Robert Spurr

An improved retrieval of tropospheric nitrogen dioxide from GOME

[1] We present a retrieval of tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment (GOME) satellite instrument that improves in several ways over previous retrievals, especially in the accounting of Rayleigh and cloud scattering. Slant columns, which are directly fitted without low-pass filtering or spectral smoothing, are corrected for an artificial offset likely induced by spectral structure on the diffuser plate of the GOME instrument. The stratospheric column is determined from NO2 columns over the remote Pacific Ocean to minimize contamination from tropospheric NO2. The air mass factor (AMF) used to convert slant columns to vertical columns is calculated from the integral of the relative vertical NO2 distribution from a global 3-D model of tropospheric chemistry driven by assimilated meteorological data (Global Earth Observing System (GEOS)-CHEM), weighted by altitude-dependent scattering weights computed with a radiative transfer model (Linearized Discrete Ordinate Radiative Transfer), using local surface albedos determined from GOME observations at NO2 wavelengths. The AMF calculation accounts for cloud scattering using cloud fraction, cloud top pressure, and cloud optical thickness from a cloud retrieval algorithm (GOME Cloud Retrieval Algorithm). Over continental regions with high surface emissions, clouds decrease the AMF by 20– 30% relative to clear sky. GOME is almost twice as sensitive to tropospheric NO2 columns over ocean than over land. Comparison of the retrieved tropospheric NO2 columns for July 1996 with GEOS-CHEM values tests both the retrieval and the nitrogen oxide radical

Ring effect studies: Rayleigh scattering, including molecular parameters for rotational Raman scattering, and the Fraunhofer spectrum

Improved parameters for the description of Rayleigh scattering in air and for the detailed rotational Raman scattering component for scattering by O(2) and N(2) are presented for the wavelength range 200-1000 nm. These parameters enable more accurate calculations to be made of bulk molecular scattering and of the Ring effect for a variety of atmospheric radiative transfer and constituent retrieval applications. A solar reference spectrum with accurate absolute vacuum wavelength calibration, suitable for convolution with the rotational Raman spectrum for Ring effect calculations, has been produced at 0.01-nm resolution from several sources. It is convolved with the rotational Raman spectra of O(2) and N(2) to produce an atmospheric Ring effect source spectrum.

Satellite observations of formaldehyde over North America from GOME

Formaldehyde (HCHO) is an important indicator of tropospheric hydrocarbon emissions and photochemical activity. We present HCHO observations over North America for July 1996 from the GOME instrument on-board the ESA ERS-2 satellite. Slant columns are determined to < 4 × 1015 molecules cm−2 sensitivity by directly fitting GOME radiance measurements. These show a distinct enhancement over the southeastern United States, consistent with a large regional source from oxidation of non-methane hydrocarbons including in particular isoprene. Conversion of slant to vertical columns is done by combining species vertical distribution information from the GEOS-CHEM 3-D tropospheric chemistry and transport model with scattering weights from the Smithsonian Astrophysical Observatory LIDORT multiple scattering radiative transfer model. The results demonstrate the ability to measure HCHO from space in typical continental atmospheres, and imply that space-based measurements of HCHO may provide valuable information on emission fluxes of reactive hydrocarbons.

GOMETRAN : A radiative transfer model for the satellite project GOME, the plane-parallel version

The Global Ozone Monitoring Experiment (GOME) is a new, nadir-viewing instrument on the European Space Agency satellite ERS 2 which was launched in April 1995. With diode-array detector technology, spectra of the upwelling radiance are measured simultaneously at thousands of wavelengths in the UV, visible, and near-IR regions. Inversion of these measurements by appropriate algorithms allows the retrieval of the distribution of gaseous and particulate constituents, which modulate the radiance by absorption, emission, or scattering processes. Such a retrieval algorithm requires an accurate radiative transfer model to describe the propagation of light through the atmosphere. The model GOMETRAN has been specially designed to fulfill the needs of GOME, but it applies generally to other downward looking space instrumentation in the UV, visible, or near-IR. In this paper the model is described in the plane-parallel version, and the optimization of computational parameters and comparisons with other radiative transfer models is presented.

Ozone profile and tropospheric ozone retrievals from the Global Ozone Monitoring Experiment: Algorithm description and validation

Received 18 May 2005; revised 4 August 2005; accepted 1 September 2005; published 29 October 2005. [1] Ozone profiles are derived from back scattered radiance spectra in the ultraviolet (289–339 nm) measured by the Global Ozone Monitoring Experiment (GOME) using the optimal estimation technique. Tropospheric Column Ozone (TCO) is directly derived using the known tropopause to divide the stratosphere and troposphere. To optimize the retrieval and improve the fitting precision needed for tropospheric ozone, we perform extensive wavelength and radiometric calibrations and improve forward model inputs. The a priori influence of retrieved TCO is � 15% in the tropics and increases to � 50% at high latitudes. The dominant error terms are the smoothing errors, instrumental randomnoise errors, and systematic temperature errors. We compare our GOME retrievals with Earth-Probe Total Ozone Mapping Spectrometer (TOMS) Total column Ozone (TO), Dobson/Brewer (DB) TO, and ozonesonde TCO at 33 World Ozone and Ultraviolet Radiation Data Centre (WOUDC) stations between 71� S and 75� N during 1996–1999. The mean biases with TOMS and DB TO are within 6 DU (2%, 1 DU = 2.69 � 10 16 molecules cm � 2 ) at most of the stations. The retrieved Tropospheric Column Ozone (TCO) captures most of the temporal variability in ozonesonde TCO; the mean biases are mostly within 3 DU (15%) and the standard deviations (1s) are within 3–8 DU (13–27%). We also compare our retrieved ozone profiles above � 15 km against Stratospheric Aerosol and Gas Experiment II measurements from 1996 to 1999. The mean biases and standard deviations are usually within 15%.

Ten years of GOME/ERS-2 total ozone data- : The new GOME data processor (GDP) version 4: 1. Algorithm description

The Global Ozone Monitoring Instrument (GOME) was launched on European Space Agencys ERS-2 platform in April 1995. The GOME data processor (GDP) operational retrieval algorithm has generated total ozone columns since July 1995. In 2004 the GDP system was given a major upgrade to version 4.0, a new validation was performed, and the 10-year GOME level 1 data record was reprocessed. In two papers, we describe the GDP 4.0 retrieval algorithm and present an error budget and sensitivity analysis (paper 1) and validation of the GDP total ozone product and the overall accuracy of the entire GOME ozone record (paper 2). GDP 4.0 uses an optimized differential optical absorption spectroscopy (DOAS) algorithm, with air mass factor (AMF) conversions calculated using the radiative transfer code linearized discrete ordinate radiative transfer (LIDORT). AMF computation is based on the TOMS version 8 ozone profile climatology, classified by total column, and AMFs are adjusted iteratively to reflect the DOAS slant column result. GDP 4.0 has improved wavelength calibration and reference spectra and includes a new molecular Ring correction to deal with distortion of ozone absorption features due to inelastic rotational Raman scattering effects. Preprocessing for cloud parameter estimation in GDP 4.0 is done using two new cloud correction algorithms: OCRA and ROCINN. For clear and cloudy scenes the precision of the ozone column product is better than 2.4 and 3.3%, respectively, for solar zenith angles up to 80°. Comparisons with ground-based data are generally at the 1-1.5% level or better for all regions outside the poles.

Simultaneous derivation of intensities and weighting functions in a general pseudo-spherical discrete ordinate radiative transfer treatment

The retrieval of atmospheric constituents from measurements of backscattered light requires a radiative transfer forward model that can simulate both intensities and weighting functions (partial derivatives of intensity with respect to atmospheric parameters being retrieved). The radiative transfer equation is solved in a multi-layer multiply-scattering atmosphere using the discrete ordinate method. In an earlier paper dealing with the upwelling top-of-the-atmosphere radiation 1eld, it was shown that a full internal perturbation analysis of the plane-parallel discrete ordinate solution leads in a natural way to the simultaneous generation of analytically-derived weighting functions with respect to a wide range of atmospheric variables. In the present paper, a more direct approach is used to evaluate explicitly all partial derivatives of the intensity 1eld. A generalization of the post-processing function is developed for the derivation of weighting functions at arbitrary optical depth and stream angles for both upwelling and downwelling directions. Further, a complete treatment is given for the pseudo-spherical approximation of the direct beam attenuation; this is an important extension to the range of viewing geometries encountered in practical radiative transfer applications. The numerical model LIDORT developed for this work is able to generate intensities and weighting functions for a wide range of retrieval scenarios, in addition to the passive remote sensing application from space. We present a number of examples in an atmosphere with O3 absorption in the UV, for satellite (upwelling radiation) and ground-based (downwelling radiation) applications. In particular, we examine the e=ect of various pseudo-spherical parameterizations on backscatter intensities and weighting functions with respect to O3 volume mixing ratio. In addition, the use of layer-integrated multiple scatter output from the model is shown to be important for satellite instruments with wide-angle o=-nadir viewing geometries. Published by Elsevier Science Ltd.

Detection of biomass burning combustion products in Southeast Asia from backscatter data taken by the GOME spectrometer

We show that atmospheric UV/visible backscatter spectra obtained by the Global Ozone Monitoring Experiment (GOME) spectrometer on board the ESA ERS-2 satellite may be used to retrieve column amounts of key trace species associated with smoke cloud combustion from biomass burning events. This paper focuses on the recent rain forest burning in SE Asia (August–October 1997). For ground scenes with low cloudiness, differential absorption fitting applied to backscatter spectra yields column distributions of NO2 and H2CO in and around smoke-polluted regions. A two-fold increase in the vertical NO2 content is apparent over large parts of the smoke cloud; this clearly indicates the ability of GOME to measure tropospheric NO2 content. H2CO is detected only in areas closest to combustion sources. Slant column amounts in the range 2.5 - 4 × 1016 mol cm−2 have been determined; these correspond with previous estimations of vertical columns of H2CO for biomass Savannah burning.

Evaluation of the OMI cloud pressures derived from rotational Raman scattering by comparisons with other satellite data and radiative transfer simulations

[1] 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.

The GOME‐2 total column ozone product: Retrieval algorithm and ground‐based validation

The Global Ozone Monitoring Instrument (GOME-2) was launched on EUMESATs MetOp-A satellite in October 2006. This paper is concerned with the retrieval algorithm GOME Data Processor (GDP) version 4.4 used by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF) for the operational generation of GOME-2 total ozone products. GDP 4.4 is the latest version of the GDP 4.0 algorithm, which is employed for the generation of official Level 2 total ozone and other trace gas products from GOME and SCIAMACHY. Here we focus on enhancements introduced in GDP 4.4: improved cloud retrieval algorithms including detection of Sun glint effects, a correction for intracloud ozone, better treatment of snow and ice conditions, accurate radiative transfer modeling for large viewing angles, and elimination of scan angle dependencies inherited from Level 1 radiances. Furthermore, the first global validation results for 3 years (2007–2009) of GOME-2/MetOp-A total ozone measurements using Brewer and Dobson measurements as references are presented. The GOME-2/MetOp-A total ozone data obtained with GDP 4.4 slightly underestimates ground-based ozone by about 0.5% to 1% over the middle latitudes of the Northern Hemisphere and slightly overestimates by around 0.5% over the middle latitudes in the Southern Hemisphere. Over high latitudes in the Northern Hemisphere, GOME-2 total ozone has almost no offset relative to Dobson readings, while over high latitudes in the Southern Hemisphere GOME-2 exhibits a small negative bias below 1%. For tropical latitudes, GOME-2 measures on average lower ozone by 0% to 2% compared to Dobson measurements.