The Ozone Monitoring Instrument (OMI) multiwavelength algorithm has been developed to retrieve aerosol optical depth using OMI‐measured reflectance at the top of the atmosphere. This algorithm was ...further developed by using surface reflectance data from a field campaign in Cabauw (The Netherlands), a new cloud‐screening method, and a global aerosol database derived from the aerosol transport model TM5. The first results from an application of this algorithm over western Europe are presented. The OMI‐retrieved aerosol optical depth is evaluated by comparison with both ground‐based measurements from Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The various aerosol optical depth values compare favorably, except in situations where large changes occur in the surface properties, which is illustrated over the Iberian peninsula. OMI and MODIS aerosol optical depth are well correlated (with a correlation coefficient of 0.66 over land and 0.79 over sea), although the multiwavelength algorithm appears to overestimate the aerosol optical depth values with respect to MODIS. The multiwavelength algorithm performs better over sea than over land. Qualitatively, the multiwavelength algorithm well reproduces the expected spatial aerosol optical depth gradient over western Europe.
A case study for feldspar aerosols is conducted to assess the errors introduced by simple model particles in radiance and flux simulations. The spectral radiance field and net flux are computed for a ...realistic phase function of feldspar aerosols measured in the laboratory at 633 nm. Results are compared to computations with spherical and spheroidal model particles. It is found that the use of spherical model particles introduces large spectral radiance errors at top of atmosphere (TOA) between −6 and 31%. Using a new shape parameterization of spheroids reduces the error range to −1 to 6%. Spherical model particles yield an absolute TOA spectral net flux error of −6.1 mW m−2 nm−1. An equiprobable shape distribution of spheroids results in only minor improvements, but the new shape parameterization yields an error of only −0.8 mW m−2 nm−1. A variation of the refractive index m reveals that the resulting changes in the TOA spectral net flux are slightly smaller than the error caused by assuming the particles to be spherical. However, the uncertainty of m is commonly considered the major error source in aerosol radiative forcing simulations, whereas the use of spherical model particles is often not seriously questioned. This study implies that this notion needs to be reconsidered. Should the relative spectral net flux errors be representative for the entire spectrum, then the use of spherical model particles may be among the major error sources in broadband flux simulations. The new spheroidal shape parameterization can, however, substantially improve the results.
The quality of trace gas products derived from measurements of a space-borne imaging spectrometer is affected by the inhomogeneity of the illumination of the instrument slit and thus by the ...heterogeneity of the observed scene. This paper aims to quantify this effect and summarise findings on how to mitigate the impact of inhomogeneous slit illumination on tropospheric O3, NO2, SO2 and HCHO columns derived from measurements of the Sentinel-4 UVN imaging spectrometer. For this purpose, spectra for inhomogeneous ground scenes have been simulated based on a combination of a radiative transfer model and spatially high resolved MODIS (Moderate Resolution Imaging Spectroradiometer) data. The resulting errors on tropospheric O3, NO2, SO2 and HCHO columns derived from these spectra have been determined via an optimal estimation approach. We conclude that inhomogeneous illumination results in significant errors in the data products if the natural inhomogeneity of the observed scenes are not accounted for. O3 columns are less affected than the other data products; largest errors occur for NO2 (mean absolute errors about 5%, maximum error exceeding 50%, standard deviation of the errors about 8%). These errors may be significantly reduced (by factors up to about 10) by an appropriate wavelength calibration applied individually to each Earthshine radiance spectrum. With wavelength calibration the estimated mean absolute errors due to inhomogeneity are for all gases well below 1%; standard deviations of the errors are 1.5% or lower; maximum errors are about 10% for NO2 and around 5% for the other gases.
We present measurements of the whole scattering matrix as a function of the scattering angle at a wavelength of 632.8 nm in the scattering angle range 3°–174° of randomly oriented particles taken ...from seven samples of volcanic ashes corresponding to four different volcanic eruptions: the 18 May 1980 Mount St. Helens eruption, the 1989–1990 Redoubt eruption, and the 18 August and 17 September 1992 Mount Spurr eruptions. The samples were collected at different distances from the vent. The samples studied contain large mass fractions of fine particles and were chosen to represent ash that could remain in the atmosphere for at least hours or days. They include fine ashfall samples that fell at a variety of distances from the volcano and pyroclastic flows that retained their fine fractions. Together, they represent a range of ashes likely to remain in the atmosphere in volcanic clouds following eruptions from convergent plate boundary volcanoes, Earth's most important group of explosive sources of ash. All measured scattering matrix elements are confined to rather limited domains when plotted as functions of the scattering angle following the general trends presented by irregular mineral particles. This similarity in the scattering behavior justifies the construction of an average scattering matrix for volcanic ash particles as a function of the scattering angle. To facilitate the use of the average scattering matrix for multiple‐scattering calculations with polarization included, we present a synthetic scattering matrix based on the average scattering matrix for volcanic ashes and the assumption that the diffraction forward scattering peak is the same for randomly oriented nonspherical particles and projected‐surface‐area‐equivalent spheres. This synthetic scattering matrix is normalized so that the average of its 1‐1 element over all directions equals unity. It is available in the full range from 0° to 180° and can be used, for example, for interpretation of remote‐sensing data after a volcanic eruption when the actual properties of the volcanic ash are not known. The measured results for the Mount St. Helens sample have been compared with results of Lorenz‐Mie calculations for projected‐surface‐area‐equivalent spheres with the refractive index of the Mount St. Helens particles. We find strong differences between measured and calculated values.
This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was ...transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.
The single-scattering properties of Gaussian random spheres are calculated using the discrete dipole approximation. The ensemble of model particles is assumed to be representative for a feldspar dust ...sample that is characteristic for weakly absorbing irregularly shaped mineral aerosol. The morphology of Gaussian random spheres is modeled based on a statistical shape analysis using microscope images of the dust sample. The size distribution of the dust sample is based on a particle sizing experiment. The refractive index of feldspar is estimated using literature values. All input parameters used in the light scattering simulations are thus obtained in an objective way based on the true properties of the mineral sample. The orientation-averaged and ensemble-averaged scattering matrices and cross sections of the Gaussian random spheres are compared with light scattering simulations using spheroidal shape models which have been shown to be applicable to the feldspar sample. The Gaussian random sphere model and the spheroidal shape model are assessed using the measured scattering matrix of the feldspar dust sample as a reference. Generally, the spheroidal model with strongly elongated prolate and strongly flattened oblate shapes agrees better with the measurement than the Gaussian random sphere model. In contrast, some features that are characteristic for light scattering by truly irregular mineral dust particles are rendered best by the Gaussian random sphere model; these features include the flat shape of the phase function and a minimum in the scattering matrix element
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We simulate polarimetric satellite observations of sunlight reflected by a turbid atmosphere over the ocean. We determine the sensitivity of these observations with respect to the optical thickness ...and the single‐scattering albedo of irregular mineral aerosol. Simulated results indicate that both quantities can be retrieved from simultaneous polarization and intensity measurements. Aerosol scattering is modelled using a true measured scattering matrix of irregularly‐shaped mineral dust aerosol. We study the suitability of various approximations of the particle shape used for the numerical calculation of scattering matrices. Approximations with spheres or spheroids with a distribution of moderate axis ratios can lead to large errors of the simulated light intensities. A spheroidal approximation including extreme axis ratios is found to be the most appropriate one for simulations of light scattering by irregular mineral aerosol particles, if measured scattering matrices are not available.
TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch between 2018 and 2021. It will measure atmospheric pollution for greater North America from space using ...ultraviolet and visible spectroscopy. TEMPO observes from Mexico City, Cuba, and the Bahamas to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution (~2.1km N/S×4.4km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry, as well as contributing to carbon cycle knowledge. Measurements are made hourly from geostationary (GEO) orbit, to capture the high variability present in the diurnal cycle of emissions and chemistry that are unobservable from current low-Earth orbit (LEO) satellites that measure once per day. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies.
TEMPO takes advantage of a commercial GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), bromine monoxide (BrO), IO (iodine monoxide), water vapor, aerosols, cloud parameters, ultraviolet radiation, and foliage properties. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides these near-real-time air quality products that will be made publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with the European Sentinel-4 (S4) and Korean Geostationary Environment Monitoring Spectrometer (GEMS) instruments.
•TEMPO is under development to collect geostationary air quality measurements.•TEMPO will measure every hour during daylight over greater North America.•TEMPO will have the spatial resolution to measure sub-urban variability.•The mission’s primary data products include tropospheric ozone and related species.•TEMPO’s time-resolved observations form a revolutionary data set for air quality.
Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally ...implement a simple cloud model based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2–O2) absorption at 477 nm or on the oxygen A-band around 760 nm to determine an effective cloud height. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. Although clouds have significant effects on trace gas retrievals, the current cloud correction schemes are based on a simple cloud model, and the retrieved cloud parameters must be interpreted as effective values. Consequently, it is difficult to assess the accuracy of the cloud correction only based on analysis of the accuracy of the cloud retrievals, and this study focuses solely on the impact of the 3D cloud structures on the trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2–O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows measurements to be identified for which the standard NO2 retrieval produces a significant bias and therefore provides a way to improve the current data flagging approach.
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