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NASA NTRS2011

Estimation of Smoothing Error in SBUV Profile and Total Ozone Retrieval

Data from the Nimbus-4, Nimbus-7 Solar Backscatter Ultra Violet (SBUV) and seven of the NOAA series of SBUV/2 instruments spanning 41 years are being reprocessed using V8.6 algorithm. The data are scheduled to be released by the end of August 2011. An important focus of the new algorithm is to estimate various sources of errors in the SBUV profiles and total ozone retrievals. We discuss here the smoothing errors that describe the components of the profile variability that the SBUV observing system can not measure. The SBUV(/2) instruments have a vertical resolution of 5 km in the middle stratosphere, decreasing to 8 to 10 km below the ozone peak and above 0.5 hPa. To estimate the smoothing effect of the SBUV algorithm, the actual statistics of the fine vertical structure of ozone profiles must be known. The covariance matrix of the ensemble of measured ozone profiles with the high vertical resolution would be a formal representation of the actual ozone variability. We merged the MLS (version 3) and sonde ozone profiles to calculate the covariance matrix, which in general case, for single profile retrieval, might be a function of the latitude and month. Using the averaging kernels of the SBUV(/2) measurements and calculated total covariance matrix one can estimate the smoothing errors for the SBUV ozone profiles. A method to estimate the smoothing effect of the SBUV algorithm is described and the covariance matrixes and averaging kernels are provided along with the SBUV(/2) ozone profiles. The magnitude of the smoothing error varies with altitude, latitude, season and solar zenith angle. The analysis of the smoothing errors, based on the SBUV(/2) monthly zonal mean time series, shows that the largest smoothing errors were detected in the troposphere and might be as large as 15-20% and rapidly decrease with the altitude. In the stratosphere above 40 hPa the smoothing errors are less than 5% and between 10 and 1 hPa the smoothing errors are on the order of 1%. We validate our estimated smoothing errors by comparing the SBUV ozone profiles with other ozone profiling sensors.

Kramarova, N. A.↗
NASA NTRS2012

SBUV version 8.6 Retrieval Algorithm: Error Analysis and Validation Technique

SBUV version 8.6 algorithm was used to reprocess data from the Back Scattered Ultra Violet (BUV), the Solar Back Scattered Ultra Violet (SBUV) and a number of SBUV/2 instruments, which 'span a 41-year period from 1970 to 2011 (except a 5-year gap in the 1970s)[see Bhartia et al, 2012]. In the new version Daumont et al. [1992] ozone cross section were used, and new ozone [McPeters et ai, 2007] and cloud climatologies Doiner and Bhartia, 1995] were implemented. The algorithm uses the Optimum Estimation technique [Rodgers, 2000] to retrieve ozone profiles as ozone layer (partial column, DU) on 21 pressure layers. The corresponding total ozone values are calculated by summing ozone columns at individual layers. The algorithm is optimized to accurately retrieve monthly zonal mean (mzm) profiles rather than an individual profile, since it uses monthly zonal mean ozone climatology as the A Priori. Thus, the SBUV version 8.6 ozone dataset is better suited for long-term trend analysis and monitoring ozone changes rather than for studying short-term ozone variability. Here we discuss some characteristics of the SBUV algorithm and sources of error in the SBUV profile and total ozone retrievals. For the first time the Averaging Kernels, smoothing errors and weighting functions (or Jacobians) are included in the SBUV metadata. The Averaging Kernels (AK) represent the sensitivity of the retrieved profile to the true state and contain valuable information about the retrieval algorithm, such as Vertical Resolution, Degrees of Freedom for Signals (DFS) and Retrieval Efficiency [Rodgers, 2000]. Analysis of AK for mzm ozone profiles shows that the total number of DFS for ozone profiles varies from 4.4 to 5.5 out of 6-9 wavelengths used for retrieval. The number of wavelengths in turn depends on solar zenith angles. Between 25 and 0.5 hPa, where SBUV vertical resolution is the highest, DFS for individual layers are about 0.5.

Kramarova, N. A.↗
NASA NTRS1994

The ground-based measurement of ozone in the 9.6 micron band

Stratospheric ozone has been measured using infrared emission spectroscopy of the 9.6 micron band. Thermal emission spectra of the zenith sky were measured from the ground. The spectra show the presence of the 1020 cm(exp -1) spectral feature of ozone on clear days. The spectra were measured with a BOMEM model 100 emission interferometer with a resolution of 4 cm(exp -1). The feature corresponds to a mixing ratio of 5 ppmv if the ozone is assumed to be uniformly distributed in the stratosphere from 25 to 35 km. The development of an inversion algorithm to derive the altitude distribution of the ozone in 3 layers is described. These measurements have been conducted from Peterborough, Ontario since June 1991; further investigations are planned to study the comparisons with Dobson and LIDAR ozone measurements.

Evans, W. F. J.↗
NASA NTRS2000

Tropospheric Ozone Pollution Transport Traced from the TOMS (Total Ozone Mapping Spectrometer) Instrument During the Nashville-1999 Campaign

Over the past several years, we have developed two new tropospheric ozone retrievals from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument that are of sufficient resolution to follow pollution episodes. The modified-residual technique [Hudson and Thompson, 1998; Thompson and Hudson, 1999] uses v. 7 TOMS total ozone and is applicable to tropical regimes in which the wave-one pattern in total ozone is observed. The TOMS-direct method [("TDOT" = TOMS Direct Ozone in the Troposphere; Frolov et al., 2000] represents a new algorithm that uses TOMS radiances directly (i.e., not previously processed for TOMS ozone) to extract tropospheric ozone in regions of constant stratospheric ozone and tropospheric ozone displaying high mixing ratios and variability characteristic of pollution. These events tend to occur in certain meteorological regimes. For example, mid-latitude pollution usually occurs on the backside of subtropical fronts, as low pv, usually moist air intrudes to the extra-tropics. July 1999 was a month characterized by robust pollution in the eastern US, with high ozone, as detected by TOMS, originating over south central states and moving up the Atlantic seaboard. This corresponds to 50-80 DU in tropospheric ozone column depth. In most cases, further transport occurred to the North Atlantic, with ozone plumes traveling to western Europe in 4-5 days. Examples of high ozone and transit across boundaries within the US, as well as US->Europe, give a regional context for model results and field measurements taken in the SE US during the Nashville-1999 campaign period. Validation of the TDOT maps is made with ozonesondes taken during that time. TDOT maps also show ozone pollution from Asia traveling to the western US in July 1999.

Thompson, Anne M.↗
NASA NTRS1990

Calibration of long term satellite ozone data sets using the space shuttle

Trends in atmospheric ozone continue to be an environmental concern. Drifts in satellite observations are the major obstacle in the detection of changes in global ozone over the long term. Careful re-analysis of satellite ozone data along with groundbased observations have more or less corroborated photochemical models which predict ozone depletion. However, there remains the margin of error in the observations that is as large as the trend itself. The National Plan for Stratospheric Monitoring calls for monitoring global ozone for at lease the next ten years employing the NOAA polar orbiting satellites. Ozone observations will be made with the Solar Backscatter Ultraviolet Spectral Radiometer Mod 2 (SBUV/2) which ia a refinement of the SBUV instrument flying on NASA's Nimbus-7 satellite. The first instrument in the operational series began taking data from the NOAA-9 spacecraft in February 1985. A second instrument was launched on NOAA-11 in September 1988. Both continue to operate. Earlier attempts to calibrate satellite data relied on comparisons with ground based observations. However, differences in instrumental techniques severely complicated these efforts. This problem will be over come by regular flights, about once per year, of the Shuttle Solar Backscatter Ultraviolet radiometer (SSBUV). The data from the SSBUV instrument will be compared with nearly coincident data taken by the NOAA satellite instruments. This procedure will permit a direct calibration transfer in space, since the two instruments observe the same qualities thereby bypassing the inversion algorithm which converts the observations to ozone amounts.

Hilsenrath, Ernest↗
NASA NTRS2002

TOMS UV Algorithm: Problems and Enhancements

Satellite instruments provide global maps of surface ultraviolet (UV) irradiance by combining backscattered radiance measurements with radiative transfer models. The models are limited by uncertainties in input parameters of the atmosphere and the surface. We evaluate the effects of possible enhancements of the current Total Ozone Mapping Spectrometer (TOMS) surface UV irradiance algorithm focusing on effects of diurnal variation of cloudiness and improved treatment of snow/ice. The emphasis is on comparison between the results of the current (version 1) TOMS UV algorithm and each of the changes proposed. We evaluate different approaches for improved treatment of pixel average cloud attenuation, with and without snow/ice on the ground. In addition to treating clouds based only on the measurements at the local time of the TOMS observations, the results from other satellites and weather assimilation models can be used to estimate attenuation of the incident UV irradiance throughout the day. A new method is proposed to obtain a more realistic treatment of snow covered terrain. The method is based on a statistical relation between UV reflectivity and snow depth. The new method reduced the bias between the TOMS UV estimations and ground-based UV measurements for snow periods. The improved (version 2) algorithm will be applied to re-process the existing TOMS UV data record (since 1978) and to the future satellite sensors (e.g., Quik/TOMS, GOME, OMI on EOS/Aura and Triana/EPIC).

Krotkov, Nickolay↗
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 NTRS1985

Development of algorithms for using satellite meteorological data sets to study global transport of stratospheric aerosols and ozone

The utilization of stratospheric aerosol and ozone measurements obtained from the NASA developed SAM II and SAGE satellite instruments were investigated for their global scale transports. The stratospheric aerosols showed that during the stratospheric warming of the winter 1978 to 1979, the distribution of the zonal mean aerosol extinction ratio in the northern high latitude exhibited distinct changes. Dynamic processes might have played an important role in maintenance role in maintenance of this zonal mean distribution. As to the stratospheric ozone, large poleward ozone transports are shown to occur in the altitude region from 24 km to 38 km near 55N during this warming. This altitude region is shown to be a transition region of the phase relationship between ozone and temperature waves from an in-phase one above 38 km. It is shown that the ozone solar heating in the upper stratosphere might lead to enhancement of the damping rate of the planetary waves due to infrared radiation alone in agreement with theoretical analyses and an earlier observational study.

Want, P. H.↗
NASA NTRS1999

Global Modeling of Mineral Dust and its Optical Thickness

Global distribution of dust in the atmosphere has been simulated using the NASA Goddard chemical transport model (GEOS-CTM) to help retrieve the aerosol optical thickness from TOMS absorbing aerosol index. The model contains a dust module which accounts for sources and removal processes. The transport is driven by the assimilated meteorological fields generated by the NASA Goddard Earth Observing System Data Assimilation System (GEOS DAS). One of the key parameters, in the retrieval algorithm of optical thickness from Total Ozone Mapping Spectrometer (TOMS) data, is the vertical profile of aerosols. During the period 10- 19 September 1994, Lidar on-space Technology Experiment (LITE) was flown on space shuttle Discovery. The 53 hours of data collected cover the lower atmosphere from the earth surface to 20 kilometers altitude and from 57 N to 57 S with a high resolution of about 15 meters. The model results are compared with LITE data over the source regions of dust (Africa, Middle East, Asia, Australia) and in the remote troposphere (Atlantic and Pacific). The simulated horizontal distribution is compared with TOMS absorbing aerosol index. Finally the calculated optical thickness will be assessed with ground based sun-photometers (AERONET).

Ginoux, Paul A.↗
NASA NTRS2016

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Space-Borne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(sup 40) molecules (sup 2) per centimeters(sup -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nanometers, the O4 absorption band at 477 nanometers is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nanometers is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 meters for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 percent of retrieved aerosol effective heights are within the error range of 1 kilometer compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Air Pollution↗
NASA NTRSDate not supplied

A Principal Component and Machine Learning Approach to Spatially Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals tend to be limited in spatial coverage due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals but despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we propose a spatial gap filling approach using machine learning to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from a standard ocean color algorithm such as the MODIS atmospheric correction algorithm. This machine learning approach is independent of a priori information and does not rely on any radiative transfer modeling. We apply the approach to two hyperspectral UV/VIS instruments, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) which will be onboard NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) ocean color satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the geostationary satellite Tropospheric Emissions: Monitoring of Pollution (TEMPO) to better understand diurnal variability in ocean ecology.

MODIS atmospheric correction algorithm↗
NASA NTRS1994

Northern hemisphere total ozone values from 1989-1993 determined with the NOAA-11 Solar Backscatter Ultraviolet (SBUV/2) instrument

Determinations of global total ozone amounts have been made from recently reprocessed measurements with the SBUV/2 on the NOAA-11 environmental satellite since January 1989. This data set employs a new algorithm and an updated calibration. Comparisons with total ozone amounts derived from a significant subset of the global network of Dobson spectrophotometers shows a 0.3% bias between the satellite and ground measurements for the period January 1989-May 1993. Comparisons with the data from individual stations exhibit differing degrees of agreement which could be due to the matchup procedures and also to the uncertainties in the Dobson data. The SBUV/2 data set discussed here traces the Northern Hemisphere total ozone from 1989 to the present, showing a marked decrease from the average of those years starting in the summer of 1992 and continuing into 1993, with an apparent returning to more normal levels in late 1993.

Planet, W. G.↗
NASA NTRS1976

Investigation of the effect of atmospheric dust on the determination of total ozone from the earth's ultraviolet reflectivity measurements, 1

Two computer algorithms are described. These algorithms were used for computing the aximuth-independent component of the intensity of the monochromatic radiation emerging at the top of a pseudo-spherical atmosphere with arbitrary vertical distribution of ozone, and with any arbitrary height distribution of up to two different kinds of aerosol. This atmospheric model was assumed to rest on a surface obeying Lambert's law of reflection.

Dave, J. V.↗
NASA NTRS2004

Comparison of TOMS, SBW & SBUV/2 Version 8 Total Column Ozone Data with Data from Groundstations

The Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) data as well as SBUV and SBUV/2 data have been reprocessed with a new retrieval algorithm (Version 8) and an updated calibration procedure. An overview will be presented systematically comparing ozone values to an ensemble of Brewer and Dobson spectrophotometers. The comparisons were made as a function of latitude, solar zenith angle, reflectivity and total ozone. Results show that the accuracy of the TOMS retrieval has been improved when aerosols are present in the atmosphere, when snow/ice and sea glint are present, and when ozone in the northern hemisphere is extremely low. TOMS overpass data are derived from the single TOMS best match measurement, almost always located within one degree of the ground station and usually made within an hour of local noon. The Version 8 Earth Probe TOMS ozone values have decreased by an average of about 1% due to a much better understanding of the calibration of the instrument. N-7 SBUV as well as the series of NOAA SBUV/2 column ozone values have also been processed with the Version 8 algorithm and have been compared to values from an ensemble of groundstations. Results show that the SBW column ozone values agree well with the groundstations and the datasets are useful for trend studies.

Labow, G. J.↗
NASA NTRS1983

Vertical ozone profile determination from Nimbus-7 SBUV measurements

An inversion algorithm is presented, which is used to process Nimbus-7 solar backscattered UV (SBUV) data collected between November 1978 and October 1980. The SBUV experiment utilizes a double monochromator in the nadir position which measures the backscattered solar radiation in twelve 1-nm bands; a separate photometer measures the radiance at 343.0 nm in the field of view coincident with the monochromator. The primary output of the inversion is the total ozone content in umkehr layers in units of m atm cm. In addition, the diagonal elements of the covariance matrix are reported; they represent the uncertainty in the derived ozone content in each layer. The solution covariance is noted to be independent of the measurements.

Klenk, K. F.↗
NASA NTRS2006

First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm

We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds.

Joiner, Joanna↗
NASA NTRS2019

A New Discrete Wavelength BUV Algorithm for Consistent Volcanic SO2 Retrievals from Multiple Satellite Missions

This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978-1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015-) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA-NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

Bradford L Fisher↗
NASA NTRS2007

Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

Weisz, Elisabeth↗