Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark‐Target Algorithm: 1. Dust Detection
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In theory, a thermal emission spectrum of Mars (220-1600 cm(exp -1)) contains a wealth of information about the composition and thermal structure of the atmosphere and surface. However, in practice, the ability to retrieve quantitative information from the spectrum is limited by a number of factors including (1) the ill-posed nature of the spectral inversion problem and the resulting nonuniqueness of all solutions; (2) assumptions built into any spectral inversion program; (3) uncertainties in surface pressure, temperature, and emissivity; and (4) uncertainties in the optical properties of atmospheric aerosols. Below, factors (1) and (2) are discussed as fundamental limitations on temperature retrievals from Mariner 9 Infrared Interferometer Spectrometer (IRIS) spectra. In preparation for the Mars Observer mission and the return of tens of thousands of infrared spectra per day from the Thermal Emission Spectrometer (TES), we have developed a fast inversion algorithm to retrieve temperature structure and aerosol opacity from the infrared spectra. The derived atmospheric models will be used to provide the atmospheric contribution to the TES spectra, so that the thermal emission spectra of the underlying surface can be determined for making mineralogical identifications. As a test of our algorithm, we are undertaking a systematic analysis of the entire Mariner 9 Infrared Interferometric Spectrometer (IRIS) dataset of 21,000 plus spectra. While portions of the IRIS dataset have been previously analyzed, the lack of a speedy and robust algorithm to invert the IRIS spectra to retrieve temperature profiles and aerosol opacities has been a major impediment to a truly comprehensive analysis.
The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in assessing the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the direct use of these parameters as input to the OMI (Ozone Monitoring Instrument) near UV retrieval algorithm. A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) CO observations are used in an upgraded version of the OMI near UV aerosol algorithm. AIRS CO measurements are used as a reliable tracer of carbonaceous aerosols, which allows the identification of smoke layers in areas and times of the year where the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of elevated levels of boundary layer pollution undetectable by near UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show a significant improvement in OMI aerosol retrieval capabilities.
The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.
The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct., the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse aerosol particles. The information is more precise over the ocean where we derive also the effective radius and scattering asymmetry parameter of the aerosol. New methods to derive the aerosol single scattering albedo are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. The AErosol RObotic NETwork of ground based radiometers is used for global validation of the satellite derived optical thickness, size parameters and single scattering albedo and measure additional aerosol parameters that cannot be derived from space.
The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct, the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse (mainly natural) aerosol particles. New methods to derive the aerosol absorption of sunlight are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. However MODIS or any present satellite sensor cannot measure absorption by Black Carbon over the oceans, a critical component in studying climate change and human health. For this purpose we propose the COBRA mission that observes the ocean at glint and off glint simultaneously measuring the spectral polarized light and deriving precisely the aerosol absorption.
Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes associated with the aerosol-cloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regional of the world. Contrary to the cloud-free scenario over dark surface, for which aerosols are known to produce a net cooling effect (negative radiative forcing) on climate, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud depends directly on the aerosol loading, microphysical-optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of optical depth of absorbing aerosols above clouds retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA's Aura platform. The presence of absorbing aerosols above cloud reduces the upwelling radiation reflected by cloud and produces a strong 'color ratio' effect in the near-UV region, which can be unambiguously detected in the OMI measurements. Physically based on this effect, the OMACA algorithm retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. The algorithm architecture and results from a ten-year global record including global climatology of frequency of occurrence and above-cloud aerosol optical depth, and a discussion on related future field campaigns are presented.
We present the Plankton, Aerosols, Clouds and Ecosystems Microphysical Aerosol Properties from Polarimetry (PACE-MAPP) polarimetric remote sensing algorithm developed for the newly launched NASA PACE satellite observing system. The objective of PACE-MAPP is to retrieve detailed fine-mode (marine, pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using PACE’s polarimetric-imaging capabilities at multiple angles and wavelengths from the ultraviolet (UV) to the near-infrared (NIR). An additional objective for PACE-MAPP is to discriminate aerosols from thin clouds. The PACE-MAPP polarimetric remote sensing retrieval algorithm uses coupled atmosphere-ocean vector radiative transfer, optimal estimation, artificial intelligence and powerful inherent optical property look-up-tables for the Earth’s aerosol, cloud, and hydrosol particles. PACE-MAPP is the only retrieval algorithm designed to invert aerosol/ocean products using both polarimeters onboard PACE. We present results using PACE-MAPP to retrieve aerosol and ocean remote sensing products from measurements by the Hyper-Angular Rainbow Polarimeter #2 (HARP2) and Spectro-polarimeter for Planetary Exploration one (SPEXone) polarimeter instruments onboard PACE.
After 17 years, the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission ceased science operations in August 2023. For the final CALIPSO data products release (Version 5), the CALIPSO project seeks to improve the accuracy of its aerosol extinction by advancing knowledge of aerosol lidar ratios (i.e., extinction-to-backscatter ratios; LRs) for various aerosol types. The current algorithm assigns one LR value globally for each of the seven tropospheric aerosol types. The CALIPSO team aims to improve the retrieval algorithm through the development of regional and seasonal LR climatologies for the same aerosol types. In this study, aerosol LRs are inferred through Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscatter profiles constrained by collocated aerosol optical depth (AOD) from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data over oceans during daytime. This analysis is subsampled for those profiles that are cloud-free and contain only one CALIOP-classified aerosol type. The CALIOP profiles are then collocated with aerosol volume fractions obtained through Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulations. This presentation will reveal findings that the 12-year (June 2006-August 2018) mean spatial distributions of inferred aerosol LRs for CALIOP-classified marine and dusty marine aerosols correspond inversely with patterns of GOCART sea salt volume fraction (SSVF). For example, smaller SSVFs (< 65%) and larger LRs (> 55 sr), are found near land masses (Fig. 1). This indicates the influence of advected anthropogenic aerosols (e.g., pollution and biomass burning smoke). In the remote oceans (i.e., regions likely less impacted by non-sea salt aerosols), the SSVFs are larger (> 95%) and the LRs are smaller (< 25 sr) (Fig. 1). A polynomial fit of the MODIS AOD constrained LRs to the corresponding GOCART SSVFs (intersect values of ~58 sr for SSVF of 0% and ~21 sr for SSVF of 100%) is further used to produce model-assisted climatological LR maps on seasonal scales. Additionally, we will show results of a LR validation analysis for which we compare the revised CALIPSO AODs obtained by applying the seasonal/regional constrained LRs against CALIPSO Version 4.51 Ocean Derived Column Optical Depth (ODCOD). While the majority of the presentation will focus on LRs for CALIOP-classified marine and dusty marine aerosols, an overview of LR results will show preliminary results for other aerosol types over ocean, such as dust and elevated smoke. The technique demon-strated in this study highlights the benefits not only to the final planned CALIPSO data release in 2025, but similar methods can be applied to future spaceborne elastic backscatter lidars with collocated passive sensors (e.g., such as those associated with NASA’s proposed Atmosphere Observing System).
The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.
Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).
Based on the fact that the part of downward radiance that depends on the optical properties of the aerosol in the atmosphere can be extracted from the measured sky radiance, a new scheme for retrieval of the aerosol phase function and the single-scattering albedo over the ocean is developed. This retrieval algorithm is tested with simulations for several cases. It is found that the retrieved aerosol phase function and the single-scattering albedo are virtually error-free if the vertical structure of the atmosphere is known and if the sky radiance and the aerosol optical thickness can be measured accurately. The robustness of the algorithm in realistic situations, in which the measurements are contaminated by calibration errors or noise, is examined. It is found that the retrieved value of omega(0) is usually in error by less than about 10 percent, and the phase function is accurately retrieved for theta less than about 90 deg. However, as the aerosol optical thickness becomes small, e.g., less than about 0.1, errors in the sky radiance measurement can lead to serious problems with the retrieval algorithm, especially in the blue. The use of the retrieval scheme should be limited to the red and near IR when the aerosol optical thickness is small.
Models that assess aerosol effects on regional air quality and global climate parameterize aerosol sources in terms of amount, type, and injection height. The multiangle imaging spectroradiometer (MISR) aboard NASA's Terra satellite retrieves total column aerosol optical thickness (AOT), and aerosol type over cloud-free land and water. A stereo-matching algorithm automatically retrieves reflecting-layer altitude wherever clouds or aerosol plumes have discernable spatial contrast, with about 500-m accuracy, at 1.1-km horizontal resolution. Near-source biomass burning smoke, volcanic effluent, and desert dust plumes are observed routinely, providing information about aerosol amount, particle type, and injection height useful for modeling applications. Compared to background aerosols, the plumes sampled have higher AOT, contain particles having expected differences in Angstrom exponent, size, single-scattering albedo, and for volcanic plume and dust cloud cases, particle shape. As basic thermodynamics predicts, thin aerosol plumes lifted only by regional winds or less intense heat sources are confined to the boundary layer. However, when sources have sufficient buoyancy, the representative plumes studied tend to concentrate within discrete, high-elevation layers of local stability; the aerosol is not uniformly distributed up to a peak altitude, as is sometimes assumed in modeling. MISR-derived plume heights, along with meteorological profile data from other sources, make it possible to relate radiant energy flux observed by the moderate resolution imaging spectroradiometer (MODIS), also aboard the Terra spacecraft, to convective heat flux that plays a major role in buoyant plume dynamics. A MISR climatology of plume behavior based on these results is being developed.
The Total Ozone Mapping Spectrometer (TOMS) aerosol algorithm uses measurements of radiances at two near UV channels in the range 331-380 nm to derive aerosol optical depth and single scattering albedo. Because of the low near UV surface albedo of all terrestrial surfaces (between 0.02 and 0.08), the TOMS algorithm has the capability of retrieving aerosol properties over the oceans and the continents. The Aerosol Robotic Network (AERONET) routinely derives spectral aerosol optical depth and single scattering albedo at a large number of sites around the globe. We have performed comparisons of both aerosol optical depth and single scattering albedo derived from TOMS and AERONET. In general, the TOMS aerosol products agree well with the ground-based observations, Results of this validation will be discussed.
The presence of absorbing aerosol layers above clouds is unambiguously detected by the TOMS/OMI UV Aerosol Index (AI) that uses satellite observations at two near-UV channels. A sensitivity study using radiative transfer calculations shows that the AI signal of resulting from the presence of aerosols above clouds is mainly driven by the aerosol absorption optical depth and the optical depth of the underlying cloud. Based on these results, an inversion algorithm has been developed to retrieve the aerosol optical depth (AOD) of aerosol layers above clouds. In this presentation we will discuss the sensitivity analysis, describe the retrieval approach, and present results of applications of the retrieval method to OMI observations over the South Atlantic Ocean. Preliminary error analyses, to be discussed, indicate that the AOD can be underestimated (up to -30%) or overestimated (up to 60%) depending on algorithmic assumptions.
Among the many components contributing to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative forcing effect on the weather/climate system. As much as one-third to half of the global dust emissions, estimated about 800 Tg, are introduced annually into Earth's atmosphere from various deserts in China. Asian dust storm outbreaks are believed to have persisted for hundreds and thousands years over the vast territory of north and northwest China, but not until recent decades that many studies reveal the compelling evidence in recognizing the importance of these eolian dust particles for forming Chinese Loess Plateau and for biogeochemical cycling in the North Pacific Ocean to as far as in the Greenland ice-sheets through long-range transport. The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites and its evolution monitored by satellite and surface network. In this paper, we will demonstrate the capability of a new satellite algorithm, called Deep Blue, to retrieve aerosol properties, particularly but not limited to, over bright-reflecting surfaces such as urban areas and deserts. Recently, many field campaigns were designed and executed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. We will provide an overview of the outbreak of Asian dust storms, near source/sink and their evolution along transport pathway, from space and surface observations. The climatic effects and societal impacts of the Asian dusts will be addressed in depth. (to be presented in the International Workshop on Semi-Arid Land Surface-
With their extensive coverage, low clouds greatly impact global climate. Presently, low clouds are poorly represented in global climate models (GCMs), and the response of low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The poor representations of low clouds in GCMs are in part due to inadequate observations of their microphysical and macrophysical structures, radiative effects, and the associated aerosol distribution and budget in regions where the aerosol impact is the greatest. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer (MBL) clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. Boundary-layer aerosol in the ENA region is influenced by a variety of sources, leading to strong variations in cloud condensation nuclei (CCN) concentration and aerosol optical properties. A permanent ENA site was established by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility on Graciosa Island in the Azores, providing invaluable information on MBL aerosol and low clouds. At the same time, the vertical structures and horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol, the radiative properties, precipitation efficiency, and lifecycle of MBL clouds, and the cloud response to aerosol perturbations. Much of this data can be obtained only through aircraft-based measurements. In addition, the interconnected aerosol and cloud processes are best investigated by a study involving simultaneous in situ aerosol, cloud, and thermodynamics measurements. Furthermore, in situ measurements are also necessary for validating and improving ground-based retrieval algorithms at the ENA site. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) project was motivated by the need for comprehensive in situ characterizations of boundary-layer structure, and associated vertical distributions and horizontal variabilities of low clouds and aerosol over the Azores. The ARM Aerial Facility (AAF) Gulfstream-1 (G-1) aircraft was deployed during two intensive measurement periods (IOPs). The first deployment took place from June 21 to July 20, 2017, and the second one took place from January 15 to February 18, 2018. Flights were carried out in the Azores, near the ARM ENA site on Graciosa Island. Deployments during both seasons allow for examination of key aerosol and cloud processes under a variety of representative meteorological and cloud conditions. The science themes for the deployments include: (1) Budget of MBL CCN and its seasonal variation; (2) Effects of aerosol on cloud and precipitation; (3) Cloud microphysical and macrophysical structures, and entrainment mixing; (4) Advancing retrievals of turbulence, cloud, and drizzle; and (5) Model evaluation and processes studies.