Ozone profile retrieval from GOME data
TL;DR: GOME is the first satellite instrument with the capability to retrieve height-resolved ozone densities in both stratosphere and troposphere as mentioned in this paper, which enables the derivation of accurate ozone profiles.
Abstract: GOME is the first satellite instrument with the possibility to retrieve height-resolved ozone densities in both stratosphere and troposphere. The high accuracy and spectral resolution of the GOME spectrometer in the range of 240-790 nm combined with sophisticated retrieval algorithms enables the derivation of accurate ozone profiles. This paper discusses in detail the retrieval procedure of ozone profiles from the GOME observations. The resulting profiles and their calculated errors are discussed and compared to local ozone profiles form ozone sonde measurements.
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TL;DR: In this paper, OMI provides daily ozone profiles for the entire sunlit portion of the earth at a horizontal resolution of 13 km×48 km for the nadir position.
Abstract: . Ozone profiles from the surface to about 60 km are retrieved from Ozone Monitoring Instrument (OMI) ultraviolet radiances using the optimal estimation technique. OMI provides daily ozone profiles for the entire sunlit portion of the earth at a horizontal resolution of 13 km×48 km for the nadir position. The retrieved profiles have sufficient accuracy in the troposphere to see ozone perturbations caused by convection, biomass burning and anthropogenic pollution, and to track their spatiotemporal transport. However, to achieve such accuracy it has been necessary to calibrate OMI radiances carefully (using two days of Aura/Microwave Limb Sounder data taken in the tropics). The retrieved profiles contain ~6–7 degrees of freedom for signal, with 5–7 in the stratosphere and 0–1.5 in the troposphere. Vertical resolution varies from 7–11 km in the stratosphere to 10–14 km in the troposphere. Retrieval precisions range from 1% in the middle stratosphere to 10% in the lower stratosphere and troposphere. Solution errors (i.e., root sum square of precisions and smoothing errors) vary from 1–6% in the middle stratosphere to 6–35% in the troposphere, and are dominated by smoothing errors. Total, stratospheric, and tropospheric ozone columns can be retrieved with solution errors typically in the few Dobson unit range at solar zenith angles less than 80°.
240 citations
TL;DR: In this article, a more direct approach is used to evaluate explicitly all partial derivatives of the intensity 1eld, and 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.
Abstract: 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.
120 citations
TL;DR: In this article, the authors presented the validation results of the operational vertical ozone profiles retrieved from the nadir observations by the Ozone Monitoring Instrument (OMI) aboard the NASA Earth Observing System (EOS) Aura platform.
Abstract: [1] In this paper we present the validation results of the operational vertical ozone profiles retrieved from the nadir observations by the Ozone Monitoring Instrument (OMI) aboard the NASA Earth Observing System (EOS) Aura platform. The operational ozone profile retrieval algorithm was developed at the Royal Netherlands Meteorological Institute and the OMI mission data has been processed and made publicly available. Advantages of these nadir sounded ozone profiles are the excellent spatial resolution at nadir and daily global coverage while the vertical resolution is limited to 6–7 km. Comparisons with well-validated ozone profile recordings by the Microwave Limb Sounder (MLS) and the Tropospheric Emission Spectrometer (TES), both aboard the NASA EOS-Aura platform, provide an excellent opportunity for validation because of the large amount of collocations with OMI due to the instruments significant geographical overlap. In addition, comparisons with collocated ozone profiles from the Stratospheric Aerosol and Gas Experiment (SAGE-II), the Halogen Occultation Experiment (HALOE), the Global Ozone Monitoring by the Occultation of Stars (GOMOS) and the Optical Spectrograph and Infrared Imager System (OSIRIS) satellite instruments and balloon-borne electrochemical concentration cell (ECC) ozonesondes are presented. OMI stratospheric ozone profiles are found to agree within 20% with global correlative data except for both the polar regions during local spring. For ozone in the troposphere OMI shows a systematic positive bias versus the correlative data sets of order 60% in the tropics and 30% at midlatitude regions. The largest source of error in the tropospheric ozone profile is the fit to spectral stray light in the operational algorithm.
69 citations
TL;DR: In this paper, the in-flight calibration of the Global Ozone Monitoring Experiment (GOME) reflectivity spectra needs to be corrected before the spectra can be used for profile retrieval.
Abstract: [1] The satellite instrument Global Ozone Monitoring Experiment (GOME), on board the ERS-2 mission of the European Space Agency, is measuring backscattered sunlight from the atmosphere in the range from 240 to 790 nm. This spectrum is used for deriving global, height-resolved information on the ozone distribution in the atmosphere. Contrary to total ozone column retrieval, the retrieval algorithm for ozone profiles requires absolutely calibrated reflectivity spectra. However, the in-flight calibration of the GOME reflectivity spectra needs to be corrected before the spectra can be used for profile retrieval. A general method for this calibration correction of satellite data and the profile retrieval method are described in this paper. The retrieved profiles from the recalibrated reflectivity spectra of GOME differ in the stratosphere by up to 50% from retrieved profiles without the correction. With the calibration correction, improved ozone profiles are retrieved for the complete range of 0–50 km. The GOME ozone profiles have been validated with ground and satellite measurements at a representative urban midlatitude and a rural tropical ground station.
55 citations
TL;DR: This work develops fast and analytic 4 stream and 6 stream linearized discrete ordinate models designed to satisfy performance and accuracy requirements for radiative transfer forward model in the ozone profile retrieval context.
Abstract: The global and long-term measurement of ozone vertical and horizontal distributions is one of the most important tasks in the monitoring of the earth's atmosphere. A number of satellite instruments are capable of delivering ozone profile distributions from UV nadir backscatter measurements. Retrieval algorithms should be efficient enough to deliver profiles in real-time without compromising accuracy. Such algorithms require a radiative transfer model that can generate quickly and accurately both simulated radiances and Jacobian matrices of weighting functions. We develop fast and analytic 4 stream and 6 stream linearized discrete ordinate models designed to satisfy performance and accuracy requirements for such an algorithm. The models have the pseudo-spherical treatment of the direct beam attenuation. For anisotropic scattering we use the delta-M scaling method to deal with strong forward scattering peaks. We demonstrate that the accuracy of the models is improved greatly upon application of a single scatter correction based on an exact specification of the phase function. For wide-angle off-nadir viewing, a sphericity correction is developed to deal more precisely with attenuation in a curved atmosphere. Radiances and weighting functions for the 4 and 6 stream models are compared with 20 stream output from the LIDORT model. We show that for the UV range pertinent to ozone profile retrieval from space, the 4 stream model generates backscatter radiances to an accuracy >1.25% for all viewing situations in a clear sky Rayleigh and background aerosol reference atmosphere, and up to 1.75% for a number of special scenarios with optically thick particulate layers. Six stream radiances are accurate to the 0.25% level for clear sky situations, and 0.65% for the special cases; weighting functions for the 6 stream output are accurate to ±2% in all cases. We discuss the implications of these comparisons regarding the performance and accuracy of the radiative transfer forward model in the ozone profile retrieval context.
48 citations
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TL;DR: In this paper, a formal analysis for profile retrieval is developed which is independent of the nature of the retrieval method, provided that the measurement process can be characterized adequately, and the relationship between the retrieved and true profiles is expressed in terms of a smoothing function which can be straightforwardly calculated.
Abstract: The characterization and error analysis of profiles retrieved from remote measurements present conceptual problems, particularly concerning interlevel correlations between errors, the smoothing effect of remote sounding and the contribution of a priori information to profile. A formal analysis for profile retrieval is developed which is independent of the nature of the retrieval method, provided that the measurement process can be characterized adequately. The relationship between the retrieved and true profiles is expressed in terms of a smoothing function which can be straightforwardly calculated. The retrieval error separates naturally into three components, (1) random error due to measurement noise, (2) systematic error due to uncertain model parameters and inverse model bias, and (3) null-space error due to the inherent finite vertical resolution of the observing system. A recipe is given for evaluating each of the components in any particular case. Most of the error terms appear as covariance matrices, rather than simple error variances. These matrices can be interpreted in terms of “error patterns”, which are statistically independent contributions to the total error. They are the multidimensional equivalent of “error bars”. An approach is described which clarifies the relation of a priori data to the retrieved profile, and identifies a priori in cases where it is not an explicit part of the retrieval.
708 citations