K. Chance, X. Liu, C. Chan Miller, G. González Abad, G. Huang, C. Nowlan, A. Souri, R. Suleiman, K. Sun, H. Wang, L. Zhu, P. Zoogman, J. Al-Saadi, J. -C. Antuña-Marrero, J. Carr, R. Chatfield, M. Chin, R. Cohen, D. Edwards, J. Fishman, D. Flittner, J. Geddes, M. Grutter, J. Herman, D. Jacob, S. Janz, J. Joiner, J. Kim, N. Krotkov, B. Lefer, R. Martin, O. Mayol-Bracero, A. Naeger, M. Newchurch, G. Pfister, K. Pickering, R. Pierce, C. Rivera Cárdenas, A. Saiz-Lopez, W. Simpson, E. Spinei, R. J. Spurr, J. Szykman, O. Torres, J. Wang
The NASA/Smithsonian Tropospheric Emissions: Monitoring of Pollution (TEMPO; tempo.si.edu) satellite instrument will measure atmospheric pollution and much more over Greater North America at high temporal resolution (hourly or better in daylight, with selected observations at 10 minute or better sampling) and high spatial resolution (10 km2 at the center of the field of regard). It will measure ozone (O3) profiles (including boundary layer O3), and columns of nitrogen dioxide (NO2), nitrous acid (HNO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), water vapor (H2O), bromine oxide (BrO), iodine oxide (IO), chlorine dioxide (OClO), as well as clouds and aerosols, foliage properties, and ultraviolet B (UVB) radiation. The instrument has been delivered and is awaiting spacecraft integration and launch in 2022. This talk describes a selection of TEMPO applications based on the TEMPO Green Paper living document (http://tempo.si.edu/publications.html).
Applications to air quality and health will be summarized. Other applications presented include: biomass burning and O3 production; aerosol products including synergy with GOES infrared measurements; lightning NOx; soil NOx and fertilizer application; crop and forest damage from O3; chlorophyll and primary productivity; foliage studies; halogens in coastal and lake regions; ship tracks and drilling platform plumes; water vapor studies including atmospheric rivers, hurricanes, and corn sweat; volcanic emissions; air pollution and economic evolution; high-resolution pollution versus traffic patterns; tidal effects on estuarine circulation and outflow plumes; air quality response to power blackouts and other exceptional events.
An alternative algorithm is being developed to retrieve ozone vertical distribution information from the OMPS/LP sensor
which will be manifested on the upcoming NPOESS Preparatory Project (NPP) platform in late 2011. In contrast to most
limb sensors retrieval methods, the proposed algorithm will forgo the spherical symmetry assumption for the
atmospheric structure, and will attempt to simultaneously retrieve the ozone distribution in both the vertical and the
along-track directions. The paper describes the two-dimensional forward model as well as the methods which have been
developed to simultaneously retrieve a whole orbit of data. Sample retrieval results are shown to illustrate the technique.
For remote sensing over snow-covered surfaces, the bidirectional reflectance distribution function (BRDF) of snow plays an important role that should be considered in inverse algorithms for the retrieval of snow properties. However, to simplify retrievals, many researchers assume that snow is a Lambertian reflector. This “forward model” error affects the accuracy of retrieved snow parameters (such as albedo, snow grain size, and impurity concentration). To quantify this error and to compensate for it, we provide a simple yet accurate semi-empirical correction formula. It allows for easy conversion of top-of-the-atmosphere (TOA) reflectance arising from an anisotropically reflecting snow surface to an equivalent TOA reflectance for a Lambertian surface with the same albedo. Conversely, this correction can be used to translate TOA radiance computed with the Lambertian assumption into a more realistic value based on a BRDF treatment. The coefficients in this correction formula are stored in a look-up table (LUT), and a simple LUT interpolation program is provided to allow the user to extract TOA reflectances for any sun-satellite geometry by quick interpolation in the LUTs. For the first 8 channels of the VIIRS spectrometer, the R-square regression coefficient for fitting this correction formula is better than 0.95 for a wide range of sun-satellite geometries.
Recent work has shown the need for accurate treatment of radiative transfer in ocean color retrieval. The plane-parallel coupled atmosphere-ocean discrete ordinate model CAO-DISORT has been used to investigate the validity of current approximative inverse methods and to study new techniques for improved ocean color retrieval. In this paper we show that CAO-DISORT is fully differentiable with respect to its input optical properties, so that we can define analytic Jacobians with respect to any profile element in the atmosphere and ocean. A single call to the linearized model will produce radiances and Jacobians at arbitrary optical depth and viewing geometry in either medium. The model also has a pseudo-spherical treatment for solar beam attenuation in a curved atmosphere. The linearized model can be used directly in iterative least-squares retrievals requiring forward model simulations of backscatter measurements and their parameter derivatives; there is no need for approximations involving an atmospheric correction. We demonstrate the model's new capability by performing closed-loop least squares fitting to simultaneously retrieve the aerosol optical thickness and marine chlorophyll concentration from a set of 6 synthetic measurements at SeaWifs wavelengths.
A new method for simultaneous retrieval of aerosol properties and marine constituents in turbid waters is described. This method is an extension to turbid waters of an approach developed previously for simultaneous retrieval of aerosol properties and chlorophyll concentrations in clear waters. This extension is accomplished by employing near-infrared (NIR) channels not available on the SeaWiFS and MERIS instruments to help retrieve aerosol parameters over turbid waters. Optimal estimation theory is used to retrieve in-water parameters from multi- and hyperspectral information. Both forward and inverse modeling strategies will be discussed, as well as the uniqueness of the solutions, the information content available in multi- and hyperspectral data, and the error analysis approach. Our results indicate that it is important to use forward models that accurately treat the radiative transfer in the coupled (combined) atmosphere-ocean system, and to carefully select the most suitable bio-optical models for the in-water inherent optical properties (IOPs). Synthetic data, as well as multi- and hyperspectral images of data obtained over clear as well as turbid waters, are used to test the validity of the new retrieval approach.
Retrieval of surface properties of highly reflecting targets such as snow and ice is a challenging problem due to the influence of aerosols
which varies considerably in space and time. Also, accounting for the bidirectional properties of a bright surface such as snow is very important for reliable retrievals. The main purpose of the work described in this paper is to explore the opportunities and possibilities offered by multi- and hyperspectral data such as those available provided by MODIS, GLI, the Advanced Land Imager (ALI), and Hyperion to retrieve reliable aerosol and surface properties. Over snow and ice surfaces these include aerosol optical depth and single scattering albedo, the mean size of snow grains and ice "particles" (inclusions), and the spectral and broadband snow/ice albedo. In particular the following question will be addressed: To what extent can multi- and hyperspectral data help improve our knowledge of snow and ice parameters that are important for understanding global climate change?
The LIDPORT V2PLUS radiative transfer package is designed for simulation and retrieval applications for nadir viewing remote sensing instruments such as GOME, GOME-2, SCIAMACHY, OMI and MODIS. The package is based on the LIDORT family of linearized discrete ordinate models, and it will deliver earthshine radiances, analytic profile, total column and surface property Jacobians. LIDORT V2PLUS includes a quasi-exact single scatter computation for all solar beams and the line of sight direction in a curved spherical-shell refracting atmosphere, and a full treatment of the diffuse radiation field in the pseudo-spherical approximation at all points along the line-of-sight. We give examples of radiances and O3 air mass factors at 325 nm, and Jacobians for O3 total column and profiles and for surface albedos, with particular emphasis on the wide-angle spherically-corrected viewing mode. We also look at the effect of horizontal inhomogeneity caused by varying surface properties along the line of sight.
The Global Ozone Monitoring Experiment (GOME) was launched on the European Space Agency's ERS-2 satellite in April 20, 1995. GOME measures the Earth's atmosphere in the nadir geometry, using a set of spectrometers that cover the UV and visible (240 - 790 nm) at moderate resolution (0.2 nm in the UV, 0.4 nm in the visible), employing silicon diode array detectors. GOME takes some 30,000 spectra per day, obtaining full global coverage in three days. We directly fit GOME radiance spectra using nonlinear least-squares analysis to obtain column amounts of several trace species with significant tropospheric concentrations, including ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO). Measurements of HCHO due to biogenic activity in the troposphere are presented here.
The Global Ozone Monitoring Experiment (GOME) is an atmospheric chemistry instrument on-board the ERS-2 satellite which is able to measure a range of important atmospheric trace constituents on a global scale. Atmospheric UV/visible backscatter spectra obtained by the GOME spectrometer were used to retrieve column amounts of key trace species associated with biomass burning events and ozone hole chemistry. In particular, the column distributions of ozone (O3), nitrogen dioxide (NO2), formaldehyde (CH2O), and bromine-monoxide (BrO) were retrieved on an operational basis. The differential optical absorption spectroscopy technique (DOAS) is applied to backscatter spectra and yields slant column distributions of the aforementioned species. Additionally, the vertical columns of O3 and NO2 are provided. A strong enhancement of both the NO2 and CH2O contents were detected during the severe biomass burning event in September 1997 in SE Asia. A higher NO2 content is apparent over a large area within the smoke clouds, where formaldehyde is detected only in areas closest to combustion sources. BrO has been detected on a global scale and under Antarctic winter (ozone hole) conditions. The knowledge about the spatial distribution and the amount of BrO is of high relevance because BrO is a key species for the depletion of stratospheric ozone.
The Global Ozone Monitoring Experiment (GOME) is a new atmospheric chemistry instrument on-board the ERS-2 satellite which was launched in April 1995. The GOME is designed to measure a range of atmospheric trace constituents, with particular emphasis on global ozone distributions. We show that atmospheric UV/visible backscatter spectra obtained by the GOME spectrometer may be used to retrieve column amounts of key trace species associated with smoke cloud combustion from biomass burning events. We focus on the severe rain forest burning in SE Asia from August to October 1997. The current operational GOME Data Processor (GDP) was used to retrieve column distributions of NO2 and CH2O in and around the smoke-polluted region. For ground scenes with low cloudiness, the differential optical absorption spectroscopy technique (DOAS) applied to backscatter spectra yields column distributions of NO2 and CH2O in and around the smoke- polluted region. An increase by almost a factor of two of the vertical NO2 content in the tropical atmosphere is apparent over a large area within the smoke cloud; this clearly indicates the ability of GOME to measure tropospheric NO2 content. CH2O is detected only in areas closest to combustion sources and the detected slant column amounts correspond with previous estimations of vertical column amounts of CH2O for biomass savannah burning.
The Global Ozone Monitoring Experiment (GOME) on board the ERS-2 satellite is an across-track nadir-viewing spectrometer which measures solar light reflected from the Earth's atmosphere and surface in the UV visible. The cloud retrieval algorithm presented here combines spectral threshold test on GOME's broad-band radiances with the fitting of reflectances to GOME's moderately high resolution spectra in and around the O2 A band to retrieve cloud- cover fraction, cloud-top height and cloud optical thickness. The algorithm utilizes the latest O2 spectroscopic data and features dynamical updating procedures to provide global threshold sets of GOME reflectances. Auxiliary information is obtained from GOME measurements of the Ring effect and the degree of polarization of the Earth's radiation field.
The GOME was launched on the European Space Agency's ERS-2 satellite on April 20, 1995. GOME measures the Earth's atmosphere in the nadir geometry, using four spectrometers that cover the UV and visible at moderate resolution, employing silicon diode array detectors. GOME takes some 30,000 spectra per day, obtaining full global coverage at 40 X 320 km2 resolution in three days. It provides measurements of ozone, NO2, SO2, H2CO, H2O, BrO, ClO, and OClO. We directly fit GOME radiance spectra using nonlinear least-squares analysis to obtain column amounts of several trace species, including ClO, BrO, SO2, and H2CO. The use of recent improvements in the underlying physical and spectroscopy permits the fitting of radiances to very high precision, approaching 2 X 10-4 in favorable case, for standard 1.5s integration time GOME measurements. Examples of the fitting of BrO and SO2 are presented here.
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