in the tropics extending to middle and high latitudes over the Pacific. Comparisons of SAGE I1 version 6.2 SCO and TOMS version 8 Cloud Slicing SCO for 1984-2003 exhibit remarkable agreement in monthly ensemble means to within 1-3 DU (1 - 1.5% of SCO) despite being independently-calibrated measurements. An important component of our study is to incorporate these column ozone measurements to investigate long-term trends for the period 1979-2003. Our study includes Solar Backscatter Ultraviolet (SBW) version 8 measurements of upper stratospheric column ozone (i.e., zero to 32 hPa column ozone) to characterize seasonal cycles and seasonal trends in this region, as well as the lower stratosphere and troposphere when combined with TOMS SCO and total column ozone. The trend analyses suggest that most ozone reduction in the atmosphere since 1979 in mid-to-high latitudes has occurred in the Lower stratosphere below approx. 25 km. The delineation of upper and lower stratospheric column ozone indicate that trends in the upper stratosphere during the latter half of the 1979-2003 period have reduced to near zero globally, while trends in the lower stratosphere have become larger by approx. 5 DU decade%om the tropics extending to mid-latitudes in both hemispheres. For TCO, the trend analyses suggest moderate increases over the 25-year time record in the extra-tropics of both hemispheres of around 4-6 DU (Northern Hemisphere) and 6-8 DU (Southern Hemisphere).

Ziemke, Jerry R.↗

NASA NTRS2004

First Look at the Upper Tropospheric Ozone Mixing Ratio from OMI Estimated using the Cloud Slicing Technique

The Cloud Slicing technique has emerged as a powerful tool for the study of ozone in the upper troposphere. In this technique one looks at the variation with cloud height of the above-cloud column ozone derived from the backscattered ultraviolet instruments, such as TOMS, to determine the ozone mixing ratio. For this technique to work properly one needs an instrument with relatively good horizontal resolution with very good signal to noise in measuring above-cloud column ozone. In addition, one needs the (radiatively) effective cloud pressure rather than the cloud-top pressure, for the ultraviolet photons received by a satellite instrument are scattered from inside the cloud rather than from the top. For this study we use data from the OMI sensor, which was recently launched on the EOS Aura satellite. OMI is a W-Visible backscattering instrument with a nadir pixel size of 13 x 24 km. The effective cloud pressure is derived from a new algorithm based on Rotational Raman Scattering and O2-O2, absorption in the 340-400 nm band of OMI.

Bhartia, Pawan K.↗