331 research outputs found

    Global Aerosol Optical Models and Lookup Tables for the New MODIS Aerosol Retrieval over Land

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    Since 2000, MODIS has been deriving aerosol properties over land from MODIS observed spectral reflectance, by matching the observed reflectance with that simulated for selected aerosol optical models, aerosol loadings, wavelengths and geometrical conditions (that are contained in a lookup table or 'LUT'). Validation exercises have showed that MODIS tends to under-predict aerosol optical depth (tau) in cases of large tau (tau greater than 1.0), signaling errors in the assumed aerosol optical properties. Using the climatology of almucantur retrievals from the hundreds of global AERONET sunphotometer sites, we found that three spherical-derived models (describing fine-sized dominated aerosol), and one spheroid-derived model (describing coarse-sized dominated aerosol, presumably dust) generally described the range of observed global aerosol properties. The fine dominated models were separated mainly by their single scattering albedo (omega(sub 0)), ranging from non-absorbing aerosol (omega(sub 0) approx. 0.95) in developed urban/industrial regions, to neutrally absorbing aerosol (omega(sub 0) approx.90) in forest fire burning and developing industrial regions, to absorbing aerosol (omega(sub 0) approx. 0.85) in regions of savanna/grassland burning. We determined the dominant model type in each region and season, to create a 1 deg. x 1 deg. grid of assumed aerosol type. We used vector radiative transfer code to create a new LUT, simulating the four aerosol models, in four MODIS channels. Independent AERONET observations of spectral tau agree with the new models, indicating that the new models are suitable for use by the MODIS aerosol retrieval

    Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

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    The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO₂) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) X_(CO₂) retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O₂ A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO₂ and H₂O column abundances using observations taken at 1.61 µm (weak CO₂ band) and 2.06 µm (strong CO₂ band), while neglecting atmospheric scattering. The CO₂ and H₂O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of  ≃ 20–25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be  ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April–May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1

    Influence of aerosols, clouds, and sunglint on polarization spectra of Earthshine

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    Ground-based observations of the Earthshine, i.e., the light scattered by Earth to the Moon, and then reflected back to Earth, simulate space observations of our planet and represent a powerful benchmark for the studies of Earth-like planets. Earthshine spectra are strongly linearly polarized, owing to scattering by molecules and small particles in the atmosphere of the Earth and surface reflection, and may allow us to measure global atmospheric and surface properties of planet Earth. Aims. We aim to interpret already published spectropolarimetric observations of the Earthshine by comparing them with new radiative transfer model simulations including a fully realistic three-dimensional (3D) surface-atmosphere model for planet Earth. We used the highly advanced Monte Carlo radiative transfer model MYSTIC to simulate polarized radiative transfer in the atmosphere of the Earth without approximations regarding the geometry, taking into account the polarization from surface reflection and multiple scattering by molecules, aerosol particles, cloud droplets, and ice crystals. We have shown that Earth spectropolarimetry is highly sensitive to all these input parameters, and we have presented simulations of a fully realistic Earth atmosphere-surface model including 3D cloud fields and two-dimensional (2D) surface property maps. Our modeling results show that scattering in high ice water clouds and reflection from the ocean surface are crucial to explain the continuum polarization at longer wavelengths as has been reported in Earthshine observations taken at the Very Large Telescope in 2011 (3.8 % and 6.6 % at 800 nm, depending on which part of Earth was visible from the Moon at the time of the observations). We found that the relatively high degree of polarization of 6.6 % can be attributed to light reflected by the ocean surface in the sunglint region

    Passive remote sensing of tropospheric aerosol and atmospheric correction for the aerosol effect

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    The launch of ADEOS in August 1996 with POLDER, TOMS, and OCTS instruments on board and the future launch of EOS-AM 1 in mid-1998 with MODIS and MISR instruments on board start a new era in remote sensing of aerosol as part of a new remote sensing of the whole Earth system (see a list of the acronyms in the Notation section of the paper). These platforms will be followed by other international platforms with unique aerosol sensing capability, some still in this century (e.g., ENVISAT in 1999). These international spaceborne multispectral, multiangular, and polarization measurements, combined for the first time with international automatic, routine monitoring of aerosol from the ground, are expected to form a quantum leap in our ability to observe the highly variable global aerosol. This new capability is contrasted with present single-channel techniques for AVHRR, Meteosat, and GOES that although poorly calibrated and poorly characterized already generated important aerosol global maps and regional transport assessments. The new data will improve significantly atmospheric corrections for the aerosol effect on remote sensing of the oceans and be used to generate first real-time atmospheric corrections over the land. This special issue summarizes the science behind this change in remote sensing, and the sensitivity studies and applications of the new algorithms to data from present satellite and aircraft instruments. Background information and a summary of a critical discussion that took place in a workshop devoted to this topic is given in this introductory paper. In the discussion it was concluded that the anticipated remote sensing of aerosol simultaneously from several space platforms with different observation strategies, together with continuous validations around the world, is expected to be of significant importance to test remote sensing approaches to characterize the complex and highly variable aerosol field. So far, we have only partial understanding of the information content and accuracy of the radiative transfer inversion of aerosol information from the satellite data, due to lack of sufficient theoretical analysis and applications to proper field data. This limitation will make the anticipated new data even more interesting and challenging. A main concern is the present inadequate ability to sense aerosol absorption, from space or from the ground. Absorption is a critical parameter for climate studies and atmospheric corrections. Over oceans, main concerns are the effects of white caps and dust on the correction scheme. Future improvement in aerosol retrieval and atmospheric corrections will require better climatology of the aerosol properties and understanding of the effects of mixed composition and shape of the particles. The main ingredient missing in the planned remote sensing of aerosol are spaceborne and ground-based lidar observations of the aerosol profiles

    Analysis of Visible/SWIR surface reflectance ratios for aerosol retrievals from satellite in Mexico City urban area

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    International audienceThe surface reflectance ratio between the visible (VIS) and shortwave infrared (SWIR) radiation is an important quantity for the retrieval of the aerosol optical depth (?a) from the MODIS sensor data. Based on empirically determined VIS/SWIR ratios, MODIS ?a retrieval uses the surface reflectance in the SWIR band (2.1 µm), where the interaction between solar radiation and the aerosol layer is small, to predict the visible reflectances in the blue (0.47 µm) and red (0.66 µm) bands. Therefore, accurate knowledge of the VIS/SWIR ratio is essential for achieving accurate retrieval of aerosol optical depth from MODIS. We analyzed the surface reflectance over some distinct surface covers in and around the Mexico City metropolitan area (MCMA) using MODIS radiances at 0.66 µm and 2.1 µm. The analysis was performed at 1.5 km×1.5 km spatial resolution. Also, ground-based AERONET sun-photometer data acquired in Mexico City from 2002 to 2005 were analyzed for aerosol depth and other aerosol optical properties. In addition, a network of hand-held sun-photometers deployed in Mexico City, as part of the MCMA-2006 Study during the MILAGRO Campaign, provided an unprecedented measurement of ?a in 5 different sites well distributed in the city. We found that the average RED/SWIR ratio representative of the urbanized sites analyzed is 0.73±0.06 for scattering angles a averaged from sun-photometer measurements. The use of the new RED/SWIR ratio of 0.73 in the MODIS retrieval over Mexico City led to a significant improvement in the agreement between the MODIS and sun-photometer AOD results; with the slope, offset, and the correlation coefficient of the linear regression changing from (?aMODIS=0.91?a sun-photometer+0.33, R2=0.66) to (?aMODIS=0.96 ?a sun-photometer?0.006, R2=0.87). Indeed, an underestimation of this ratio in urban areas lead to a significant overestimation of the AOD retrieved from satellite. Therefore, we strongly encourage similar analyses in other urban areas to enhance the development of a parameterization of the surface ratios accounting for urban heterogeneities

    Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors

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    When retrieving Aerosol Optical Depth (AOD) from passive satellite sensors, the vertical distribution of aerosols usually needs to be assumed, potentially causing uncertainties in the retrievals. In this study, we use the Moderate Resolution Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors as examples to investigate the impact of aerosol vertical distribution on AOD retrievals. A series of sensitivity experiments was conducted using radiative transfer models with different aerosol profiles and surface conditions. Assuming a 0.2 AOD, we found that the AOD retrieval error is the most sensitive to the vertical distribution of absorbing aerosols; a −1 km error in aerosol scale height can lead to a ~30% AOD retrieval error. Moreover, for this aerosol type, ignoring the existence of the boundary layer can further result in a ~10% AOD retrieval error. The differences in the vertical distribution of scattering and absorbing aerosols within the same column may also cause −15% (scattering aerosols above absorbing aerosols) to 15% (scattering aerosols below absorbing aerosols) errors. Surface reflectance also plays an important role in affecting the AOD retrieval error, with higher errors over brighter surfaces in general. The physical mechanism associated with the AOD retrieval errors is also discussed. Finally, by replacing the default exponential profile with the observed aerosol vertical profile by a micro-pulse lidar at the Beijing-PKU site in the VIIRS retrieval algorithm, the retrieved AOD shows a much better agreement with surface observations, with the correlation coefficient increased from 0.63 to 0.83 and bias decreased from 0.15 to 0.03. Our study highlights the importance of aerosol vertical profile assumption in satellite AOD retrievals, and indicates that considering more realistic profiles can help reduce the uncertainties

    Validation of MODIS derived aerosol optical depth over Western India

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    MODIS (Moderate Resolution Imaging Spectroradiometer) derived aerosol optical depths (AODs) were compared against the ground based observations from Microtops sunphotometer over Ahmedabad (72.5°E, 23.03°N) in Western India. The region is semiarid and poses challenge for the satellite remote sensing of aerosols. Besides comparing the ground truth with the Collection Version 4 of MODIS aerosol product, the paper reports the first ever validation of the updated Collection Version 5 of the MODIS aerosol product over India. The AOD data from Aqua platform is averaged over 0.5° × 0.5° centered at Ahmedabad and compared with the sunphotometer observation taken within half an hour to the satellite overpass time. The Version 4 data comparison showed a large scatter. Further, the comparison for 470 nm and 660 nm behave differently over different years. Overall, the comparison shows considerable improvement in the Collection Version 5 aerosol product. Among seasons, Pre-Monsoon (April to May) has the best correlation and Dry season (December to March) the least. The updated product has scope for further improvement as the correlations are less than unity, and the extent of underestimation for 470 nm is more during Dry and Post-Monsoon seasons whereas that for 660 nm is more during Pre-Monsoon and Monsoon seasons which are dominated by fine and coarse particles respectively. The results show a better surface reflectance parameterization by the MODIS Collection Version 5 algorithm as compared to Version 4 but the aerosol model used in the retrieval algorithm is still not adequate

    Evaluating The Impact Of Above-Cloud Aerosols On Cloud Optical Depth Retrievals From Modis

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    Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (visible and shortwave infrared), the impacts of above-cloud absorbing aerosols on the standard COD retrievals are evaluated. For fine-mode aerosol particles, aerosol optical depth (AOD) values diminish sharply from the visible to the shortwave infrared channels. Thus, a suppressed above-cloud particle radiance aliasing effect occurs for COD retrievals using shortwave infrared channels. Aerosol Index (AI) from the spatially and temporally collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African sub-continent. MODIS and OMI Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to constrain cloud phase and provide contextual above-cloud AOD values. The frequency of occurrence of above-cloud aerosols is depicted on a global scale for the spring and summer seasons from OMI and CALIOP, thus indicating the significance of the problem. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10–20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1.0. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS visible and shortwave in channels are vulnerable to dust particle aliasing, and thus a COD impact cannot be isolated with this method. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above–cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS shortwave infrared COD products

    Retrievals of atmospheric CO_2 from simulated space-borne measurements of backscattered near-infrared sunlight: accounting for aerosol effects

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    Retrievals of atmospheric carbon dioxide (CO_2) from space-borne measurements of backscattered near-infrared sunlight are hampered by aerosol and cirrus cloud scattering effects. We propose a retrieval approach that allows for the retrieval of a few effective aerosol parameters simultaneously with the CO_2 total column by parameterizing particle amount, height distribution, and microphysical properties. Two implementations of the proposed method covering different spectral bands are tested for an ensemble of simulated nadir observations for aerosol (and cirrus) loaded scenes over low- and mid-latitudinal land surfaces. The residual aerosol-induced CO_2 errors are mostly below 1% up to aerosol optical thickness 0.5. The proposed methods also perform convincing for scenes where cirrus clouds of optical thickness 0.1 overlay the aerosol

    Urban Visible/SWIR surface reflectance ratios from satellite and sun photometer measurements in Mexico City

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    International audienceThe surface reflectance ratio between the visible (VIS) and shortwave infrared (SWIR) radiation is an important quantity for the retrieval of the aerosol optical depth (?a) from the MODIS sensor data. Based on empirically determined VIS/SWIR ratios, MODIS ?a retrieval uses the surface reflectance in the SWIR band (2.1 ?m), where the interaction between solar radiation and the aerosol layer is small, to predict the visible reflectances in the blue (0.47 ?m) and red (0.66 ?m) bands. Therefore, accurate knowledge of the VIS/SWIR ratio is essential for achieving accurate retrieval of aerosol optical depth from MODIS. The heterogeneity of the surface cover in an urban environment increases the uncertainties in the estimation of the surface reflectance and, consequently, ?a. We analyzed the surface reflectance over some distinct surface covers in and around the Mexico City metropolitan area (MCMA) using MODIS radiances at 0.66 ?m and 2.1 ?m. The analysis was performed at 1.5 km×1.5 km spatial resolution. Also, ground-based AERONET sun-photometer data acquired in Mexico City from 2002 to 2005 were analyzed for aerosol optical thickness and other aerosol optical properties. In addition, a network of hand-held sun-photometers deployed in Mexico City, as part of the MCMA-2006 Study during the MILAGRO Campaign, provided an unprecedented measurement of ?a in 5 different sites well distributed in the city. We found that the average RED/SWIR ratio representative of the urbanized sites analyzed is 0.73±0.06. This average ratio was significantly different for non-urban sites, which was approximately 0.55. The aerosol optical thickness retrieved from MODIS radiances at a spatial resolution of 1.5 km×1.5 km and averaged within 10 x 10 km boxes were compared with collocated 1-h ?a averaged from sun-photometer measurements. The use of the new RED/SWIR ratio of 0.73 in the MODIS retrieval led to a significant improvement in the agreement between the MODIS and sun-photometer results; with the slope, offset, and the correlation coefficient of the linear regression changing from (?aMODIS = 0.91 ?a sun-photometer + 0.33 ,R2=0.66) to (?aMODIS = 0.96 ?a sun-photometer ?0.006, R2=0.87)
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