Validation and Uncertainty Estimates for MODIS Collection 6 "Deep Blue" Aerosol Data

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.

2013-01-01

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.

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Holben, Brent; Eck, Thomas F.; Li, Zhengqiang; Song, Chul H.

2018-01-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 τG has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD τA from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (τG - τA) is within -0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.

Comparison of a single-view and a double-view aerosol optical depth retrieval algorithm

NASA Astrophysics Data System (ADS)

Henderson, Bradley G.; Chylek, Petr

2003-11-01

We compare the results of a single-view and a double-view aerosol optical depth (AOD) retrieval algorithm applied to image pairs acquired over NASA Stennis Space Center, Mississippi. The image data were acquired by the Department of Energy's (DOE) Multispectral Thermal Imager (MTI), a pushbroom satellite imager with 15 bands from the visible to the thermal infrared. MTI has the ability to acquire imagery in pairs in which the first image is a near-nadir view and the second image is off-nadir with a zenith angle of approximately 60°. A total of 15 image pairs were used in the analysis. For a given image pair, AOD retrieval is performed twice---once using a single-view algorithm applied to the near-nadir image, then again using a double-view algorithm. Errors for both retrievals are computed by comparing the results to AERONET AOD measurements obtained at the same time and place. The single-view algorithm showed an RMS error about the mean of 0.076 in AOD units, whereas the double-view algorithm showed a modest improvement with an RMS error of 0.06. The single-view errors show a positive bias which is presumed to be a result of the empirical relationship used to determine ground reflectance in the visible. A plot of AOD error of the double-view algorithm versus time shows a noticeable trend which is interpreted to be a calibration drift. When this trend is removed, the RMS error of the double-view algorithm drops to 0.030. The single-view algorithm qualitatively appears to perform better during the spring and summer whereas the double-view algorithm seems to be less sensitive to season.

GOCI Yonsei aerosol retrieval version 2 aerosol products: improved algorithm description and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; KIM, M.; Park, Y. J.; Holben, B. N.; Eck, T. F.; Li, Z.; Song, C. H.

2017-12-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed for retrieving hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD showed comparable accuracy compared to ground-based and other satellite-based observations, but still had errors due to uncertainties in surface reflectance and simple cloud masking. Also, it was not capable of near-real-time (NRT) processing because it required a monthly database of each year encompassing the day of retrieval for the determination of surface reflectance. This study describes the improvement of GOCI YAER algorithm to the version 2 (V2) for NRT processing with improved accuracy from the modification of cloud masking, surface reflectance determination using multi-year Rayleigh corrected reflectance and wind speed database, and inversion channels per surface conditions. Therefore, the improved GOCI AOD ( ) is similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD compared to V1 of the YAER algorithm. The shows reduced median bias and increased ratio within range (i.e. absolute expected error range of MODIS AOD) compared to V1 in the validation results using Aerosol Robotic Network (AERONET) AOD ( ) from 2011 to 2016. The validation using the Sun-Sky Radiometer Observation Network (SONET) over China also shows similar results. The bias of error ( is within -0.1 and 0.1 range as a function of AERONET AOD and AE, scattering angle, NDVI, cloud fraction and homogeneity of retrieved AOD, observation time, month, and year. Also, the diagnostic and prognostic expected error (DEE and PEE, respectively) of are estimated. The estimated multiple PEE of GOCI V2 AOD is well matched with actual error over East Asia, and the GOCI V2 AOD over Korea shows higher ratio within PEE compared to over China and Japan. Hourly AOD products based on the improved GOCI YAER AOD could contribute to better understandings of aerosols in terms of long-term climate changes and short-term air quality monitoring and forecasting perspectives over East Asia, especially rapid diurnal variation and transboundary transport.

Improvement of Aerosol Optical Depth Retrieval from MODIS Spectral Reflectance over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database

NASA Technical Reports Server (NTRS)

Lee, J.; Kim, J.; Yang, P.; Hsu, N. C.

2012-01-01

New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.

Aerosol Airmass Type Mapping Over the Urban Mexico City Region From Space-based Multi-angle Imaging

NASA Technical Reports Server (NTRS)

Patadia, F.; Kahn, R. A.; Limbacher, J. A.; Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.

2013-01-01

Using Multi-angle Imaging SpectroRadiometer (MISR) and sub-orbital measurements from the 2006 INTEX-B/MILAGRO field campaign, in this study we explore MISR's ability to map different aerosol air mass types over the Mexico City metropolitan area. The aerosol air mass distinctions are based on shape, size and single scattering albedo retrievals from the MISR Research Aerosol Retrieval algorithm. In this region, the research algorithm identifies dust-dominated aerosol mixtures based on non-spherical particle shape, whereas spherical biomass burning and urban pollution particles are distinguished by particle size. Two distinct aerosol air mass types based on retrieved particle microphysical properties, and four spatially distributed aerosol air masses, are identified in the MISR data on 6 March 2006. The aerosol air mass type identification results are supported by coincident, airborne high-spectral-resolution lidar (HSRL) measurements. Aerosol optical depth (AOD) gradients are also consistent between the MISR and sub-orbital measurements, but particles having single-scattering albedo of approx. 0.7 at 558 nm must be included in the retrieval algorithm to produce good absolute AOD comparisons over pollution-dominated aerosol air masses. The MISR standard V22 AOD product, at 17.6 km resolution, captures the observed AOD gradients qualitatively, but retrievals at this coarse spatial scale and with limited spherical absorbing particle options underestimate AOD and do not retrieve particle properties adequately over this complex urban region. However, we demonstrate how AOD and aerosol type mapping can be accomplished with MISR data over complex urban regions, provided the retrieval is performed at sufficiently high spatial resolution, and with a rich enough set of aerosol components and mixtures.

Evaluation of MODIS aerosol optical depth for semi­-arid environments in complex terrain

NASA Astrophysics Data System (ADS)

Holmes, H.; Loria Salazar, S. M.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2015-12-01

The use of satellite remote sensing to estimate spatially resolved ground level air pollutant concentrations is increasing due to advancements in remote sensing technology and the limited number of surface observations. Satellite retrievals provide global, spatiotemporal air quality information and are used to track plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Ground level PM2.5 concentrations can be estimated using columnar aerosol optical depth (AOD) from MODIS, where the satellite retrieval serves as a spatial surrogate to simulate surface PM2.5 gradients. The spatial statistical models and MODIS AOD retrieval algorithms have been evaluated for the dark, vegetated eastern US, while the semi-arid western US continues to be an understudied region with associated complexity due to heterogeneous emissions, smoke from wildfires, and complex terrain. The objective of this work is to evaluate the uncertainty of MODIS AOD retrievals by comparing with columnar AOD and surface PM2.5 measurements from AERONET and EPA networks. Data is analyzed from multiple stations in California and Nevada for three years where four major wildfires occurred. Results indicate that MODIS retrievals fail to estimate column-integrated aerosol pollution in the summer months. This is further investigated by quantifying the statistical relationships between MODIS AOD, AERONET AOD, and surface PM2.5 concentrations. Data analysis indicates that the distribution of MODIS AOD is significantly (p<0.05) different than AERONET AOD. Further, using the results of distributional and association analysis the impacts of MODIS AOD uncertainties on the spatial gradients are evaluated. Additionally, the relationships between these uncertainties and physical parameters in the retrieval algorithm (e.g., surface reflectance, Ångström Extinction Exponent) are discussed.

Validation of new satellite aerosol optical depth retrieval algorithm using Raman lidar observations at radiative transfer laboratory in Warsaw

NASA Astrophysics Data System (ADS)

Zawadzka, Olga; Stachlewska, Iwona S.; Markowicz, Krzysztof M.; Nemuc, Anca; Stebel, Kerstin

2018-04-01

During an exceptionally warm September of 2016, the unique, stable weather conditions over Poland allowed for an extensive testing of the new algorithm developed to improve the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) aerosol optical depth (AOD) retrieval. The development was conducted in the frame of the ESA-ESRIN SAMIRA project. The new AOD algorithm aims at providing the aerosol optical depth maps over the territory of Poland with a high temporal resolution of 15 minutes. It was tested on the data set obtained between 11-16 September 2016, during which a day of relatively clean atmospheric background related to an Arctic airmass inflow was surrounded by a few days with well increased aerosol load of different origin. On the clean reference day, for estimating surface reflectance the AOD forecast available on-line via the Copernicus Atmosphere Monitoring Service (CAMS) was used. The obtained AOD maps were validated against AODs available within the Poland-AOD and AERONET networks, and with AOD values obtained from the PollyXT-UW lidar. of the University of Warsaw (UW).

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-10-01

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-07-01

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångstrom Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ∼ 0.025), while reducing the differences between AE. We characterize algorithm retrievibility through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Remote sensing measurements of biomass burning aerosol optical properties during the 2015 Indonesian burning season from AERONET and MODIS satellite data

NASA Astrophysics Data System (ADS)

2016-04-01

The strong El Nino event in 2015 resulted in below normal rainfall leading to very dry conditions throughout Indonesia from August though October 2015. These conditions in turn allowed for exceptionally large numbers of biomass burning fires with very high emissions of aerosols. Over the island of Borneo, three AERONET sites (Palangkaraya, Pontianak, and Kuching) measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in September and October ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain any significant signal in the mid-visible wavelengths, therefore a previously developed new algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the red and near-infrared wavelengths (675, 870, 1020, and 1640 nm) as possible to analyze the AOD in those wavelengths. These AOD at longer wavelengths are then utilized to provide some estimate the AOD in the mid-visible. Additionally, satellite retrievals of AOD at 550 nm from MODIS sensor data and the Dark Target, Beep Blue, and MAIAC algorithms were also analyzed and compared to AERONET measured AOD. Not surprisingly, the AOD was often too high for the satellite algorithms to also measure accurate AOD on many days in the densest smoke regions. The AERONET sky radiance inversion algorithm was utilized to analyze retrievals of the aerosol optical properties of complex refractive indices and size distributions. Since the AOD was often extremely high there was sometimes insufficient direct sun signal for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, the new hybrid sky radiance scan can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for many more retrievals and also at higher AOD levels during this event. Due to extreme dryness occurring in the region, significant biomass burning of peat soils occurred in some areas. The retrieved volume median radius of the fine mode increased from ~0.18 micron to ~0.25 micron as AOD increased from 1 to 3 at 440 nm. These are very large size particles for biomass burning aerosol and are similar in size to smoke particles measured in Alaska during the very dry years of 2004 and 2005 when peat soil burning also contributed to the fuel burned. The average single scattering albedo over the wavelength range of 440 to 1020 nm was very high ranging from ~0.96 to 0.98, indicative of dominant smoldering phase combustion. These very high values of single scattering albedo for biomass burning aerosols are similar to those retrieved by AERONET for the Alaska smoke in 2004 and 2005.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; Kim, M.; Park, Y. Je; Jeong, U.; Kim, W.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.

2015-09-01

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1-3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD - 0.041. GOCI and MODIS AODs are more highly correlated over ocean than land. Over land, especially, GOCI AOD shows better agreement with MODIS DB than MODIS DT because of the choice of surface reflectance assumptions. Other GOCI YAER products show lower correlation with AERONET than AOD, but are still qualitatively useful.

MODIS Aerosol Optical Depth retrieval over land considering surface BRDF effects

NASA Astrophysics Data System (ADS)

Wu, Yerong; de Graaf, Martin; Menenti, Massimo

2016-04-01

Aerosols in the atmosphere play an important role in the climate system and human health. Retrieval from satellite data, Aerosol Optical Depth (AOD), one of most important indices of aerosol optical properties, has been extensively investigated. Benefiting from the high resolution at spatial and temporal and the maturity of the aerosol retrieval algorithm, MOderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOD product has been extensively applied in other scientific research such as climate change and air pollution. The latest product - MODIS Collection 6 Dark Target AOD (C6_DT) has been released. However, the accuracy of C6_DT AOD (global mean ±0.03) over land is still too low for the constraint on radiative forcing in the climate system, where the uncertainty should be reduced to ±0.02. The major uncertainty mainly lies on the underestimation/overestimation of the surface contribution to the Top Of Atmosphere (TOA) radiance since a lambertian surface is assumed in the C6_DT land algorithm. In the real world, it requires considering the heterogeneity of the surface reflection in the radiative transfer process. Based on this, we developed a new algorithm to retrieve AOD by considering surface Bidirectional Reflectance Distribution Function (BRDF) effects. The surface BRDF is much more complicated than isotropic reflection, described as 4 elements: directional-directional, directional-hemispherical, hemispherical-directional and hemispherical-hemispherical reflectance, and coupled into radiative transfer equation to generate an accurate top of atmosphere reflectance. The limited MODIS measurements (three channels available) allow us to retrieve only three parameters, which including AOD, the surface directional-directional reflectance and fine aerosol ratio η. The other three elements of the surface reflectance are expected to be constrained by ancillary data and assumptions or "a priori" information since there are more unknowns than MODIS measurements in our algorithm. We validated three case studies with AErosol Robotic NETwork (AERONET) AOD, and the results show that the AOD retrieval was improved compared to C6_DT AOD, with the increase of within expected accuracy ±(0.05 + 15%) by ranging from 2.7% to 7.5% for the best quality only (Quality Assurance =3), and from 5.8% to 9.5% for the marginal and better quality (Quality Assurance ≥ 1).

Validation of MODIS aerosol optical depth product over China using CARSNET measurements

NASA Astrophysics Data System (ADS)

Xie, Yong; Zhang, Yan; Xiong, Xiaoxiong; Qu, John J.; Che, Huizheng

2011-10-01

This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km 2) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005-2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6-30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial-temporal collocation and instrument calibration are discussed briefly.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.; Song, Chul H.; Lim, Jae-Hyun; Song, Chang-Keun

2016-04-01

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

NASA Technical Reports Server (NTRS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.;

Statistical intercomparison and validation of multisensory aerosol optical depth retrievals over three AERONET sites in Kenya, East Africa

NASA Astrophysics Data System (ADS)

Boiyo, Richard; Kumar, K. Raghavendra; Zhao, Tianliang

2017-11-01

Over the last two decades, a number of space-borne sensors have been used to retrieve aerosol optical depth (AOD). The reliability of these datasets over East Africa (EA), however, is an important issue in the interpretation of regional aerosol variability. This study provides an intercomparison and validation of AOD retrievals from the MODIS-Terra (DT and DB), MISR and OMI sensors against ground-based measurements from the AERONET over three sites (CRPSM_Malindi, Nairobi, and ICIPE_Mbita) in Kenya, EA during the periods 2008-2013, 2005-2009 and 2006-2015, respectively. The analysis revealed that MISR performed better over the three sites with about 82.5% of paired AOD data falling within the error envelope (EE). MODIS-DT showed good agreement against AERONET with 59.05% of paired AOD falling within the sensor EE over terrestrial surfaces with relatively high vegetation cover. The comparison between MODIS-DB and AERONET revealed an overall lower performance with lower Gfraction (48.93%) and lower correlation r = 0.58; while AOD retrieved from OMI showed less correspondence with AERONET data with lower Gfraction (68.89%) and lowest correlation r = 0.31. The monthly evaluation of AODs retrieved from the sensors against AERONET AOD indicates that MODIS-DT has the best performance over the three sites with highest correlation (0.71-0.84), lowest RMSE and spread closer to the AERONET. Regarding seasonal analysis, MISR performed well during most seasons over Nairobi and Mbita; while MODIS-DT performed better than all other sensors during most seasons over Malindi. Furthermore, the best seasonal performance of most sensors relative to AERONET data occurred during June-August (JJA) attributed to modulations induced by a precipitation-vegetation factor to AOD satellite retrieval algorithms. The study revealed the strength and weakness of each of the retrieval algorithm and forms the basis for further research on the validation of satellite retrieved aerosol products over EA.

Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain

NASA Technical Reports Server (NTRS)

Zhu, Jun; Xia, Xiangao; Wang, Jun; Che, Huizheng; Chen, Hongbin; Zhang, Jinqiang; Xu, Xiaoguang; Levy, Robert; Oo, Min; Holz, Robert;

Evaluation of aerosol optical depth and aerosol models from VIIRS retrieval algorithms over North China Plain.

PubMed

Zhu, Jun; Xia, Xiangao; Wang, Jun; Che, Huizheng; Chen, Hongbin; Zhang, Jinqiang; Xu, Xiaoguang; Levy, Robert; Oo, Min; Holz, Robert; Ayoub, Mohammed

2017-01-01

The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The "MODIS-like" VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the "dark-target" algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012 - 31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04-0.06 and the correlation of 0.83-0.86, with the largest MB (0.10-0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13-0.14 and a higher correlation (0.93-0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02-0.04 for fine mode, 0.06-0.12 for coarse mode and 0.03-0.05 for bi-mode at 440nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g. surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models.

An algorithm for estimating aerosol optical depth from HIMAWARI-8 data over Ocean

NASA Astrophysics Data System (ADS)

Lee, Kwon Ho

2016-04-01

The paper presents currently developing algorithm for aerosol detection and retrieval over ocean for the next generation geostationary satellite, HIMAWARI-8. Enhanced geostationary remote sensing observations are now enables for aerosol retrieval of dust, smoke, and ash, which began a new era of geostationary aerosol observations. Sixteen channels of the Advanced HIMAWARI Imager (AHI) onboard HIMAWARI-8 offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS). Aerosols were estimated in detection processing from visible and infrared channel radiances, and in retrieval processing using the inversion-optimization of satellite-observed radiances with those calculated from radiative transfer model. The retrievals are performed operationally every ten minutes for pixel sizes of ~8 km. The algorithm currently under development uses a multichannel approach to estimate the effective radius, aerosol optical depth (AOD) simultaneously. The instantaneous retrieved AOD is evaluated by the MODIS level 2 operational aerosol products (C006), and the daily retrieved AOD was compared with ground-based measurements from the AERONET databases. The results show that the detection of aerosol and estimated AOD are in good agreement with the MODIS data and ground measurements with a correlation coefficient of ˜0.90 and a bias of 4%. These results suggest that the proposed method applied to the HIMAWARI-8 satellite data can accurately estimate continuous AOD. Acknowledgments This work was supported by "Development of Geostationary Meteorological Satellite Ground Segment(NMSC-2014-01)" program funded by National Meteorological Satellite Centre(NMSC) of Korea Meteorological Administration(KMA).

The 2015 Indonesian biomass-burning season with extensive peat fires: Remote sensing measurements of biomass burning aerosol optical properties from AERONET and MODIS satellite data

NASA Astrophysics Data System (ADS)

Eck, T. F.; Holben, B. N.; Giles, D. M.; Smirnov, A.; Slutsker, I.; Sinyuk, A.; Schafer, J.; Sorokin, M. G.; Reid, J. S.; Sayer, A. M.; Hsu, N. Y. C.; Levy, R. C.; Lyapustin, A.; Wang, Y.; Rahman, M. A.; Liew, S. C.; Salinas Cortijo, S. V.; Li, T.; Kalbermatter, D.; Keong, K. L.; Elifant, M.; Aditya, F.; Mohamad, M.; Mahmud, M.; Chong, T. K.; Lim, H. S.; Choon, Y. E.; Deranadyan, G.; Kusumaningtyas, S. D. A.

2016-12-01

The strong El Nino event in 2015 resulted in below normal rainfall throughout Indonesia, which in turn allowed for exceptionally large numbers of biomass burning fires (including much peat burning) from Aug though Oct 2015. Over the island of Borneo, three AERONET sites measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in Sep and Oct ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain significant signal at mid-visible, therefore a newly developed algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the longer wavelengths as possible. The AOD at longer wavelengths were then utilized to provide estimates of AOD at 550 nm with maximum values of 9 to 11. Additionally, satellite retrievals of AOD at 550 nm from MODIS data and the Dark Target, Deep Blue, and MAIAC algorithms were analyzed and compared to AERONET measured AOD. The AOD was sometimes too high for the satellite algorithms to make retrievals in the densest smoke regions. Since the AOD was often extremely high there was often insufficient AERONET direct sun signal at 440 nm for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, new hybrid sky radiance scans can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for more retrievals and at higher AOD levels. The retrieved volume median radius of the fine mode increased from 0.18 to 0.25 micron as AOD increased from 1 to 3 (at 440 nm). These are very large size particles for biomass burning aerosol and are similar in size to smoke particles measured in Alaska during the very dry years of 2004 and 2005 (Eck et al. 2009) when peat soil burning also contributed to the fuel burned. The average single scattering albedo over the wavelength range of 440 to 1020 nm was very high ranging from 0.96 to 0.98 (spectrally flat), indicative of dominant smoldering phase combustion which produces very little black carbon. Additionally, we have analyzed measured (pyranometer) and modeled total solar flux at ground level for these extremely high aerosol loadings that resulted in significant attenuation of downwelling solar energy.

An operational retrieval algorithm for determining aerosol optical properties in the ultraviolet

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan S.; Slusser, James R.; Stephens, Graeme L.; Goering, Christian D.

2008-02-01

This paper describes a number of practical considerations concerning the optimization and operational implementation of an algorithm used to characterize the optical properties of aerosols across part of the ultraviolet (UV) spectrum. The algorithm estimates values of aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) at seven wavelengths in the UV, as well as total column ozone (TOC) and wavelength-independent asymmetry factor (g) using direct and diffuse irradiances measured with a UV multifilter rotating shadowband radiometer (UV-MFRSR). A novel method for cloud screening the irradiance data set is introduced, as well as several improvements and optimizations to the retrieval scheme which yield a more realistic physical model for the inversion and increase the efficiency of the algorithm. Introduction of a wavelength-dependent retrieval error budget generated from rigorous forward model analysis as well as broadened covariances on the a priori values of AOD, SSA and g and tightened covariances of TOC allows sufficient retrieval sensitivity and resolution to obtain unique solutions of aerosol optical properties as demonstrated by synthetic retrievals. Analysis of a cloud screened data set (May 2003) from Panther Junction, Texas, demonstrates that the algorithm produces realistic values of the optical properties that compare favorably with pseudo-independent methods for AOD, TOC and calculated Ångstrom exponents. Retrieval errors of all parameters (except TOC) are shown to be negatively correlated to AOD, while the Shannon information content is positively correlated, indicating that retrieval skill improves with increasing atmospheric turbidity. When implemented operationally on more than thirty instruments in the Ultraviolet Monitoring and Research Program's (UVMRP) network, this retrieval algorithm will provide a comprehensive and internally consistent climatology of ground-based aerosol properties in the UV spectral range that can be used for both validation of satellite measurements as well as regional aerosol and ultraviolet transmission studies.

Aerosol Optical Properties Derived from the DRAGON-NE Asia Campaign, and Implications for a Single-Channel Algorithm to Retrieve Aerosol Optical Depth in Spring from Meteorological Imager (MI) On-Board the Communication, Ocean, and Meteorological Satellite (COMS)

NASA Technical Reports Server (NTRS)

Kim, M.; Kim, J.; Jeong, U.; Kim, W.; Hong, H.; Holben, B.; Eck, T. F.; Lim, J.; Song, C.; Lee, S.;

Sensitivity of Multiangle Imaging to the Optical and Microphysical Properties of Biomass Burning Aerosols

NASA Technical Reports Server (NTRS)

Chen, Wei-Ting; Kahn, Ralph A.; Nelson, David; Yau, Kevin; Seinfeld, John H.

2008-01-01

The treatment of biomass burning (BB) carbonaceous particles in the Multiangle Imaging SpectroRadiometer (MISR) Standard Aerosol Retrieval Algorithm is assessed, and algorithm refinements are suggested, based on a theoretical sensitivity analysis and comparisons with near-coincident AERONET measurements at representative BB sites. Over the natural ranges of BB aerosol microphysical and optical properties observed in past field campaigns, patterns of retrieved Aerosol Optical Depth (AOD), particle size, and single scattering albedo (SSA) are evaluated. On the basis of the theoretical analysis, assuming total column AOD of 0.2, over a dark, uniform surface, MISR can distinguish two to three groups in each of size and SSA, except when the assumed atmospheric particles are significantly absorbing (mid-visible SSA approx.0.84), or of medium sizes (mean radius approx.0.13 pin); sensitivity to absorbing, medium-large size particles increases considerably when the assumed column AOD is raised to 0.5. MISR Research Aerosol Retrievals confirm the theoretical results, based on coincident AERONET inversions under BB-dominated conditions. When BB is externally mixed with dust in the atmosphere, dust optical model and surface reflection uncertainties, along with spatial variability, contribute to differences between the Research Retrievals and AERONET. These results suggest specific refinements to the MISR Standard Aerosol Algorithm complement of component particles and mixtures. They also highlight the importance for satellite aerosol retrievals of surface reflectance characterization, with accuracies that can be difficult to achieve with coupled surface-aerosol algorithms in some higher AOD situations.

Lessons learned and way forward from 6 years of Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, Thomas; de Leeuw, Gerrit; Pinnock, Simon

2017-04-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve and qualify algorithms for the retrieval of aerosol information from European sensors. Meanwhile, several validated (multi-) decadal time series of different aerosol parameters from complementary sensors are available: Aerosol Optical Depth (AOD), stratospheric extinction profiles, a qualitative Absorbing Aerosol Index (AAI), fine mode AOD, mineral dust AOD; absorption information and aerosol layer height are in an evaluation phase and the multi-pixel GRASP algorithm for the POLDER instrument is used for selected regions. Validation (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account in an iterative evolution cycle. The datasets contain pixel level uncertainty estimates which were also validated and improved in the reprocessing. The use of an ensemble method was tested, where several algorithms are applied to the same sensor. The presentation will summarize and discuss the lessons learned from the 6 years of intensive collaboration and highlight major achievements (significantly improved AOD quality, fine mode AOD, dust AOD, pixel level uncertainties, ensemble approach); also limitations and remaining deficits shall be discussed. An outlook will discuss the way forward for the continuous algorithm improvement and re-processing together with opportunities for time series extension with successor instruments of the Sentinel family and the complementarity of the different satellite aerosol products.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

What is the Uncertainty in MODIS Aerosol Optical Depth in the Vicinity of Clouds?

NASA Technical Reports Server (NTRS)

Patadia, Falguni; Levy, Rob; Mattoo, Shana

2017-01-01

MODIS dark-target (DT) algorithm retrieves aerosol optical depth (AOD) using a Look Up Table (LUT) approach. Global comparison of AOD (Collection 6 ) with ground-based sun photometer gives an Estimated Error (EE) of +/-(0.04 + 10%) over ocean. However, EE does not represent per-retrieval uncertainty. For retrievals that are biased high compared to AERONET, here we aim to closely examine the contribution of biases due to presence of clouds and per-pixel retrieval uncertainty. We have characterized AOD uncertainty at 550 nm, due to standard deviation of reflectance in 10 km retrieval region, uncertainty related to gas (H2O, O3) absorption, surface albedo, and aerosol models. The uncertainty in retrieved AOD seems to lie within the estimated over ocean error envelope of +/-(0.03+10%). Regions between broken clouds tend to have higher uncertainty. Compared to C6 AOD, a retrieval omitting observations in the vicinity of clouds (< or = 1 km) is biased by about +/- 0.05. For homogeneous aerosol distribution, clear sky retrievals show near zero bias. Close look at per-pixel reflectance histograms suggests retrieval possibility using median reflectance values.

Validation of high-resolution MAIAC aerosol product over South America

NASA Astrophysics Data System (ADS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-07-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD550 was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (RTerra:0.956 and RAqua: 0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 ( 66%) of retrievals are within the expected error (EE = ±(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset 0.006). Additionally, MAIAC CWV presents quantitative information with R 0.97 and more than 70% of retrievals within error (±15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Sayer, Andrew M.; Ahmad, Ziauddin; Franz, Bryan A.

2016-01-01

As atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-View Sensor (SeaWiFS) algorithm atmospheric correction with approximately 13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD(sub 440)) is overestimated for AOD below approximately 0.1-0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value less than approximately 0.96.AOD(sub 440) and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.

A novel method to improve MODIS AOD retrievals in cloudy pixels using an analog ensemble approach

NASA Astrophysics Data System (ADS)

Kumar, R.; Raman, A.; Delle Monache, L.; Alessandrini, S.; Cheng, W. Y. Y.; Gaubert, B.; Arellano, A. F.

2016-12-01

Particulate matter (PM) concentrations are one of the fundamental indicators of air quality. Earth orbiting satellite platforms acquire column aerosol abundance that can in turn provide information about the PM concentrations. One of the serious limitations of column aerosol retrievals from low earth orbiting satellites is that these algorithms are based on clear sky assumptions. They do not retrieve AOD in cloudy pixels. After filtering cloudy pixels, these algorithms also arbitrarily remove brightest and darkest 25% of remaining pixels over ocean and brightest and darkest 50% pixels over land to filter any residual contamination from clouds. This becomes a critical issue especially in regions that experience monsoon, like Asia and North America. In case of North America, monsoon season experiences wide variety of extreme air quality events such as fires in California and dust storms in Arizona. Assessment of these episodic events warrants frequent monitoring of aerosol observations from remote sensing retrievals. In this study, we demonstrate a method to fill in cloudy pixels in Moderate Imaging Resolution Spectroradiometer (MODIS) AOD retrievals based on ensembles generated using an analog-based approach (AnEn). It provides a probabilistic distribution of AOD in cloudy pixels using historical records of model simulations of meteorological predictors such as AOD, relative humidity, and wind speed, and past observational records of MODIS AOD at a given target site. We use simulations from a coupled community weather forecasting model with chemistry (WRF-Chem) run at a resolution comparable to MODIS AOD. Analogs selected from summer months (June, July) of 2011-2013 from model and corresponding observations are used as a training dataset. Then, missing AOD retrievals in cloudy pixels in the last 31 days of the selected period are estimated. Here, we use AERONET stations as target sites to facilitate comparison against in-situ measurements. We use two approaches to evaluate the estimated AOD: 1) by comparing against reanalysis AOD, 2) by inverting AOD to PM10 concentrations and then comparing those with measured PM10. AnEn is an efficient approach to generate an ensemble as it involves only one model run and provides an estimate of uncertainty that complies with the physical and chemical state of the atmosphere.

Validation of High-Resolution MAIAC Aerosol Product over South America

NASA Technical Reports Server (NTRS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-01-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD(sub 550) was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (R(sub Terra):0.956 and R(sub Aqua):0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 (approximately 66%) of retrievals are within the expected error (EE = +/-(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset approximately 0.006). Additionally, MAIAC CWV presents quantitative information with R approximatley 0.97 and more than 70% of retrievals within error (+/-15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the "Deep Blue" Aerosol Project

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Lee, J.; Bettenhausen, C.; Kim, W. V.; Smirnov, A.

2018-01-01

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue data set also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's S-NPP VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nm AOD of order ±(0.03+10%), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Ångström exponent and fine-mode AOD fraction are also well correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

Evaluating the Assumptions of Surface Reflectance and Aerosol Type Selection Within the MODIS Aerosol Retrieval Over Land: The Problem of Dust Type Selection

NASA Technical Reports Server (NTRS)

Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.

2011-01-01

Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the MODIS retrieval algorithm over land (Collection 5) are compared with ground based sun photometer measurements at eleven sites spanning the globe. Although, in general, total AOD compares well at these sites (R2 values generally over 0.8), there are cases (from 2 to 67% of the measurements depending on the site) where MODIS clearly retrieves the wrong spectral dependence, and hence, an unrealistic AE value. Some of these poor AE retrievals are due to the aerosol signal being too small (total AOD<0.3) but in other cases the AOD should have been high enough to derive accurate AE. However, in these cases, MODIS indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the MODIS observed reflectance. Yet, according to evidence from the collocated sun photometer measurements and back-trajectory analyses, there should be no dust present. This indicates that the assumptions about aerosol model and surface properties made by the MODIS algorithm may have been incorrect. Here we focus on problems related to parameterization of the land-surface optical properties in the algorithm, in particular the relationship between the surface reflectance at 660 and 2130 nm.

Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange-1 point

NASA Astrophysics Data System (ADS)

Xu, Xiaoguang; Wang, Jun; Wang, Yi; Zeng, Jing; Torres, Omar; Yang, Yuekui; Marshak, Alexander; Reid, Jeffrey; Miller, Steve

2017-07-01

We presented an algorithm for inferring aerosol layer height (ALH) and optical depth (AOD) over ocean surface from radiances in oxygen A and B bands measured by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) orbiting at Lagrangian-1 point. The algorithm was applied to EPIC imagery of a 2 day dust outbreak over the North Atlantic Ocean. Retrieved ALHs and AODs were evaluated against counterparts observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer, and Aerosol Robotic Network. The comparisons showed 71.5% of EPIC-retrieved ALHs were within ±0.5 km of those determined from CALIOP and 74.4% of EPIC AOD retrievals fell within a ± (0.1 + 10%) envelope of MODIS retrievals. This study demonstrates the potential of EPIC measurements for retrieving global aerosol height multiple times daily, which are essential for evaluating aerosol profile simulated in climate models and for better estimating aerosol radiative effects.

A modeling approach for aerosol optical depth analysis during forest fire events

NASA Astrophysics Data System (ADS)

Aube, Martin P.; O'Neill, Normand T.; Royer, Alain; Lavoue, David

2004-10-01

Measurements of aerosol optical depth (AOD) are important indicators of aerosol particle behavior. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as DDV (Dense Dark Vegetation) based inversion algorithms which yield AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new assimilation methodology that links AOD measurements and the predictions of a particulate matter Transport Model. This modelling package (AODSEM V2.0 for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution may be tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important and robust parameter. We applied this methodology to a significant smoke event that occurred over the eastern part of North America in July 2002.

Characterization and error analysis of an operational retrieval algorithm for estimating column ozone and aerosol properties from ground-based ultra-violet irradiance measurements

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan; Slusser, James; Stephens, Graeme; Krotkov, Nick; Davis, John; Goering, Christian

2005-08-01

Extensive sensitivity and error characteristics of a recently developed optimal estimation retrieval algorithm which simultaneously determines aerosol optical depth (AOD), aerosol single scatter albedo (SSA) and total ozone column (TOC) from ultra-violet irradiances are described. The algorithm inverts measured diffuse and direct irradiances at 7 channels in the UV spectral range obtained from the United States Department of Agriculture's (USDA) UV-B Monitoring and Research Program's (UVMRP) network of 33 ground-based UV-MFRSR instruments to produce aerosol optical properties and TOC at all seven wavelengths. Sensitivity studies of the Tropospheric Ultra-violet/Visible (TUV) radiative transfer model performed for various operating modes (Delta-Eddington versus n-stream Discrete Ordinate) over domains of AOD, SSA, TOC, asymmetry parameter and surface albedo show that the solutions are well constrained. Realistic input error budgets and diagnostic and error outputs from the retrieval are analyzed to demonstrate the atmospheric conditions under which the retrieval provides useful and significant results. After optimizing the algorithm for the USDA site in Panther Junction, Texas the retrieval algorithm was run on a cloud screened set of irradiance measurements for the month of May 2003. Comparisons to independently derived AOD's are favorable with root mean square (RMS) differences of about 3% to 7% at 300nm and less than 1% at 368nm, on May 12 and 22, 2003. This retrieval method will be used to build an aerosol climatology and provide ground-truthing of satellite measurements by running it operationally on the USDA UV network database.

Retrieval of AOD and PM2.5 Concentrations over Urban Areas of Shenyang City using MODIS Data

NASA Astrophysics Data System (ADS)

Wang, Z.

2016-12-01

Atmospheric aerosols play an important part in the Earth's radiation balance as well as global climate change, aerosols also have very important impact on environment as well as human and other organisms' health, PM2.5 and other small particle aerosols, can enter bronchi directly, thus causing bronchitis, cardiovascular disease, asthma and so on.Detection of AOD by satellite and remote sensing is currently one of the hotest issues , diffierent from the traditional monitoring method, this method has much more advantanges, for emample wide area coverage, fast and convenient etc. So it is possible for people to know the regional changes of AOD real time over large area. Now, detection aerosol by RS technology has reached a high level in marine and dense vegetation land areas, but result is not ideal for urban areas, the higher surface reflectance in urban areas is a bottleneck of AOD retrieval. Focus on the high surface reflectance and low accuracy of the AOD products of urban areas, this paper propose an algorithm coupled with surface reflectance to get red band surface reflectance, based on Dens Dark Vegetation algorithm and geometrical optics model theory, to distinguish urban reflectivity from other targets. Considering the appropriate aerosol model which adapt to season and other proper parameters, this paper uses 6S model to establish look-up table, thus retrieve AOD for urban as well as other high reflectance areas. This paper take Shenyang region as pilot area, then retrieve the AOD and PM2.5 concentration of Shenyang in 2015 based on MODIS data, thus get 1km resolution distribution map, and then analyzed the results in spatial, intensity and temporal. At last, real-time monitoring data from the ground monitor station is used to verify the outcome, the results have good accuracy and the the correlation reached 0.9004 when the weather is sunny. The research shows that this algorithm has relatively higher precision and certain universality. This method has better applicability to retrieve AOD and PM2.5 concentration by remote sensing in Shenyang and Liaoning Provience, and owes guiding and reference significance, and it has a high value in terms of atmospheric environment monitoring.

MISR Aerosol Product Attributes and Statistical Comparisons with MODIS

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Nelson, David L.; Garay, Michael J.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Paradise, Susan R.; Hansen, Earl G.; Remer, Lorraine A.

2009-01-01

In this paper, Multi-angle Imaging SpectroRadiometer (MISR) aerosol product attributes are described, including geometry and algorithm performance flags. Actual retrieval coverage is mapped and explained in detail using representative global monthly data. Statistical comparisons are made with coincident aerosol optical depth (AOD) and Angstrom exponent (ANG) retrieval results from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The relationship between these results and the ones previously obtained for MISR and MODIS individually, based on comparisons with coincident ground-truth observations, is established. For the data examined, MISR and MODIS each obtain successful aerosol retrievals about 15% of the time, and coincident MISR-MODIS aerosol retrievals are obtained for about 6%-7% of the total overlap region. Cloud avoidance, glint and oblique-Sun exclusions, and other algorithm physical limitations account for these results. For both MISR and MODIS, successful retrievals are obtained for over 75% of locations where attempts are made. Where coincident AOD retrievals are obtained over ocean, the MISR-MODIS correlation coefficient is about 0.9; over land, the correlation coefficient is about 0.7. Differences are traced to specific known algorithm issues or conditions. Over-ocean ANG comparisons yield a correlation of 0.67, showing consistency in distinguishing aerosol air masses dominated by coarse-mode versus fine-mode particles. Sampling considerations imply that care must be taken when assessing monthly global aerosol direct radiative forcing and AOD trends with these products, but they can be used directly for many other applications, such as regional AOD gradient and aerosol air mass type mapping and aerosol transport model validation. Users are urged to take seriously the published product data-quality statements.

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

NASA Astrophysics Data System (ADS)

Naeger, Aaron R.; Gupta, Pawan; Zavodsky, Bradley T.; McGrath, Kevin M.

2016-06-01

The primary goal of this study was to generate a near-real time (NRT) aerosol optical depth (AOD) product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean, in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15) and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT-2) to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America as the frequent geostationary observations lead to a greater coverage of cloud-free AOD retrievals equatorward of about 35° N, while the polar-orbiting satellites provide a greater coverage of AOD poleward of 35° N. However, we note several areas across the domain of interest from Asia to North America where the GOES-15 and MTSAT-2 retrieval algorithms can introduce significant uncertainties into the new product.

Desert Dust Satellite Retrieval Intercomparison

NASA Technical Reports Server (NTRS)

Carboni, E.; Thomas, G. E.; Sayer, A. M.; Siddans, R.; Poulsen, C. A.; Grainger, R. G.; Ahn, C.; Antoine, D.; Bevan, S.; Braak, R.;

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

NASA Technical Reports Server (NTRS)

Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim

2014-01-01

Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0.41tAERONET + 0.16 to tMI [new algorithm] = 0.70tAERONET + 0.01.

High temporal resolution aerosol retrieval using Geostationary Ocean Color Imager: application and initial validation

NASA Astrophysics Data System (ADS)

Zhang, Yuhuan; Li, Zhengqiang; Zhang, Ying; Hou, Weizhen; Xu, Hua; Chen, Cheng; Ma, Yan

2014-01-01

The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.

Bias Correction of MODIS AOD using DragonNET to obtain improved estimation of PM2.5

NASA Astrophysics Data System (ADS)

Gross, B.; Malakar, N. K.; Atia, A.; Moshary, F.; Ahmed, S. A.; Oo, M. M.

2014-12-01

MODIS AOD retreivals using the Dark Target algorithm is strongly affected by the underlying surface reflection properties. In particular, the operational algorithms make use of surface parameterizations trained on global datasets and therefore do not account properly for urban surface differences. This parameterization continues to show an underestimation of the surface reflection which results in a general over-biasing in AOD retrievals. Recent results using the Dragon-Network datasets as well as high resolution retrievals in the NYC area illustrate that this is even more significant at the newest C006 3 km retrievals. In the past, we used AERONET observation in the City College to obtain bias-corrected AOD, but the homogeneity assumptions using only one site for the region is clearly an issue. On the other hand, DragonNET observations provide ample opportunities to obtain better tuning the surface corrections while also providing better statistical validation. In this study we present a neural network method to obtain bias correction of the MODIS AOD using multiple factors including surface reflectivity at 2130nm, sun-view geometrical factors and land-class information. These corrected AOD's are then used together with additional WRF meteorological factors to improve estimates of PM2.5. Efforts to explore the portability to other urban areas will be discussed. In addition, annual surface ratio maps will be developed illustrating that among the land classes, the urban pixels constitute the largest deviations from the operational model.

Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey

Cases of absorbing aerosols above clouds (AAC), such as smoke or mineral dust, are omitted from most routinely-processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar

MISR Global Aerosol Product Assessment by Comparison with AERONET

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Gaitley, Barbara J.; Garay, Michael J.; Diner, David J.; Eck, Thomas F.; Smirnov, Alexander; Holben, Brent N.

2010-01-01

A statistical approach is used to assess the quality of the MISR Version 22 (V22) aerosol products. Aerosol Optical Depth (AOD) retrieval results are improved relative to the early post- launch values reported by Kahn et al. [2005a], varying with particle type category. Overall, about 70% to 75% of MISR AOD retrievals fall within 0.05 or 20% AOD of the paired validation data, and about 50% to 55% are within 0.03 or 10% AOD, except at sites where dust, or mixed dust and smoke, are commonly found. Retrieved particle microphysical properties amount to categorical values, such as three groupings in size: "small," "medium," and "large." For particle size, ground-based AERONET sun photometer Angstrom Exponents are used to assess statistically the corresponding MISR values, which are interpreted in terms of retrieved size categories. Coincident Single-Scattering Albedo (SSA) and fraction AOD spherical data are too limited for statistical validation. V22 distinguishes two or three size bins, depending on aerosol type, and about two bins in SSA (absorbing vs. non-absorbing), as well as spherical vs. non-spherical particles, under good retrieval conditions. Particle type sensitivity varies considerably with conditions, and is diminished for mid-visible AOD below about 0.15 or 0.2. Based on these results, specific algorithm upgrades are proposed, and are being investigated by the MISR team for possible implementation in future versions of the product.

Beyond MODIS: Developing an aerosol climate data record

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Laszlo, I.; Holz, R.

2013-12-01

As defined by the National Research Council, a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. As one of our most pressing research questions concerns changes in global direct aerosol radiative forcing (DARF), creating an aerosol CDR is of high importance. To reduce our uncertainties in DARF, we need uncertainty in global aerosol optical depth (AOD) reduced to ×0.02 or better, or about 10% of global mean AOD (~0.15-0.20). To quantify aerosol trends with significance, we also need a stable time series at least 20-30 years. By this Fall-2013 AGU meeting, the Moderate Resolution Imaging Spectrometer (MODIS) has been flying on NASA's Terra and Aqua satellites for 14 years and 11.5 years, respectively. During this time, we have fine-tuned the aerosol retrieval algorithms and data processing protocols, resulting in a well characterized product of aerosol optical depth (AOD). MODIS AOD has been extensively compared to ground-based sunphotometer data, showing per-retrieval expected error (EE) of ×(0.03 + 5%) over ocean, and has been generally adopted as a robust and stable environmental data record (EDR). With the 2011 launch of the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, we have begun a new aerosol time series. The VIIRS AOD product has stabilized to the point where, compared to ground-based AERONET sunphotometer, the VIIRS AOD is within similar EE envelope as MODIS. Thus, if VIIRS continues to perform as expected, it too can provide a robust and stable aerosol EDR. What will it take to stitch MODIS and VIIRS into a robust aerosol CDR? Based on the recent experience of MODIS 'Collection 6' development, there are many details of aerosol retrieval that each lead to ×0.01 uncertainties in global AOD. These include 'radiative transfer' assumptions such as calculations for gas absorption and sea-level Rayleigh optical depth, 'decision making' assumptions such as cloud masking and pixel selection, as well as 'retrieval' assumptions such as aerosol type, and surface reflectance model. Also there are instrument issues such as calibration and geo-location, which even on the level of 1-2%, will lead to 10% error in retrieved AOD. At this point, however, many of these issues have been solved, or are being quantified for MODIS and VIIRS. In the past year, we created a generic dark-target aerosol retrieval algorithm, which can be applied to MODIS, VIIRS, or any other sensor with a similar set of wavelength bands. We applied the same radiative transfer codes for creating lookup tables, the same protocols for deriving non-aerosol assumptions, and the same criteria for cloud masking. Although there are still inconsistencies to work out, this generic algorithm is being applied to selected months having VIIRS/MODIS overlap. Comparing to AERONET, and with each other, we quantify the statistical agreement between MODIS and VIIRS, both for the official algorithms run on each sensor, as well as for our generic algorithm run on both.

What We are Learning about Airborne Particles from MISR Multi-angle Imaging

NASA Astrophysics Data System (ADS)

Kahn, Ralph

The NASA Earth Observing System’s Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global observations in 36 angular-spectral channels about once per week for over 14 years. Regarding airborne particles, MISR is contributing in three broad areas: (1) aerosol optical depth (AOD), especially over land surface, including bright desert, (2) wildfire smoke, desert dust, and volcanic ash injection and near-source plume height, and (3) aerosol type, the aggregate of qualitative constraints on particle size, shape, and single-scattering albedo (SSA). Early advances in the retrieval of these quantities focused on AOD, for which surface-based sun photometers provided a global network of ground truth, and plume height, for which ground-based and airborne lidar offered near-coincident validation data. MSIR monthly, global AOD products contributed directly to the advances in modeling aerosol impacts on climate made between the Inter-governmental Panel on Climate Change (IPCC) third and fourth assessment reports. MISR stereo-derived plume heights are now being used to constrain source inventories for the AeroCom aerosol-climate modeling effort. The remaining challenge for the MISR aerosol effort is to refine and validate our global aerosol type product. Unlike AOD and plume height, aerosol type as retrieved by MISR is a qualitative classification derived from multi-dimensional constraints, so evaluation must be done on a categorical basis. Coincident aerosol type validation data are far less common than for AOD, and, except for rare Golden Days during aircraft field campaigns, amount to remote sensing retrievals from suborbital instruments having uncertainties comparable to those from the MISR product itself. And satellite remote sensing retrievals of aerosol type are much more sensitive to scene conditions such as surface variability and AOD than either AOD or plume height. MISR aerosol type retrieval capability and information content have been demonstrated in case studies using the MISR Operational as especially the MISR Research aerosol retrieval algorithms. Refinements to the Operational algorithm, as indicated by these studies, are required to generate a high-quality next-generation aerosol type product from the MISR data. This presentation will briefly review the MISR AOD and plume height product attributes, and will then focus on the MISR aerosol type product: validation, data quality, and refinements.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

PubMed

Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

2018-04-01

We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar + polarimeter retrieval using both HSRL and RSP measurements.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the “MAPP” algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stamnes, S.; Hostetler, C.; Ferrare, R.

We present an optimal estimation based retrieval framework, the Microphysical Aerosol Properties from Polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High Spectral Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355, 532, and 1064 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ã…ngstrømmore » exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio- Optical Research (SABOR) campaign. For the SABOR campaign, 71% RSP MAPP retrievals fall within 0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.925 and root-mean-square deviation of 0.04. For the TCAP campaign, 55% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.925 and root-mean-square deviation of 0.07. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.96 and a root-mean-square deviation of also 0.07. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar+polarimeter retrieval using both HSRL and RSP measurements.« less

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

NASA Technical Reports Server (NTRS)

Gupta, Pawan; Torres, Omar; Jethva, Hiren; Ahn, Changwoo

2014-01-01

Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.

Development and assessment of a higher-spatial-resolution (4.4 km) MISR aerosol optical depth product using AERONET-DRAGON data

NASA Astrophysics Data System (ADS)

Garay, Michael J.; Kalashnikova, Olga V.; Bull, Michael A.

2017-04-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been acquiring data that have been used to produce aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the current operational (Version 22) MISR algorithm performs well, with about 75 % of MISR AOD retrievals globally falling within 0.05 or 20 % × AOD of paired validation data from the ground-based Aerosol Robotic Network (AERONET). This paper describes the development and assessment of a prototype version of a higher-spatial-resolution 4.4 km MISR aerosol optical depth product compared against multiple AERONET Distributed Regional Aerosol Gridded Observations Network (DRAGON) deployments around the globe. In comparisons with AERONET-DRAGON AODs, the 4.4 km resolution retrievals show improved correlation (r = 0. 9595), smaller RMSE (0.0768), reduced bias (-0.0208), and a larger fraction within the expected error envelope (80.92 %) relative to the Version 22 MISR retrievals.

Modeling of Aerosol Optical Depth Variability during the 1998 Canadian Forest Fire Smoke Event

NASA Astrophysics Data System (ADS)

Aubé, M.; O`Neill, N. T.; Royer, A.; Lavoué, D.

2003-04-01

Monitoring of aerosol optical depth (AOD) is of particular importance due to the significant role of aerosols in the atmospheric radiative budget. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as based DDV (Dense Dark Vegetation) inversion algorithms which extract AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new methodology that links AOD measurements and particulate matter Transport Model using a data assimilation approach. This modelling package (AODSEM for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian-Eulerian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution is tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important but crude parameter. We applied this methodology to a significant smoke event that occurred over Canada in august 1998. The results show the potential of this approach inasmuch as residuals between AODSEM assimilated analysis and measurements are smaller than typical errors associated to remotely sensed AOD (satellite or ground based). The AODSEM assimilation approach also gives better results than classical interpolation techniques. This improvement is especially evident when the available number of AOD measurements is small.

Spatio-temporal PM and AOD estimations over Northeast Asia during DRAGON NE-Asia campaign

NASA Astrophysics Data System (ADS)

Park, M.; Song, C.; Kim, J.

2013-12-01

Particulate matter (PM) is closely related to human health, air quality, and climate changes. It has been directly measured on the surface level. However, ground-based measurements have a limitation in spatial coverage of PM concentrations. In order to overcome this spatial limitation of ground measurements, AOD, which is considered as a proxy to PM concentration, was used in this study. AOD was first utilized to figure out the characteristics of PM and was then used to estimate the PM concentrations in Northeast Asia during the DRAGON Northeast-Asia campaign (March-May 2012), using CMAQ-estimated AOD, COMS/GOCI-retrieved AOD, and the AOD data from the DRAGON NE-Asia campaign. First of all, current emission inventories (MEIC and INTEX-B based emission inventories) were evaluated to improve CMAQ modeling results. Next, several algorithms to convert aerosol composition to AOD were evaluated using intensive measurement data from the DRAGON NE-Asia campaign. The accuracy of the CMAQ-estimated AOD was further evaluated with hourly observing GOCI-retrieved AOD. After the evaluation, CMAQ-calculated AOD was mathematically combined with GOCI-retrieved AOD via data assimilation. After this, AERONET AOD measured by the DRAGON NE-Asia campaign was again combined with the assimilated AOD from CMAQ and GOCI AODs to produce more accurate spatio-temporal AOD fields over Northeast Asia. Using several relationships between PM (PM10 and PM2.5) and AOD, the best surface-PM concentrations over the entire domain were calculated. It was then evaluated with ground-based PM2.5 measurements from the DRAGON NE-Asia campaign. A good agreement between estimated PM2.5 and measured PM2.5 over the domain was found. Finally, the PM and AOD information was used to investigate the effects of transboundary PM pollution from China to the Korean peninsula.

Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

NASA Astrophysics Data System (ADS)

Zhang, L.; Xu, S.; Wang, L.; Cai, K.; Ge, Q.

2017-05-01

Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.

Effect of black carbon on dust property retrievals from satellite observations

NASA Astrophysics Data System (ADS)

Lin, Tang-Huang; Yang, Ping; Yi, Bingqi

2013-01-01

The effect of black carbon on the optical properties of polluted mineral dust is studied from a satellite remote-sensing perspective. By including the auxiliary data of surface reflectivity and aerosol mixing weight, the optical properties of mineral dust, or more specifically, the aerosol optical depth (AOD) and single-scattering albedo (SSA), can be retrieved with improved accuracy. Precomputed look-up tables based on the principle of the Deep Blue algorithm are utilized in the retrieval. The mean differences between the retrieved results and the corresponding ground-based measurements are smaller than 1% for both AOD and SSA in the case of pure dust. However, the retrievals can be underestimated by as much as 11.9% for AOD and overestimated by up to 4.1% for SSA in the case of polluted dust with an estimated 10% (in terms of the number-density mixing ratio) of soot aggregates if the black carbon effect on dust aerosols is neglected.

MAX-DOAS retrieval of aerosol extinction properties in Madrid, Spain

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Cuevas, Carlos A.; Frieß, Udo; Saiz-Lopez, Alfonso

2017-04-01

We present Multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements performed in the urban environment of Madrid, Spain, from March to September 2015. The O4 absorption in the ultraviolet (UV) spectral region was used to retrieve the aerosol extinction profile using an inversion algorithm. The results show a good agreement between the hourly retrieved aerosol optical depth (AOD) and the correlative Aerosol Robotic Network (AERONET) product. Higher AODs are found in the summer season due to the more frequent occurrence of Saharan dust intrusions. The surface aerosol extinction coefficient as retrieved by the MAX-DOAS measurements was also compared to in situ PM2:5 concentrations. The level of agreement between both measurements indicates that the MAX-DOAS retrieval has the ability to characterize the extinction of aerosol particles near the surface. The retrieval algorithm was also used to study a case of severe dust intrusion on 12 May 2015. The capability of the MAX-DOAS retrieval to recognize the dust event including an elevated particle layer is investigated along with air mass back-trajectory analysis.

Validation of aerosol optical depth uncertainties within the ESA Climate Change Initiative

NASA Astrophysics Data System (ADS)

Stebel, Kerstin; Povey, Adam; Popp, Thomas; Capelle, Virginie; Clarisse, Lieven; Heckel, Andreas; Kinne, Stefan; Klueser, Lars; Kolmonen, Pekka; de Leeuw, Gerrit; North, Peter R. J.; Pinnock, Simon; Sogacheva, Larisa; Thomas, Gareth; Vandenbussche, Sophie

2017-04-01

Uncertainty is a vital component of any climate data record as it provides the context with which to understand the quality of the data and compare it to other measurements. Therefore, pixel-level uncertainties are provided for all aerosol products that have been developed in the framework of the Aerosol_cci project within ESA's Climate Change Initiative (CCI). Validation of these estimated uncertainties is necessary to demonstrate that they provide a useful representation of the distribution of error. We propose a technique for the statistical validation of AOD (aerosol optical depth) uncertainty by comparison to high-quality ground-based observations and present results for ATSR (Along Track Scanning Radiometer) and IASI (Infrared Atmospheric Sounding Interferometer) data records. AOD at 0.55 µm and its uncertainty was calculated with three AOD retrieval algorithms using data from the ATSR instruments (ATSR-2 (1995-2002) and AATSR (2002-2012)). Pixel-level uncertainties were calculated through error propagation (ADV/ASV, ORAC algorithms) or parameterization of the error's dependence on the geophysical retrieval conditions (SU algorithm). Level 2 data are given as super-pixels of 10 km x 10 km. As validation data, we use direct-sun observations of AOD from the AERONET (AErosol RObotic NETwork) and MAN (Maritime Aerosol Network) sun-photometer networks, which are substantially more accurate than satellite retrievals. Neglecting the uncertainty in AERONET observations and possible issues with their ability to represent a satellite pixel area, the error in the retrieval can be approximated by the difference between the satellite and AERONET retrievals (herein referred to as "error"). To evaluate how well the pixel-level uncertainty represents the observed distribution of error, we look at the distribution of the ratio D between the "error" and the ATSR uncertainty. If uncertainties are well represented, D should be normally distributed and 68.3% of values should fall within the range [-1, +1]. A non-zero mean of D indicates the presence of residual systematic errors. If the fraction is smaller than 68%, uncertainties are underestimated; if it is larger, uncertainties are overestimated. For the three ATSR algorithms, we provide statistics and an evaluation at a global scale (separately for land and ocean/coastal regions), for high/low AOD regimes, and seasonal and regional statistics (e.g. Europe, N-Africa, East-Asia, N-America). We assess the long-term stability of the uncertainty estimates over the 17-year time series, and the consistency between ATSR-2 and AATSR results (during their period of overlap). Furthermore, we exploit the possibility to adapt the uncertainty validation concept to the IASI datasets. Ten-year data records (2007-2016) of dust AOD have been generated with four algorithms using IASI observations over the greater Sahara region [80°W - 120°E, 0°N - 40°N]. For validation, the coarse mode AOD at 0.55 μm from the AERONET direct-sun spectral deconvolution algorithm (SDA) product may be used as a proxy for desert dust. The uncertainty validation results for IASI are still tentative, as larger IASI pixel sizes and the conversion of the IASI AOD values from infrared to visible wavelengths for comparison to ground-based observations introduces large uncertainties.

The analysis to understand temporal variation and long-range transport of aerosol over Northeast-Asia Using COMS, MI

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, J.

2016-12-01

Numerous efforts to retrieve aerosol optical properties (AOPs) using satellite measurements have been accumulated for decades, resulted in several qualified data which can be used for the analysis of spatiotemporal characteristics of AOPs. However, the limitation in the instrument lifetime restricts temporal window of the analysis of long-term AOPs variation. In this point of view, single channel algorithm, which uses a single visible channel to retrieve aerosol optical depth (AOD), has an advantage to extent the time domain of the analysis. The Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean and Meteorological Satellite (COMS) includes the single channel Meteorological Imager (MI), which can also be utilized for the retrieval of AOPs. Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs over Northeast Asia, we can analyze the spatiotemporal characteristic of the aerosol using MI observations. In this study, we investigate the trend of AOD and also discuss the impact of long-range transport of aerosol on the temporal variation. Since the year 2010 when the COMS was launched, AODs over Northeast China and Yellow Sea region show 3.02 % and 2.74 % decrease per year, respectively, which are significant trends in spite of only 5-year short period. The decreasing behavior seems associated with the recent decreasing frequency of dust event over the region. But other Northeast Asia regions do not show clear temporal change. The accuracy of retrieved AOD can relates to the uncertainty of this trend analysis. According to the error analysis, cloud contamination and error in bright surface reflectance results in the accuracy of AOD. Therefore, improvements of cloud masking process and surface reflectance estimation in the developed single channel MI algorithm will be required for the future study.

Eyjafjallajokull Volcano Plume Particle-Type Characterization from Space-Based Multi-angle Imaging

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Limbacher, James

2012-01-01

The Multi-angle Imaging SpectroRadiometer (MISR) Research Aerosol algorithm makes it possible to study individual aerosol plumes in considerable detail. From the MISR data for two optically thick, near-source plumes from the spring 2010 eruption of the Eyjafjallaj kull volcano, we map aerosol optical depth (AOD) gradients and changing aerosol particle types with this algorithm; several days downwind, we identify the occurrence of volcanic ash particles and retrieve AOD, demonstrating the extent and the limits of ash detection and mapping capability with the multi-angle, multi-spectral imaging data. Retrieved volcanic plume AOD and particle microphysical properties are distinct from background values near-source, as well as for overwater cases several days downwind. The results also provide some indication that as they evolve, plume particles brighten, and average particle size decreases. Such detailed mapping offers context for suborbital plume observations having much more limited sampling. The MISR Standard aerosol product identified similar trends in plume properties as the Research algorithm, though with much smaller differences compared to background, and it does not resolve plume structure. Better optical analogs of non-spherical volcanic ash, and coincident suborbital data to validate the satellite retrieval results, are the factors most important for further advancing the remote sensing of volcanic ash plumes from space.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-07-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-03-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

Aerosol Climate Time Series in ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, Thomas; de Leeuw, Gerrit; Pinnock, Simon

2016-04-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. Meanwhile, full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer, but also from ATSR instruments and the POLDER sensor), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which were also validated and improved in the reprocessing. For the three ATSR algorithms the use of an ensemble method was tested. The paper will summarize and discuss the status of dataset reprocessing and validation. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of VIIRS, OMPS, and CALIOP Observations

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

2015-01-01

Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height as well as single scattering albedo (SSA) for biomass burning smoke aerosols. One of the advantages of this algorithm was that the aerosol layer height can be retrieved over broad areas, which had not been available from lidar observations only. The algorithm utilized aerosol properties from three different satellite sensors, i.e., aerosol optical depth (AOD) and Ångström exponent (AE) from Moderate Resolution Imaging Spectroradiometer (MODIS), UV aerosol index (UVAI) from Ozone Monitoring Instrument (OMI), and aerosol layer height from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Here, we extend the application of the algorithm to Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) data. We also now include dust layers as well as smoke. Other updates include improvements in retrieving the AOD of nonspherical dust from VIIRS, better determination of the aerosol layer height from CALIOP, and more realistic input aerosol profiles in the forward model for better accuracy.

GOSAT CO2 retrieval results using TANSO-CAI aerosol information over East Asia

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, W.; Jung, Y.; Lee, S.; Kim, J.; Lee, H.; Boesch, H.; Goo, T. Y.

2015-12-01

In the satellite remote sensing of CO2, incorrect aerosol information could induce large errors as previous studies suggested. Many factors, such as, aerosol type, wavelength dependency of AOD, aerosol polarization effect and etc. have been main error sources. Due to these aerosol effects, large number of data retrieved are screened out in quality control, or retrieval errors tend to increase if not screened out, especially in East Asia where aerosol concentrations are fairly high. To reduce these aerosol induced errors, a CO2 retrieval algorithm using the simultaneous TANSO-CAI aerosol information is developed. This algorithm adopts AOD and aerosol type information as a priori information from the CAI aerosol retrieval algorithm. The CO2 retrieval algorithm based on optimal estimation method and VLIDORT, a vector discrete ordinate radiative transfer model. The CO2 algorithm, developed with various state vectors to find accurate CO2 concentration, shows reasonable results when compared with other dataset. This study concentrates on the validation of retrieved results with the ground-based TCCON measurements in East Asia and the comparison with the previous retrieval from ACOS, NIES, and UoL. Although, the retrieved CO2 concentration is lower than previous results by ppm's, it shows similar trend and high correlation with previous results. Retrieved data and TCCON measurements data are compared at three stations of Tsukuba, Saga, Anmyeondo in East Asia, with the collocation criteria of ±2°in latitude/longitude and ±1 hours of GOSAT passing time. Compared results also show similar trend with good correlation. Based on the TCCON comparison results, bias correction equation is calculated and applied to the East Asia data.

Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

NASA Astrophysics Data System (ADS)

Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

2014-10-01

The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

Using OMI Observations to Measure Aerosol Absorption of Biomass Burning Aerosols Above Clouds

NASA Technical Reports Server (NTRS)

Torres, Omar; Bhartia, P. K.; Jethva, Hiren

2011-01-01

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.

Assessment of 10 Year Record of Aerosol Optical Depth from OMI UV Observations

NASA Technical Reports Server (NTRS)

Ahn, Changwoo; Torres, Omar; Jethva, Hiren

2014-01-01

The Ozone Monitoring Instrument (OMI) onboard the EOS-Aura satellite provides information on aerosol optical properties by making use of the large sensitivity to aerosol absorption in the near-ultraviolet (UV) spectral region. Another important advantage of using near UV observations for aerosol characterization is the low surface albedo of all terrestrial surfaces in this spectral region that reduces retrieval errors associated with land surface reflectance characterization. In spite of the 13 × 24 square kilometers coarse sensor footprint, the OMI near UV aerosol algorithm (OMAERUV) retrieves aerosol optical depth (AOD) and single-scattering albedo under cloud-free conditions from radiance measurements at 354 and 388 nanometers. We present validation results of OMI AOD against space and time collocated Aerosol Robotic Network measured AOD values over multiple stations representing major aerosol episodes and regimes. OMAERUV's performance is also evaluated with respect to those of the Aqua-MODIS Deep Blue and Terra-MISR AOD algorithms over arid and semi-arid regions in Northern Africa. The outcome of the evaluation analysis indicates that in spite of the "row anomaly" problem, affecting the sensor since mid-2007, the long-term aerosol record shows remarkable sensor stability.

Aerosol Climate Time Series Evaluation In ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, T.; de Leeuw, G.; Pinnock, S.

2015-12-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. By the end of 2015 full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which are also validated. The paper will summarize and discuss the results of major reprocessing and validation conducted in 2015. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

AERONET-Based Nonspherical Dust Optical Models and Effects on the VIIRS Deep Blue/SOAR Over Water Aerosol Product

NASA Astrophysics Data System (ADS)

Lee, Jaehwa; Hsu, N. Christina; Sayer, Andrew M.; Bettenhausen, Corey; Yang, Ping

2017-10-01

Aerosol Robotic Network (AERONET)-based nonspherical dust optical models are developed and applied to the Satellite Ocean Aerosol Retrieval (SOAR) algorithm as part of the Version 1 Visible Infrared Imaging Radiometer Suite (VIIRS) NASA "Deep Blue" aerosol data product suite. The optical models are created using Version 2 AERONET inversion data at six distinct sites influenced frequently by dust aerosols from different source regions. The same spheroid shape distribution as used in the AERONET inversion algorithm is assumed to account for the nonspherical characteristics of mineral dust, which ensures the consistency between the bulk scattering properties of the developed optical models and the AERONET-retrieved microphysical and optical properties. For the Version 1 SOAR aerosol product, the dust optical model representative for Capo Verde site is used, considering the strong influence of Saharan dust over the global ocean in terms of amount and spatial coverage. Comparisons of the VIIRS-retrieved aerosol optical properties against AERONET direct-Sun observations at five island/coastal sites suggest that the use of nonspherical dust optical models significantly improves the retrievals of aerosol optical depth (AOD) and Ångström exponent by mitigating the well-known artifact of scattering angle dependence of the variables, which is observed when incorrectly assuming spherical dust. The resulting removal of these artifacts results in a more natural spatial pattern of AOD along the transport path of Saharan dust to the Atlantic Ocean; that is, AOD decreases with increasing distance transported, whereas the spherical assumption leads to a strong wave pattern due to the spurious scattering angle dependence of AOD.

Aerosol Correction for Remotely Sensed Sea Surface Temperatures From the NOAA AVHRR: Phase II

NASA Astrophysics Data System (ADS)

Nalli, N. R.; Ignatov, A.

2002-05-01

For over two decades, the National Oceanic and Atmospheric Administration (NOAA) has produced global retrievals of sea surface temperature (SST) using infrared (IR) data from the Advanced Very High Resolution Radiometer (AVHRR). The standard multichannel retrieval algorithms are derived from regression analyses of AVHRR window channel brightness temperatures against in situ buoy measurements under non-cloudy conditions thus providing a correction for IR attenuation due to molecular water vapor absorption. However, for atmospheric conditions with elevated aerosol levels (e.g., arising from dust, biomass burning and volcanic eruptions), such algorithms lead to significant negative biases in SST because of IR attenuation arising from aerosol absorption and scattering. This research presents the development of a 2nd-phase aerosol correction algorithm for daytime AVHRR SST. To accomplish this, a long-term (1990-1998), global AVHRR-buoy matchup database was created by merging the Pathfinder Atmospheres (PATMOS) and Oceans (PFMDB) data sets. The merged data are unique in that they include multi-year, global daytime estimates of aerosol optical depth (AOD) derived from AVHRR channels 1 and 2 (0.63 and 0.83 μ m, respectively), along with an effective Angstrom exponent derived from the AOD retrievals (Ignatov and Nalli, 2002). Recent enhancements in the aerosol data constitute an improvement over the Phase I algorithm (Nalli and Stowe, 2002) which relied only on channel 1 AOD and the ratio of normalized reflectance from channels 1 and 2. The Angstrom exponent and channel 2 AOD provide important statistical information about the particle size distribution of the aerosol. The SST bias can be parametrically expressed as a function of observed AVHRR channels 1 and 2 slant-path AOD, normalized reflectance ratio and the Angstrom exponent. Based upon these empirical relationships, aerosol correction equations are then derived for the daytime multichannel and nonlinear SST (MCSST and NLSST) algorithms. Separate sets of coefficients are utilized for two aerosol modes, these being stratospheric/tropospheric (e.g., volcanic aerosol) and tropospheric (e.g., dust, smoke). The algorithms are subsequently applied to retrospective PATMOS data to demonstrate the potential for climate applications. The minimization of cold biases in the AVHRR SST, as demonstrated in this work, should improve its overall utility for the general user community.

A Comparison Between SST and AOT Derived from AVHRR and MODIS Data in the Frame of the CREPAD Program

NASA Astrophysics Data System (ADS)

Robles-Gonzalez, Cristina; Fernandez-Renau, Alix; Lopez Gordillo, Noelia; Sevilla, Angel Garcia; Suarez, Juana Santana

2010-12-01

Since 1997, the INTA-CREPAD (Centre for REception, Processing, Archiving and Dissemination of Earth Observation Data) program distributes freely some of the most demanded low-resolution remote sensing products: SST, Ocean Chl-a, NDVI, AOD... The data input for such products are captured at the Canary Space Station (Centro Espacial de Canarias, CEC). The data sensors received at the station and used in the CREPAD program are AVHRR, SEAWIFS and MODIS. In this study SST and AOD retrieved by CREPAD algorithms from AVHRR and the SEADAS derived SST and AOD from MODIS have compared. SST values agree very well within 0.1±0.5oC and the coefficient of correlation of the images is 0.9. AOD validation gives good results taking into account the differences in the algorithms used. Mean AOD difference at 0.630 μm is 0.01±0.05 and the correlation coefficient is 0.6.

Evaluation of Different MODIS AOD Retrieval Algorithms for PM (sub 2.5) Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Burrows, Erica; Coffield, Shane; Crane, Breanna

2016-01-01

This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP (Minority University Research and Education Project) Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns PM (sub 2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM (sub 2.5) varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target versus Deep Blue), Collections (5.1 versus 6) and spatial resolutions (10-kilometers versus 3-kilometers) for cities in the Western, Midwestern and Southeastern U.S. We developed and validated PM (sub 2.5) prediction models using remotely-sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM (sub 2.5) models, especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Our study re-establishes the connection between PM (sub 2.5) and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM (sub 2.5) data and health data from the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS), our statistical analysis showed that heart attack and stroke occurrences had the strongest correlations with PM (sub 2.5).

Evaluation of Different MODIS AOD Retrieval Algorithms for PM2.5 Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Crosson, W. L.; Burrows, E. C.; Coffield, S.; Crane, B.

2016-12-01

This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns (PM2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM2.5 varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target vs. Deep Blue), Collections (5.1 vs. 6) and spatial resolutions (10-km vs. 3-km) for cities in the Western, Midwestern and Southeastern United States. We developed and validated PM2.5 prediction models using remotely sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM2.5 models, and especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Finally, our study re-establishes the connection between PM2.5 and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM2.5 data and health data from the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS), our statistical analysis showed that heart attack and stroke occurrences had the strongest correlations with PM2.5.

Determination of nocturnal aerosol properties from a combination of lunar photometer and lidar observations

NASA Astrophysics Data System (ADS)

Li, Donghui; Li, Zhengqiang; Lv, Yang; Zhang, Ying; Li, Kaitao; Xu, Hua

2015-10-01

Aerosol plays a key role in the assessment of global climate change and environmental health, while observation is one of important way to deepen the understanding of aerosol properties. In this study, the newly instrument - lunar photometer is used to measure moonlight and nocturnal column aerosol optical depth (AOD, τ) is retrieved. The AOD algorithm is test and verified with sun photometer both in high and low aerosol loading. Ångström exponent (α) and fine/coarse mode AOD (τf, τc) 1 is derived from spectral AOD. The column aerosol properties (τ, α, τf, τc) inferred from the lunar photometer is analyzed based on two month measurement in Beijing. Micro-pulse lidar has advantages in retrieval of aerosol vertical distribution, especially in night. However, the typical solution of lidar equation needs lidar ratio(ratio of aerosol backscatter and extinction coefficient) assumed in advance(Fernald method), or constrained by AOD2. Yet lidar ratio is varied with aerosol type and not easy to fixed, and AOD is used of daylight measurement, which is not authentic when aerosol loading is different from day and night. In this paper, the nocturnal AOD measurement from lunar photometer combined with mie scattering lidar observations to inverse aerosol extinction coefficient(σ) profile in Beijing is discussed.

The satellite-based remote sensing of particulate matter (PM) in support to urban air quality: PM variability and hot spots within the Cordoba city (Argentina) as revealed by the high-resolution MAIAC-algorithm retrievals applied to a ten-years dataset (2

NASA Astrophysics Data System (ADS)

Della Ceca, Lara Sofia; Carreras, Hebe A.; Lyapustin, Alexei I.; Barnaba, Francesca

2016-04-01

Particulate matter (PM) is one of the major harmful pollutants to public health and the environment [1]. In developed countries, specific air-quality legislation establishes limit values for PM metrics (e.g., PM10, PM2.5) to protect the citizens health (e.g., European Commission Directive 2008/50, US Clean Air Act). Extensive PM measuring networks therefore exist in these countries to comply with the legislation. In less developed countries air quality monitoring networks are still lacking and satellite-based datasets could represent a valid alternative to fill observational gaps. The main PM (or aerosol) parameter retrieved from satellite is the 'aerosol optical depth' (AOD), an optical parameter quantifying the aerosol load in the whole atmospheric column. Datasets from the MODIS sensors on board of the NASA spacecrafts TERRA and AQUA are among the longest records of AOD from space. However, although extremely useful in regional and global studies, the standard 10 km-resolution MODIS AOD product is not suitable to be employed at the urban scale. Recently, a new algorithm called Multi-Angle Implementation of Atmospheric Correction (MAIAC) was developed for MODIS, providing AOD at 1 km resolution [2]. In this work, the MAIAC AOD retrievals over the decade 2003-2013 were employed to investigate the spatiotemporal variation of atmospheric aerosols over the Argentinean city of Cordoba and its surroundings, an area where a very scarce dataset of in situ PM data is available. The MAIAC retrievals over the city were firstly validated using a 'ground truth' AOD dataset from the Cordoba sunphotometer operating within the global AERONET network [3]. This validation showed the good performances of the MAIAC algorithm in the area. The satellite MAIAC AOD dataset was therefore employed to investigate the 10-years trend as well as seasonal and monthly patterns of particulate matter in the Cordoba city. The first showed a marked increase of AOD over time, particularly evident in some areas of the city (hot spots). These hot spots were put in relation with changes in vehicular traffic flows after the construction of new roads in the urban area. The monthly-resolved analysis showed a marked seasonal cycle, evidencing the influence of both meteorological conditions and season-dependent sources on the AOD parameter. For instance, in the Cordoba rural area an increase of AOD is observed during March-April, which is the soybean harvesting period, the main agricultural activity in the region. Furthermore, higher AOD signals were observed in the vicinity of main roads during summer months (December to February), likely related to the increase in vehicular traffic flow due to tourism. Long-range transport is also shown to play a role at the city scale, as high AODs throughout the study area are observed between August and November. In fact, this is the biomass-burning season over the Amazon region and over most of South America, with huge amounts of fire-related particles injected into the atmosphere and transported across the continent [4]. References [1] WHO, 2013; REVIHAAP, Project Technical Report [2] Lyapustin et al., 2011; doi: 10.1029/2010JD014986 [3] Holben et al., 1998, doi:10.1016/S0034-4257(98)00031-5 [4] Castro et al., 2013; doi:10.1016/j.atmosres.2012.10.026

Assessment of OMI Near-UV Aerosol Optical Depth over Land

NASA Technical Reports Server (NTRS)

Ahn, Changwoo; Torres, Omar; Jethva, Hiren

2014-01-01

This is the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the near-UV observations by the Ozone Monitoring Instrument (OMI) onboard the Aura satellite. The OMI-retrieved AOD by the ultraviolet (UV) aerosol algorithm (OMAERUV version 1.4.2) was evaluated using collocated Aerosol Robotic Network (AERONET) level 2.0 direct Sun AOD measurements over 8 years (2005-2012). A time series analysis of collocated satellite and ground-based AOD observations over 8 years shows no discernible drift in OMI's calibration. A rigorous validation analysis over 4 years (2005-2008) was carried out at 44 globally distributed AERONET land sites. The chosen locations are representative of major aerosol types such as smoke from biomass burning or wildfires, desert mineral dust, and urban/industrial pollutants. Correlation coefficient (p) values of 0.75 or better were obtained at 50 percent of the sites with about 33 percent of the sites in the analysis reporting regression line slope values larger than 0.70 but always less than unity. The combined AERONET-OMAERUV analysis of the 44 sites yielded a p of 0.81, slope of 0.79, Y intercept of 0.10, and 65 percent OMAERUV AOD falling within the expected uncertainty range (largest of 30 percent or 0.1) at 440 nanometers. The most accurate OMAERUV retrievals are reported over northern Africa locations where the predominant aerosol type is desert dust and cloud presence is less frequent. Reliable retrievals were documented at many sites characterized by urban-type aerosols with low to moderate AOD values, concentrated in the boundary layer. These results confirm that the near-ultraviolet observations are sensitive to the entire aerosol column. A simultaneous comparison of OMAERUV, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue, and Multiangle Imaging Spectroradiometer (MISR) AOD retrievals to AERONET measurements was also carried out to evaluate the OMAERUV accuracy in relation to those of the standard aerosol satellite products. The outcome of the comparison indicates that OMAERUV, MODIS Deep Blue, and MISR retrieval accuracies in arid and semiarid environments are statistically comparable.

Evaluation of the MODIS Retrievals of Dust Aerosol over the Ocean during PRIDE

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Holben, Brent N.; Livingston, John M.; Russell, Philip B.; Maring, Hal

2002-01-01

The Puerto Rico Dust Experiment (PRIDE) took place in Roosevelt Roads, Puerto Rico from June 26 to July 24,2000 to study the radiative and physical properties of African dust aerosol transported into the region. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from the MODerate Imaging Spectro-radiometer (MODIS) with sunphotometer and in-situ aerosol measurements. Over the ocean, the MODIS algorithm retrieves aerosol optical depth (AOD) as well as information about the aerosols size distribution. During PRIDE, MODIS derived AODs in the red wavelengths (0.66 micrometers) compare closely with AODs measured from sunphotometers, but, are too large at blue and green wavelengths (0.47 and 0.55 micrometers) and too small in the infrared (0.87 micrometers). This discrepancy of spectral slope results in particle size distributions retrieved by MODIS that are small compared to in-situ measurements, and smaller still when compared to sunphotometer sky radiance inversions. The differences in size distributions are, at least in part, associated with MODIS simplification of dust as spherical particles. Analysis of this PRIDE data set is a first step towards derivation of realistic non-spherical models for future MODIS retrievals.

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

NASA Astrophysics Data System (ADS)

Huttunen, Jani; Kokkola, Harri; Mielonen, Tero; Esa Juhani Mononen, Mika; Lipponen, Antti; Reunanen, Juha; Vilhelm Lindfors, Anders; Mikkonen, Santtu; Erkki Juhani Lehtinen, Kari; Kouremeti, Natalia; Bais, Alkiviadis; Niska, Harri; Arola, Antti

2016-07-01

In order to have a good estimate of the current forcing by anthropogenic aerosols, knowledge on past aerosol levels is needed. Aerosol optical depth (AOD) is a good measure for aerosol loading. However, dedicated measurements of AOD are only available from the 1990s onward. One option to lengthen the AOD time series beyond the 1990s is to retrieve AOD from surface solar radiation (SSR) measurements taken with pyranometers. In this work, we have evaluated several inversion methods designed for this task. We compared a look-up table method based on radiative transfer modelling, a non-linear regression method and four machine learning methods (Gaussian process, neural network, random forest and support vector machine) with AOD observations carried out with a sun photometer at an Aerosol Robotic Network (AERONET) site in Thessaloniki, Greece. Our results show that most of the machine learning methods produce AOD estimates comparable to the look-up table and non-linear regression methods. All of the applied methods produced AOD values that corresponded well to the AERONET observations with the lowest correlation coefficient value being 0.87 for the random forest method. While many of the methods tended to slightly overestimate low AODs and underestimate high AODs, neural network and support vector machine showed overall better correspondence for the whole AOD range. The differences in producing both ends of the AOD range seem to be caused by differences in the aerosol composition. High AODs were in most cases those with high water vapour content which might affect the aerosol single scattering albedo (SSA) through uptake of water into aerosols. Our study indicates that machine learning methods benefit from the fact that they do not constrain the aerosol SSA in the retrieval, whereas the LUT method assumes a constant value for it. This would also mean that machine learning methods could have potential in reproducing AOD from SSR even though SSA would have changed during the observation period.

An Observing System Simulation Experiment (OSSE) Investigating the OMI Aerosol Products Using Simulated Aerosol and Atmospheric Fields from the NASA GEOS-5 Model

NASA Astrophysics Data System (ADS)

Colarco, P. R.; Gasso, S.; Jethva, H. T.; Buchard, V.; Ahn, C.; Torres, O.; daSilva, A.

2016-12-01

Output from the NASA Goddard Earth Observing System, version 5 (GEOS-5) Earth system model is used to simulate the top-of-atmosphere 354 and 388 nm radiances observed by the Ozone Monitoring Instrument (OMI) onboard the Aura spacecraft. The principle purpose of developing this simulator tool is to compute from the modeled fields the so-called OMI Aerosol Index (AI), which is a more fundamental retrieval product than higher level products such as the aerosol optical depth (AOD) or absorbing aerosol optical depth (AAOD). This lays the groundwork for eventually developing a capability to assimilate either the OMI AI or its radiances, which would provide further constraint on aerosol loading and absorption properties for global models. We extend the use of the simulator capability to understand the nature of the OMI aerosol retrieval algorithms themselves in an Observing System Simulation Experiment (OSSE). The simulated radiances are used to calculate the AI from the modeled fields. These radiances are also provided to the OMI aerosol algorithms, which return their own retrievals of the AI, AOD, and AAOD. Our assessment reveals that the OMI-retrieved AI can be mostly harmonized with the model-derived AI given the same radiances provided a common surface pressure field is assumed. This is important because the operational OMI algorithms presently assume a fixed pressure field, while the contribution of molecular scattering to the actual OMI signal in fact responds to the actual atmospheric pressure profile, which is accounted for in our OSSE by using GEOS-5 produced atmospheric reanalyses. Other differences between the model and OMI AI are discussed, and we present a preliminary assessment of the OMI AOD and AAOD products with respect to the known inputs from the GEOS-5 simulation.

Aerosol variation over Continental Europe from 1980 to 2015 Using ALAD Aerosol Retrievals

NASA Astrophysics Data System (ADS)

Che, Yahui; Xue, Yong; Mei, Linlu; Guang, Jie; She, Lu

2017-04-01

The Advanced Very High Resolution Radiometer (AVHRR) on-board National Oceanic and Atmospheric Administration (NOAA) series satellites has been used to observe the Earth and is the only spaceborne instrument which can provide users continuous long time series global coverage for more than 35 years since 1979. The initial purpose of AVHRR is for cloud detection and monitoring thermal emission of the Earth so that it lacks visible channels (only 0.64μm) and spaceborne which is unignorably unfavourable to its applications in aerosol retrieving over bright and inhomogeneous surface. Using AVHRR data, an Algorithm for the retrieval over Land of the Aerosol optical Depth (ALAD) was developed data which has great potential to be used to retrieve long time series aerosol globally from 1979 to now. The core of ALAD is to assume that the contribution of aerosol at 3.75μm wavelength to reflectance at top of the atmosphere (TOA) is negligible. At this basis, one stable and firm relationship between surface reflectance at 0.64μm and 3.75μm will be found by regression analysis at different land types after separating reflectance from radiance at 3.75μm. Then, an atmospheric transfer model is applied to calculate AOD at 0.64μm. In this study, we recalibrate AVHRR Global Area Coverage (GAC) data and then apply ALAD to calculate AOD over continental Europe (30°N to 80°N, 170°W to 40°E) to investigate aerosol changes and possible reason in past 35 years from 1981 to 2015. The retrieved AOD has been validated with ground-based data from Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) and AErosol RObotic NETwork (AERONET). The correlation of ALAD AOD with AERONET and ACTRIS is 0.77 and 0.66, respectively. Further, we also make long time series comparison of monthly averaged ALAD AOD with AERONET, ACTRIS and MODIS, showing that ALAD underestimate AOD a little. Finally, we find that the AOD over most areas in Continental Europe are less than 0.3, even less than 0.1, changing little without any obvious increase.

The Collection 6 'dark-target' MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Mattoo, Shana; Munchak, Leigh A.; Kleidman, Richard G.; Patadia, Falguni; Gupta, Pawan; Remer, Lorraine

2013-01-01

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

NASA Astrophysics Data System (ADS)

Patadia, Falguni; Levy, Robert C.; Mattoo, Shana

2018-06-01

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in window regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are similar, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Intercomparison of Desert Dust Optical Depth from Satellite Measurements

NASA Technical Reports Server (NTRS)

Carboni, E.; Thomas, G. E.; Sayer, A. M.; Siddans, R.; Poulsen, C. A.; Grainger, R. G.; Ahn, C.; Antoine, D.; Bevan, S.; Braak, R.;

Aerosol correction for remotely sensed sea surface temperatures from the National Oceanic and Atmospheric Administration advanced very high resolution radiometer

NASA Astrophysics Data System (ADS)

Nalli, Nicholas R.; Stowe, Larry L.

2002-10-01

This research presents the first-phase derivation and implementation of daytime aerosol correction algorithms for remotely sensed sea surface temperature (SST) from the advanced very high resolution radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To accomplish this, a long-term (1990-1998), global AVHRR-buoy match-up database was created by merging the NOAA/NASA Pathfinder Atmospheres and Pathfinder Oceans data sets. The merged data set is unique in that it includes daytime estimates of aerosol optical depth (AOD) derived from AVHRR channel 1 (0.63 μm) under global conditions of significant aerosol loading. Histograms of retrieved AOD reveal monomodal, lognormal distributions for both tropospheric and stratospheric aerosol modes. It is then shown empirically that the SST depression caused under each aerosol mode can be expressed as a linear function in two predictors, these being the slant path AOD retrieved from AVHRR channel 1 along with the ratio of channels 1 and 2 normalized reflectances. On the basis of these relationships, parametric equations are derived to provide an aerosol correction for retrievals from the daytime NOAA operational multichannel and nonlinear SST algorithms. Separate sets of coefficients are utilized for two aerosol modes: tropospheric (i.e., dust, smoke, haze) and stratospheric/tropospheric (i.e., following a major volcanic eruption). The equations are shown to significantly reduce retrieved SST bias using an independent set of match-ups. Eliminating aerosol-induced bias in both real-time and retrospective processing will enhance the utility of the AVHRR SST for the general user community and in climate research.

Monthly analysis of PM ratio characteristics and its relation to AOD.

PubMed

Sorek-Hamer, Meytar; Broday, David M; Chatfield, Robert; Esswein, Robert; Stafoggia, Massimo; Lepeule, Johanna; Lyapustin, Alexei; Kloog, Itai

2017-01-01

Airborne particulate matter (PM) is derived from diverse sources-natural and anthropogenic. Climate change processes and remote sensing measurements are affected by the PM properties, which are often lumped into homogeneous size fractions that show spatiotemporal variation. Since different sources are attributed to different geographic locations and show specific spatial and temporal PM patterns, we explored the spatiotemporal characteristics of the PM 2.5 /PM 10 ratio in different areas. Furthermore, we examined the statistical relationships between AERONET aerosol optical depth (AOD) products, satellite-based AOD, and the PM ratio, as well as the specific PM size fractions. PM data from the northeastern United States, from San Joaquin Valley, CA, and from Italy, Israel, and France were analyzed, as well as the spatial and temporal co-measured AOD products obtained from the MultiAngle Implementation of Atmospheric Correction (MAIAC) algorithm. Our results suggest that when both the AERONET AOD and the AERONET fine-mode AOD are available, the AERONET AOD ratio can be a fair proxy for the ground PM ratio. Therefore, we recommend incorporating the fine-mode AERONET AOD in the calibration of MAIAC. Along with a relatively large variation in the observed PM ratio (especially in the northeastern United States), this shows the need to revisit MAIAC assumptions on aerosol microphysical properties, and perhaps their seasonal variability, which are used to generate the look-up tables and conduct aerosol retrievals. Our results call for further scrutiny of satellite-borne AOD, in particular its errors, limitations, and relation to the vertical aerosol profile and the particle size, shape, and composition distribution. This work is one step of the required analyses to gain better understanding of what the satellite-based AOD represents. The analysis results recommend incorporating the fine-mode AERONET AOD in MAIAC calibration. Specifically, they indicate the need to revisit MAIAC regional aerosol microphysical model assumptions used to generate look-up tables (LUTs) and conduct retrievals. Furthermore, relatively large variations in measured PM ratio shows that adding seasonality in aerosol microphysics used in LUTs, which is currently static, could also help improve accuracy of MAIAC retrievals. These results call for further scrutiny of satellite-borne AOD for better understanding of its limitations and relation to the vertical aerosol profile and particle size, shape, and composition.

MODIS 3km Aerosol Product: Algorithm and Global Perspective

NASA Technical Reports Server (NTRS)

Remer, L. A.; Mattoo, S.; Levy, R. C.; Munchak, L.

2013-01-01

After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

NASA Astrophysics Data System (ADS)

Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

2011-12-01

Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

An Evaluation of MODIS-Retrieved Aerosol Optical Depth over a Mountainous AERONET Site in the Southeastern US

NASA Technical Reports Server (NTRS)

Sherman, James P.; Gupta, Pawan; Levy, Robert C.; Sherman, Peter J.

2016-01-01

The literature shows that aerosol optical depth (AOD) derived from the MODIS Collection 5 (C5) dark target algorithm has been extensively validated by spatiotemporal collocation with AERONET sites on both global and regional scales.Although generally comparing well over the eastern US region, poor performance over mountains in other regions indicate the need to evaluate the MODIS product over a mountain site. This study compares MODIS C5 AOD at 550nm to AOD measured at the Appalachian State University AERONET site in Boone, NC over 30 months between August 2010 and September 2013. For the combined Aqua and Terra datasets, although more than 70% of the 500 MODIS AOD measurements agree with collocated AERONET AOD to within error envelope of +/- (0.05 + 15%), MODIS tends to have a low bias (0.02-0.03). The agreement between MODIS and AERONET AOD does not depend on MODIS quality assurance confidence (QAC) value. However, when stratified by satellite, MODIS-Terra data does not perform as well as Aqua, with especially poor correlation (r = 0.39) for low aerosol loading conditions (AERONET AOD less than 0.15).Linear regressions between Terra and AERONET possess statistically-different slopes for AOD < 0.15 and AOD > or = 0.15. AERONET AOD measured only during MODIS overpass hours is highly correlated with daily-averaged AERONET AOD. MODIS monthly-averaged AOD also tracks that of AERONET over the study period. These results indicate that MODIS is sensitive to the day-to-day variability, as well as the annual cycle of AOD over the Appalachian State AERONET site. The complex topography and high seasonality in AOD and vegetation indices allow us to specifically evaluate MODIS dark target algorithm surface albedo and aerosol model assumptions at a regionally-representative SE US mountain site.

Evaluation of VIIRS AOD over North China Plain: biases from aerosol models

NASA Astrophysics Data System (ADS)

Zhu, J.; Xia, X.; Wang, J.; Chen, H.; Zhang, J.; Oo, M. M.; Holz, R.

2014-12-01

With the launch of the Visible Infrared Imaging Radiometer Suit (VIIRS) instrument onboard Suomi National Polar-orbiting Partnership(S-NPP) in late 2011, the aerosol products of VIIRS are receiving much attention.To date, mostevaluations of VIIRS aerosol productswere carried out about aerosol optical depth (AOD). To further assess the VIIRS AOD in China which is a heavy polluted region in the world,we made a comparison between VIIRS AOD and CE-318 radiometerobservation at the following three sites overNorth China Plain (NCP): metropolis-Beijing (AERONET), suburbs-XiangHe (AERONET) and regional background site- Xinglong (CARSNET).The results showed the VIIRS AOD at 550 nm has a positive mean bias error (MBE) of 0.14-0.15 and root mean square error (RMBE) 0.20. Among three sites, Beijing is mainly a source of bias with MBE 0.17-0.18 and RMBE 0.23-0.24, and this bias is larger than some recent global statics recently published in the literature. Further analysis shows that this large bias in VIIRS AOD overNCP may be partly caused by the aerosol model selection in VIIRS aerosol inversion. According to the retrieval of sky radiance from CE-318 at three sites, aerosols in NCP have high mean real part of refractive indices (1.52-1.53), large volume mean radius (0.17-0.18) and low concentration (0.04-0.09) of fine aerosol, and small mean radius (2.86-2.92) and high concentration (0.06-0.16) of coarse mode aerosol. These observation-based aerosol single scattering properties and size of fine and coarse aerosols differ fromthe aerosol properties used in VIIRSoperational algorithm.The dominant aerosol models used in VIIRS algorithm for these three sites are less polluted urban aerosol in Beijing and low-absorption smoke in other two sites, all of which don't agree with the high imaginary part of refractive indices from CE-318 retrieval. Therefore, the aerosol models in VIIRS algorithm are likely to be refined in NCP region.

Comparing MODIS-Terra and GOES surface albedo for New York City NY, Baltimore MD and Washington DC for 2005

NASA Astrophysics Data System (ADS)

Mubenga, K.; Hoff, R.; McCann, K.; Chu, A.; Prados, A.

2006-05-01

The NOAA GOES Aerosol and Smoke Product (GASP) is a product displaying the Aerosol Optical Depth (AOD) over the United States. The GASP retrieval involves discriminating the upwelling radiance from the atmosphere from that of the variable underlying surface. Unlike other sensors with more visible and near- infrared spectral channels such as MODIS, the sensors on GOES 8 through 12 only have one visible and a several far infrared channels. The GASP algorithm uses the detection of the second-darkest pixel from the visible channel over a 28-day period as the reference from which a radiance look-up table gives the corresponding AOD. GASP is reliable in capturing the AOD during large events. As an example, GASP was able to precisely show the Alaska and British Columbia smoke plume advecting from Alaska to the northeastern U.S. during the summer of 2004. Knapp et al. (2005) has shown that the AOD retrieval for GOES- 8 is within +/-0.13 of AERONET ground data with a coefficient of correlation of 0.72. Prados (this meeting) will update that study. However, GASP may not be as reliable when it comes to observing smaller AOD events in the northeast where the surface brightness is relatively high. The presence of large cities, such as New York, increases the surface albedo and produces a bright background against which it may be difficult to deduce the AOD. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Earth Observing System Terra and Aqua platforms provides an independent measurement of the surface albedo at a resolution greater than available on GOES. In this research, the MODIS and GOES surface albedo product for New York, Washington and Baltimore are compared in order to see how we can improve the AOD retrieval in urban areas for air quality applications. Ref: K. Knapp et al. 2005. Toward aerosol optical depth retrievals over land from GOES visible radiances: determining surface reflectance. Int.Journal of Remote Sensing 26, 4097-4116

Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements

NASA Astrophysics Data System (ADS)

Andrews, Elisabeth; Ogren, John A.; Kinne, Stefan; Samset, Bjorn

2017-05-01

Here we present new results comparing aerosol optical depth (AOD), aerosol absorption optical depth (AAOD) and column single scattering albedo (SSA) obtained from in situ vertical profile measurements with AERONET ground-based remote sensing from two rural, continental sites in the US. The profiles are closely matched in time (within ±3 h) and space (within 15 km) with the AERONET retrievals. We have used Level 1.5 inversion retrievals when there was a valid Level 2 almucantar retrieval in order to be able to compare AAOD and column SSA below AERONET's recommended loading constraint (AOD > 0.4 at 440 nm). While there is reasonable agreement for the AOD comparisons, the direct comparisons of in situ-derived to AERONET-retrieved AAOD (or SSA) reveal that AERONET retrievals yield higher aerosol absorption than obtained from the in situ profiles for the low aerosol optical depth conditions prevalent at the two study sites. However, it should be noted that the majority of SSA comparisons for AOD440 > 0.2 are, nonetheless, within the reported SSA uncertainty bounds. The observation that, relative to in situ measurements, AERONET inversions exhibit increased absorption potential at low AOD values is generally consistent with other published AERONET-in situ comparisons across a range of locations, atmospheric conditions and AOD values. This systematic difference in the comparisons suggests a bias in one or both of the methods, but we cannot assess whether the AERONET retrievals are biased towards high absorption or the in situ measurements are biased low. Based on the discrepancy between the AERONET and in situ values, we conclude that scaling modeled black carbon concentrations upwards to match AERONET retrievals of AAOD should be approached with caution as it may lead to aerosol absorption overestimates in regions of low AOD. Both AERONET retrievals and in situ measurements suggest there is a systematic relationship between SSA and aerosol amount (AOD or aerosol light scattering) - specifically that SSA decreases at lower aerosol loading. This implies that the fairly common assumption that AERONET SSA values retrieved at high-AOD conditions can be used to obtain AAOD at low-AOD conditions may not be valid.

Optimal estimation for global ground-level fine particulate matter concentrations

NASA Astrophysics Data System (ADS)

Donkelaar, Aaron; Martin, Randall V.; Spurr, Robert J. D.; Drury, Easan; Remer, Lorraine A.; Levy, Robert C.; Wang, Jun

2013-06-01

We develop an optimal estimation (OE) algorithm based on top-of-atmosphere reflectances observed by the MODIS satellite instrument to retrieve near-surface fine particulate matter (PM2.5). The GEOS-Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5. We adjust the shape of the GEOS-Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1-σ error = 1 µg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 µg/m3 + 31%) and Europe of ±(3.5 µg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of ±(3.0 µg/m3 + 35%), may be underestimated. Global population-weighted PM2.5 at 50% relative humidity is estimated as 27.8 µg/m3 at 0.1° × 0.1° resolution.

Satellite remote sensing of aerosol and cloud properties over Eurasia

NASA Astrophysics Data System (ADS)

Sogacheva, Larisa; Kolmonen, Pekka; Saponaro, Giulia; Virtanen, Timo; Rodriguez, Edith; Sundström, Anu-Maija; Atlaskina, Ksenia; de Leeuw, Gerrit

2015-04-01

Satellite remote sensing provides the spatial distribution of aerosol and cloud properties over a wide area. In our studies large data sets are used for statistical studies on aerosol and cloud interaction in an area over Fennoscandia, the Baltic Sea and adjacent regions over the European mainland. This area spans several regimes with different influences on aerosol cloud interaction such as a the transition from relative clean air over Fennoscandia to more anthropogenically polluted air further south, and the influence maritime air over the Baltic and oceanic air advected from the North Atlantic. Anthropogenic pollution occurs in several parts of the study area, and in particular near densely populated areas and megacities, but also in industrialized areas and areas with dense traffic. The aerosol in such areas is quite different from that produced over the boreal forest and has different effects on air quality and climate. Studies have been made on the effects of aerosols on air quality and on the radiation balance in China. The aim of the study is to study the effect of these different regimes on aerosol-cloud interaction using a large aerosol and cloud data set retrieved with the (Advanced) Along Track Scanning Radiometer (A)ATSR Dual View algorithm (ADV) further developed at Finnish Meteorological Institute and aerosol and cloud data provided by MODIS. Retrieval algorithms for aerosol and clouds have been developed for the (A)ATSR, consisting of a series of instruments of which we use the second and third one: ATSR-2 which flew on the ERS-2 satellite (1995-2003) and AATSR which flew on the ENVISAT satellite (2002-2012) (both from the European Space Agency, ESA). The ADV algorithm provides aerosol data on a global scale with a default resolution of 10x10km2 (L2) and an aggregate product on 1x1 degree (L3). Optional, a 1x1 km2 retrieval products is available over smaller areas for specific studies. Since for the retrieval of AOD no prior knowledge is needed on surface properties, the surface reflectance can be independently retrieved using the AOD for atmospheric correction. For the retrieval of cloud properties, the SACURA algorithm has been implemented in the ADV/ASV aerosol retrieval suite. Cloud properties retrieved from AATSR data are cloud fraction, cloud optical thickness, cloud top height, cloud droplet effective radius, liquid water path. Aerosol and cloud properties are applied for different studies over the Eurasia area. Using the simultaneous retrieval of aerosol and cloud properties allows for study of the transition from the aerosol regime to the cloud regime, such as changes in effective radius or AOD (aerosol optical depth) to COT (cloud optical thickness). The column- integrated aerosol extinction, aerosol optical depth or AOD, which is primarily reported from satellite observations, can be used as a proxy for cloud condensation nuclei (CCN) and hence contains information on the ability of aerosol particles to form clouds. Hence, connecting this information with direct observations of cloud properties provides information on aerosol-cloud interactions.

Simultaneous Retrieval of Aerosol Optical Depth and Surface Reflectance over Land within Short Temporal Interval Using MSG Data

NASA Astrophysics Data System (ADS)

Li, C.; Xue, Y.; Li, Y. J.; Yang, L. K.; Hou, T. T.

2012-04-01

Aerosols cause a major uncertainty in the research of climatology and global change, whereas satellite aerosol remote sensing over land still remains a big challenge. Due to their short time repeat cycle, geostationary satellites are capable of monitoring the temporal features of aerosols, while its limited number of visible bands is an obstacle. On the other hand, a main uncertainty in aerosol retrieval is the difficulty to separate the relatively weaker contribution of the atmosphere to the signal received by the satellite from the contribution of the Earth's surface. In this paper, an analytical retrieval strategy is presented to solve the both problems above. For the lack of surface reflectance, we use the Ross-Li BRDF (Bidirectional Reflectance Distribution Function) model and assume that the surface reflective property changes mainly due to the change of illumination geometry in a short time interval while the kernals of Ross-Li model remain the same. For the limited visible band, we take advantage of the Aerosol Optical Depth (AOD) consistence within short distances, thus to reduce the number of unknown parameters. A parameterization of the atmospheric radiative transfer model is used which is proved to be proper to retrieve aerosol and surface parameters by sensitivity analysis. Taking the three kernels of kernel-driven BRDF model and AOD as unknown parameters and based on prior knowledge of aerosol types, a series of nonlinear equations can be established then. Both AOD and surface reflectance can be obtained by using a numerical method to solve these equations. By applying this method, called LABITS-MSG (Land Aerosol and Bidirectional reflectance Inversion by Time Series technique for MSG), to data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations on board Meteosat Second Generation (MSG), we obtain regional maps of AOD and surface reflectance in July 11, 2010 within a temporal interval of as short as 1 hour, and a spatial resolution of 10 km. Preliminary validation results by comparing our retrieved AOD with Aerosol Robotic Network (AERONET) data show that the correlation coefficient R is about 0.81, the root-mean-square error (RMSE) is less than 0.1, and the uncertainty is found to be Δτ = ± 0.05 ± 0.20τ. Time serial comparison of MSG and AERONET AODs on Granada site also shows a good fitting. To conclude, this algorithm shows its potential to retrieve real-time AODs over land from geostationary satellites.

Global Long-Term SeaWiFS Deep Blue Aerosol Products available at NASA GES DISC

NASA Technical Reports Server (NTRS)

Shen, Suhung; Sayer, A. M.; Bettenhausen, Corey; Wei, Jennifer C.; Ostrenga, Dana M.; Vollmer, Bruce E.; Hsu, Nai-Yung; Kempler, Steven J.

2012-01-01

Long-term climate data records about aerosols are needed in order to improve understanding of air quality, radiative forcing, and for many other applications. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a global well-calibrated 13- year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). Recently, global aerosol products derived from SeaWiFS with Deep Blue algorithm (SWDB) have become available for the entire mission, as part of the NASA Making Earth Science data records for Use in Research for Earth Science (MEaSUREs) program. The latest Deep Blue algorithm retrieves aerosol properties not only over bright desert surfaces, but also vegetated surfaces, oceans, and inland water bodies. Comparisons with AERONET observations have shown that the data are suitable for quantitative scientific use [1],[2]. The resolution of Level 2 pixels is 13.5x13.5 km2 at the center of the swath. Level 3 daily and monthly data are composed by using best quality level 2 pixels at resolution of both 0.5ox0.5o and 1.0ox1.0o. Focusing on the southwest Asia region, this presentation shows seasonal variations of AOD, and the result of comparisons of 5-years (2003- 2007) of AOD from SWDB (Version 3) and MODIS Aqua (Version 5.1) for Dark Target (MYD-DT) and Deep Blue (MYD-DB) algorithms.

Assessment of 10-Year Global Record of Aerosol Products from the OMI Near-UV Algorithm

NASA Astrophysics Data System (ADS)

Ahn, C.; Torres, O.; Jethva, H. T.

2014-12-01

Global observations of aerosol properties from space are critical for understanding climate change and air quality applications. The Ozone Monitoring Instrument (OMI) onboard the EOS-Aura satellite provides information on aerosol optical properties by making use of the large sensitivity to aerosol absorption and dark surface albedo in the UV spectral region. These unique features enable us to retrieve both aerosol extinction optical depth (AOD) and single scattering albedo (SSA) successfully from radiance measurements at 354 and 388 nm by the OMI near UV aerosol algorithm (OMAERUV). Recent improvements to algorithms in conjunction with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Atmospheric Infrared Sounder (AIRS) carbon monoxide data also reduce uncertainties due to aerosol layer heights and types significantly in retrieved products. We present validation results of OMI AOD against space and time collocated Aerosol Robotic Network (AERONET) measured AOD values over multiple stations representing major aerosol episodes and regimes. We also compare the OMI SSA against the inversion made by AERONET as well as an independent network of ground-based radiometer called SKYNET in Japan, China, South-East Asia, India, and Europe. The outcome of the evaluation analysis indicates that in spite of the "row anomaly" problem, affecting the sensor since mid-2007, the long-term aerosol record shows remarkable sensor stability. The OMAERUV 10-year global aerosol record is publicly available at the NASA data service center web site (http://disc.sci.gsfc.nasa.gov/Aura/data-holdings/OMI/omaeruv_v003.shtml).

Monthly AOD maps combining strengths of remote sensing products

NASA Astrophysics Data System (ADS)

Kinne, Stefan

2010-05-01

The mid-visible aerosol optical depth (AOD) is the most prominent property to quantify aerosol amount the atmospheric column. Almost all aerosol retrievals of satellite sensors provide estimates for this property, however, often with limited success. As sensors differ in capabilities individual retrievals have local and regional strengths and weaknesses. Focusing on individual retrieval strengths a satellite based AOD composite has been constructed. Hereby, every retrieval performance has been assessed in statistical comparisons to ground-based sun-photometry, which provide highly accurate references though only at few globally distributed monitoring sites. Based on these comparisons, which consider bias as well as spatial patterns and seasonality, the regionally best performing satellite AOD products are combined. The resulting remote sensing AOD composite provide a general reference for the spatial and temporal AOD distribution on an (almost) global basis - solely tied to sensor data.

The Dynamics of Fine Mode Aerosol Optical Properties in South Korea from AERONET and Aircraft Observations with a Focus on Cases with Large Cloud Fraction and/or Fog During KORUS-AQ

NASA Astrophysics Data System (ADS)

Eck, T. F.; Holben, B. N.; Kim, J.; Choi, M.; Giles, D. M.; Schafer, J.; Smirnov, A.; Slutsker, I.; Sinyuk, A.; Sorokin, M. G.; Kraft, J.; Beyersdorf, A. J.; Anderson, B. E.; Thornhill, K. L., II; Crawford, J. H.

2017-12-01

The focus of our investigation is of major fine mode aerosol pollution events in South Korea, particularly when cloud fraction is high. This work includes the analysis of AERONET data utilizing the Spectral Deconvolution Algorithm to enable detection of fine mode aerosol optical depth (AOD) near to clouds. Additionally we analyze the newly developed AERONET V3 data sets that have significant changes to cloud screening algorithms. Comparisons of aerosol optical depth are made between AERONET Versions 2 and 3 for both long-term climatology data and for specific 2016 cases, especially in May and June 2016 during the KORUS-AQ field campaign. In general the Version 3 cloud screening allows many more fine mode AOD observations to reach Level 2 when cloud amount is high, as compared to Version 2, thereby enabling more thorough analysis of these types of cases. Particular case studies include May 25-26, 2016 when cloud fraction was very high over much of the peninsula, associated with a frontal passage and advection of pollution from China. Another interesting case is June 9, 2016 when there was fog over the West Sea, and this seems to have affected aerosol properties well downwind over the Korean peninsula. Both of these days had KORUS-AQ research aircraft flights that provided observations of aerosol absorption, particle size distributions and vertical profiles of extinction. AERONET retrievals and aircraft in situ measurements both showed high single scattering albedo (weak absorption) on these cloudy days. We also investigate the relationship between aerosol fine mode radius and AOD and the relationship between aerosol single scattering albedo and fine mode particle radius from the AERONET almucantar retrievals for the interval of April through June 2016 for 17 AERONET sites in South Korea. Strongly increasing fine mode radius (leading to greater scattering efficiency) as fine mode AOD increased is one factor contributing to a trend of increasing single scattering albedo as fine AOD increased. Additionally, the new AERONET Hybrid sky radiance scan retrievals that allow for inversions to be made at much smaller solar zenith angles are analyzed and compared to almucantar retrievals.

Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms

NASA Astrophysics Data System (ADS)

de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team

2011-12-01

The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for several runs with a prescribed set of aerosol models and an a priori data set derived from the median of AEROCOM model runs. The aerosol models and a priori data can be used in several ways, i.e. fully prescribed or with some freedom to choose a combination of aerosol models, based on the a priori or not. Another test gives insight in the effect of the cloud masks used, i.e. retrievals using the same cloud mask (the AATSR APOLLO cloud mask for collocated instruments) are compared with runs using the standard cloud masks. Tests to determine the influence of surface treatment are planned as well. The results of all these tests are evaluated by an independent team which compares the retrieval results with ground-based remote sensing (in particular AERONET) and in-situ data, and by a scoring method. Results are compared with other satellites such as MODIS and MISR. Blind tests using synthetic data are part of the algorithm characterization. The presentation will summarize results of the ongoing phase 1 inter-comparison and evaluation work within the Aerosol_cci project.

Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS.

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.

2005-04-01

The Chesapeake Lighthouse Aircraft Measurements for Satellites (CLAMS) experiment took place from 10 July to 2 August 2001 in a combined ocean-land region that included the Chesapeake Lighthouse [Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE)] and the Wallops Flight Facility (WFF), both along coastal Virginia. This experiment was designed mainly for validating instruments and algorithms aboard the Terra satellite platform, including the Moderate Resolution Imaging Spectroradiometer (MODIS). Over the ocean, MODIS retrieved aerosol optical depths (AODs) at seven wavelengths and an estimate of the aerosol size distribution. Over the land, MODIS retrieved AOD at three wavelengths plus qualitative estimates of the aerosol size. Temporally coincident measurements of aerosol properties were made with a variety of sun photometers from ground sites and airborne sites just above the surface. The set of sun photometers provided unprecedented spectral coverage from visible (VIS) to the solar near-infrared (NIR) and infrared (IR) wavelengths. In this study, AOD and aerosol size retrieved from MODIS is compared with similar measurements from the sun photometers. Over the nearby ocean, the MODIS AOD in the VIS and NIR correlated well with sun-photometer measurements, nearly fitting a one-to-one line on a scatterplot. As one moves from ocean to land, there is a pronounced discontinuity of the MODIS AOD, where MODIS compares poorly to the sun-photometer measurements. Especially in the blue wavelength, MODIS AOD is too high in clean aerosol conditions and too low under larger aerosol loadings. Using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative code to perform atmospheric correction, the authors find inconsistency in the surface albedo assumptions used by the MODIS lookup tables. It is demonstrated how the high bias at low aerosol loadings can be corrected. By using updated urban/industrial aerosol climatology for the MODIS lookup table over land, it is shown that the low bias for larger aerosol loadings can also be corrected. Understanding and improving MODIS retrievals over the East Coast may point to strategies for correction in other locations, thus improving the global quality of MODIS. Improvements in regional aerosol detection could also lead to the use of MODIS for monitoring air pollution.

New Approach to Monitor Transboundary Particulate Pollution over Northeast Asia

NASA Technical Reports Server (NTRS)

Park, M. E.; Song, C. H.; Park, R. S.; Lee, Jaehwa; Kim, J.; Lee, S.; Woo, J. H.; Carmichael, G. R.; Eck, Thomas F.; Holben, Brent N.;

New approach to monitor transboundary particulate pollution over Northeast Asia

NASA Astrophysics Data System (ADS)

Park, M. E.; Song, C. H.; Park, R. S.; Lee, J.; Kim, J.; Lee, S.; Woo, J.-H.; Carmichael, G. R.; Eck, T. F.; Holben, B. N.; Lee, S.-S.; Song, C. K.; Hong, Y. D.

2014-01-01

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched.

Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing

PubMed Central

Seidel, Felix; Schläpfer, Daniel; Nieke, Jens; Itten, Klaus I.

2008-01-01

This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD) by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτλaer) and compared to the available measuring sensitivity of the sensor (NEΔLλsensor). This is done for multiple signal-to-noise ratios (SNR) and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions. PMID:27879801

Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing.

PubMed

Seidel, Felix; Schläpfer, Daniel; Nieke, Jens; Itten, Klaus I

2008-03-18

This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD) by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτ λ aer ) and compared to the available measuring sensitivity of the sensor (NE ΔL λ sensor ). This is done for multiple signal-to-noise ratios (SNR) and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions.

Retrieval of Aerosol Optical Properties from Ground-Based Remote Sensing Measurements: Aerosol Asymmetry Factor and Single Scattering Albedo

NASA Astrophysics Data System (ADS)

Qie, L.; Li, Z.; Li, L.; Li, K.; Li, D.; Xu, H.

2018-04-01

The Devaux-Vermeulen-Li method (DVL method) is a simple approach to retrieve aerosol optical parameters from the Sun-sky radiance measurements. This study inherited the previous works of retrieving aerosol single scattering albedo (SSA) and scattering phase function, the DVL method was modified to derive aerosol asymmetric factor (g). To assess the algorithm performance at various atmospheric aerosol conditions, retrievals from AERONET observations were implemented, and the results are compared with AERONET official products. The comparison shows that both the DVL SSA and g were well correlated with those of AERONET. The RMSD and the absolute value of MBD deviations between the SSAs are 0.025 and 0.015 respectively, well below the AERONET declared SSA uncertainty of 0.03 for all wavelengths. For asymmetry factor g, the RMSD deviations are smaller than 0.02 and the absolute values of MBDs smaller than 0.01 at 675, 870 and 1020 nm bands. Then, considering several factors probably affecting retrieval quality (i.e. the aerosol optical depth (AOD), the solar zenith angle, and the sky residual error, sphericity proportion and Ångström exponent), the deviations for SSA and g of these two algorithms were calculated at varying value intervals. Both the SSA and g deviations were found decrease with the AOD and the solar zenith angle, and increase with sky residual error. However, the deviations do not show clear sensitivity to the sphericity proportion and Ångström exponent. This indicated that the DVL algorithm is available for both large, non-spherical particles and spherical particles. The DVL results are suitable for the evaluation of aerosol direct radiative effects of different aerosol types.

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

NASA Astrophysics Data System (ADS)

de Leeuw, Gerrit; Sogacheva, Larisa; Rodriguez, Edith; Kourtidis, Konstantinos; Georgoulias, Aristeidis K.; Alexandri, Georgia; Amiridis, Vassilis; Proestakis, Emmanouil; Marinou, Eleni; Xue, Yong; van der A, Ronald

2018-02-01

The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth - AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

DSCOVR EPIC AERUV Parameters

Atmospheric Science Data Center

2018-06-27

... AerosolType      The aerosol type associated with the ground pixel.        1 - Smoke ... algorithm flag associated with the ground pixel:     Aerosol extinction Optical Depth (AOD), Single Scattering Albedo (SSA), and     Aerosol Absorption Optical Depth (AAOD) Retrievals:        0 - Most ...

Aeronet-based Microphysical and Optical Properties of Smoke-dominated Aerosol near Source Regions and Transported over Oceans, and Implications for Satellite Retrievals of Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.

2013-01-01

Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad families of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA 0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA 0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savanna at Mongu (Zambia), with average SSA 0.85 in the midvisible. These can serve as candidate sets of aerosol microphysicaloptical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.

Aerosol optical depth determination in the UV using a four-channel precision filter radiometer

NASA Astrophysics Data System (ADS)

Carlund, Thomas; Kouremeti, Natalia; Kazadzis, Stelios; Gröbner, Julian

2017-03-01

The determination of aerosol properties, especially the aerosol optical depth (AOD) in the ultraviolet (UV) wavelength region, is of great importance for understanding the climatological variability of UV radiation. However, operational retrievals of AOD at the biologically most harmful wavelengths in the UVB are currently only made at very few places. This paper reports on the UVPFR (UV precision filter radiometer) sunphotometer, a stable and robust instrument that can be used for AOD retrievals at four UV wavelengths. Instrument characteristics and results of Langley calibrations at a high-altitude site were presented. It was shown that due to the relatively wide spectral response functions of the UVPFR, the calibration constants (V0) derived from Langley plot calibrations underestimate the true extraterrestrial signals. Accordingly, correction factors were introduced. In addition, the instrument's spectral response functions also result in an apparent air-mass-dependent decrease in ozone optical depth used in the AOD determinations. An adjusted formula for the calculation of AOD, with a correction term dependent on total column ozone amount and ozone air mass, was therefore introduced. Langley calibrations performed 13-14 months apart resulted in sensitivity changes of ≤ 1.1 %, indicating good instrument stability. Comparison with a high-accuracy standard precision filter radiometer, measuring AOD at 368-862 nm wavelengths, showed consistent results. Also, very good agreement was achieved by comparing the UVPFR with AOD at UVB wavelengths derived with a Brewer spectrophotometer, which was calibrated against the UVPFR at an earlier date. Mainly due to non-instrumental uncertainties connected with ozone optical depth, the total uncertainty of AOD in the UVB is higher than that reported from AOD instruments measuring in UVA and visible ranges. However, the precision can be high among instruments using harmonized algorithms for ozone and Rayleigh optical depth as well as for air mass terms. For 4 months of comparison measurements with the UVPFR and a Brewer, the root mean squared AOD differences were found < 0.01 at all the 306-320 nm Brewer wavelengths.

High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

NASA Technical Reports Server (NTRS)

Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.

Quantifying the response of the ORAC aerosol optical depth retrieval for MSG SEVIRI to aerosol model assumptions

NASA Astrophysics Data System (ADS)

Bulgin, Claire E.; Palmer, Paul I.; Merchant, Christopher J.; Siddans, Richard; Gonzi, Siegfried; Poulsen, Caroline A.; Thomas, Gareth E.; Sayer, Andrew M.; Carboni, Elisa; Grainger, Roy G.; Highwood, Eleanor J.; Ryder, Claire L.

2011-03-01

We test the response of the Oxford-RAL Aerosol and Cloud (ORAC) retrieval algorithm for Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (MSG SEVIRI) to changes in the aerosol properties used in the dust aerosol model, using data from the Dust Outflow and Deposition to the Ocean (DODO) flight campaign in August 2006. We find that using the observed DODO free tropospheric aerosol size distribution and refractive index increases simulated top of the atmosphere radiance at 0.55 μm assuming a fixed aerosol optical depth of 0.5 by 10-15%, reaching a maximum difference at low solar zenith angles. We test the sensitivity of the retrieval to the vertical distribution of the aerosol and find that this is unimportant in determining simulated radiance at 0.55 μm. We also test the ability of the ORAC retrieval when used to produce the GlobAerosol data set to correctly identify continental aerosol outflow from the African continent, and we find that it poorly constrains aerosol speciation. We develop spatially and temporally resolved prior distributions of aerosols to inform the retrieval which incorporates five aerosol models: desert dust, maritime, biomass burning, urban, and continental. We use a Saharan Dust Index and the GEOS-Chem chemistry transport model to describe dust and biomass burning aerosol outflow and compare AOD using our speciation against the GlobAerosol retrieval during January and July 2006. We find AOD discrepancies of 0.2-1 over regions of intense biomass burning outflow, where AOD from our aerosol speciation and GlobAerosol speciation can differ by as much as 50-70%.

Mixing weight determination for retrieving optical properties of polluted dust with MODIS and AERONET data

NASA Astrophysics Data System (ADS)

Chang, Kuo-En; Hsiao, Ta-Chih; Hsu, N. Christina; Lin, Neng-Huei; Wang, Sheng-Hsiang; Liu, Gin-Rong; Liu, Chian-Yi; Lin, Tang-Huang

2016-08-01

In this study, an approach in determining effective mixing weight of soot aggregates from dust-soot aerosols is proposed to improve the accuracy of retrieving properties of polluted dusts by means of satellite remote sensing. Based on a pre-computed database containing several variables (such as wavelength, refractive index, soot mixing weight, surface reflectivity, observation geometries and aerosol optical depth (AOD)), the fan-shaped look-up tables can be drawn out accordingly for determining the mixing weights, AOD and single scattering albedo (SSA) of polluted dusts simultaneously with auxiliary regional dust properties and surface reflectivity. To validate the performance of the approach in this study, 6 cases study of polluted dusts (dust-soot aerosols) in Lower Egypt and Israel were examined with the ground-based measurements through AErosol RObotic NETwork (AERONET). The results show that the mean absolute differences could be reduced from 32.95% to 6.56% in AOD and from 2.67% to 0.83% in SSA retrievals for MODIS aerosol products when referenced to AERONET measurements, demonstrating the soundness of the proposed approach under different levels of dust loading, mixing weight and surface reflectivity. Furthermore, the developed algorithm is capable of providing the spatial distribution of the mixing weights and removing the requirement to assume that the dust plume properties are uniform. The case study further shows the spatially variant dust-soot mixing weight would improve the retrieval accuracy in AODmixture and SSAmixture about 10.0% and 1.4% respectively.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and <0.5 km, respectively. At RSP's footprint scale ( 323 m), mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

Combing Visible and Infrared Spectral Tests for Dust Identification

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Levy, Robert; Kleidman, Richard; Remer, Lorraine; Mattoo, Shana

2016-01-01

The MODIS Dark Target aerosol algorithm over Ocean (DT-O) uses spectral reflectance in the visible, near-IR and SWIR wavelengths to determine aerosol optical depth (AOD) and Angstrom Exponent (AE). Even though DT-O does have "dust-like" models to choose from, dust is not identified a priori before inversion. The "dust-like" models are not true "dust models" as they are spherical and do not have enough absorption at short wavelengths, so retrieved AOD and AE for dusty regions tends to be biased. The inference of "dust" is based on postprocessing criteria for AOD and AE by users. Dust aerosol has known spectral signatures in the near-UV (Deep blue), visible, and thermal infrared (TIR) wavelength regions. Multiple dust detection algorithms have been developed over the years with varying detection capabilities. Here, we test a few of these dust detection algorithms, to determine whether they can be useful to help inform the choices made by the DT-O algorithm. We evaluate the following methods: The multichannel imager (MCI) algorithm uses spectral threshold tests in (0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 micrometer) channels and spatial uniformity test [Zhao et al., 2010]. The NOAA dust aerosol index (DAI) uses spectral contrast in the blue channels (412nm and 440nm) [Ciren and Kundragunta, 2014]. The MCI is already included as tests within the "Wisconsin" (MOD35) Cloud mask algorithm.

Retrieval of aerosol optical depth over bare soil surfaces using time series of MODIS imagery

NASA Astrophysics Data System (ADS)

Yuan, Zhengwu; Yuan, Ranyin; Zhong, Bo

2014-11-01

Aerosol Optical Depth (AOD) is one of the key parameters which can not only reflect the characterization of atmospheric turbidity, but also identify the climate effects of aerosol. The current MODIS aerosol estimation algorithm over land is based on the "dark-target" approach which works only over densely vegetated surfaces. For non-densely vegetated surfaces (such as snow/ice, desert, and bare soil surfaces), this method will be failed. In this study, we develop an algorithm to derive AOD over the bare soil surfaces. Firstly, this method uses the time series of MODIS imagery to detect the " clearest" observations during the non-growing season in multiple years for each pixel. Secondly, the "clearest" observations after suitable atmospheric correction are used to fit the bare soil's bidirectional reflectance distribution function (BRDF) using Kernel model. As long as the bare soil's BRDF is established, the surface reflectance of "hazy" observations can be simulated. Eventually, the AOD over the bare soil surfaces are derived. Preliminary validation results by comparing with the ground measurements from AERONET at Xianghe sites show a good agreement.

Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

NASA Technical Reports Server (NTRS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Perez Garcia-Pando, Carlos

2017-01-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

NASA Astrophysics Data System (ADS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Pérez García-Pando, Carlos

2017-03-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets. The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Aerosol retrieval experiments in the ESA Aerosol_cci project

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.; de Leeuw, G.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.

2013-03-01

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010-2013) algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components and their mixing ratios. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data qualitatively by visible analysis of monthly mean AOD maps and quantitatively by comparing global daily gridded satellite data against daily average AERONET sun photometer observations for the different versions of each algorithm. The analysis allowed an assessment of sensitivities of all algorithms which helped define the best algorithm version for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR.

Moderate Imaging Resolution Spectroradiometer (MODIS) Aerosol Optical Depth Retrieval for Aerosol Radiative Forcing

NASA Astrophysics Data System (ADS)

Asmat, A.; Jalal, K. A.; Ahmad, N.

2018-02-01

The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AODMODIS) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AODMODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AODAERONET) and the results shows high correlation coefficient (R2) for AODMODIS and AODAERONET with 0.93. AODMODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm-2 for top of atmosphere (TOA), -2.13 Wm-2 at the surface and 2.00 Wm-2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD Retrievals Against Ground Sunphotometer Observations Over East Asia

NASA Technical Reports Server (NTRS)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-01-01

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51% of VIIRS Environmental Data Record (EDR) AOD, 37% of GOCI AOD, 33% of VIIRS Intermediate Product (IP) AOD, 26% of Terra MODIS C6 3km AOD, and 16% of Aqua MODIS C6 3km AOD fell within the reference expected error (EE) envelope (+/-0.05/+/- 0.15 AOD). Comparing against AERONET AOD over the JapanSouth Korea region, 64% of EDR, 37% of IP, 61% of GOCI, 39% of Terra MODIS, and 56% of Aqua MODIS C6 3km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3km products had positive biases.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

NASA Astrophysics Data System (ADS)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-02-01

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra MODIS C6 3 km AOD, and 16 % of Aqua MODIS C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra MODIS, and 56 % of Aqua MODIS C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

2016-01-01

The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.

Global and Regional Trends of Aerosol Optical Depth over Land and Ocean Using SeaWiFS Measurements from 1997 to 2010

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Gautam, R.; Sayer, A. M.; Bettenhausen, C.; Li, C.; Jeong, M. J.; Tsay, S. C.; Holben, B. N.

2012-01-01

Both sensor calibration and satellite retrieval algorithm play an important role in the ability to determine accurately long-term trends from satellite data. Owing to the unprecedented accuracy and long-term stability of its radiometric calibration, the SeaWiFS measurements exhibit minimal uncertainty with respect to sensor calibration. In this study, we take advantage of this well-calibrated set of measurements by applying a newly-developed aerosol optical depth (AOD) retrieval algorithm over land and ocean to investigate the distribution of AOD, and to identify emerging patterns and trends in global and regional aerosol loading during its 13-year mission. Our results indicate that the averaged AOD trend over global ocean is weakly positive from 1998 to 2010 and comparable to that observed by MODIS but opposite in sign to that observed by AVHRR during overlapping years. On a smaller scale, different trends are found for different regions. For example, large upward trends are found over the Arabian Peninsula that indicate a strengthening of the seasonal cycle of dust emission and transport processes over the whole region as well as over downwind oceanic regions. In contrast, a negative-neutral tendency is observed over the desert/arid Saharan region as well as in the associated dust outflow over the north Atlantic. Additionally, we found decreasing trends over the eastern US and Europe, and increasing trends over countries such as China and India that are experiencing rapid economic development. In general, these results are consistent with those derived from ground-based AERONET measurements.

Development and Applications of a New, High-Resolution, Operational MISR Aerosol Product

NASA Astrophysics Data System (ADS)

Garay, M. J.; Diner, D. J.; Kalashnikova, O.

2014-12-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the operational MISR algorithm performs well, with about 75% of MISR AOD retrievals falling within 0.05 or 20% × AOD of the paired validation data from the ground-based Aerosol Robotic Network (AERONET), and is able to distinguish aerosol particles by size and sphericity, over both land and water. These attributes enable a variety of applications, including aerosol transport model validation and global air quality assessment. Motivated by the adverse impacts of aerosols on human health at the local level, and taking advantage of computational speed advances that have occurred since the launch of Terra, we have implemented an operational MISR aerosol product with 4.4 km spatial resolution that maintains, and sometimes improves upon, the quality of the 17.6 km resolution product. We will describe the performance of this product relative to the heritage 17.6 km product, the global AERONET validation network, and high spatial density AERONET-DRAGON sites. Other changes that simplify product content, and make working with the data much easier for users, will also be discussed. Examples of how the new product demonstrates finer spatial variability of aerosol fields than previously retrieved, and ways this new dataset can be used for studies of local aerosol effects, will be shown.

A New Satellite Aerosol Retrieval Using High Spectral Resolution Oxygen A-Band Measurements

NASA Astrophysics Data System (ADS)

Winker, D. M.; Zhai, P.

2014-12-01

Efforts to advance current satellite aerosol retrieval capabilities have mostly focused on polarimetric techniques. While there has been much interest in recent decades in the use of the oxygen A-band for retrievals of cloud height or surface pressure, these techniques are mostly based on A-band measurements with relatively low spectral resolution. We report here on a new aerosol retrieval technique based on high-resolution A-band spectra. Our goal is the development of a technique to retrieve aerosol absorption, one of the critical parameters affecting the global radiation budget and one which is currently poorly constrained by satellite measurements. Our approach relies on two key factors: 1) the use of high spectral resolution measurements which resolve the A-band line structure, and 2) the use of co-located lidar profile measurements to constrain the vertical distribution of scatterers. The OCO-2 satellite, launched in July this year and now flying in formation with the CALIPSO satellite, carries an oxygen A-band spectrometer with a spectral resolution of 21,000:1. This is sufficient to resolve the A-band line structure, which contains information on atmospheric photon path lengths. Combining channels with oxygen absorption ranging from weak to strong allows the separation of atmospheric and surface scattering. An optimal estimation algorithm for simultaneous retrieval of aerosol optical depth, aerosol absorption, and surface albedo has been developed. Lidar profile data is used for scene identification and to provide constraints on the vertical distribution of scatterers. As calibrated OCO-2 data is not expected until the end of this year, the algorithm has been developed and tested using simulated OCO-2 spectra. The simulations show that AOD and surface albedo can be retrieved with high accuracy. Retrievals of aerosol single scatter albedo are encouraging, showing good performance when AOD is larger than about 0.15. Retrieval performance improves as the albedo of the underlying surface increases. Thus, the technique shows great promise for retrieving the absorption optical depth of aerosols located above clouds. This presentation will discuss the basis of the approach and results of the A-band/lidar retrievals based on simulated data.

Global and regional trends of aerosol optical depth over land and ocean using SeaWiFS measurements from 1997 to 2010

NASA Astrophysics Data System (ADS)

Hsu, N. C.; Gautam, R.; Sayer, A. M.; Bettenhausen, C.; Li, C.; Jeong, M. J.; Tsay, S.-C.; Holben, B. N.

2012-09-01

Both sensor calibration and satellite retrieval algorithm play an important role in the ability to determine accurately long-term trends from satellite data. Owing to the unprecedented accuracy and long-term stability of its radiometric calibration, SeaWiFS measurements exhibit minimal uncertainty with respect to sensor calibration. In this study, we take advantage of this well-calibrated set of measurements by applying a newly-developed aerosol optical depth (AOD) retrieval algorithm over land and ocean to investigate the distribution of AOD, and to identify emerging patterns and trends in global and regional aerosol loading during its 13-yr mission. Our correlation analysis between climatic indices (such as ENSO) and AOD suggests strong relationships for Saharan dust export as well as biomass-burning activity in the tropics, associated with large-scale feedbacks. The results also indicate that the averaged AOD trend over global ocean is weakly positive from 1998 to 2010 and comparable to that observed by MODIS but opposite in sign to that observed by AVHRR during overlapping years. On regional scales, distinct tendencies are found for different regions associated with natural and anthropogenic aerosol emission and transport. For example, large upward trends are found over the Arabian Peninsula that indicate a strengthening of the seasonal cycle of dust emission and transport processes over the whole region as well as over downwind oceanic regions. In contrast, a negative-neutral tendency is observed over the desert/arid Saharan region as well as in the associated dust outflow over the north Atlantic. Additionally, we found decreasing trends over the eastern US and Europe, and increasing trends over countries such as China and India that are experiencing rapid economic development. In general, these results are consistent with those derived from ground-based AERONET measurements.

Explicit and Observation-based Aerosol Treatment in Tropospheric NO2 Retrieval over China from the Ozone Monitoring Instrument

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.; Boersma, F.; Pinardi, G.; Wang, Y.; Chimot, J.; Wagner, T.; Xie, P.; Eskes, H.; Van Roozendael, M.; Hendrick, F.

2017-12-01

Satellite retrieval of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is influenced by aerosols substantially. Aerosols affect the retrieval of "effective cloud fraction (CF)" and "effective cloud top pressure (CP)" that are used in the subsequent NO2 retrieval to account for the presentence of clouds. And aerosol properties and vertical distributions directly affect the NO2 air mass factor (AMF) calculations. Our published POMINO algorithm uses a parallelized LIDORT-driven AMFv6 code to derive CF, CP and NO2 VCD. Daily information on aerosol optical properties are taken from GEOS-Chem simulations, with aerosol optical depth (AOD) further constrained by monthly MODIS AOD. However, the published algorithm does not include an observation-based constraint of aerosol vertical distribution. Here we construct a monthly climatological observation dataset of aerosol extinction profiles, based on Level-2 CALIOP data over 2007-2015, to further constrain aerosol vertical distributions. GEOS-Chem captures the temporal variations of CALIOP aerosol layer heights (ALH) but has an overall underestimate by about 0.3 km. It tends to overestimate the aerosol extinction by 10% below 2 km but with an underestimate by 30% above 2 km, leading to a low bias by 10-30% in the retrieved tropospheric NO2 VCD. After adjusting GEOS-Chem aerosol extinction profiles by the CALIOP monthly ALH climatology, the retrieved NO2 VCDs increase by 4-16% over China on a monthly basis in 2012. The improved NO2 VCDs are better correlated to independent MAX-DOAS observations at three sites than POMINO and DOMINO are - especially for the polluted cases, R2 reaches 0.76 for the adjusted POMINO, much higher than that for the published POMINO (0.68) and DOMINO (0.38). The newly retrieved CP increases by 60 hPa on average, because of a stronger aerosol screening effect. Compared to the CF used in DOMINO, which implicitly includes aerosol information, our improved CF is much lower and can reach a value of zero on actual cloud-free days. Overall, constraining aerosol vertical profiles greatly improves the retrievals of clouds and NO2 VCDs from satellite remote sensing. Our algorithm can be applied, with minimum modifications, to formaldehyde, sulfur dioxide and other species with similar retrieval methodologies.

Quantifying the sensitivity of aerosol optical depths retrieved from MSG SEVIRI to a priori data

NASA Astrophysics Data System (ADS)

Bulgin, C. E.; Palmer, P. I.; Merchant, C. J.; Siddans, R.; Poulsen, C.; Grainger, R. G.; Thomas, G.; Carboni, E.; McConnell, C.; Highwood, E.

2009-12-01

Radiative forcing contributions from aerosol direct and indirect effects remain one of the most uncertain components of the climate system. Satellite observations of aerosol optical properties offer important constraints on atmospheric aerosols but their sensitivity to prior assumptions must be better characterized before they are used effectively to reduce uncertainty in aerosol radiative forcing. We assess the sensitivity of the Oxford-RAL Aerosol and Cloud (ORAC) optimal estimation retrieval of aerosol optical depth (AOD) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) to a priori aerosol data. SEVIRI is a geostationary satellite instrument centred over Africa and the neighbouring Atlantic Ocean, routinely sampling desert dust and biomass burning outflow from Africa. We quantify the uncertainty in SEVIRI AOD retrievals in the presence of desert dust by comparing retrievals that use prior information from the Optical Properties of Aerosol and Cloud (OPAC) database, with those that use measured aerosol properties during the Dust Outflow and Deposition to the Ocean (DODO) aircraft campaign (August, 2006). We also assess the sensitivity of retrieved AODs to changes in solar zenith angle, and the vertical profile of aerosol effective radius and extinction coefficient input into the retrieval forward model. Currently the ORAC retrieval scheme retrieves AODs for five aerosol types (desert dust, biomass burning, maritime, urban and continental) and chooses the most appropriate AOD based on the cost functions. We generate an improved prior aerosol speciation database for SEVIRI based on a statistical analysis of a Saharan Dust Index (SDI) determined using variances of different brightness temperatures, and organic and black carbon tracers from the GEOS-Chem chemistry transport model. This database is described as a function of season and time of day. We quantify the difference in AODs between those chosen based on prior information from the SDI and GEOS-Chem and those chosen based on the smallest cost function.

Indirect estimation of absorption properties for fine aerosol particles using AATSR observations: a case study of wildfires in Russia in 2010

NASA Astrophysics Data System (ADS)

Rodriguez, E.; Kolmonen, P.; Virtanen, T. H.; Sogacheva, L.; Sundstrom, A.-M.; de Leeuw, G.

2015-08-01

The Advanced Along-Track Scanning Radiometer (AATSR) on board the ENVISAT satellite is used to study aerosol properties. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured reflectances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties. The retrieval process utilizes a combination of four aerosol components, each of which is defined by their (lognormal) size distribution and a complex refractive index: a weakly and a strongly absorbing fine-mode component, coarse mode sea salt aerosol and coarse mode desert dust aerosol). These components are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). In the AATSR aerosol retrieval algorithm, the mixing of these components is decided by minimizing the error function given by the sum of the differences between measured and calculated path radiances at 3-4 wavelengths, where the path radiances are varied by varying the aerosol component mixing ratios. The continuous variation of the fine-mode components allows for the continuous variation of the fine-mode aerosol absorption. Assuming that the correct aerosol model (i.e. the correct mixing fractions of the four components) is selected during the retrieval process, also other aerosol properties could be computed such as the single scattering albedo (SSA). Implications of this assumption regarding the ratio of the weakly/strongly absorbing fine-mode fraction are investigated in this paper by evaluating the validity of the SSA thus obtained. The SSA is indirectly estimated for aerosol plumes with moderate-to-high AOD resulting from wildfires in Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE (root mean square error) is 0.03 for SSA and 0.02 for AAOD lower than 0.05. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, with generally lower AATSR-estimated SSA values over areas affected by wildfires.

Steps Toward an EOS-Era Aerosol Type Climatology

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2012-01-01

We still have a way to go to develop a global climatology of aerosol type from the EOS-era satellite data record that currently spans more than 12 years of observations. We have demonstrated the ability to retrieve aerosol type regionally, providing a classification based on the combined constraints on particle size, shape, and single-scattering albedo (SSA) from the MISR instrument. Under good but not necessarily ideal conditions, the MISR data can distinguish three-to-five size bins, two-to-four bins in SSA, and spherical vs. non-spherical particles. However, retrieval sensitivity varies enormously with scene conditions. So, for example, there is less information about aerosol type when the mid-visible aerosol optical depth (AOD) is less that about 0.15 or 0.2, or when the range of scattering angles observed is reduced by solar geometry, even though the quality of the AOD retrieval itself is much less sensitive to these factors. This presentation will review a series of studies aimed at assessing the capabilities, as well as the limitations, of MISR aerosol type retrievals involving wildfire smoke, desert dust, volcanic ash, and urban pollution, in specific cases where suborbital validation data are available. A synthesis of results, planned upgrades to the MISR Standard aerosol algorithm to improve aerosol type retrievals, and steps toward the development of an aerosol type quality flag for the Standard product, will also be covered.

MODIS volcanic ash retrievals vs FALL3D transport model: a quantitative comparison

NASA Astrophysics Data System (ADS)

Corradini, S.; Merucci, L.; Folch, A.

2010-12-01

Satellite retrievals and transport models represents the key tools to monitor the volcanic clouds evolution. Because of the harming effects of fine ash particles on aircrafts, the real-time tracking and forecasting of volcanic clouds is key for aviation safety. Together with the security reasons also the economical consequences of a disruption of airports must be taken into account. The airport closures due to the recent Icelandic Eyjafjöll eruption caused millions of passengers to be stranded not only in Europe, but across the world. IATA (the International Air Transport Association) estimates that the worldwide airline industry has lost a total of about 2.5 billion of Euro during the disruption. Both security and economical issues require reliable and robust ash cloud retrievals and trajectory forecasting. The intercomparison between remote sensing and modeling is required to assure precise and reliable volcanic ash products. In this work we perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands operating in the VIS-TIR spectral range and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 micron have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. Three MODIS images collected the October 28, 29 and 30 on Mt. Etna volcano during the 2002 eruption have been considered as test cases. The results show a general good agreement between the retrieved and the modeled volcanic clouds in the first 300 km from the vents. Even if the modeled volcanic cloud area is systematically wider than the retrieved area, the ash total mass is comparable and varies between 35 and 60 kt and between 20 and 42 kt for FALL3D and MODIS respectively. The mean AOD values are in good agreement and approximately equal to 0.8. When the whole volcanic clouds are considered the ash areas and the total ash masses, computed by FALL3D model are significantly greater than the same parameters retrieved from the MODIS data, while the mean AOD values remain in a very good agreement and equal to about 0.6. The volcanic cloud direction in its distal part is not coincident for the 29 and 30 October 2002 images due to the difference between the real and the modeled local wind fields. Finally the MODIS maps show regions of high mass and AOD due to volcanic puffs not modeled by FALL3D.

Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

NASA Technical Reports Server (NTRS)

Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier

2011-01-01

The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.

Assimilating AOD retrievals from GOCI and VIIRS to forecast surface PM2.5 episodes over Eastern China

NASA Astrophysics Data System (ADS)

Pang, Jiongming; Liu, Zhiquan; Wang, Xuemei; Bresch, Jamie; Ban, Junmei; Chen, Dan; Kim, Jhoon

2018-04-01

In this study, Geostationary Ocean Color Imager (GOCI) AOD and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD data were assimilated to forecast surface PM2.5 concentrations over Eastern China, by using the three-dimensional variational (3DAVR) data assimilation (DA) system, to compare DA impacts by assimilating AOD retrievals from these two types of satellites. Three experiments were conducted, including a CONTROL without the AOD assimilation, and GOCIDA and VIIRSDA with the assimilation of AOD retrievals from GOCI and VIIRS, respectively. By utilizing the Weather Research and Forecasting with Chemistry (WRF/Chem) model, 48-h forecasts were initialized at each 06 UTC from 19 November to 06 December 2013. These forecasts were evaluated with 248 ground-based measurements from the air quality monitoring network across 67 China cities. The results show that overall the CONTROL underestimated surface PM2.5 concentrations, especially over Jing-Jin-Ji (JJJ) region and Yangtze River Delta (YRD) region. Both the GOCIDA and VIIRSDA produced higher surface PM2.5 concentrations mainly over Eastern China, which fits well with the PM2.5 measurements at these eastern sites, with more than 8% error reductions (ER). Moreover, compared to CONTROL, GOCIDA reduced 14.0% and 6.4% error on JJJ region and YRD region, respectively, while VIIRSDA reduced respectively 2.0% and 13.4% error over the corresponding areas. During the heavy polluted period, VIIRSDA improved all sites within YRD region, and GOCIDA enhanced 84% sites. Meanwhile, GOCIDA improved 84% sites on JJJ region, while VIIRSDA did not affect that region. These geographic distinctions might result from spatial dissimilarity between GOCI AOD and VIIRS AOD at time intervals. Moreover, the larger increment produced by AOD DA under stable meteorological conditions could lead to a longer duration (e.g., 1-2 days, > 2 days) of AOD DA impacts. Even though with AOD DA, surface PM2.5 concentrations were still underestimated clearly over heavy polluted periods. And 3% sites performed worse, where low PM2.5 values were observed and CONTROL performed well. With this study, the results indicate that AOD DA can partially improve the accuracy of PM2.5 forecasts. And the obvious geographic differences on forecasts emphasize the potential and importance of combining AOD retrievals from GOCI and VIIRS into data assimilation.

Intercomparison of Satellite Dust Retrieval Products over the West African Sahara During the Fennec Campaign in June 2011

NASA Technical Reports Server (NTRS)

Banks, J.R.; Brindley, H. E.; Flamant, C.; Garay, M. J.; Hsu, N. C.; Kalashnikova, O. V.; Klueser, L.; Sayer, A. M.

2013-01-01

Dust retrievals over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface properties, and the magnitude of the dust loading. The period of study corresponds to the time of the first Fennec intensive measurement campaign, which provides new ground-based and aircraft measurements of the dust characteristics and loading. Validation using ground-based AERONET sunphotometer data indicate that of the satellite instruments, SEVIRI is most able to retrieve dust during optically thick dust events, whereas IASI and MODIS perform better at low dust loadings. This may significantly affect observations of dust emission and the mean dust climatology. MISR and MODIS are least sensitive to variations in meteorological conditions, while SEVIRI tends to overestimate the aerosol optical depth (AOD) under moist conditions (with a bias against AERONET of 0.31), especially at low dust loadings where the AOD<1. Further comparisons are made with airborne LIDAR measurements taken during the Fennec campaign, which provide further evidence for the inferences made from the AERONET comparisons. The effect of surface properties on the retrievals is also investigated. Over elevated surfaces IASI retrieves AODs which are most consistent with AERONET observations, while the AODs retrieved by MODIS tend to be biased low. In contrast, over the least emissive surfaces IASI significantly underestimates the AOD (with a bias of -0.41), while MISR and SEVIRI show closest agreement.

Seasonal monitoring and estimation of regional aerosol distribution over Po valley, northern Italy, using a high-resolution MAIAC product

NASA Astrophysics Data System (ADS)

Arvani, Barbara; Pierce, R. Bradley; Lyapustin, Alexei I.; Wang, Yujie; Ghermandi, Grazia; Teggi, Sergio

2016-09-01

In this work, the new 1 km-resolved Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is employed to characterize seasonal PM10 - AOD correlations over northern Italy. The accuracy of the new dataset is assessed compared to the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data, retrieved at 0.55 μm with spatial resolution of 10 km (MYD04_L2). We focused on evaluating the ability of these two products to characterize both temporal and spatial distributions of aerosols within urban and suburban areas. Ground PM10 measurements were obtained from 73 of the Italian Regional Agency for Environmental Protection (ARPA) monitoring stations, spread across northern Italy, during a three-year period from 2010 to 2012. The Po Valley area (northern Italy) was chosen as the study domain because of its severe urban air pollution, resulting from it having the highest population and industrial manufacturing density in the country, being located in a valley where two surrounding mountain chains favor the stagnation of pollutants. We found that the global correlations between the bin-averaged PM10 and AOD are R2 = 0.83 and R2 = 0.44 for MYD04_L2 and for MAIAC, respectively, suggesting a greater sensitivity of the high-resolution product to small-scale deviations. However, the introduction of Relative Humidity (RH) and Planetary Boundary Layer (PBL) depth corrections allowed for a significant improvement to the bin-averaged PM - AOD correlation, which led to a similar performance: R2 = 0.96 for MODIS and R2 = 0.95 for MAIAC. Furthermore, the introduction of the PBL information in the corrected AOD values was found to be crucial in order to capture the clear seasonal cycle shown by measured PM10 values. The study allowed us to define four seasonal linear correlations that estimate PM10 concentrations satisfactorily from the remotely sensed MAIAC AOD retrieval. Overall, the results show that the high resolution provided by MAIAC retrieval data is much more relevant than the 10 km MODIS data to characterize PM10 in this region of Italy which has a pretty limited geographical domain but a broad variety of land usages and consequent particulate concentrations.

Seasonal Monitoring and Estimation of Regional Aerosol Distribution over Po Valley, Northern Italy, Using a High-Resolution MAIAC Product

NASA Technical Reports Server (NTRS)

Arvani, Barbara; Pierce, R. Bradley; Lyapustin, Alexei I.; Wang, Yujie; Ghermandi, Grazia; Teggi, Sergio

2016-01-01

In this work, the new 1-km-resolved Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is employed to characterize seasonal AOD-PM10 correlations over northern Italy. The accuracy of the new dataset is assessed versus the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data, retrieved at 0.55 microns with spatial resolution of 10 km (MYD04). We focused on evaluating the ability of these two products to characterize both temporal and spatial distributions of aerosols within urban and suburban areas. Ground PM10 measurements were obtained from 73 of the Italian Regional Agency for Environmental Protection (ARPA) monitoring stations, spread across northern Italy, for a three-year period from 2010 to 2012. The Po Valley area (northern Italy) was chosen as the study domain because of severe urban air pollution, resulting from the highest population and industrial manufacturing density in the country, being located in a valley where two surrounding mountain chains favor the stagnation of pollutants. We found that the global correlations between PM10 and AOD are R(sup 2) = 0.83 and R(sup 2) = 0.44 for MYD04_L2 and for MAIAC, respectively, suggesting for a greater sensitiveness of the high-resolution product to small-scale deviations. However, the introduction of Relative Humidity (RH) and Planetary Boundary Layer (PBL) depth corrections gave a significant improvement to the PM AOD correlation, which led to similar performance: R(sup 2) = 0.96 for MODIS and R(sup 2) = 0.95 for MAIAC. Furthermore, the introduction of the PBL information in the corrected AOD values was found to be crucial in order to capture the clear seasonal cycle shown by measured PM10 values. The study allowed us to define four seasonal linear correlations that estimate PM10 concentrations satisfactorily from the remotely sensed MAIAC AOD retrieval. Overall, the results show that the high resolution provided by MAIAC retrieval data is much more relevant than 10km MODIS data to characterize PM10 in this region of Italy which has a pretty limited geographical domain, but a broad variety of land usages and consequent particulate concentrations.

Airborne Sunphotometer Measurements of Aerosol Optical Depth and Columnar Water Vapor During the Puerto Rico Dust Experiment, and Comparison with Land, Aircraft, and Satellite Measurements

NASA Technical Reports Server (NTRS)

Livingston, John M.; Russell, Philip B.; Reid, Jeffrey; Redemann, Jens; Schmid, Beat; Allen, Duane A.; Torres, Omar; Levy, Robert C.; Remer, Lorraine A.; Holben, Brent N.;

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

2014-01-01

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Satellite-based retrieval of particulate matter concentrations over the United Arab Emirates (UAE)

NASA Astrophysics Data System (ADS)

Zhao, Jun; Temimi, Marouane; Hareb, Fahad; Eibedingil, Iyasu

2016-04-01

In this study, an empirical algorithm was established to retrieve particulate matter (PM) concentrations (PM2.5 and PM10) using satellite-derived aerosol optical depth (AOD) over the United Arab Emirates (UAE). Validation of the proposed algorithm using ground truth data demonstrates its good accuracy. Time series of in situ measured PM concentrations between 2014 and 2015 showed high values in summer and low values in winter. Estimated and in situ measured PM concentrations were higher in 2015 than 2014. Remote sensing is an essential tool to reveal and back track the seasonality and inter-annual variations of PM concentrations and provide valuable information on the protection of human health and the response of air quality to anthropogenic activities and climate change.

Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

2015-01-01

The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

The importance of the diurnal cycle of Aerosol Optical Depth in West Africa

NASA Astrophysics Data System (ADS)

Kocha, Cécile; Tulet, Pierre; Lafore, Jean-Philippe; Flamant, Cyrille; Banks, Jamie; Marnas, Fabien; Brindley, Helen; Marsham, Jonh

2013-04-01

High resolution atmospheric simulations with the AROME model coupled with a dust module over West Africa for the whole of June 2006 and 2011 were used to calculate Aerosol Optical Depth (AOD). But the simulations showed a significant diurnal cycle of 0.2 in the dust AOD that could not be inferred from the MODIS Deep Blue satellite retrievals due to their time of overpass. The AROME AOD diurnal cycle have been compared to the new SEVIRI AOD retrievals in June 2011 and shows simlar AOD diurnal cycle. In fact, dust sources are mainly driven by the breakdown of the early morning low-level jet and by moist convection in the afternoon, leading to opposite diurnal cycles. The contribution in dust production is calculated for each processes. Moreover, simulations show that cloud cover significantly prevents the observation of AOD in convective areas. The under-sampling of the diurnal cycle by satellites like MODIS plus the impact of cloud masks on the space-borne AOD retrievals induce an underestimation of 0.28 (~40%) over the convective regions and an overestimation of 0.1 (17%) over morning source areas like Bodélé. Finally, the vertical dust distribution is explored via CALIPSO monthly mean from 2006 to 2011. The vertical dust distribution is a clue element to determine the dust raciative impact. Over the June month, the dust radiative impact affect the atmospheric energetic budget by an absorption of the short wave of 58W/m²/AOD into the atmosphere and a reduction of 50W/m²/AOD at the surface.

Creating Aerosol Types from CHemistry (CATCH): A New Algorithm to Extend the Link Between Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Dawson, K. W.; Meskhidze, N.; Burton, S. P.; Johnson, M. S.; Kacenelenbogen, M. S.; Hostetler, C. A.; Hu, Y.

2017-11-01

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

Retrieval of the ultraviolet aerosol optical depth during a spring campaign in the Bavarian Alps.

PubMed

Lenoble, Jacqueline; Martin, Timothy; Blumthaler, Mario; Philipona, Rolf; Albold, Astrid; Cabot, Thierry; de La Casinière, Alain; Gröbner, Julian; Masserot, Dominique; Müller, Martin; Pichler, Thomas; Seckmeyer, Günther; Schmucki, Daniel; Touré, Mamadou Lamine; Yvon, Alexis

2002-03-20

A measurement campaign was organized in March 1999 in the Bavarian Alps as part of the European project, Characteristics of the UV Radiation Field in the Alps (CUVRA), to analyze the effect of altitude, aerosols, and snow cover on ground-level UV spectral irradiance. We present the results of simultaneous measurements of aerosol optical depth (AOD) made at various sites on two cloudless days in March 1999. The two days exhibited different aerosol conditions. Results derived from spectral measurements of UV irradiance are compared with data from filter radiometer measurements made at discrete wavelengths extending from the UV to the near IR. The different methods generated values for the AOD that were in good agreement. This result confirms that one can use either method to retrieve the AOD with an uncertainty of approximately 0.03-0.05. On 18 March, high turbidity was observed at low altitude (400-nm AOD approximately 0.5 at 700 m above sea level), and the AOD decreased regularly with altitude; on 24 March, the turbidity was much less (0.11 at 700 m above sea level). On both days very low AODs (0.05-0.09) were measured at 3000 m above sea level. The spectral dependence of the AOD is often parameterized by the angstrom relationship; the alpha parameter is generally difficult or impossible to retrieve from spectral measurements because of the relatively narrow wavelength range (320-400 nm), and only one of the spectro-radiometers used during the campaign permits this retrieval. In most cases, during this field campaign, alpha was found by filter sunphotometers to be 1.1-1.5.

Impact of the ozone monitoring instrument row anomaly on the long-term record of aerosol products

NASA Astrophysics Data System (ADS)

Torres, Omar; Bhartia, Pawan K.; Jethva, Hiren; Ahn, Changwoo

2018-05-01

Since about three years after the launch the Ozone Monitoring Instrument (OMI) on the EOS-Aura satellite, the sensor's viewing capability has been affected by what is believed to be an internal obstruction that has reduced OMI's spatial coverage. It currently affects about half of the instrument's 60 viewing positions. In this work we carry out an analysis to assess the effect of the reduced spatial coverage on the monthly average values of retrieved aerosol optical depth (AOD), single scattering albedo (SSA) and the UV Aerosol Index (UVAI) using the 2005-2007 three-year period prior to the onset of the row anomaly. Regional monthly average values calculated using viewing positions 1 through 30 were compared to similarly obtained values using positions 31 through 60, with the expectation of finding close agreement between the two calculations. As expected, mean monthly values of AOD and SSA obtained with these two scattering-angle dependent subsets of OMI observations agreed over regions where carbonaceous or sulphate aerosol particles are the predominant aerosol type. However, over arid regions, where desert dust is the main aerosol type, significant differences between the two sets of calculated regional mean values of AOD were observed. As it turned out, the difference in retrieved desert dust AOD between the scattering-angle dependent observation subsets was due to the incorrect representation of desert dust scattering phase function. A sensitivity analysis using radiative transfer calculations demonstrated that the source of the observed AOD bias was the spherical shape assumption of desert dust particles. A similar analysis in terms of UVAI yielded large differences in the monthly mean values for the two sets of calculations over cloudy regions. On the contrary, in arid regions with minimum cloud presence, the resulting UVAI monthly average values for the two sets of observations were in very close agreement. The discrepancy under cloudy conditions was found to be caused by the parameterization of clouds as opaque Lambertian reflectors. When properly accounting for cloud scattering effects using Mie theory, the observed UVAI angular bias was significantly reduced. The analysis discussed here has uncovered important algorithmic deficiencies associated with the model representation of the angular dependence of scattering effects of desert dust aerosols and cloud droplets. The resulting improvements in the handling of desert dust and cloud scattering have been incorporated in an improved version of the OMAERUV algorithm.

Toward Obtaining Reliable Particulate Air Quality Information from Satellites

NASA Astrophysics Data System (ADS)

Strawa, A. W.; Chatfield, R. B.; Legg, M.; Esswein, R.; Justice, E.

2009-12-01

Air quality agencies use ground sites to monitor air quality, providing accurate information at particular points. Using measurements from satellite imagery has the potential to provide air quality information in a timely manner with better spatial resolution and at a lower cost that can also useful for model validation. While previous studies show acceptable correlations between Aerosol Optical Depth (AOD) derived from MODIS and surface Particulate Matter (PM) measurements on the eastern US, the data do not correlate well in the western US (Al-Saadi et al., 2005; Engle-Cox et al., 2004) . This paper seeks to improve the AOD-PM correlations by using advanced statistical analysis techniques. Our study area is the San Joaquin Valley in California because air quality in this region has failed to meet state and federal attainment standards for PM for the past several years. A previous investigation found good correlation of the AOD values between MODIS, MISR and AERONET, but poor correlations (R2 ~ 0.02) between satellite-based AOD and surface PM2.5 measurements. PM2.5 measurements correlated somewhat better (R2 ~ 0.18) with MODIS-derived AOD using the Deep Blue surface reflectance algorithm (Hsu et al., 2006) rather than the standard MODIS algorithm. This level of correlation is not adequate for reliable air quality measurements. Pelletier et al. (2007) used generalized additive models (GAMs) and meteorological data to improve the correlation between PM and AERONET AOD in western Europe. Additive models are more flexible than linear models and the functional relationships can be plotted to give a sense of the relationship between the predictor and the response. In this paper we use GAMs to improve surface PM2.5 to MODIS-AOD correlations. For example, we achieve an R2 ~ 0.44 using a GAM that includes the Deep Blue AOD, and day of year as parameters. Including NOx observations, improves the R2 ~ 0.64. Surprisingly Ångström exponent did not prove to be a significant factor. The relationships between the predictor and the response are discussed. Al-Saadi, J., J. Szykman, R.B. Pierce, C. Kittaka, D. Neil, D.A. Chu, L. Remer, L. Gumley, E. Prins, L. Weinstock, C. MacDonald, R. Wayland, F. Dimmick, and J. Fishman, Imporving national air quality forecasts with satellite aerosol observations, Bull. Amer, Met. Soc. (Sept), 1249-1261, 2005. Engle-Cox, J.A., C.H. Holloman, B.W. Coutant, and R.M. Hoff, Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality, Atmos. En., 38, 2495-2509, 2004. Hsu, N.C., S.-C. Tsay, M.D. King, and J.R. Herman, Deep blue retrievals of Asian Aerosol properties during ACE-Asia, IEEE Trans. on Geosci.a nd Remote Sensing, 44 (11), 3180, 2006. Pelletier, B., R. Santer, and J. Vidot, Retrieving of particulate matter from optical measurements: A semi-parametric approach, J. Geophys. Res., 112 (D06208), 2007.

Theoretical evaluation of errors in aerosol optical depth retrievals from ground-based direct-sun measurements due to circumsolar and related effects

NASA Astrophysics Data System (ADS)

Kocifaj, Miroslav; Gueymard, Christian A.

2011-02-01

Aerosol optical depth (AOD) has a crucial importance for estimating the optical properties of the atmosphere, and is constantly present in optical models of aerosol systems. Any error in aerosol optical depth (∂AOD) has direct and indirect consequences. On the one hand, such errors affect the accuracy of radiative transfer models (thus implying, e.g., potential errors in the evaluation of radiative forcing by aerosols). Additionally, any error in determining AOD is reflected in the retrieved microphysical properties of aerosol particles, which might therefore be inaccurate. Three distinct effects (circumsolar radiation, optical mass, and solar disk's brightness distribution) affecting ∂AOD are qualified and quantified in the present study. The contribution of circumsolar (CS) radiation to the measured flux density of direct solar radiation has received more attention than the two other effects in the literature. It varies rapidly with meteorological conditions and size distribution of the aerosol particles, but also with instrument field of view. Numerical simulations of the three effects just mentioned were conducted, assuming otherwise "perfect" experimental conditions. The results show that CS is responsible for the largest error in AOD, while the effect of brightness distribution (BD) has only a negligible impact. The optical mass (OM) effect yields negligible errors in AOD generally, but noticeable errors for low sun (within 10° of the horizon). In general, the OM and BD effects result in negative errors in AOD (i.e. the true AOD is smaller than that of the experimental determination), conversely to CS. Although the rapid increase in optical mass at large zenith angles can change the sign of ∂AOD, the CS contribution frequently plays the leading role in ∂AOD. To maximize the accuracy in AOD retrievals, the CS effect should not be ignored. In practice, however, this effect can be difficult to evaluate correctly unless the instantaneous aerosols size distribution is known from, e.g., inversion techniques.

The CU 2-D-MAX-DOAS instrument – Part 2: Raman scattering probability measurements and retrieval of aerosol optical properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ortega, Ivan; Coburn, Sean; Berg, Larry K.

The multiannual global mean of aerosol optical depth at 550 nm (AOD 550) over land is ~0.19, and that over oceans is ~0.13. About 45 % of the Earth surface shows AOD 550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity. We employ radiativemore » transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 < AOD 430 < 0.6) and (2) near-molecular scattering conditions (22 July, AOD 430 < 0.13) we compare RSP-based retrievals of AOD 430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD 430 is +0.012 ± 0.023 (CIMEL), -0.012 ± 0.024 (MFRSR), -0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMEL AOD - MFRSR AOD) and yields the following expressions for correlations between different instruments: DOAS AOD = - (0.019 ± 0.006) + (1.03 ± 0.02)×CIMEL AOD ( R 2 = 0.98), DOAS AOD = -(0.006 ± 0.005)+(1.08 ± 0.02)×MFRSR AOD ( R 2 = 0.98), and CIMEL AOD=(0.013 ± 0.004)+(1.05 ± 0.01)× MFRSR AOD ( R 2=0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD 430 ~ 0.4 and 0.10 the absolute AOD errors are ~ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35°SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.« less

The CU 2-D-MAX-DOAS instrument – Part 2: Raman scattering probability measurements and retrieval of aerosol optical properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ortega, Ivan; Coburn, Sean; Berg, Larry K.

In this study, the multiannual global mean of aerosol optical depth at 550 nm (AOD 550) over land is ~0.19, and that over oceans is ~0.13. About 45 % of the Earth surface shows AOD 550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity.more » We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 < AOD 430 < 0.6) and (2) near-molecular scattering conditions (22 July, AOD 430 < 0.13) we compare RSP-based retrievals of AOD 430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD 430 is +0.012 ± 0.023 (CIMEL), –0.012 ± 0.024 (MFRSR), –0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMEL AOD –MFRSR AOD) and yields the following expressions for correlations between different instruments: DOAS AOD = –(0.019 ± 0.006) + (1.03 ± 0.02) × CIMEL AOD ( R 2 = 0.98), DOAS AOD = –(0.006 ± 0.005) + (1.08 ± 0.02) × MFRSR AOD ( R 2 = 0.98), and CIMEL AOD = (0.013 ± 0.004) + (1.05 ± 0.01) × MFRSR AOD ( R 2 = 0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD 430 ~0.4 and 0.10 the absolute AOD errors are ~ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35° SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.« less

The CU 2-D-MAX-DOAS instrument – Part 2: Raman scattering probability measurements and retrieval of aerosol optical properties

DOE PAGES

Ortega, Ivan; Coburn, Sean; Berg, Larry K.; ...

2016-08-23

In this study, the multiannual global mean of aerosol optical depth at 550 nm (AOD 550) over land is ~0.19, and that over oceans is ~0.13. About 45 % of the Earth surface shows AOD 550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity.more » We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 < AOD 430 < 0.6) and (2) near-molecular scattering conditions (22 July, AOD 430 < 0.13) we compare RSP-based retrievals of AOD 430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD 430 is +0.012 ± 0.023 (CIMEL), –0.012 ± 0.024 (MFRSR), –0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMEL AOD –MFRSR AOD) and yields the following expressions for correlations between different instruments: DOAS AOD = –(0.019 ± 0.006) + (1.03 ± 0.02) × CIMEL AOD ( R 2 = 0.98), DOAS AOD = –(0.006 ± 0.005) + (1.08 ± 0.02) × MFRSR AOD ( R 2 = 0.98), and CIMEL AOD = (0.013 ± 0.004) + (1.05 ± 0.01) × MFRSR AOD ( R 2 = 0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD 430 ~0.4 and 0.10 the absolute AOD errors are ~ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35° SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.« less

Aerosol Remote Sensing From Space

NASA Astrophysics Data System (ADS)

Kokhanovsky, A.; Kinne, S.

2010-01-01

Determination of Atmospheric Aerosol Properties Using Satellite Measurements;Bad Honnef, Germany, 16-19 August 2009; Aerosol optical depth (AOD), a measure of how much light is attenuated by aerosol particles, provides scientists information about the amount and type of aerosols in the atmosphere. Recent developments in aerosol remote sensing was the theme of a workshop held in Germany. The workshop was sponsored by the Wilhelm and Else Heraeus Foundation and attracted 67 participants from 12 countries. The workshop focused on the determination (retrieval) of AOD and its spectral dependence using measurements of changes to the solar radiation back-scattered to space. The midvisible AOD is usually applied to define aerosol amount, while the size of aerosol particles is indicated by the AOD spectral dependence and is commonly expressed by the Angstrom parameter. Identical properties retrieved by different sensors, however, display significant diversity, especially over continents. A major reason for this is that the derivation of AOD requires more accurate determination of nonaerosol contributions to the sensed satellite signal than is usually available. In particular, surface reflectance data as a function of the viewing geometry and robust cloud-clearing methods are essential retrieval elements. In addition, the often needed assumptions about aerosol properties in terms of absorption and size are more reasons for the discrepancy between different AOD measurements.

Validation of MODIS aerosol optical depth over the Mediterranean Coast

NASA Astrophysics Data System (ADS)

Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

2013-04-01

Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial statistics from MODIS with corresponding temporal statistics from AERONET, as proposed by Ichoku et al. (2002). Eight Mediterranean coastal sites (in Spain, France, Italy, Crete, Turkey and Israel) with available AERONET and MODIS data have been used. These stations have been selected following QA criteria (minimum 1000 days of level 2.0 data) and a maximum distance of 8 km from the coast line. Results of the validation over each site show analogous behaviour, giving similar results regarding to the accuracy of the algorithms. Greatest differences are found for the AOD obtained over land, especially for drier regions, where the surface tends to be brighter. In general, the MODIS AOD has better a agreement with AERONET retrievals for the ocean algorithm than the land algorithm when validated over coastal sites, and the agreement is within the expected uncertainty estimated for MODIS data. References: - C. Ichoku et al., "A spatio-temporal approach for global validation and analysis of MODIS aerosol products", Geophysical Research Letters, 219, 12, 10.1029/2001GL013206, 2002.

Can the physical properties associated with uncertainties in the NASA MODIS AOD retrievals in the western U.S. be determined?

NASA Astrophysics Data System (ADS)

Loria Salazar, S. M.; Holmes, H.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2016-12-01

Previous investigations have used satellite remote sensing to estimate surface air pollution concentrations. While most of these studies rely on models developed for the dark-vegetated eastern U.S., they are being used in the semi-arid western U.S without modifications. These models are not robust in the western U.S. due to: 1. Irregular topography that leads to complicated boundary layer physics, 2. Pollutant mixtures, 3. Heterogeneous vertical profile of aerosol concentrations, and 4. High surface reflectance. Here, results from Nevada and California demonstrate poor AOD correlation between AERONET MODIS retrievals. Smoke from wildfires strengthened the aerosol signal, but the MODIS versus AERONET AOD correlation did not improve significantly during fire events [r2 0.17 (non-fire), r2 0.2 (fire)]. Furthermore, aerosol from fires increased the normalized mean bias (NMB) of MODIS retrievals of AOD[NMB 82% (non-fire), NMB 146% (fire)]. Additional results of this investigation found that aerosol plumes confined with the boundary layer improves MODIS AOD retrievals. However, when this condition is not met (i.e., 70% of the time downwind of mountains regions) MODIS AOD has a poor correlation and high bias with respect to AERONET AOD. Fire injection height, complicated boundary layer mixing, and entrainment disperse smoke plumes into the free atmosphere. Therefore, smoke plumes exacerbate the complex aerosol transport typical in the western U.S. and the non-linear relationship between surface pollutant concentrations and conditions aloft. This work uses stochastic methods, including regression to investigate the influence of each of these physical behaviors on the MODIS, AERONET AOD discrepancy using surrogates for each physical phenomenon, e.g., surface albedo for surface reflectance, boundary layer height and elevation for complex mixing, aerosol optical height for vertical aerosol concentrations, and fire radiative power for smoke plume injection height.

The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

NASA Astrophysics Data System (ADS)

Jung, Y.; Kim, J.; Kim, W.; Boesch, H.; Yoshida, Y.; Cho, C.; Lee, H.; Goo, T. Y.

2016-12-01

The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties.

Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes

NASA Astrophysics Data System (ADS)

Sayer, Andrew M.; Hsu, N. Christina; Bettenhausen, Corey; Holz, Robert E.; Lee, Jaehwa; Quinn, Greg; Veglio, Paolo

2017-04-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) is being used to continue the record of Earth Science observations and data products produced routinely from National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. However, the absolute calibration of VIIRS's reflected solar bands is thought to be biased, leading to offsets in derived data products such as aerosol optical depth (AOD) as compared to when similar algorithms are applied to different sensors. This study presents a cross-calibration of these VIIRS bands against MODIS Aqua over dark water scenes, finding corrections to the NASA VIIRS Level 1 (version 2) reflectances between approximately +1 and -7 % (dependent on band) are needed to bring the two into alignment (after accounting for expected differences resulting from different band spectral response functions), and indications of relative trending of up to ˜ 0.35 % per year in some bands. The derived calibration gain corrections are also applied to the VIIRS reflectance and then used in an AOD retrieval, and they are shown to decrease the bias and total error in AOD across the mid-visible spectral region compared to the standard VIIRS NASA reflectance calibration. The resulting AOD bias characteristics are similar to those of NASA MODIS AOD data products, which is encouraging in terms of multi-sensor data continuity.

The OMI Aerosol Absorption Product: An A-train application

NASA Astrophysics Data System (ADS)

Torres, O.; Jethva, H. T.; Ahn, C.

2017-12-01

Because of the uniquely large sensitivity of satellite-measured near-UV radiances to absorption by desert dust, carbonaceous and volcanic ash aerosols, observations by a variety of UV-capable sensors have been routinely used over the last forty years in both qualitative and quantitative applications for estimating the absorption properties of these aerosol types. In this presentation we will discuss a multi-sensor application involving observations from A-train sensors OMI, AIRS and CALIOP for the creation of a 13-year record of aerosol optical depth (AOD) and single scattering albedo (SSA). Determination of aerosol type, in terms of particle size distribution and refractive index, is an important algorithmic step that requires using external information. AIRS CO measurements are used as carbonaceous aerosols tracer to differentiate this aerosol type from desert dust. On the other hand, the height of the absorbing aerosol layer, an important parameter in UV aerosol retrievals, is prescribed using a CALIOP-based climatology. The combined use of these observations in the developments of the OMI long-term AOD/SSA record will be discussed along with an evaluation of retrieval results using independent observations.

Estimation of Aerosol Optical Depth at Different Wavelengths by Multiple Regression Method

NASA Technical Reports Server (NTRS)

Tan, Fuyi; Lim, Hwee San; Abdullah, Khiruddin; Holben, Brent

2015-01-01

This study aims to investigate and establish a suitable model that can help to estimate aerosol optical depth (AOD) in order to monitor aerosol variations especially during non-retrieval time. The relationship between actual ground measurements (such as air pollution index, visibility, relative humidity, temperature, and pressure) and AOD obtained with a CIMEL sun photometer was determined through a series of statistical procedures to produce an AOD prediction model with reasonable accuracy. The AOD prediction model calibrated for each wavelength has a set of coefficients. The model was validated using a set of statistical tests. The validated model was then employed to calculate AOD at different wavelengths. The results show that the proposed model successfully predicted AOD at each studied wavelength ranging from 340 nm to 1020 nm. To illustrate the application of the model, the aerosol size determined using measure AOD data for Penang was compared with that determined using the model. This was done by examining the curvature in the ln [AOD]-ln [wavelength] plot. Consistency was obtained when it was concluded that Penang was dominated by fine mode aerosol in 2012 and 2013 using both measured and predicted AOD data. These results indicate that the proposed AOD prediction model using routine measurements as input is a promising tool for the regular monitoring of aerosol variation during non-retrieval time.

The GEOS-5 Neural Network Retrieval for AOD

NASA Astrophysics Data System (ADS)

Castellanos, P.; da Silva, A. M., Jr.

2017-12-01

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

The GEOS-5 Neural Network Retrieval (NNR) for AOD

NASA Technical Reports Server (NTRS)

Castellanos, Patricia; Da Silva, Arlindo

2017-01-01

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

Aerosol-type retrieval and uncertainty quantification from OMI data

NASA Astrophysics Data System (ADS)

Kauppi, Anu; Kolmonen, Pekka; Laine, Marko; Tamminen, Johanna

2017-11-01

We discuss uncertainty quantification for aerosol-type selection in satellite-based atmospheric aerosol retrieval. The retrieval procedure uses precalculated aerosol microphysical models stored in look-up tables (LUTs) and top-of-atmosphere (TOA) spectral reflectance measurements to solve the aerosol characteristics. The forward model approximations cause systematic differences between the modelled and observed reflectance. Acknowledging this model discrepancy as a source of uncertainty allows us to produce more realistic uncertainty estimates and assists the selection of the most appropriate LUTs for each individual retrieval.This paper focuses on the aerosol microphysical model selection and characterisation of uncertainty in the retrieved aerosol type and aerosol optical depth (AOD). The concept of model evidence is used as a tool for model comparison. The method is based on Bayesian inference approach, in which all uncertainties are described as a posterior probability distribution. When there is no single best-matching aerosol microphysical model, we use a statistical technique based on Bayesian model averaging to combine AOD posterior probability densities of the best-fitting models to obtain an averaged AOD estimate. We also determine the shared evidence of the best-matching models of a certain main aerosol type in order to quantify how plausible it is that it represents the underlying atmospheric aerosol conditions.The developed method is applied to Ozone Monitoring Instrument (OMI) measurements using a multiwavelength approach for retrieving the aerosol type and AOD estimate with uncertainty quantification for cloud-free over-land pixels. Several larger pixel set areas were studied in order to investigate the robustness of the developed method. We evaluated the retrieved AOD by comparison with ground-based measurements at example sites. We found that the uncertainty of AOD expressed by posterior probability distribution reflects the difficulty in model selection. The posterior probability distribution can provide a comprehensive characterisation of the uncertainty in this kind of problem for aerosol-type selection. As a result, the proposed method can account for the model error and also include the model selection uncertainty in the total uncertainty budget.

Aerosol retrieval experiments in the ESA Aerosol_cci project

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.; de Leeuw, G.; Griesfeller, J.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.

2013-08-01

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010-2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust).

Estimating regional spatial and temporal variability of PM(2.5) concentrations using satellite data, meteorology, and land use information.

PubMed

Liu, Yang; Paciorek, Christopher J; Koutrakis, Petros

2009-06-01

Studies of chronic health effects due to exposures to particulate matter with aerodynamic diameters

SEOM's Sentinel-3/OLCI' project CAWA: advanced GRASP aerosol retrieval

NASA Astrophysics Data System (ADS)

Dubovik, Oleg; litvinov, Pavel; Huang, Xin; Aspetsberger, Michael; Fuertes, David; Brockmann, Carsten; Fischer, Jürgen; Bojkov, Bojan

2016-04-01

The CAWA "Advanced Clouds, Aerosols and WAter vapour products for Sentinel-3/OLCI" ESA-SEOM project aims on the development of advanced atmospheric retrieval algorithms for the Sentinel-3/OLCI mission, and is prepared using Envisat/MERIS and Aqua/MODIS datasets. This presentation discusses mainly CAWA aerosol product developments and results. CAWA aerosol retrieval uses recently developed GRASP algorithm (Generalized Retrieval of Aerosol and Surface Properties) algorithm described by Dubovik et al. (2014). GRASP derives extended set of atmospheric parameters using multi-pixel concept - a simultaneous fitting of a large group of pixels under additional a priori constraints limiting the time variability of surface properties and spatial variability of aerosol properties. Over land GRASP simultaneously retrieves properties of both aerosol and underlying surface even over bright surfaces. GRAPS doesn't use traditional look-up-tables and performs retrieval as search in continuous space of solution. All radiative transfer calculations are performed as part of the retrieval. The results of comprehensive sensitivity tests, as well as results obtained from real Envisat/MERIS data will be presented. The tests analyze various aspects of aerosol and surface reflectance retrieval accuracy. In addition, the possibilities of retrieval improvement by means of implementing synergetic inversion of a combination of OLCI data with observations by SLSTR are explored. Both the results of numerical tests, as well as the results of processing several years of Envisat/MERIS data illustrate demonstrate reliable retrieval of AOD (Aerosol Optical Depth) and surface BRDF. Observed retrieval issues and advancements will be discussed. For example, for some situations we illustrate possibilities of retrieving aerosol absorption - property that hardly accessible from satellite observations with no multi-angular and polarimetric capabilities.

Observing a Severe Dust Storm Event over China using Multiple Satellite Data

NASA Astrophysics Data System (ADS)

Xu, Hui; Xue, Yong; Guang, Jie; Mei, Linlu

2013-04-01

A severe dust storm (SDS) event occurred from 19 to 21 March 2010 in China, originated in western China and Mongolia and propagated into eastern/southern China, affecting human's life in a large area. As reported by National Meteorological Center of CMA (China Meteorological Administration), 16 provinces (cities) of China were hit by the dust storm (Han et al., 2012). Satellites can provide global measurements of desert dust and have particular importance in remote areas where there is a lack of in situ measurements (Carboni et al., 2012). To observe a dust, it is necessary to estimate the spatial and temporal distributions of dust aerosols. An important metric in the characterisation of aerosol distribution is the aerosol optical depth (AOD) (Adhikary et al., 2008). Satellite aerosol retrievals have improved considerably in the last decade, and numerous satellite sensors and algorithms have been generated. Reliable retrievals of dust aerosol over land were made using POLarization and Directionality of the Earth's Reflectance instrument-POLDER (Deuze et al., 2001), Moderate Resolution Imaging Spectroradiometer-MODIS (Kaufman et al., 1997; Hsu et al., 2004), Multiangle Imaging Spectroradiometer-MISR (Martonchik et al., 1998), and Cloud-aerosol Lidar and infrared pathfinder satellite observations (CALIPSO). However, intercomparison exercises (Myhre et al., 2005) have revealed that discrepancies between satellite measurements are particularly large during events of heavy aerosol loading. The reason is that different AOD retrieval algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. For MISR, POLDER and MODIS instrument, the multi-angle approaches, the polarization measurements and single-view approaches were used to retrieval AOD respectively. Combining of multi-sensor AOD data can potentially create a more consistent, reliable and complete picture of the space-time evolution of dust storms (Ehlers, 1991). In order to make use of all useful satellite data to observe one severe dust procedure, multi-sensor and multi-algorithm AOD data were combined. In this paper, the satellite instruments considered are MISR, MODIS, POLDER and CALIPSO. In addition, air pollution index (API) data were used to validate the satellite AOD data. We chose the study region with a longitude range from 76°N to 136°N and a latitude range from 15°E to 60°E. Index Terms—aerosol optical depth, dust, satellite REFERENCES Adhikary, B., Kulkarni, S., Dallura A., Tang, Y., Chai, T., Leung, L. R., Qian, Y., Chung, C. E., Ramanathan,V. and Carmichael, G. R., 2008, A regional scale chemical transport modeling of Asian aerosols with data assimilation of AOD observations using optimal interpolation technique, Atmospheric Environment, 42(37), 8600-8615. Carboni, E., Thomas, G. E., Sayer, A. M., Siddans, R., Poulsen, C. A., Grainger, R. G., Ahn, C., Antoine, D., Bevan, S., Braak, R., Brindley, H., DeSouza-Machado, S., Deuz'e, J. L., Diner, D., Ducos, F., Grey, W., Hsu, C., Kalashnikova, O. V., Kahn, R., North, P. R. J., Salustro, C., Smith, A., Tanr'e, D., Torres, O., and Veihelmann, B., 2012, Intercomparison of desert dust optical depth from satellite measurements, Atmospheric Measurement Techniques, 5, 1973-2002. Deuze', J. L., Bre'on, F. M., Devaux, C., Goloub, Herman, M., Lafrance, B., Maignan, F., Marchand, A.,Nadal, F., Perry, G., and Tanre', D., 2001, Remote sensing of aerosols over land surfaces from POLDER-ADEOS-1 polarized measurements, Journal of Geophysical Research, 106(D5), 4913-4926. Ehlers, M., 1991, Multisensor image fusion techniques in remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 46, 19-30. Han, X., Ge. C., Tao, J. H., Zhang, M. G., Zhang, R. J., 2012, Air Quality Modeling for a Strong Dust Event in East Asia in March 2010, Aerosol and Air Quality Research, 12: 615-628. Hsu, N. C., Tsay, S. C., King, M. D. and Herman, J. R., 2004, Aerosol Properties over Bright-Reflecting Source Regions, IEEE Transactions on Geoscience and Remote Sensing, 42(3), 557-569. Martonchik, J. V., Diner, D. J., Kahn, R., Ackerman, T. P., Verstraete, M. M., Pinty, B., and Gordon, H. R., 1998, Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging, IEEE Transactions on Geoscience and Remote Sensing, 36(4), 1212-1227. Myhre, G., Stordal, F., Johnsrud, M., Diner, D. J., Geogdzhayev, I. V., Haywood, J. M., Holben, B. N., Holzer-Popp, T., Ignatov, A., Kahn, R. A., Kaufman, Y. J., Loeb, N., Martonchik, J. V., Mishchenko, M. I., Nalli, N. R., Remer, L. A., Schroedter-Homscheidt, M., Tanr'e, D., Torres, O., and Wang, M., 2005, Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000, Atmospheric Chemistry and Physics, 5, 1697-1719. Kaufman, Y.J., Tanre', D., Remer, L.A., Vermote, E.F., Chu, A., and Holben, B.N., 1997, Operationalremote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer, Journal of Geophysical Research, 102(D14), 17,051-17,067.

Aerosol optical properties over the Svalbard region of Arctic: ground-based measurements and satellite remote sensing

NASA Astrophysics Data System (ADS)

Gogoi, Mukunda M.; Babu, S. Suresh

2016-05-01

In view of the increasing anthropogenic presence and influence of aerosols in the northern polar regions, long-term continuous measurements of aerosol optical parameters have been investigated over the Svalbard region of Norwegian Arctic (Ny-Ålesund, 79°N, 12°E, 8 m ASL). This study has shown a consistent enhancement in the aerosol scattering and absorption coefficients during spring. The relative dominance of absorbing aerosols is more near the surface (lower single scattering albedo), compared to that at the higher altitude. This is indicative of the presence of local anthropogenic activities. In addition, long-range transported biomass burning aerosols (inferred from the spectral variation of absorption coefficient) also contribute significantly to the higher aerosol absorption in the Arctic spring. Aerosol optical depth (AOD) estimates from ground based Microtop sun-photometer measurements reveals that the columnar abundance of aerosols reaches the peak during spring season. Comparison of AODs between ground based and satellite remote sensing indicates that deep blue algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over Arctic snow surfaces overestimate the columnar AOD.

The influence of aerosols and land-use type on NO2 satellite retrieval over China

NASA Astrophysics Data System (ADS)

Liu, Mengyao; Lin, Jintai; Boersma, Folkert; Eskes, Henk; Chimot, Julien

2017-04-01

Both aerosols and surface reflectance have a strong influence on the retrieval of NO2 tropospheric vertical column densities (VCDs), especially over China with its heavy aerosol loading and rapid changes in land-use type. However, satellite retrievals of NO2 VCDs usually do not explicitly account for aerosol optical effects and surface reflectance anisotropy (BRDF) that varies in space and time. We develop an improved algorithm to derive tropospheric AMFs and VCDs over China from the OMI instrument - POMINO and DOMINO. This method can also be applied to TropOMI NO2 retrievals in the future. With small pixels of TropOMI and higher probability of encountering clear-sky scenes, the influence of BRDF and aerosol interference becomes more important than for OMI. Daily aerosol information is taken from the GEOS-Chem chemistry transport model and the aerosol optical depth (AOD) is adjusted via MODIS AOD climatology. We take the MODIS MCD43C2 C5 product to account for BRDF effects. The relative altitude of NO2 and aerosols is critical factor influencing the NO2 retrieval. In order to evaluate the aerosol extinction profiles (AEP) of GEOS-Chem improve our algorithm, we compare the GEOS-Chem simulation with CALIOP and develop a CALIOP AEP climatology to regulate the model's AEP. This provides a new way to include aerosol information into the tracer gas retrieval for OMI and TropOMI. Preliminary results indicate that the model performs reasonably well in reproducing the AEP shape. However, it seems to overestimate aerosols under 2km and underestimate above. We find that relative humidity (RH) is an important factor influencing the AEP shape when comparing the model with observations. If we adjust the GEOS-Chem RH to CALIOP's RH, the correlations of their AEPs also improve. Besides, take advantage of our retrieval method, we executed sensitivity tests to analyze their influences on NO2 trend and spatiotemporal variations in retrieval. It' the first time to investigate influence from aerosols and surface reflectance in 10-year period (2005-2015) in the real retrieval. We find their influences are largely time and space dependent, but their effects on trend are small, leading relative 7% differences in different areas.

XCO2 retrieval error over deserts near critical surface albedo

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Shia, Run-Lie; Sander, Stanley P.; Yung, Yuk L.

2016-02-01

Large retrieval errors in column-weighted CO2 mixing ratio (XCO2) over deserts are evident in the Orbiting Carbon Observatory 2 version 7 L2 products. We argue that these errors are caused by the surface albedo being close to a critical surface albedo (αc). Over a surface with albedo close to αc, increasing the aerosol optical depth (AOD) does not change the continuum radiance. The spectral signature caused by changing the AOD is identical to that caused by changing the absorbing gas column. The degeneracy in the retrievals of AOD and XCO2 results in a loss of degrees of freedom and information content. We employ a two-stream-exact single scattering radiative transfer model to study the physical mechanism of XCO2 retrieval error over a surface with albedo close to αc. Based on retrieval tests over surfaces with different albedos, we conclude that over a surface with albedo close to αc, the XCO2 retrieval suffers from a significant loss of accuracy. We recommend a bias correction approach that has significantly improved the XCO2 retrieval from the California Laboratory for Atmospheric Remote Sensing data in the presence of aerosol loading.

Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.

PubMed

Paciorek, Christopher J; Liu, Yang

2012-05-01

Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional observations. Given the public health and resultant public policy implications of the potential health effects of particulate matter (PM*) air pollution, specifically fine PM with an aerodynamic diameter < or = 2.5 pm (PM2.5), there has been substantial recent interest in the use of remote-sensing information, in particular aerosol optical depth (AOD) retrieved from satellites, to help characterize variability in ground-level PM2.5 concentrations in space and time. While the United States and some other developed countries have extensive PM monitoring networks, gaps in data across space and time necessarily occur; the hope is that remote sensing can help fill these gaps. In this report, we are particularly interested in using remote-sensing data to inform estimates of spatial patterns in ambient PM2.5 concentrations at monthly and longer time scales for use in epidemiologic analyses. However, we also analyzed daily data to better disentangle spatial and temporal relationships. For AOD to be helpful, it needs to add information beyond that available from the monitoring network. For analyses of chronic health effects, it needs to add information about the concentrations of long-term average PM2.5; therefore, filling the spatial gaps is key. Much recent evidence has shown that AOD is correlated with PM2.5 in the eastern United States, but the use of AOD in exposure analysis for epidemiologic work has been rare, in part because discrepancies necessarily exist between satellite-retrieved estimates of AOD, which is an atmospheric-column average, and ground-level PM2.5. In this report, we summarize the results of a number of empirical analyses and of the development of statistical models for the use of proxy information, in particular satellite AOD, in predicting PM2.5 concentrations in the eastern United States. We analyzed the spatiotemporal structure of the relationship between PM2.5 and AOD, first using simple correlations both before and after calibration based on meteorology, as well as large-scale spatial and temporal calibration to account for discrepancies between AOD and PM2.5. We then used both raw and calibrated AOD retrievals in statistical models to predict PM2.5 concentrations, accounting for AOD in two ways: primarily as a separate data source contributing a second likelihood to a Bayesian statistical model, as well as a data source on which we could directly regress. Previous consideration of satellite AOD has largely focused on the National Aeronautics and Space Administration (NASA) moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments. One contribution of our work is more extensive consideration of AOD derived from the Geostationary Operational Environmental Satellite East Aerosol/Smoke Product (GOES GASP) AOD and its relationship with PM2.5. In addition to empirically assessing the spatiotemporal relationship between GASP AOD and PM2.5, we considered new statistical techniques to screen anomalous GOES reflectance measurements and account for background surface reflectance. In our statistical work, we developed a new model structure that allowed for more flexible modeling of the proxy discrepancy than previous statistical efforts have had, with a computationally efficient implementation. We also suggested a diagnostic for assessing the scales of the spatial relationship between the proxy and the spatial process of interest (e.g., PM2.5). In brief, we had little success in improving predictions in our eastern-United States domain for use in epidemiologic applications. We found positive correlations of AOD with PM2.5 over time, but less correlation for long-term averages over space, unless we used calibration that adjusted for large-scale discrepancy between AOD and PM2.5 (see sections 3, 4, and 5). Statistical models that combined AOD, PM2.5 observations, and land-use and meteorologic variables were highly predictive of PM2.5 observations held out of the modeling, but AOD added little information beyond that provided by the other sources (see sections 5 and 6). When we used PM2.5 data estimates from the Community Multiscale Air Quality model (CMAQ) as the proxy instead of using AOD, we similarly found little improvement in predicting held-out observations of PM2.5, but when we regressed on CMAQ PM2.5 estimates, the predictions improved moderately in some cases. These results appeared to be caused in part by the fact that large-scale spatial patterns in PM2.5 could be predicted well by smoothing the monitor values, while small-scale spatial patterns in AOD appeared to weakly reflect the variation in PM2.5 inferred from the observations. Using a statistical model that allowed for potential proxy discrepancy at both large and small spatial scales was an important component of our modeling. In particular, when our models did not include a component to account for small-scale discrepancy, predictive performance decreased substantially. Even long-term averages of MISR AOD, considered the best, albeit most sparse, of the AOD products, were only weakly correlated with measured PM2.5 (see section 4). This might have been partly related to the fact that our analysis did not account for spatial variation in the vertical profile of the aerosol. Furthermore, we found evidence that some of the correlation between raw AOD and PM2.5 might have been a function of surface brightness related to land use, rather than having been driven by the detection of aerosol in the AOD retrieval algorithms (see sections 4 and 7). Difficulties in estimating the background surface reflectance in the retrieval algorithms likely explain this finding. With regard to GOES, we found moderate correlations of GASP AOD and PM2.5. The higher correlations of monthly and yearly averages after calibration reflected primarily the improved large-scale correlation, a necessary result of the calibration procedure (see section 3). While the results of this study's GOES reflectance screening and surface reflection correction appeared sensible, correlations of our proposed reflectance-based proxy with PM2.5 were no better than GASP AOD correlations with PM2.5 (see section 7). We had difficulty improving spatial prediction of monthly and yearly average PM2.5 using AOD in the eastern United States, which we attribute to the spatial discrepancy between AOD and measured PM2.5, particularly at smaller scales. This points to the importance of paying attention to the discrepancy structure of proxy information, both from remote-sensing and deterministic models. In particular, important statistical challenges arise in accounting for the discrepancy, given the difficulty in the face of sparse observations of distinguishing the discrepancy from the component of the proxy that is informative about the process of interest. Associations between adverse health outcomes and large-scale variation in PM2.5 (e.g., across regions) may be confounded by unmeasured spatial variation in factors such as diet. Therefore, one important goal was to use AOD to improve predictions of PM2.5 for use in epidemiologic analyses at small-to-moderate spatial scales (within urban areas and within regions). In addition, large-scale PM2.5 variation is well estimated from the monitoring data, at least in the United States. We found little evidence that current AOD products are helpful for improving prediction at small-to-moderate scales in the eastern United States and believe more evidence for the reliability of AOD as a proxy at such scales is needed before making use of AOD for PM2.5 prediction in epidemiologic contexts. While our results relied in part on relatively complicated statistical models, which may be sensitive to modeling assumptions, our exploratory correlation analyses (see sections 3 and 5) and relatively simple regression-style modeling of MISR AOD (see section 4) were consistent with the more complicated modeling results. When assessing the usefulness of AOD in the context of studying chronic health effects, we believe efforts need to focus on disentangling the temporal from the spatial correlations of AOD and PM2.5 and on understanding the spatial scale of correlation and of the discrepancy structure. While our results are discouraging, it is important to note that we attempted to make use of smaller-scale spatial variation in AOD to distinguish spatial variations of relatively small magnitude in long-term concentrations of ambient PM2.5. Our efforts pushed the limits of current technology in a spatial domain with relatively low PM2.5 levels and limited spatial variability. AOD may hold more promise in areas with higher aerosol levels, as the AOD signal would be stronger there relative to the background surface reflectance. Furthermore, for developing countries with high aerosol levels, it is difficult to build statistical models based on PM2.5 measurements and land-use covariates, so AOD may add more incremental information in those contexts. More generally, researchers in remote sensing are involved in ongoing efforts to improve AOD products and develop new approaches to using AOD, such as calibration with model-estimated vertical profiles and the use of speciation information in MISR AOD; these efforts warrant continued investigation of the usefulness of remotely sensed AOD for public health research.

Case studies of aerosol and ocean color retrieval using a Markov chain radiative transfer model and AirMSPI measurements

NASA Astrophysics Data System (ADS)

Xu, F.; Diner, D. J.; Seidel, F. C.; Dubovik, O.; Zhai, P.

2014-12-01

A vector Markov chain radiative transfer method was developed for forward modeling of radiance and polarization fields in a coupled atmosphere-ocean system. The method was benchmarked against an independent Successive Orders of Scattering code and linearized through the use of Jacobians. Incorporated with the multi-patch optimization algorithm and look-up-table method, simultaneous aerosol and ocean color retrievals were performed using imagery acquired by the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) when it was operated in step-and-stare mode with 9 viewing angles ranging between ±67°. Data from channels near 355, 380, 445, 470*, 555, 660*, and 865* nm were used in the retrievals, where the asterisk denotes the polarimetric bands. Retrievals were run for AirMSPI overflights over Southern California and Monterey Bay, CA. For the relatively high aerosol optical depth (AOD) case (~0.28 at 550 nm), the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration were compared to those reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California on 6 February 2013. For the relatively low AOD case (~0.08 at 550 nm), the retrieved aerosol concentration and size distribution were compared to those reported by the Monterey Bay AERONET site on 28 April 2014. Further, we evaluate the benefits of multi-angle and polarimetric observations by performing the retrievals using (a) all view angles and channels; (b) all view angles but radiances only (no polarization); (c) the nadir view angle only with both radiance and polarization; and (d) the nadir view angle without polarization. Optimized retrievals using different initial guesses were performed to provide a measure of retrieval uncertainty. Removal of multi-angular or polarimetric information resulted in increases in both parameter uncertainty and systematic bias. Potential accuracy improvements afforded by applying constraints on the surface and aerosol parametric models will also be discussed.

Dust altitude and infrared optical depth retrieved from 6 years of AIRS observations : a focus on Saharan dust using A-Train synergy (MODIS, CALIOP)

NASA Astrophysics Data System (ADS)

Peyridieu, S.; Chédin, A.; Capelle, V.; Pierangelo, C.; Lamquin, N.; Armante, R.

2009-04-01

Observation from space, being global and quasi-continuous, is a first importance tool for aerosol studies. Remote sensing in the visible domain has been widely used to obtain better characterization of these particles and their effect on solar radiation. On the opposite, remote sensing of aerosols in the thermal infrared domain still remains marginal. However, knowledge of the effect of aerosols on terrestrial radiation is needed for the evaluation of their total radiative forcing. Infrared remote sensing provides a way to retrieve other aerosol characteristics, including their mean altitude. Moreover, observations are possible at night and day, over ocean and over land. In this context, six years (2003-2008) of the 2nd generation vertical sounder AIRS observations have been processed over the tropical belt (30°N-30°S). Our results of the dust optical depth at 10 µm have been compared to the 0.55 µm Aqua/MODIS optical depth product for this period. The detailed study of Atlantic regions shows a very good agreement between the two products, with a VIS/IR ratio around 0.3-0.5 during the Saharan dust season. Comparing these two AOD products should allow separating different aerosols signals, given that our retrieval algorithm is specifically designed for dust coarse mode whereas MODIS retrieves both accumulation and fine aerosol modes. Mean aerosol layer altitude has also been retrieved from AIRS data and we show global maps and time series of altitude retrieved from space. Altitude retrievals are compared to the CALIOP/Calipso Level-2 product starting June 2006. This comparison, for a region located downwind from the Sahara, again shows a good agreement demonstrating that our algorithm effectively allows retrieving reliable mean dust layer altitude. A global climatology of the dust optical depth at 10 µm and of the aerosol layer mean altitude has also been established. An interesting conclusion is the fact that if the AOD decreases from Africa to the Caribbean as a result of transport and dilution, altitude decreases less rapidly. This is in agreement with in situ measurements made during the Puerto Rico Dust Experiment (PRIDE) campaign and modelled forward trajectories.

Estimating Regional Spatial and Temporal Variability of PM2.5 Concentrations Using Satellite Data, Meteorology, and Land Use Information

PubMed Central

Liu, Yang; Paciorek, Christopher J.; Koutrakis, Petros

2009-01-01

Background Studies of chronic health effects due to exposures to particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) are often limited by sparse measurements. Satellite aerosol remote sensing data may be used to extend PM2.5 ground networks to cover a much larger area. Objectives In this study we examined the benefits of using aerosol optical depth (AOD) retrieved by the Geostationary Operational Environmental Satellite (GOES) in conjunction with land use and meteorologic information to estimate ground-level PM2.5 concentrations. Methods We developed a two-stage generalized additive model (GAM) for U.S. Environmental Protection Agency PM2.5 concentrations in a domain centered in Massachusetts. The AOD model represents conditions when AOD retrieval is successful; the non-AOD model represents conditions when AOD is missing in the domain. Results The AOD model has a higher predicting power judged by adjusted R2 (0.79) than does the non-AOD model (0.48). The predicted PM2.5 concentrations by the AOD model are, on average, 0.8–0.9 μg/m3 higher than the non-AOD model predictions, with a more smooth spatial distribution, higher concentrations in rural areas, and the highest concentrations in areas other than major urban centers. Although AOD is a highly significant predictor of PM2.5, meteorologic parameters are major contributors to the better performance of the AOD model. Conclusions GOES aerosol/smoke product (GASP) AOD is able to summarize a set of weather and land use conditions that stratify PM2.5 concentrations into two different spatial patterns. Even if land use regression models do not include AOD as a predictor variable, two separate models should be fitted to account for different PM2.5 spatial patterns related to AOD availability. PMID:19590678

Evaluation of AVHRR Aerosol Properties Over Mainland China from Deepblue Algorithm

NASA Astrophysics Data System (ADS)

Xue, Y.; Che, Y.; She, L.

2017-12-01

Advanced Very High Resolution Radiometer (AVHRR) on-board NOAA series satellites is the only operational senor which keeps observing surface of the Earth and cloud over 30 years since 1979. Such long time coverage helps to expand the application of AVHRR to aerosol properties retrieval over both land and ocean successfully. Recently in 2017, the Deep Blue Project has published AVHRR `Deep Blue' dataset version 001 (V001) using `Deep Blue (DB)' algorithm(Sayer et al., 2017). This dataset includes not only aerosol properties over land but also oceanic aerosol product at three periods (NOAA-11: 1989-1990, NOAA-14: 1995-1999, NOAA-18: 2006-2011). We pay much of our attention to DB's performance over mainland China. Therefore, in the presenting paper, we focus on validating AVHRR/DB dataset over different land covers in China in 2007, 2008 and 2010. Both of data from ground-based networks from the Aerosol Robotic NETwork (AERONET) and China Aerosol Remote Sensing Network (CARSNET) are used as reference data. The collocation method is to match data at a time range of of satellite pass-by and at a spatial frame of pixels around ground-based site. Totally, data from 18 AERONET and 25 CARSNET are used as shown in figure, collocating 922 matches with AERONET and 2325 matches with CARSNET. Additionally, we introduced a corrected RMS error as main evaluation metric. As a result, AVHRR/DB underestimates AOD increasingly and more uncertainties and errors will be introduced with the growth of AOD. Otherwise, the performance of AVHRR/DB are better compared with AERONET data than with CARSNET data from RMSbc of 0.35 vs. 0.42. Their Rs (0.757 vs. 0.654) prove this characteristic too. For urban areas, the performances in Beijing are better than that in Xi'an from RMSbc, otherwise RMS in Xi'an (0.324) is lower than others' (0.346 and 0.383) mainly because of small AOD observed range and low R (0.624). For croplands, those performances are at same levels with RMSbc from 0.312 to 0.380 except Huimin with RMSbc = 0.445. For grasslands and sparsely vegetated areas, it lacks AERONET observation sites that only SACOL in central China. Obviously, the algorithm has best performance over Dunhuang site, where the RMSbc = 0.338 and highest R about 0.771. Over the rest of sites, the AVHRR/DB has serious problem in retrieving AOD, high dispersion or poor correlation.

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, M.; Ichoku, C.

2013-01-01

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

Reflections on current and future applications of multiangle imaging to aerosol and cloud remote sensing

NASA Astrophysics Data System (ADS)

Diner, David

2010-05-01

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its 9 along-track view angles, 4 spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space, nor is there is a similar capability currently available on any other satellite platform. Multiangle imaging offers several tools for remote sensing of aerosol and cloud properties, including bidirectional reflectance and scattering measurements, stereoscopic pattern matching, time lapse sequencing, and potentially, optical tomography. Current data products from MISR employ several of these techniques. Observations of the intensity of scattered light as a function of view angle and wavelength provide accurate measures of aerosol optical depths (AOD) over land, including bright desert and urban source regions. Partitioning of AOD according to retrieved particle classification and incorporation of height information improves the relationship between AOD and surface PM2.5 (fine particulate matter, a regulated air pollutant), constituting an important step toward a satellite-based particulate pollution monitoring system. Stereoscopic cloud-top heights provide a unique metric for detecting interannual variability of clouds and exceptionally high quality and sensitivity for detection and height retrieval for low-level clouds. Using the several-minute time interval between camera views, MISR has enabled a pole-to-pole, height-resolved atmospheric wind measurement system. Stereo imagery also makes possible global measurement of the injection heights and advection speeds of smoke plumes, volcanic plumes, and dust clouds, for which a large database is now available. To build upon what has been learned during the first decade of MISR observations, we are evaluating algorithm updates that not only refine retrieval accuracies but also include enhancements (e.g., finer spatial resolution) that would have been computationally prohibitive just ten years ago. In addition, we are developing technological building blocks for future sensors that enable broader spectral coverage, wider swath, and incorporation of high-accuracy polarimetric imaging. Prototype cameras incorporating photoelastic modulators have been constructed. To fully capitalize on the rich information content of the current and next-generation of multiangle imagers, several algorithmic paradigms currently employed need to be re-examined, e.g., the use of aerosol look-up tables, neglect of 3-D effects, and binary partitioning of the atmosphere into "cloudy" or "clear" designations. Examples of progress in algorithm and technology developments geared toward advanced application of multiangle imaging to remote sensing of aerosols and clouds will be presented.

Aerosol Optical Depths over Oceans: a View from MISR Retrievals and Collocated MAN and AERONET in Situ Observations

NASA Technical Reports Server (NTRS)

Witek, Marcin L.; Garay, Michael J.; Diner, David J.; Smirnov, Alexander

2013-01-01

In this study, aerosol optical depths over oceans are analyzed from satellite and surface perspectives. Multiangle Imaging SpectroRadiometer (MISR) aerosol retrievals are investigated and validated primarily against Maritime Aerosol Network (MAN) observations. Furthermore, AErosol RObotic NETwork (AERONET) data from 19 island and coastal sites is incorporated in this study. The 270 MISRMAN comparison points scattered across all oceans were identified. MISR on average overestimates aerosol optical depths (AODs) by 0.04 as compared to MAN; the correlation coefficient and root-mean-square error are 0.95 and 0.06, respectively. A new screening procedure based on retrieval region characterization is proposed, which is capable of substantially reducing MISR retrieval biases. Over 1000 additional MISRAERONET comparison points are added to the analysis to confirm the validity of the method. The bias reduction is effective within all AOD ranges. Setting a clear flag fraction threshold to 0.6 reduces the bias to below 0.02, which is close to a typical ground-based measurement uncertainty. Twelve years of MISR data are analyzed with the new screening procedure. The average over ocean AOD is reduced by 0.03, from 0.15 to 0.12. The largest AOD decrease is observed in high latitudes of both hemispheres, regions with climatologically high cloud cover. It is postulated that the screening procedure eliminates spurious retrieval errors associated with cloud contamination and cloud adjacency effects. The proposed filtering method can be used for validating aerosol and chemical transport models.

Satellite retrievals of dust aerosol over the Red Sea and the Persian Gulf (2005-2015)

NASA Astrophysics Data System (ADS)

Banks, Jamie R.; Brindley, Helen E.; Stenchikov, Georgiy; Schepanski, Kerstin

2017-03-01

The inter-annual variability of the dust aerosol presence over the Red Sea and the Persian Gulf is analysed over the period 2005-2015. Particular attention is paid to the variation in loading across the Red Sea, which has previously been shown to have a strong, seasonally dependent latitudinal gradient. Over the 11 years considered, the July mean 630 nm aerosol optical depth (AOD) derived from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) varies between 0.48 and 1.45 in the southern half of the Red Sea. In the north, the equivalent variation is between 0.22 and 0.66. The temporal and spatial pattern of variability captured by SEVIRI is also seen in AOD retrievals from the MODerate Imaging Spectroradiometer (MODIS), but there is a systematic offset between the two records. Comparisons of both sets of retrievals with ship- and land-based AERONET measurements show a high degree of correlation with biases of < 0.08. However, these comparisons typically only sample relatively low aerosol loadings. When both records are stratified by AOD retrievals from the Multi-angle Imaging SpectroRadiometer (MISR), opposing behaviour is revealed at high MISR AODs ( > 1), with offsets of +0.19 for MODIS and -0.06 for SEVIRI. Similar behaviour is also seen over the Persian Gulf. Analysis of the scattering angles at which retrievals from the SEVIRI and MODIS measurements are typically performed in these regions suggests that assumptions concerning particle sphericity may be responsible for the differences seen.

The Influence of Aerosol Hygroscopicity on Retrieving the Aerosol Extincting Coefficient from MPL Data

NASA Astrophysics Data System (ADS)

Zhao, G.; Zhao, C.

2016-12-01

Micro-pulse Lidar (MPL) measurements have been widely used to profile the ambient aerosol extincting coefficient(). Lidar Ratio (LR) ,which highly depends on the particle number size distribution (PNSD) and aerosol hygroscopicity, is the most important factor to retrieve the profile. A constant AOD constrained LR is usually used in current algorithms, which would lead to large bias when the relative humidity (RH) in the mixed layer is high. In this research, the influences of PNSD, aerosol hygroscopicity and RH profiles on the vertical variation of LR were investigated based on the datasets from field measurements in the North China Plain (NCP). Results show that LR can have an enhancement factor of more than 120% when the RH reaches to 92%. A new algorithm of retrieving the profile is proposed based on the variation of LR due to aerosol hygroscopicity. The magnitude and vertical structures of retrieved using this method can be significantly different to that of the fiexed LR method. The relative difference can reach up to 40% when the RH in the mixed layer is higher than 90% . Sensitivity studies show that RH profile and PNSD affect most on the retrieved by fiexed LR method. In view of this, a scheme of LR enhancement factor by RH is proposed in the NCP. The relative differnce of the calculated between using this scheme and the new algorithm with the variable LR can be less than 10%.

Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

NASA Astrophysics Data System (ADS)

Zhan, Yu; Luo, Yuzhou; Deng, Xunfei; Chen, Huajin; Grieneisen, Michael L.; Shen, Xueyou; Zhu, Lizhong; Zhang, Minghua

2017-04-01

A high degree of uncertainty associated with the emission inventory for China tends to degrade the performance of chemical transport models in predicting PM2.5 concentrations especially on a daily basis. In this study a novel machine learning algorithm, Geographically-Weighted Gradient Boosting Machine (GW-GBM), was developed by improving GBM through building spatial smoothing kernels to weigh the loss function. This modification addressed the spatial nonstationarity of the relationships between PM2.5 concentrations and predictor variables such as aerosol optical depth (AOD) and meteorological conditions. GW-GBM also overcame the estimation bias of PM2.5 concentrations due to missing AOD retrievals, and thus potentially improved subsequent exposure analyses. GW-GBM showed good performance in predicting daily PM2.5 concentrations (R2 = 0.76, RMSE = 23.0 μg/m3) even with partially missing AOD data, which was better than the original GBM model (R2 = 0.71, RMSE = 25.3 μg/m3). On the basis of the continuous spatiotemporal prediction of PM2.5 concentrations, it was predicted that 95% of the population lived in areas where the estimated annual mean PM2.5 concentration was higher than 35 μg/m3, and 45% of the population was exposed to PM2.5 >75 μg/m3 for over 100 days in 2014. GW-GBM accurately predicted continuous daily PM2.5 concentrations in China for assessing acute human health effects.

Comparative Time Series Analysis of Aerosol Optical Depth over Sites in United States and China Using ARIMA Modeling

NASA Astrophysics Data System (ADS)

Li, X.; Zhang, C.; Li, W.

2017-12-01

Long-term spatiotemporal analysis and modeling of aerosol optical depth (AOD) distribution is of paramount importance to study radiative forcing, climate change, and human health. This study is focused on the trends and variations of AOD over six stations located in United States and China during 2003 to 2015, using satellite-retrieved Moderate Resolution Imaging Spectrometer (MODIS) Collection 6 retrievals and ground measurements derived from Aerosol Robotic NETwork (AERONET). An autoregressive integrated moving average (ARIMA) model is applied to simulate and predict AOD values. The R2, adjusted R2, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Bayesian Information Criterion (BIC) are used as indices to select the best fitted model. Results show that there is a persistent decreasing trend in AOD for both MODIS data and AERONET data over three stations. Monthly and seasonal AOD variations reveal consistent aerosol patterns over stations along mid-latitudes. Regional differences impacted by climatology and land cover types are observed for the selected stations. Statistical validation of time series models indicates that the non-seasonal ARIMA model performs better for AERONET AOD data than for MODIS AOD data over most stations, suggesting the method works better for data with higher quality. By contrast, the seasonal ARIMA model reproduces the seasonal variations of MODIS AOD data much more precisely. Overall, the reasonably predicted results indicate the applicability and feasibility of the stochastic ARIMA modeling technique to forecast future and missing AOD values.

Aerosol Retrieval from Multiangle Multispectral Photopolarimetric Measurements: Importance of Spectral Range and Angular Resolution

NASA Technical Reports Server (NTRS)

Wu, L.; Hasekamp, O.; Van Diedenhoven, B.; Cairns, B.

2015-01-01

We investigated the importance of spectral range and angular resolution for aerosol retrieval from multiangle photopolarimetric measurements over land. For this purpose, we use an extensive set of simulated measurements for different spectral ranges and angular resolutions and subsets of real measurements of the airborne Research Scanning Polarimeter (RSP) carried out during the PODEX and SEAC4RS campaigns over the continental USA. Aerosol retrievals performed from RSP measurements show good agreement with ground-based AERONET measurements for aerosol optical depth (AOD), single scattering albedo (SSA) and refractive index. Furthermore, we found that inclusion of shortwave infrared bands (1590 and/or 2250 nm) significantly improves the retrieval of AOD, SSA and coarse mode microphysical properties. However, accuracies of the retrieved aerosol properties do not improve significantly when more than five viewing angles are used in the retrieval.

Trend analysis of the aerosol optical depth from fusion of MISR and MODIS retrievals over China

NASA Astrophysics Data System (ADS)

Guo, Jing; Gu, Xingfa; Yu, Tao; Cheng, Tianhai; Chen, Hao

2014-03-01

Atmospheric aerosol plays an important role in the climate change though direct and indirect processes. In order to evaluate the effects of aerosols on climate, it is necessary to have a research on their spatial and temporal distributions. Satellite aerosol remote sensing is a developing technology that may provide good temporal sampling and superior spatial coverage to study aerosols. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have provided aerosol observations since 2000, with large coverage and high accuracy. However, due to the complex surface, cloud contamination, and aerosol models used in the retrieving process, the uncertainties still exist in current satellite aerosol products. There are several observed differences in comparing the MISR and MODIS AOD data with the AERONET AOD. Combing multiple sensors could reduce uncertainties and improve observational accuracy. The validation results reveal that a better agreement between fusion AOD and AERONET AOD. The results confirm that the fusion AOD values are more accurate than single sensor. We have researched the trend analysis of the aerosol properties over China based on nine-year (2002-2010) fusion data. Compared with trend analysis in Jingjintang and Yangtze River Delta, the accuracy has increased by 5% and 3%, respectively. It is obvious that the increasing trend of the AOD occurred in Yangtze River Delta, where human activities may be the main source of the increasing AOD.

A decade of infrared versus visible AOD analysis within the dust belt

NASA Astrophysics Data System (ADS)

Capelle, Virginie; Chédin, Alain; Pondrom, Marc; Crevoisier, Cyril; Armante, Raymond; Crépeau, Laurent; Scott, Noëlle

2017-04-01

Aerosols represent one of the dominant uncertainties in radiative forcing, partly because of their very high spatiotemporal variability, a still insufficient knowledge of their microphysical and optical properties, or of their vertical distribution. A better understanding and forecasting of their impact on climate therefore requires precise observations of dust emission and transport. Observations from space offer a good opportunity to follow, day by day and at high spatial resolution, dust evolution at global scale and over long time series. In this context, infrared observations, by allowing retrieving simultaneously dust optical depth (AOD) as well as the mean dust layer altitude, daytime and nighttime, over oceans and over continents, in particular over desert, appears highly complementary to observations in the visible. In this study, a decade of infrared observations (Metop-A/IASI and AIRS/AQUA) has been processed pixel by pixel, using a "Look-Up-Table" (LUT) physical approach. The retrieved infrared 10µm coarse-mode AOD is compared with the Spectral Deconvolution Algorithm (SDA) 500nm coarse mode AOD observed at 50 ground-based Aerosol RObotic NETwork (AERONET) sites located within the dust belt. Analyzing their brings into evidence an important geographical variability. Lowest values are found close to dust sources ( 0.45 for the Sahel or Arabian Peninsula, 0.6-0.7 for the Northern part of Africa or India), whereas the ratio increases for transported dust with values of 0.9-1 for the Caribbean and for the Mediterranean basin. This variability is interpreted as a marker of clays abundance, and might be linked to the dust particle illite to kaolinite ratio, a recognized tracer of dust sources and transport. More generally, it suggests that the difference between the radiative impact of dust aerosols in the visible and in the infrared depends on the type of particles observed. This highlights the importance of taking into account the specificity of the infrared when considering the role of mineral dust on the Earth's energy budget.

Estimating Ground-Level PM(sub 2.5) Concentrations in the Southeastern United States Using MAIAC AOD Retrievals and a Two-Stage Model

NASA Technical Reports Server (NTRS)

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Al-Hamdan, Mohammad Z.; Crosson, William L.; Estes, Maurice G., Jr.; Estes, Sue M.; Quattrochi, Dale A.; Puttaswamy, Sweta Jinnagara;

The CU 2-D-MAX-DOAS instrument - Part 2: Raman scattering probability measurements and retrieval of aerosol optical properties

NASA Astrophysics Data System (ADS)

Ortega, Ivan; Coburn, Sean; Berg, Larry K.; Lantz, Kathy; Michalsky, Joseph; Ferrare, Richard A.; Hair, Johnathan W.; Hostetler, Chris A.; Volkamer, Rainer

2016-08-01

The multiannual global mean of aerosol optical depth at 550 nm (AOD550) over land is ˜ 0.19, and that over oceans is ˜ 0.13. About 45 % of the Earth surface shows AOD550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity. We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 < AOD430 < 0.6) and (2) near-molecular scattering conditions (22 July, AOD430 < 0.13) we compare RSP-based retrievals of AOD430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD430 is +0.012 ± 0.023 (CIMEL), -0.012 ± 0.024 (MFRSR), -0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMELAOD - MFRSRAOD) and yields the following expressions for correlations between different instruments: DOASAOD = -(0.019 ± 0.006) + (1.03 ± 0.02) × CIMELAOD (R2 = 0.98), DOASAOD = -(0.006 ± 0.005) + (1.08 ± 0.02) × MFRSRAOD (R2 = 0.98), and CIMELAOD = (0.013 ± 0.004) + (1.05 ± 0.01) × MFRSRAOD (R2 = 0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD430 ˜ 0.4 and 0.10 the absolute AOD errors are ˜ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35° SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.

Retrieval and Validation of aerosol optical properties from AHI measurements: impact of surface reflectance assumption

NASA Astrophysics Data System (ADS)

Lim, H.; Choi, M.; Kim, J.; Go, S.; Chan, P.; Kasai, Y.

2017-12-01

This study attempts to retrieve the aerosol optical properties (AOPs) based on the spectral matching method, with using three visible and one near infrared channels (470, 510, 640, 860nm). This method requires the preparation of look-up table (LUT) approach based on the radiative transfer modeling. Cloud detection is one of the most important processes for guaranteed quality of AOPs. Since the AHI has several infrared channels, which are very advantageous for cloud detection, clouds can be removed by using brightness temperature difference (BTD) and spatial variability test. The Yonsei Aerosol Retrieval (YAER) algorithm is basically utilized on a dark surface, therefore a bright surface (e.g., desert, snow) should be removed first. Then we consider the characteristics of the reflectance of land and ocean surface using three visible channels. The known surface reflectivity problem in high latitude area can be solved in this algorithm by selecting appropriate channels through improving tests. On the other hand, we retrieved the AOPs by obtaining the visible surface reflectance using NIR to normalized difference vegetation index short wave infrared (NDVIswir) relationship. ESR tends to underestimate urban and cropland area, we improved the visible surface reflectance considering urban effect. In this version, ocean surface reflectance is using the new cox and munk method which considers ocean bidirectional reflectance distribution function (BRDF). Input of this method has wind speed, chlorophyll, salinity and so on. Based on validation results with the sun-photometer measurement in AErosol Robotic NETwork (AERONET), we confirm that the quality of Aerosol Optical Depth (AOD) from the YAER algorithm is comparable to the product from the Japan Aerospace Exploration Agency (JAXA) retrieval algorithm. Our future update includes a consideration of improvement land surface reflectance by hybrid approach, and non-spherical aerosols. This will improve the quality of YAER algorithm more, particularly retrieval for the dust particle over the bright surface in East Asia.

Method for estimating the atmospheric content of sub-micrometer aerosol using direct-sun photometric data

NASA Astrophysics Data System (ADS)

Stefan, S.; Filip, L.

2009-04-01

It is well known that the aerosol generated by human activity falls in the sub-micrometer rage [1]. The rapid increase of such emissions led to massive accumulations in the planetary boundary layer. Aerosol pollutants influence the quality of life on the Earth in at least two ways: by direct physiological effects following their penetration into living organisms and by the indirect implications on the overall energy balance of the Earth-atmosphere system. For these reasons monitoring the sub-micrometer aerosol on a global scale, become a stringent necessity in protecting the environment. The sun-photometry proved a very efficient way for such monitoring activities, mainly when vast networks of instruments (like AERONET [2]) are used. The size distribution of aerosols is currently a product of AERONET obtained through an inversion algorithm of sky-photometry data [3, 4]. Alternatively, various methods of investigating the aerosol size distribution have been developed through the use of direct-sun photometric data, with the advantages of simpler computation algorithms and a more convenient use [5, 6]. Our research aims to formulate a new simpler way to retrieve aerosol fine and coarse mode volume concentrations, as well as dimensional information, from direct-sun data. As in other works from the literature [3-6], the main hypothesis is that of a bi-modal shape of the size distribution of aerosols that can be reproduced rather satisfactorily by a linear combination of two lognormal functions. Essentially, the method followed in this paper relies on aerosol size information retrieval through fitting theoretical computations to measured aerosol optical depth (AOD) and related data. To this purpose, the experimental spectral dependence of AOD is interpolated and differentiated numerically to obtain the Ǻngström parameter. The reduced (i.e. normalized to the corresponding columnar volumetric content) contributions of the fine and coarse modes to the AOD have also been calculated through the Mie theory [7]. As some dimensional (e.g. standard deviations) and physical (e.g. refractive indexes) parameters of the two considered aerosol modes have relatively small variations with little influence on the AOD and Ǻngström parameter in a given area of interest [3], their values have been set to local annual averages. The theoretical AOD and Ǻngström parameter have thus been constructed from the corresponding modal contributions using the modal columnar volumetric aerosol contents and the modal radii as fitting parameters. Their values follow from a best simultaneous fit of both AOD and Ǻngström parameter. Given the fact that the Mie computations are rather time consuming for a satisfactory level of precision, the fitting procedure may be significantly accelerated by computing first the reduced AOD and the Ǻngström parameter for each mode in a limited grid of values for the modal radii and then constructing interpolation functions that allow a much faster access to intermediate points. Comparison of columnar volumetric aerosol contents and modal radii obtained through our procedure to similar AERONET sky-photometry product data show good correlation and demonstrates the reliability of the proposed method. References [1] G. E. Shaw, Sun photometry, Bulletin of the American Meteorological Society 64, pp. 4-11 (1983). [2] A description of AERONET activities can be found at the following web site: http://aeronet.gsfc.nasa.gov/index.html [3] T. Nakajima, G. Tonna, R. Rao, P. Boi, Y. Kaufman, and B. Holben, Use of sky brightness measurements from ground for remote sensing of particulate polydispersions, Applied Optics 35(15), pp. 2672-2686 (1996). [4] O. Dubovik and M. D. King, A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res. 105, pp. 20673-20696 (2000). [5] N. T. O'Neill, O. Dubovik, and T. F. Eck, Modified Ångström exponent for the characterization of submicrometer aerosols, Applied Optics 40(15), pp. 2368-2375 (2001). [6] G. P. Gobbi, Y. J. Kaufman, I. Koren, and T. F. Eck, Classification of aerosol properties derived from AERONET direct sun data, Atmospherical Chemical Physics 7, 453-458 (2007). [7] K.-N. Liou, An Introduction to Atmospheric Radiation, Academic Press, New York, 1980.

Aerosol Lidar and MODIS Satellite Comparisons for Future Aerosol Loading Forecast

NASA Technical Reports Server (NTRS)

DeYoung, Russell; Szykman, James; Severance, Kurt; Chu, D. Allen; Rosen, Rebecca; Al-Saadi, Jassim

2006-01-01

Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and Aqua satellites, were take over the Central Valley. The MODIS Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km. The Central Valley topography was overlaid with MODIS AOD (5x5 sq km resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and MODIS AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the MODIS AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.

Utilization of O4 slant column density to derive aerosol layer height from a spaceborne UV-visible hyperspectral sensor: sensitivity and case study

NASA Astrophysics Data System (ADS)

Park, S. S.; Kim, J.; Lee, H.; Torres, O.; Lee, K.-M.; Lee, S. D.

2015-03-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using simulated radiances by a radiative transfer model, Linearized Discrete Ordinate Radiative Transfer (LIDORT), and Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 SCDs to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4 SCD at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 414 m (16.5%), 564 m (22.4%), and 1343 m (52.5%) for absorbing, dust, and non-absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution type. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). The retrieved aerosol effective heights are lower by approximately 300 m (27 %) compared to those obtained from the ground-based LIDAR measurements.

Monitoring of 2007 wildfires in GA and CA by GOES Aerosol/Smoke Product (ASP): Comparisons to MODIS and CALIPSO

NASA Astrophysics Data System (ADS)

Xu, C.; Kondragunta, S.

2008-05-01

The purpose of this study is to understand the potential for using the GOES Aerosol/Smoke Product (GASP) to monitor wild fires over the United States. GASP AOD is retrieved using visible imagery from Geostationary Operational Environment Satellite (GOES) at 30 minute interval. This high temporal estimate of AOD provides significantly dense information of air quality in near real time. Hourly or daily animations of GASP aerosol optical depth for smoke plumes suggest that development and variation of wild fires can be determined by GASP. Also, the performances of GASP AOD are compared to other satellite data from MODerate-resolution Imaging Spectro- radiometers (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The results reveal that GOES AOD has same level performance for monitoring wild fires as those of MODIS and CALIPSO. Therefore, we believe that the retrieval accuracy of GOES is adequate for monitoring larger outbreaks of aerosol events.

An Accuracy Assessment of the CALIOP/CALIPSO Version 2/Version 3 Daytime Aerosol Extinction Product Based on a Detailed Multi-Sensor, Multi-Platform Case Study

NASA Technical Reports Server (NTRS)

Kacenelenbogen, M.; Vaughan, M. A.; Redemann, J.; Hoff, R. M.; Rogers, R. R.; Ferrare, R. A.; Russell, P. B.; Hostetler, C. A.; Hair, J. W.; Holben, B. N.

2011-01-01

The Cloud Aerosol LIdar with Orthogonal Polarization (CALIOP), on board the CALIPSO platform, has measured profiles of total attenuated backscatter coefficient (level 1 products) since June 2006. CALIOP s level 2 products, such as the aerosol backscatter and extinction coefficient profiles, are retrieved using a complex succession of automated algorithms. The goal of this study is to help identify potential shortcomings in the CALIOP version 2 level 2 aerosol extinction product and to illustrate some of the motivation for the changes that have been introduced in the next version of CALIOP data (version 3, released in June 2010). To help illustrate the potential factors contributing to the uncertainty of the CALIOP aerosol extinction retrieval, we focus on a one-day, multi-instrument, multiplatform comparison study during the CALIPSO and Twilight Zone (CATZ) validation campaign on 4 August 2007. On that day, we observe a consistency in the Aerosol Optical Depth (AOD) values recorded by four different instruments (i.e. spaceborne MODerate Imaging Spectroradiometer, MODIS: 0.67 and POLarization and Directionality of Earth s Reflectances, POLDER: 0.58, airborne High Spectral Resolution Lidar, HSRL: 0.52 and ground-based AErosol RObotic NETwork, AERONET: 0.48 to 0.73) while CALIOP AOD is a factor of two lower (0.32 at 532 nm). This case study illustrates the following potential sources of uncertainty in the CALIOP AOD: (i) CALIOP s low signal-to-noise ratio (SNR) leading to the misclassification and/or lack of aerosol layer identification, especially close to the Earth s surface; (ii) the cloud contamination of CALIOP version 2 aerosol backscatter and extinction profiles; (iii) potentially erroneous assumptions of the aerosol extinction-to-backscatter ratio (Sa) used in CALIOP s extinction retrievals; and (iv) calibration coefficient biases in the CALIOP daytime attenuated backscatter coefficient profiles. The use of version 3 CALIOP extinction retrieval for our case study seems to partially fix factor (i) although the aerosol retrieved by CALIOP is still somewhat lower than the profile measured by HSRL; the cloud contamination (ii) appears to be corrected; no particular change is apparent in the observation-based CALIOP Sa value (iii). Our case study also showed very little difference in version 2 and version 3 CALIOP attenuated backscatter coefficient profiles, illustrating a minor change in the calibration scheme (iv).

Aerosol single-scattering albedo over the global oceans: Comparing PARASOL retrievals with AERONET, OMI, and AeroCom models estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lacagnina, Carlo; Hasekamp, Otto P.; Bian, Huisheng

2015-09-27

The aerosol Single Scattering Albedo (SSA) over the global oceans is evaluated based on polarimetric measurements by the PARASOL satellite. The retrieved values for SSA and Aerosol Optical Depth (AOD) agree well with the ground-based measurements of the AErosol RObotic NETwork (AERONET). The global coverage provided by the PARASOL observations represents a unique opportunity to evaluate SSA and AOD simulated by atmospheric transport model runs, as performed in the AeroCom framework. The SSA estimate provided by the AeroCom models is generally higher than the SSA retrieved from both PARASOL and AERONET. On the other hand, the mean simulated AOD ismore » about right or slightly underestimated compared with observations. An overestimate of the SSA by the models would suggest that these simulate an overly strong aerosol radiative cooling at top-of-atmosphere (TOA) and underestimate it at surface. This implies that aerosols have a potential stronger impact within the atmosphere than currently simulated.« less

Comparing MODIS C6 'Deep Blue' and 'Dark Target' Aerosol Data

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Sayer, A. M.; Bettenhausen, C.; Lee, J.; Levy, R. C.; Mattoo, S.; Munchak, L. A.; Kleidman, R.

2014-01-01

The MODIS Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from MODIS Aqua measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.

Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets.

NASA Astrophysics Data System (ADS)

Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanré, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

2005-04-01

Understanding the impact of aerosols on the earth's radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth's Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product.This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions

NASA Astrophysics Data System (ADS)

Gupta, Pawan; Remer, Lorraine A.; Levy, Robert C.; Mattoo, Shana

2018-05-01

In addition to the standard resolution product (10 km), the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) data release included a higher resolution (3 km). Other than accommodations for the two different resolutions, the 10 and 3 km Dark Target (DT) algorithms are basically the same. In this study, we perform global validation of the higher-resolution aerosol optical depth (AOD) over global land by comparing against AErosol RObotic NETwork (AERONET) measurements. The MODIS-AERONET collocated data sets consist of 161 410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4 % of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2 × AOD), with a high correlation (R = 0.87). The scatter is not random, but exhibits a mean positive bias of ˜ 0.06 for Terra and ˜ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e., true AOD), but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with Terra MODIS showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

NASA Astrophysics Data System (ADS)

Antuña-Marrero, Juan Carlos; Cachorro Revilla, Victoria; García Parrado, Frank; de Frutos Baraja, Ángel; Rodríguez Vega, Albeth; Mateos, David; Estevan Arredondo, René; Toledano, Carlos

2018-04-01

In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AODt) and Aqua (AODa) satellites and those measured using a sun photometer (AODSP) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AODta) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AODt, AODa, AODta compared to AODSP. For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AODta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AODt, AODa, AODta vs. AODSP, with a slight overestimation of satellite data compared to AODSP, (f). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AODta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AODSP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS-sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

Global aerosol typing from a combination of A-Train satellite observations in clear-sky and above clouds

NASA Astrophysics Data System (ADS)

Kacenelenbogen, M. S.; Russell, P. B.; Vaughan, M.; Redemann, J.; Shinozuka, Y.; Livingston, J. M.; Zhang, Q.

2014-12-01

According to the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), the model estimates of Radiative Forcing due to aerosol-radiation interactions (RFari) for individual aerosol types are less certain than the total RFari [Boucher et al., 2013]. For example, the RFari specific to Black Carbon (BC) is uncertain due to an underestimation of its mass concentration near source regions [Koch et al., 2009]. Several recent studies have evaluated chemical transport model (CTM) predictions using observations of aerosol optical properties such as Aerosol Optical Depth (AOD) or Single Scattering Albedo (SSA) from satellite or ground-based instruments (e.g., Huneeus et al., [2010]). However, most passive remote sensing instruments fail to provide a comprehensive assessment of the particle type without further analysis and combination of measurements. To improve the predictions of aerosol composition in CTMs, we have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground based passive remote sensing instruments [Russell et al., 2014]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrial/developed economy, urban-industrial/developing economy, dark biomass smoke, light biomass smoke and pure marine. First, we apply the SCMC method to five years of clear-sky space-borne POLDER observations over Greece. We then use the aerosol extinction and SSA spectra retrieved from a combination of MODIS, OMI and CALIOP clear-sky observations to infer the aerosol type over the globe in 2007. Finally, we will extend the spaceborne aerosol classification from clear-sky to above low opaque water clouds using a combination of CALIOP AOD and backscatter observations and OMI absorption AOD values from near-by clear-sky pixels.

Climatology of the Aerosol Optical Depth by Components from the Multi-Angle Imaging Spectroradiometer (MISR) and Chemistry Transport Models

NASA Technical Reports Server (NTRS)

Lee, Huikyo; Kalashnikova, Olga V.; Suzuki, Kentaroh; Braverman, Amy; Garay, Michael J.; Kahn, Ralph A.

2016-01-01

The Multi-angle Imaging Spectroradiometer (MISR) Joint Aerosol (JOINT_AS) Level 3 product has provided a global, descriptive summary of MISR Level 2 aerosol optical depth (AOD) and aerosol type information for each month over 16+ years since March 2000. Using Version 1 of JOINT_AS, which is based on the operational (Version 22) MISR Level 2 aerosol product, this study analyzes, for the first time, characteristics of observed and simulated distributions of AOD for three broad classes of aerosols: spherical nonabsorbing, spherical absorbing, and nonspherical - near or downwind of their major source regions. The statistical moments (means, standard deviations, and skew-nesses) and distributions of AOD by components derived from the JOINT_AS are compared with results from two chemistry transport models (CTMs), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) and SPectral RadIatioN-TrAnSport (SPRINTARS). Overall, the AOD distributions retrieved from MISR and modeled by GOCART and SPRINTARS agree with each other in a qualitative sense. Marginal distributions of AOD for each aerosol type in both MISR and models show considerable high positive skewness, which indicates the importance of including extreme AOD events when comparing satellite retrievals with models. The MISR JOINT_AS product will greatly facilitate comparisons between satellite observations and model simulations of aerosols by type.

Campaign datasets for Two-Column Aerosol Project (TCAP)

DOE Data Explorer

Berg,Larry; Mei,Fan; Cairns,Brian; Chand,Duli; Comstock,Jennifer; Cziczo,Daniel; Hostetler,Chris; Hubbe,John; Long,Chuck; Michalsky,Joseph; Pekour,Mikhail; Russell,Phil; Scott,Herman; Sedlacek,Arthur; Shilling,John; Springston,Stephen; Tomlinson,Jason; Watson,Thomas; Zelenyuk-Imre,Alla

2013-12-30

This campaign was designed to provide a detailed set of observations with which to 1) perform radiative and cloud condensation nuclei (CCN) closure studies, 2) evaluate a new retrieval algorithm for aerosol optical depth (AOD) in the presence of clouds using passive remote sensing 3) extend a previously developed technique to investigate aerosol indirect effects, and 4) evaluate the performance of a detailed regional-scale model and a more parameterized global-scale model in simulating particle activation and AOD associated with the aging of anthropogenic aerosols. To meet these science objectives, the ARM Mobile Facility (AMF) and the Mobile Aerosol Observing System (MAOS) was deployed on Cape Cod, Massachusetts for a 12-month period starting in the summer of 2012 in order to quantify aerosol properties, radiation and cloud characteristics at a location subject to both clear- and cloudy- conditions, and clean- and polluted-conditions. These observations were supplemented by two aircraft intensive observation periods (IOPS), one in the summer and a second in the winter. Each IOP required two aircraft.

10-year spatial and temporal trends of PM2.5 concentrations in the southeastern US estimated using high-resolution satellite data

PubMed Central

Hu, X.; Waller, L. A.; Lyapustin, A.; Wang, Y.; Liu, Y.

2017-01-01

Long-term PM2.5 exposure has been associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of the spatiotemporally continuous distribution of PM2.5 concentrations are important. Satellite-retrieved aerosol optical depth (AOD) has been increasingly used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, previous studies indicated that an inherent disadvantage of many AOD products is their coarse spatial resolution. For instance, the available spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) AOD products are 10 and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm based on MODIS measurements was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5–AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US centered at the Atlanta metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted annually, and we obtained model fitting R2 ranging from 0.71 to 0.85, mean prediction error (MPE) from 1.73 to 2.50 μg m−3, and root mean squared prediction error (RMSPE) from 2.75 to 4.10 μg m−3. In addition, we found cross-validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 μgm−3, and RMSPE from 3.12 to 5.00 μgm−3, indicating a good agreement between the estimated and observed values. Spatial trends showed that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. Our time-series analysis showed that, for the 10-year study period, the PM2.5 levels in the southeastern US have decreased by ∼20 %. The annual decrease has been relatively steady from 2001 to 2007 and from 2008 to 2010 while a significant drop occurred between 2007 and 2008. An observed increase in PM2.5 levels in year 2005 is attributed to elevated sulfate concentrations in the study area in warm months of 2005. PMID:28966656

Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data

NASA Astrophysics Data System (ADS)

Bibi, Humera; Alam, Khan; Chishtie, Farrukh; Bibi, Samina; Shahid, Imran; Blaschke, Thomas

2015-06-01

This study provides an intercomparison of aerosol optical depth (AOD) retrievals from satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), Ozone Monitoring Instrument (OMI), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) instrumentation over Karachi, Lahore, Jaipur, and Kanpur between 2007 and 2013, with validation against AOD observations from the ground-based Aerosol Robotic Network (AERONET). Both MODIS Deep Blue (MODISDB) and MODIS Standard (MODISSTD) products were compared with the AERONET products. The MODISSTD-AERONET comparisons revealed a high degree of correlation for the four investigated sites at Karachi, Lahore, Jaipur, and Kanpur, the MODISDB-AERONET comparisons revealed even better correlations, and the MISR-AERONET comparisons also indicated strong correlations, as did the OMI-AERONET comparisons, while the CALIPSO-AERONET comparisons revealed only poor correlations due to the limited number of data points available. We also computed figures for root mean square error (RMSE), mean absolute error (MAE) and root mean bias (RMB). Using AERONET data to validate MODISSTD, MODISDB, MISR, OMI, and CALIPSO data revealed that MODISSTD data was more accurate over vegetated locations than over un-vegetated locations, while MISR data was more accurate over areas close to the ocean than over other areas. The MISR instrument performed better than the other instruments over Karachi and Kanpur, while the MODISSTD AOD retrievals were better than those from the other instruments over Lahore and Jaipur. We also computed the expected error bounds (EEBs) for both MODIS retrievals and found that MODISSTD consistently outperformed MODISDB in all of the investigated areas. High AOD values were observed by the MODISSTD, MODISDB, MISR, and OMI instruments during the summer months (April-August); these ranged from 0.32 to 0.78, possibly due to human activity and biomass burning. In contrast, high AOD values were observed by the CALIPSO instrument between September and December, due to high concentrations of smoke and soot aerosols. The variable monthly AOD figures obtained with different sensors indicate overestimation by MODISSTD, MODISDB, OMI, and CALIPSO instruments over Karachi, Lahore, Jaipur and Kanpur, relative to the AERONET data, but underestimation by the MISR instrument.

Maritime Aerosol Network as a Component of AERONET - First Results and Comparison with Global Aerosol Models and Satellite Retrievals

NASA Technical Reports Server (NTRS)

Smirnov, A.; Holben, B. N.; Giles, D. M.; Slutsker, I.; O'Neill, N. T.; Eck, T. F.; Macke, A.; Croot, P.; Courcoux, Y.; Sakerin, S. M.;

Maritime Aerosol Network as a component of AERONET - first results and comparison with global aerosol models and satellite retrievals

NASA Astrophysics Data System (ADS)

Smirnov, A.; Holben, B. N.; Giles, D. M.; Slutsker, I.; O'Neill, N. T.; Eck, T. F.; Macke, A.; Croot, P.; Courcoux, Y.; Sakerin, S. M.; Smyth, T. J.; Zielinski, T.; Zibordi, G.; Goes, J. I.; Harvey, M. J.; Quinn, P. K.; Nelson, N. B.; Radionov, V. F.; Duarte, C. M.; Losno, R.; Sciare, J.; Voss, K. J.; Kinne, S.; Nalli, N. R.; Joseph, E.; Krishna Moorthy, K.; Covert, D. S.; Gulev, S. K.; Milinevsky, G.; Larouche, P.; Belanger, S.; Horne, E.; Chin, M.; Remer, L. A.; Kahn, R. A.; Reid, J. S.; Schulz, M.; Heald, C. L.; Zhang, J.; Lapina, K.; Kleidman, R. G.; Griesfeller, J.; Gaitley, B. J.; Tan, Q.; Diehl, T. L.

2011-01-01

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurements areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops hand-held sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations.

Maritime aerosol network as a component of AERONET - first results and comparison with global aerosol models and satellite retrievals

NASA Astrophysics Data System (ADS)

Smirnov, A.; Holben, B. N.; Giles, D. M.; Slutsker, I.; O'Neill, N. T.; Eck, T. F.; Macke, A.; Croot, P.; Courcoux, Y.; Sakerin, S. M.; Smyth, T. J.; Zielinski, T.; Zibordi, G.; Goes, J. I.; Harvey, M. J.; Quinn, P. K.; Nelson, N. B.; Radionov, V. F.; Duarte, C. M.; Losno, R.; Sciare, J.; Voss, K. J.; Kinne, S.; Nalli, N. R.; Joseph, E.; Krishna Moorthy, K.; Covert, D. S.; Gulev, S. K.; Milinevsky, G.; Larouche, P.; Belanger, S.; Horne, E.; Chin, M.; Remer, L. A.; Kahn, R. A.; Reid, J. S.; Schulz, M.; Heald, C. L.; Zhang, J.; Lapina, K.; Kleidman, R. G.; Griesfeller, J.; Gaitley, B. J.; Tan, Q.; Diehl, T. L.

2011-03-01

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurement areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops hand-held sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations.

Aerosol optical depth under "clear" sky conditions derived from sea surface reflection of lidar signals.

PubMed

He, Min; Hu, Yongxiang; Huang, Jian Ping; Stamnes, Knut

2016-12-26

There are considerable demands for accurate atmospheric correction of satellite observations of the sea surface or subsurface signal. Surface and sub-surface reflection under "clear" atmospheric conditions can be used to study atmospheric correction for the simplest possible situation. Here "clear" sky means a cloud-free atmosphere with sufficiently small aerosol particles. The "clear" aerosol concept is defined according to the spectral dependence of the scattering cross section on particle size. A 5-year combined CALIPSO and AMSR-E data set was used to derive the aerosol optical depth (AOD) from the lidar signal reflected from the sea surface. Compared with the traditional lidar-retrieved AOD, which relies on lidar backscattering measurements and an assumed lidar ratio, the AOD retrieved through the surface reflectance method depends on both scattering and absorption because it is based on two-way attenuation of the lidar signal transmitted to and then reflected from the surface. The results show that the clear sky AOD derived from the surface signal agrees with the clear sky AOD available in the CALIPSO level 2 database in the westerly wind belt located in the southern hemisphere, but yields significantly higher aerosol loadings in the tropics and in the northern hemisphere.

Effects of Aerosol Pollution on Clouds over Megacities

NASA Astrophysics Data System (ADS)

Sechrist, B.; Jacobson, M. Z.

2013-12-01

The correlation between aerosol optical depth (AOD) and cloud properties - principally cloud fraction and cloud optical depth (COD) - is examined using satellite retrievals from the MODIS satellites over Los Angeles and Beijing. Ten Hoeve et al. (2011, Atmos. Chem. Phys, 11(7), 3021-3036) used satellite data to examine the impact of aerosols on warm clouds around Rondonia, Brazil, during the biomass burning season. They found that the COD-AOD relationship exhibits a 'boomerang' shape in which COD initially increases with increasing AOD but then decreases as AOD continues to increase beyond some critical level. This result is thought to reflect the balance between the microphysical and radiative components of a cloud's response to aerosols. The microphysical process dominates at low AOD, while the radiative process dominates at high AOD. This study is analogous to Ten Hoeve et al., but for aerosols derived primarily from fossil fuel combustion rather than biomass burning. Preliminary results will be presented.

An 11-year analysis of satellite retrievals of dust aerosol over the Red Sea and the Persian Gulf

NASA Astrophysics Data System (ADS)

Banks, Jamie; Brindley, Helen; Schepanski, Kerstin; Stenchikov, Georgiy

2017-04-01

As enclosed seas bordering two large desert regions, the Saharan and Arabian deserts, the maritime environments of the Red Sea and the Persian Gulf are heavily influenced by the presence of desert dust aerosol. The inter-annual variability of dust presence over the Red Sea is analysed and presented, with respect to the summer-time latitudinal gradient in dust loading, which is at a maximum in the far south of the Red Sea and at a minimum in the far north. Two satellite aerosol optical depth (AOD) products from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the MODerate resolution Imaging Spectroradiometer (MODIS) instruments are used to quantify this loading over the region. Over an eleven-year period from 2005-2015 the July mean SEVIRI AODs at 630 nm vary between 0.48 and 1.45 in the southern half of the Sea, while in the north this varies between 0.22 and 0.66. Inter-retrieval offsets are observed to occur at higher dust loadings, with pronounced positive MODIS-SEVIRI AOD offsets at AODs greater than 1, indicating substantial and systematic differences between the retrievals over the Red Sea at high dust loadings. These differences appear to be influenced in part by the differences in scattering angle range of the satellite measurements, implying that assumptions of particle shape introduce more substantial biases at the highest dust loadings.

An example of aerosol pattern variability over bright surface using high resolution MODIS MAIAC: The eastern and western areas of the Dead Sea and environs.

PubMed

Lee, Sever; Pinhas, Alpert; Alexei, Lyapustin; Yujie, Wang; Alexandra, Chudnovsky A

2017-09-01

The extreme rate of evaporation of the Dead Sea (DS) has serious implicatios for the surrounding area, including atmospheric conditions. This study analyzes the aerosol properties over the western and eastern parts of the DS during the year 2013, using MAIAC (Multi-Angle Implementation of Atmospheric Correction) for MODIS, which retrieves aerosol optical depth (AOD) data at a resolution of 1km. The main goal of the study is to evaluate MAIAC over the study area and determine, for the first time, the prevailing aerosol spatial patterns. First, the MAIAC-derived AOD data was compared with data from three nearby AERONET sites (Nes Ziona - an urban site, and Sede Boker and Masada - two arid sites), and with the conventional Dark Target (DT) and Deep Blue (DB) retrievals for the same days and locations, on a monthly basis throughout 2013. For the urban site, the correlation coefficient (r) for DT/DB products showed better performance than MAIAC (r=0.80, 0.75, and 0.64 respectively) year-round. However, in the arid zones, MAIAC showed better correspondence to AERONET sites than the conventional retrievals (r=0.58-0.60 and 0.48-0.50 respectively). We investigated the difference in AOD levels, and its variability, between the Dead Sea coasts on a seasonal basis and calculated monthly/seasonal AOD averages for presenting AOD patterns over arid zones. Thus, we demonstrated that aerosol concentrations show a strong preference for the western coast, particularly during the summer season. This preference, is most likely a result of local anthropogenic emissions combined with the typical seasonal synoptic conditions, the Mediterranean Sea breeze, and the region complex topography. Our results also indicate that a large industrial zone showed higher AOD levels compared to an adjacent reference-site, i.e., 13% during the winter season.

Prediction of daily fine particulate matter concentrations using aerosol optical depth retrievals from the Geostationary Operational Environmental Satellite (GOES).

PubMed

Chudnovsky, Alexandra A; Lee, Hyung Joo; Kostinski, Alex; Kotlov, Tanya; Koutrakis, Petros

2012-09-01

Although ground-level PM2.5 (particulate matter with aerodynamic diameter < 2.5 microm) monitoring sites provide accurate measurements, their spatial coverage within a given region is limited and thus often insufficient for exposure and epidemiological studies. Satellite data expand spatial coverage, enhancing our ability to estimate location- and/or subject-specific exposures to PM2.5. In this study, the authors apply a mixed-effects model approach to aerosol optical depth (AOD) retrievals from the Geostationary Operational Environmental Satellite (GOES) to predict PM2.5 concentrations within the New England area of the United States. With this approach, it is possible to control for the inherent day-to-day variability in the AOD-PM2.5 relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles, and ground surface reflectance. The model-predicted PM2.5 mass concentration are highly correlated with the actual observations, R2 = 0.92. Therefore, adjustment for the daily variability in AOD-PM2.5 relationship allows obtaining spatially resolved PM2.5 concentration data that can be of great value to future exposure assessment and epidemiological studies. The authors demonstrated how AOD can be used reliably to predict daily PM2.5 mass concentrations, providing determination of their spatial and temporal variability. Promising results are found by adjusting for daily variability in the AOD-PM2.5 relationship, without the need to account for a wide variety of individual additional parameters. This approach is of a great potential to investigate the associations between subject-specific exposures to PM2.5 and their health effects. Higher 4 x 4-km resolution GOES AOD retrievals comparing with the conventional MODerate resolution Imaging Spectroradiometer (MODIS) 10-km product has the potential to capture PM2.5 variability within the urban domain.

A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

2014-01-01

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the synergic use of two future geostationary satellites, GOES-R (Geostationary Operational Environmental Satellite R-series) and TEMPO (Tropospheric Emissions: Monitoring of Pollution). Strong synergy between GEOS-R and TEMPO are found especially in their characterization of surface bi-directional reflectance, and thereby, can potentially improve the AOD retrieval to the accuracy required by GEO-CAPE.

Use of A-Train Aerosol Observations to Constrain Direct Aerosol Radiative Effects (DARE) Comparisons with Aerocom Models and Uncertainty Assessments

NASA Technical Reports Server (NTRS)

Redemann, J.; Shinozuka, Y.; Kacenelenbogen, M.; Segal-Rozenhaimer, M.; LeBlanc, S.; Vaughan, M.; Stier, P.; Schutgens, N.

2017-01-01

We describe a technique for combining multiple A-Train aerosol data sets, namely MODIS spectral AOD (aerosol optical depth), OMI AAOD (absorption aerosol optical depth) and CALIOP aerosol backscatter retrievals (hereafter referred to as MOC retrievals) to estimate full spectral sets of aerosol radiative properties, and ultimately to calculate the 3-D distribution of direct aerosol radiative effects (DARE). We present MOC results using almost two years of data collected in 2007 and 2008, and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the MODIS Collection 6 AOD data derived with the dark target and deep blue algorithms has extended the coverage of the MOC retrievals towards higher latitudes. The MOC aerosol retrievals agree better with AERONET in terms of the single scattering albedo (ssa) at 441 nm than ssa calculated from OMI and MODIS data alone, indicating that CALIOP aerosol backscatter data contains information on aerosol absorption. We compare the spatio-temporal distribution of the MOC retrievals and MOC-based calculations of seasonal clear-sky DARE to values derived from four models that participated in the Phase II AeroCom model intercomparison initiative. Overall, the MOC-based calculations of clear-sky DARE at TOA over land are smaller (less negative) than previous model or observational estimates due to the inclusion of more absorbing aerosol retrievals over brighter surfaces, not previously available for observationally-based estimates of DARE. MOC-based DARE estimates at the surface over land and total (land and ocean) DARE estimates at TOA are in between previous model and observational results. Comparisons of seasonal aerosol property to AeroCom Phase II results show generally good agreement best agreement with forcing results at TOA is found with GMI-MerraV3. We discuss sampling issues that affect the comparisons and the major challenges in extending our clear-sky DARE results to all-sky conditions. We present estimates of clear-sky and all-sky DARE and show uncertainties that stem from the assumptions in the spatial extrapolation and accuracy of aerosol and cloud properties, in the diurnal evolution of these properties, and in the radiative transfer calculations.

Long-term aerosol climatology over Indo-Gangetic Plain: Trend, prediction and potential source fields

NASA Astrophysics Data System (ADS)

Kumar, M.; Parmar, K. S.; Kumar, D. B.; Mhawish, A.; Broday, D. M.; Mall, R. K.; Banerjee, T.

2018-05-01

Long-term aerosol climatology is derived using Terra MODIS (Collection 6) enhanced Deep Blue (DB) AOD retrieval algorithm to investigate decadal trend (2006-2015) in columnar aerosol loading, future scenarios and potential source fields over the Indo-Gangetic Plain (IGP), South Asia. Satellite based aerosol climatology was analyzed in two contexts: for the entire IGP considering area weighted mean AOD and for nine individual stations located at upper (Karachi, Multan, Lahore), central (Delhi, Kanpur, Varanasi, Patna) and lower IGP (Kolkata, Dhaka). A comparatively high aerosol loading (AOD: 0.50 ± 0.25) was evident over IGP with a statistically insignificant increasing trend of 0.002 year-1. Analysis highlights the existing spatial and temporal gradients in aerosol loading with stations over central IGP like Varanasi (decadal mean AOD±SD; 0.67 ± 0.28) and Patna (0.65 ± 0.30) exhibit the highest AOD, followed by stations over lower IGP (Kolkata: 0.58 ± 0.21; Dhaka: 0.60 ± 0.24), with a statistically significant increasing trend (0.0174-0.0206 year-1). In contrast, stations over upper IGP reveal a comparatively low aerosol loading, having an insignificant increasing trend. Variation in AOD across IGP is found to be mainly influenced by seasonality and topography. A distinct "aerosol pool" region over eastern part of Ganges plain is identified, where meteorology, topography, and aerosol sources favor the persistence of airborne particulates. A strong seasonality in aerosol loading and types is also witnessed, with high AOD and dominance of fine particulates over central to lower IGP, especially during post-monsoon and winter. The time series analyses by autoregressive integrated moving average (ARIMA) indicate contrasting patterns in randomness of AOD over individual stations with better performance especially over central IGP. Concentration weighted trajectory analyses identify the crucial contributions of western dry regions and partial contributions from central Highlands and north-eastern India, in regulating AOD over stations across IGP. Although our analyses provide some attributes to the observed changes in aerosol loading, we conclude that the spatial and temporal pattern of aerosol properties is highly complex and dynamic over IGP, and require further investigation in order to reduce uncertainty in aerosol-climate model.

Aerosol Extinction Profile Mapping with Lognormal Distribution Based on MPL Data

NASA Astrophysics Data System (ADS)

Lin, T. H.; Lee, T. T.; Chang, K. E.; Lien, W. H.; Liu, G. R.; Liu, C. Y.

2017-12-01

This study intends to challenge the profile mapping of aerosol vertical distribution by mathematical function. With the similarity in distribution pattern, lognormal distribution is examined for mapping the aerosol extinction profile based on MPL (Micro Pulse LiDAR) in situ measurements. The variables of lognormal distribution are log mean (μ) and log standard deviation (σ), which will be correlated with the parameters of aerosol optical depht (AOD) and planetary boundary layer height (PBLH) associated with the altitude of extinction peak (Mode) defined in this study. On the base of 10 years MPL data with single peak, the mapping results showed that the mean error of Mode and σ retrievals are 16.1% and 25.3%, respectively. The mean error of σ retrieval can be reduced to 16.5% under the cases of larger distance between PBLH and Mode. The proposed method is further applied to MODIS AOD product in mapping extinction profile for the retrieval of PM2.5 in terms of satellite observations. The results indicated well agreement between retrievals and ground measurements when aerosols under 525 meters are well-mixed. The feasibility of proposed method to satellite remote sensing is also suggested by the case study. Keyword: Aerosol extinction profile, Lognormal distribution, MPL, Planetary boundary layer height (PBLH), Aerosol optical depth (AOD), Mode

Discerning the pre-monsoon urban atmosphere aerosol characteristic and its potential source type remotely sensed by AERONET over the Bengal Gangetic plain.

PubMed

Priyadharshini, Babu; Verma, Shubha; Giles, David M; Holben, Brent N

2018-05-26

In the present study, we evaluated the pre-monsoon urban atmosphere (UA) aerosol characteristics remotely sensed by Aerosol Robotic Network (AERONET) over the Bengal Gangetic plain (BGP) at Kolkata (KOL) and their implication in potential source types and spatiotemporal features. About 70% of the AERONET-sensed aerosol optical depth at 0.50 μ m, AOD 0.5 (Angstrom exponent, α at 0.44-0.87 μ m) during the pre-monsoon period (February to June) was greater than 0.50 (≤ 1); the pre-monsoon mean of AOD 0.5 (α) was 0.73 (0.83) which was found being slightly higher (lower) than nearby AERONET stations (Dhaka/Bhola) located over the eastern Ganges basin. The volume geometric mean radius for the fine mode (FM) (coarse mode, CM) UA aerosol from AERONET retrievals was estimated to be 0.14-0.17 (2.24-2.75) μ m. The spectral distribution of the monthly mean of UA aerosol single-scattering albedo (SSA) exhibited an increasing trend with an increase in wavelength throughout all wavelengths during April, unlike the rest of the pre-monsoon months. Investigation of aerosol types indicated the pre-dominance of dust during April and a mixture of urban/open burning with mixed desert dust during the rest of the pre-monsoon months. Potential aerosol source fields were identified over the Indo-Gangetic Plain (IGP), east coast, northwestern India, and oceanic regions; these were estimated at elevated layers of atmosphere during April and May but that at surface layers during February and June. Comparison of aerosol characteristics over the BGP (at Kolkata, KOL) with that at six other coincident AERONET sites over India revealed mean AOD at KOL being 11 to 91% higher than the rest of the AERONET stations, with the relative increase at KOL being the highest during March; this was attributed to persistent high values of both FM and CM AOD unlike the rest of the stations. The monthly mean of SSA was the lowest at KOL among AERONET stations, during February and March. Comparison of the AOD from the AERONET aerosol retrievals over the BGP UA with the coincident Moderate Resolution Imaging Spectroradiometer (MODIS) latest retrievals (C005 and C006) indicated a moderate correlation between the two retrievals; discrepancy in MODIS-retrieved relative distribution of FM and CM AOD was inferred compared to AERONET in the UA.

Development of 2-D-MAX-DOAS and retrievals of trace gases and aerosols optical properties

NASA Astrophysics Data System (ADS)

Ortega, Ivan

Air pollution is a major problem worldwide that adversely a_ects human health, impacts ecosystems and climate. In the atmosphere, there are hundreds of important compounds participating in complex atmospheric reactions linked to air quality and climate. Aerosols are relevant because they modify the radiation balance, a_ect clouds, and thus Earth albedo. The amount of aerosol is often characterized by the vertical integral through the entire height of the atmosphere of the logarithm fraction of incident light that is extinguished called Aerosol Optical Depth (AOD). The AOD at 550 nm (AOD550) over land is 0.19 (multi annual global mean), and that over oceans is 0.13. About 43 % of the Earth surface shows AOD550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions, sample spatial scales that resemble satellite ground-pixels and atmospheric models, and help integrate remote sensing and in-situ observations to obtain optical closure on the effects of aerosols and trace gases in our changing environment. In this work, I present the recent development of the University of Colorado two dimensional (2-D) Multi-AXis Differential Optical Absorption Spectroscopy (2-D-MAX-DOAS) instrument to measure the azimuth and altitude distribution of trace gases and aerosol optical properties simultaneously with a single instrument. The instrument measures solar scattered light from any direction in the sky, including direct sun light in the hyperspectral domain. In Chapter 2, I describe the capabilities of 2-D measurements in the context of retrievals of azimuth distributions of nitrogen dioxide (NO2), formaldehyde (HCHO), and glyoxal (CHOCHO), which are precursors for tropospheric O3 and aerosols. The measurements were carried out during the Multi-Axis DOAS Comparison campaign for Aerosols and Trace gases (MAD-CAT) campaign in Mainz, Germany and show the ability to bridge spatial scales to satellites and atmospheric models. Chapter 3 presents an innovative retrieval approach to measure AOD430 and the aerosol phase function parameter, g, without the need for absolute radiance calibration; the retrieval is based on solar azimuth distributions of the Raman Scattering Probability (RSP), the near-absolute Rotational Raman Scattering (RRS) intensity, during the Department of Energy Two Column Aerosol Project (TCAP) at Cape Cod, MA. Furthermore, the TCAP field campaign provides a unique dataset to evaluate innovative retrieval algorithms and perform radiation closure studies. In Chapters 4 I describe the effect of persistent elevated aerosol layers on the apparent absorption of the collision induced absorption of oxygen (O2-O2, or O4) as seen by the ground based 2-D-MAX-DOAS. Chapter 5 discusses the effect of chemical composition of aerosols for optical closure of aerosol extinction as characterized by ground based (2-D-MAX-DOAS) and airborne remote sensing instruments (HSRL-2) and in-situ observations of aerosol optical properties calculated from size distributions measured aboard the DoE G-1 aircraft. Chapter 5 also includes a discussion on the effects of dry, moist, and size-corrections that need to be applied to the in-situ observations in order to infer extinction in the atmosphere. In the final Chapter 6, I present a comprehensive analysis of CHOCHO, HCHO, and NO2 column measurements obtained in multiple field deployments of MAX-DOAS under different NOx (NO + NO2) conditions and VOC precursors. In particular, I assess the magnitude of the ratio of CHOCHO to HCHO (RGF), which has been proposed as a metric to distinguish biogenic and/or anthropogenic VOC (BVOC/AVOC) influences, and show with box-modeling that the concentration of NO2 and dictates the value of RGF . I proposed a new metric of RGF based on box-modeling and field measurements to distinguish AVOC/BVOC influences and split in BVOCs.

Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China?

NASA Astrophysics Data System (ADS)

Ma, Xiaoyan; Wang, Jianying; Yu, Fangqun; Jia, Hailing; Hu, Yanan

2016-11-01

The fine particular matter (PM) concentrations in China have increased considerably due to the rapid economic growth and urbanization in the last few decades, especially in the most populated and industrialized regions. Beijing-Tianjin-Hebei is one of the most polluted regions in China, so to monitor the PM2.5 concentrations over this region is quite critical for human health. By making use the new released hourly PM2.5 mass concentration from ground-based observations in Beijing-Tianjin-Hebei over China, and collocated MODIS level 2 AOD data from April 2014 to March 2015, we explored the relation between surface PM2.5 mass concentration and MODIS AOD and possibility to derive the surface PM2.5 from satellite retrieval in the region. Our study show that the relation strongly depend on the seasons due to distinct seasonal characteristics of PM2.5 and AOD, with a relatively better correlation in spring and summertime (correlation coefficient r ranging from 0.52 to 0.79) than autumn and wintertime (r can be low as to 0.23 in site Baoding). Our analysis gave evidence that worse relationship and/or smaller number of sample in wintertime is associated with the significantly high PM2.5 concentration and a lot of missing data occurring in MODIS AOD, implying that current MODIS AOD retrieval scheme does not work very well in highly polluted cases. The derived PM2.5 mass concentration from MODIS AOD in summertime can basically capture the major observed features of the time series and about 20% large bias of the derived values compared to the observation is expected to be reduced if longer time period data is available and used for analysis.

Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China?

NASA Astrophysics Data System (ADS)

Ma, Xiaoyan

2017-04-01

The fine particular matter (PM) concentrations in China have increased considerably due to the rapid economic growth and urbanization in the last few decades, especially in the most populated and industrialized regions. The Beijing-Tianjin-Hebei is one of the most polluted regions in China, so to monitor the PM2.5 concentrations over this region is quite critical for human health. By making use the new released hourly PM2.5 mass concentration from ground-based observations in Beijing-Tianjin-Hebei over China, and the collocated MODIS level 2 AOD data from April 2014 to March 2015, we explored the relation between surface PM2.5 mass concentration and MODIS AOD and possibility to derive the surface PM2.5 from satellite retrieval in the region. Our study show that the relation strongly depend on the seasons due to distinct seasonal characteristics of PM2.5 and AOD, with a relatively better correlation in spring and summertime than autumn and wintertime. Our analysis give an evidence that worse relationship and/or smaller number of sample in wintertime is associated with the significantly high PM2.5 concentration and a lot of missing data occurring in MODIS AOD, implying that current MODIS AOD retrieval scheme does not work very well in highly polluted cases. The derived PM2.5 mass concentration from MODIS AOD in summertime can basically capture the major observed features of the time series and about 20% large bias of the derived values compared to the observation is expected to be reduced once longer time period data is available and used for analysis.

The World Optical Depth Research and Calibration Center (WORCC) quality assurance and quality control of GAW-PFR AOD measurements

NASA Astrophysics Data System (ADS)

Kazadzis, Stelios; Kouremeti, Natalia; Nyeki, Stephan; Gröbner, Julian; Wehrli, Christoph

2018-02-01

The World Optical Depth Research Calibration Center (WORCC) is a section within the World Radiation Center at Physikalisches-Meteorologisches Observatorium (PMOD/WRC), Davos, Switzerland, established after the recommendations of the World Meteorological Organization for calibration of aerosol optical depth (AOD)-related Sun photometers. WORCC is mandated to develop new methods for instrument calibration, to initiate homogenization activities among different AOD networks and to run a network (GAW-PFR) of Sun photometers. In this work we describe the calibration hierarchy and methods used under WORCC and the basic procedures, tests and processing techniques in order to ensure the quality assurance and quality control of the AOD-retrieved data.

Mini MAX-DOAS Measurements of Air Pollutants over China

NASA Astrophysics Data System (ADS)

Staadt, Steffen; Hao, Nan; Trautmann, Thomas

2016-08-01

This study continues the work of Clémer et al., (2010) and is aimed to improve trace gas retrievals with mini MAX-DOAS measurements in Nanjing. Based on that work, aerosol extinction vertical profiles are retrieved using the bePRO inversion algorithm developed by the Royal Belgian Institute for Space Aeronomy (BIRA- IASB). Afterwards, the tropospheric trace gas vertical profiles and vertical column densities (VCDs) are retrieved by applying the optimal estimation method to the O4 MAX-DOAS measurements. The Profiles for N O2 , S O2 , glyoxal, formaldehyde and nitrous acid are obtained with different results and different settings for the DOAS measurement. The AODs show small positive correlation against the AERONET values. For NO2, the retrieval shows reasonable concentrations in winter as opposed to summer and has small positive correlations with GOME-2 data. The SO2 VCDs are not correlated with the GOME-2 data, due to high uncertainties from MAX-DOAS and satellite retrievals, while the vertical mixing ratios (VMR) show good agreement with in-situ data (SORPES) at Nanjing. Nitrous acid shows a maximum in winter and a minimum in summer, while glyoxal has its maximum in August and September.

Response to Toward Unified Satellite Climatology of Aerosol Properties. 3; MODIS versus MISR versus AERONET

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didler

2010-01-01

A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD), and gives a much less favorable impression of the utility of the satellite products than that presented by the instrument teams and other groups. We trace the reasons for the differing pictures to whether known and previously documented limitations of the products are taken into account in the assessments. Specifically, the analysis approaches differ primarily in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account. Mishchenko et al. also do not distinguish between observational sampling differences and retrieval algorithm error. We assess the implications of the different analysis approaches, and cite examples demonstrating how the MISR and MODIS aerosol products have been applied successfully to a range of scientific investigations.

Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery

DTIC Science & Technology

2012-11-22

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An advanced initiative for tracking operationally aerosol events over the last decade based on MSG/SEVIRI satellite observations

NASA Astrophysics Data System (ADS)

Carrer, Dominique; Ceamanos, Xavier; Moparthy, Suman; Six, Bruno; Roujean, Jean-Louis; Descloitres, Jacques

2017-04-01

The major difficulty to detect properly the aerosol signal by using remote sensing observations in the visible range relies on a clear separation of the scattering components between the atmospheric layer and the ground surface. This turns to be quite challenging over bright targets like deserts. We propose a method that combines the directional and temporal dimensions of the satellite signal through out the use of a semi-empirical BRDF kernel-driven model of the surface/atmosphere coupled system. As a result, a simultaneous retrieval of surface albedo and aerosol properties (optical thickness) is performed. The method proves to be meaningful to track anthropogenic aerosol emissions in the troposphere, to monitor volcanic ash release and above all to estimate dust events over bright targets. The proposed method is applied to MSG/SEVIRI slots in the three spectral bands (VIS, NIR, SWIR) at the frequency of 15min and for a geographic coverage that encompasses Europe, Africa, and South America regions. The SEVIRI-derived optical aerosol depth (AOD) estimates compare favourably with measurements carried on over well distributed AERONET stations. The comparison with state of art MODIS-derived (Moderate Resolution Imaging Spectro-radiometer), and MISR-derived (Multi-angle Imaging Spectro-Radiometer) AOD products falls within 20% of accuracy while it reveals the capability of AERUS-GEO to depict more aerosol events still quantitatively. Owing to that, more AOD products offers new insights to better estimate the aerosol radiative forcing (ARF) from GEO compared to low-orbit elevation orbit (LEO) satellite data. The AERUS-GEO algorithm was implemented in the ICARE/AERIS Data Center based in Lille (France) (http://www.icare.univ-lille1.fr). It disseminates operationally from 2014 a daily AOD product (AERUS-GEO) at 670 nm over the MSG disk. In addition to the NRT AOD product, a long term reprocessing is also available over the last decade.

Evaluation of spatio-temporal variability of Hamburg Aerosol Climatology against aerosol datasets from MODIS and CALIOP

NASA Astrophysics Data System (ADS)

Pappas, V.; Hatzianastassiou, N.; Papadimas, C.; Matsoukas, C.; Kinne, S.; Vardavas, I.

2013-08-01

The new global aerosol climatology named HAC (Hamburg Aerosol Climatology) is compared against MODIS (Collection 5, 2000-2007) and CALIOP (Level 2-version 3, 2006-2011) retrievals. The comparison of aerosol optical depth (AOD) from HAC against MODIS shows larger HAC AOD values over regions with higher aerosol loads and smaller HAC AOD values than MODIS for regions with lower loads. The HAC data are found to be more reliable over land and for low AOD values. The largest differences between HAC and MODIS occur from March to August for the Northern Hemisphere and from September to February for the Southern Hemisphere. In addition, both the spectral variability and vertical distribution of the HAC AOD are examined at selected AERONET (1998-2007) sites, representative of main aerosol types (pollutants, sea salt, biomass and dust). Based on comparisons against spectral AOD values from AERONET, the mean absolute percentage error in HAC AOD data is 25% at ultraviolet wavelengths (400 nm), 6-12% at visible and 18% at near-infrared (1000 nm). For the same AERONET sites, the HAC AOD vertical distribution is compared against CALIOP space lidar data. On a daily average basis, HAD AOD is less by 9% in the lowest 3 km than CALIOP values, especially for sites with biomass burning smoke, desert dust and sea salt spray. Above the boundary layer, the HAC AOD vertical distribution is reliable.

Utilization of O4 slant column density to derive aerosol layer height from a space-borne UV-visible hyperspectral sensor: sensitivity and case study

NASA Astrophysics Data System (ADS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-02-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 1040 molecules2 cm-5, to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 % of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Space-Borne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

NASA Technical Reports Server (NTRS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-01-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(sup 40) molecules (sup 2) per centimeters(sup -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nanometers, the O4 absorption band at 477 nanometers is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nanometers is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 meters for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 percent of retrieved aerosol effective heights are within the error range of 1 kilometer compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Spaceborne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

NASA Technical Reports Server (NTRS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-01-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(exp 40) sq molecules cm(exp -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80% of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Statistical Inter-comparison Analysis of MODIS, MISR, and AERONET Over the Middle East and North Africa

NASA Astrophysics Data System (ADS)

Farahat, A.; El-Askary, H. M.; Kalashnikova, O. V.; Garay, M. J.

2016-12-01

Several space-borne and ground based sensors can provide long-standing monitoring of aerosols characteristics, but inconsistencies among different sensors reduce data reliability and lead to uncertainty in analysing long-term data. In this study, we perform statistical inter-comparison of the Aerosol Optical Depth (AOD) among MISR, MODIS/Terra, MODIS/Aqua and Aerosol Robotic Network (AERONET) over seven sites located in the Middle East and North Africa during the period (1995 -2015). The sites are categorized into two regions based on their geographic location and possible dominate particles composition. Compared to MISR, MODIS and AERONET AOD data retrievals indicate larger uncertainty over all sites with a larger daily variability in MODIS measurements. In general, MISR and MODIS AOD matches during high dust seasons but MODIS tends to under estimate the AOD values on low dust seasons. While Terra measurements give a negative trend over the time series at the dust-dominated sites, Aqua, MISR and AERONET show a positive trend. In general, MODIS/Aqua displays stable measurements over the time line at the dust dominated sites. MODIS/Terra, MODIS/Aqua and MISR display a positive trend over Cairo_EMA site while AERONET shows a negative trend over the time line. Terra was found to overestimate AOD during 2002 - 2004 and underestimates it after 2004. We also observe a deviation between Aqua and Terra regardless of the region and data sampling. Excluding Bahrain and Cairo_EMA for low data retrievals the performance of MODIS tends to be similar over all region with 68 % of the retrieved AOD values fall within the confidence range of the AERONET matched data, within global averaged level (> 66 %). MISR indicated better data performance with 72 % falls within the same confidence range. Complimentary MISR and MODIS data was found to provide a better picture of dust storms evolution over Arabian Peninsula and the Middle East. Acknowledgement The authors would like to acknowledge the support provided by the Deanship of Scientific Research (DSR) at the King Fahd University of Petroleum and Minerals (KFUPM) for funding this work through project No. IN141051.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Meyer, Kerry G.; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin; Yu, Hongbin

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

Aerosol Robotic Network (AERONET) Version 3 Aerosol Optical Depth and Inversion Products

NASA Astrophysics Data System (ADS)

Giles, D. M.; Holben, B. N.; Eck, T. F.; Smirnov, A.; Sinyuk, A.; Schafer, J.; Sorokin, M. G.; Slutsker, I.

2017-12-01

The Aerosol Robotic Network (AERONET) surface-based aerosol optical depth (AOD) database has been a principal component of many Earth science remote sensing applications and modelling for more than two decades. During this time, the AERONET AOD database had utilized a semiautomatic quality assurance approach (Smirnov et al., 2000). Data quality automation developed for AERONET Version 3 (V3) was achieved by augmenting and improving upon the combination of Version 2 (V2) automatic and manual procedures to provide a more refined near real time (NRT) and historical worldwide database of AOD. The combined effect of these new changes provides a historical V3 AOD Level 2.0 data set comparable to V2 Level 2.0 AOD. The recently released V3 Level 2.0 AOD product uses Level 1.5 data with automated cloud screening and quality controls and applies pre-field and post-field calibrations and wavelength-dependent temperature characterizations. For V3, the AERONET aerosol retrieval code inverts AOD and almucantar sky radiances using a full vector radiative transfer called Successive ORDers of scattering (SORD; Korkin et al., 2017). The full vector code allows for potentially improving the real part of the complex index of refraction and the sphericity parameter and computing the radiation field in the UV (e.g., 380nm) and degree of linear depolarization. Effective lidar ratio and depolarization ratio products are also available with the V3 inversion release. Inputs to the inversion code were updated to the accommodate H2O, O3 and NO2 absorption to be consistent with the computation of V3 AOD. All of the inversion products are associated with estimated uncertainties that include the random error plus biases due to the uncertainty in measured AOD, absolute sky radiance calibration, and retrieved MODIS BRDF for snow-free and snow covered surfaces. The V3 inversion products use the same data quality assurance criteria as V2 inversions (Holben et al. 2006). The entire AERONET V3 almucantar inversion database was computed using the NASA High End Computing resources at NASA Ames Research Center and NASA Goddard Space Flight Center. In addition to a description of data products, this presentation will provide a comparison of the V3 AOD and inversion climatology comparison of the V3 Level 2.0 and V2 Level 2.0 for sites with varying aerosol types.

Estimating Marine Aerosol Particle Volume and Number from Maritime Aerosol Network Data

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Smirnov, A.; Hsu, N. C.; Munchak, L. A.; Holben, B. N.

2012-01-01

As well as spectral aerosol optical depth (AOD), aerosol composition and concentration (number, volume, or mass) are of interest for a variety of applications. However, remote sensing of these quantities is more difficult than for AOD, as it is more sensitive to assumptions relating to aerosol composition. This study uses spectral AOD measured on Maritime Aerosol Network (MAN) cruises, with the additional constraint of a microphysical model for unpolluted maritime aerosol based on analysis of Aerosol Robotic Network (AERONET) inversions, to estimate these quantities over open ocean. When the MAN data are subset to those likely to be comprised of maritime aerosol, number and volume concentrations obtained are physically reasonable. Attempts to estimate surface concentration from columnar abundance, however, are shown to be limited by uncertainties in vertical distribution. Columnar AOD at 550 nm and aerosol number for unpolluted maritime cases are also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) data, for both the present Collection 5.1 and forthcoming Collection 6. MODIS provides a best-fitting retrieval solution, as well as the average for several different solutions, with different aerosol microphysical models. The average solution MODIS dataset agrees more closely with MAN than the best solution dataset. Terra tends to retrieve lower aerosol number than MAN, and Aqua higher, linked with differences in the aerosol models commonly chosen. Collection 6 AOD is likely to agree more closely with MAN over open ocean than Collection 5.1. In situations where spectral AOD is measured accurately, and aerosol microphysical properties are reasonably well-constrained, estimates of aerosol number and volume using MAN or similar data would provide for a greater variety of potential comparisons with aerosol properties derived from satellite or chemistry transport model data.

A New Study of Sea Spray Optical Properties from Multi-Sensor Spaceborne Observations

NASA Technical Reports Server (NTRS)

Dawson, K. W.; Meskhidze, N.; Josset, D.; Gasso, S.

2014-01-01

Retrievals of aerosol optical depth (AOD) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite sensor require the assumption of an extinction-to-backscatter ratio, also known as the lidar ratio. This paper evaluates a new method to calculate lidar ratio of sea spray aerosol using two independent sources: the AOD from Synergized Optical Depth of Aerosols (SODA) and the integrated attenuated backscatter from CALIOP. The method applied in this study allows particulate lidar ratio to be calculated for individual CALIOP retrievals of single aerosol layer columns over the ocean. Analyses are carried out using CALIOP level 2, 5km sea spray aerosol layer products and collocated SODA nighttime data from December 2007 to December 2009. The global mean lidar ratio for sea spray aerosols was found to be 26 sr, roughly 30 higher than the one prescribed by CALIOP. Data analysis also showed considerable spatiotemporal variability in calculated lidar ratio over different parts of the remote oceans. The calculated aerosol lidar ratios are shown to be inversely related to the mean ocean surface wind speed: increase in ocean surface wind speed (U10) from 0 to 15 ms-1 reduces the mean lidar ratios for sea spray particles from 32 sr (for 0 U10 4 ms-1) to 22 sr (for U10 15 ms-1). Such changes in the lidar ratio are expected to have a corresponding effect on sea spray AOD. The outcomes of this study are relevant for future improvements of the SODA and CALIOP operational product and could lead to more accurate retrievals of sea spray AOD.

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

PubMed

Zhang, Xueying; Chu, Yiyi; Wang, Yuxuan; Zhang, Kai

2018-08-01

The regulatory monitoring data of particulate matter with an aerodynamic diameter <2.5μm (PM 2.5 ) in Texas have limited spatial and temporal coverage. The purpose of this study is to estimate the ground-level PM 2.5 concentrations on a daily basis using satellite-retrieved Aerosol Optical Depth (AOD) in the state of Texas. We obtained the AOD values at 1-km resolution generated through the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm based on the images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM 2.5 concentrations (μg/m 3 ) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R 2 ) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. Mixed-effects regression models showed good prediction performance (R 2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R 2 : 0.62 for the East region; R 2 : 0.69 for the year of 2009). The PM 2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM 2.5 in more polluted areas. Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM 2.5 in Texas. Predicted PM 2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM 2.5 in Texas. Copyright © 2017 Elsevier B.V. All rights reserved.

Aerosol climate time series from ESA Aerosol_cci (Invited)

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.

2013-12-01

Within the ESA Climate Change Initiative (CCI) the Aerosol_cci project (mid 2010 - mid 2013, phase 2 proposed 2014-2016) has conducted intensive work to improve algorithms for the retrieval of aerosol information from European sensors AATSR (3 algorithms), PARASOL, MERIS (3 algorithms), synergetic AATSR/SCIAMACHY, OMI and GOMOS. Whereas OMI and GOMOS were used to derive absorbing aerosol index and stratospheric extinction profiles, respectively, Aerosol Optical Depth (AOD) and Angstrom coefficient were retrieved from the other sensors. Global datasets for 2008 were produced and validated versus independent ground-based data and other satellite data sets (MODIS, MISR). An additional 17-year dataset is currently generated using ATSR-2/AATSR data. During the three years of the project, intensive collaborative efforts were made to improve the retrieval algorithms focusing on the most critical modules. The team agreed on the use of a common definition for the aerosol optical properties. Cloud masking was evaluated, but a rigorous analysis with a pre-scribed cloud mask did not lead to improvement for all algorithms. Better results were obtained using a post-processing step in which sudden transitions, indicative of possible occurrence of cloud contamination, were removed. Surface parameterization, which is most critical for the nadir only algorithms (MERIS and synergetic AATSR / SCIAMACHY) was studied to a limited extent. The retrieval results for AOD, Ångström exponent (AE) and uncertainties were evaluated by comparison with data from AERONET (and a limited amount of MAN) sun photometer and with satellite data available from MODIS and MISR. Both level2 and level3 (gridded daily) datasets were validated. Several validation metrics were used (standard statistical quantities such as bias, rmse, Pearson correlation, linear regression, as well as scoring approaches to quantitatively evaluate the spatial and temporal correlations against AERONET), and in some cases developed further, to evaluate the datasets and their regional and seasonal merits. The validation showed that most datasets have improved significantly and in particular PARASOL (ocean only) provides excellent results. The metrics for AATSR (land and ocean) datasets are similar to those of MODIS and MISR, with AATSR better in some land regions and less good in some others (ocean). However, AATSR coverage is smaller than that of MODIS due to swath width. The MERIS dataset provides better coverage than AATSR but has lower quality (especially over land) than the other datasets. Also the synergetic AATSR/SCIAMACHY dataset has lower quality. The evaluation of the pixel uncertainties shows first good results but also reveals that more work needs to be done to provide comprehensive information for data assimilation. Users (MACC/ECMWF, AEROCOM) confirmed the relevance of this additional information and encouraged Aerosol_cci to release the current uncertainties. The paper will summarize and discuss the results of three year work in Aerosol_cci, extract the lessons learned and conclude with an outlook to the work proposed for the next three years. In this second phase a cyclic effort of algorithm evolution, dataset generation, validation and assessment will be applied to produce and further improve complete time series from all sensors under investigation, new sensors will be added (e.g. IASI), and preparation for the Sentinel missions will be made.

Interaction between aerosol and the planetary boundary layer depth at sites in the US and China

NASA Astrophysics Data System (ADS)

Sawyer, V. R.

2015-12-01

The depth of the planetary boundary layer (PBL) defines a changing volume into which pollutants from the surface can disperse, which affects weather, surface air quality and radiative forcing in the lower troposphere. Model simulations have also shown that aerosol within the PBL heats the layer at the expense of the surface, changing the stability profile and therefore also the development of the PBL itself: aerosol radiative forcing within the PBL suppresses surface convection and causes shallower PBLs. However, the effect has been difficult to detect in observations. The most intensive radiosonde measurements have a temporal resolution too coarse to detect the full diurnal variability of the PBL, but remote sensing such as lidar can fill in the gaps. Using a method that combines two common PBL detection algorithms (wavelet covariance and iterative curve-fitting) PBL depth retrievals from micropulse lidar (MPL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are compared to MPL-derived PBL depths from a multiyear lidar deployment at the Hefei Radiation Observatory (HeRO). With aerosol optical depth (AOD) measurements from both sites, it can be shown that a weak inverse relationship exists between AOD and daytime PBL depth. This relationship is stronger at the more polluted HeRO site than at SGP. Figure: Mean daily AOD vs. mean daily PBL depth, with the Nadaraya-Watson estimator overlaid on the kernel density estimate. Left, SGP; right, HeRO.

Comparison between volcanic ash satellite retrievals and FALL3D transport model

NASA Astrophysics Data System (ADS)

Corradini, Stefano; Merucci, Luca; Folch, Arnau

2010-05-01

Volcanic eruptions represent one of the most important sources of natural pollution because of the large emission of gas and solid particles into the atmosphere. Volcanic clouds can contain different gas species (mainly H2O, CO2, SO2 and HCl) and a mix of silicate-bearing ash particles in the size range from 0.1 μm to few mm. Determining the properties, movement and extent of volcanic ash clouds is an important scientific, economic, and public safety issue because of the harmful effects on environment, public health and aviation. In particular, real-time tracking and forecasting of volcanic clouds is key for aviation safety. Several encounters of en-route aircrafts with volcanic ash clouds have demonstrated the harming effects of fine ash particles on modern aircrafts. Alongside these considerations, the economical consequences caused by disruption of airports must be also taken into account. Both security and economical issues require robust and affordable ash cloud detection and trajectory forecasting, ideally combining remote sensing and modeling. We perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands from Visible (VIS) to Thermal InfraRed (TIR) and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 mm have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. We consider the Mt. Etna volcano 2002 eruptive event as a test case. Results show a good agreement between the mean AOT retrieved and the spatial ash dispersion in the different images, while the modeled FALL3D total mass retrieved results significantly overestimated.

Aerosol and Cloud Interaction Observed From High Spectral Resolution Lidar Data

NASA Technical Reports Server (NTRS)

Su, Wenying; Schuster, Gregory L.; Loeb, Norman G.; Rogers, Raymond R.; Ferrare, Richard A.; Hostetler, Chris A.; Hair, Johnathan W.; Obland, Michael D.

2008-01-01

Recent studies utilizing satellite retrievals have shown a strong correlation between aerosol optical depth (AOD) and cloud cover. However, these retrievals from passive sensors are subject to many limitations, including cloud adjacency (or 3D) effects, possible cloud contamination, uncertainty in the AOD retrieval. Some of these limitations do not exist in High Spectral Resolution Lidar (HSRL) observations; for instance, HSRL observations are not a ected by cloud adjacency effects, are less prone to cloud contamination, and offer accurate aerosol property measurements (backscatter coefficient, extinction coefficient, lidar ratio, backscatter Angstrom exponent,and aerosol optical depth) at a neospatial resolution (less than 100 m) in the vicinity of clouds. Hence, the HSRL provides an important dataset for studying aerosol and cloud interaction. In this study, we statistically analyze aircraft-based HSRL profiles according to their distance from the nearest cloud, assuring that all profile comparisons are subject to the same large-scale meteorological conditions. Our results indicate that AODs from HSRL are about 17% higher in the proximity of clouds (approximately 100 m) than far away from clouds (4.5 km), which is much smaller than the reported cloud 3D effect on AOD retrievals. The backscatter and extinction coefficients also systematically increase in the vicinity of clouds, which can be explained by aerosol swelling in the high relative humidity (RH) environment and/or aerosol growth through in cloud processing (albeit not conclusively). On the other hand, we do not observe a systematic trend in lidar ratio; we hypothesize that this is caused by the opposite effects of aerosol swelling and aerosol in-cloud processing on the lidar ratio. Finally, the observed backscatter Angstrom exponent (BAE) does not show a consistent trend because of the complicated relationship between BAE and RH. We demonstrate that BAE should not be used as a surrogate for Angstrom exponent, especially at high RH.

A-Train Aerosol Observations Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-Sky Estimates

NASA Technical Reports Server (NTRS)

Redemann, J.; Livingston, J.; Shinozuka, Y.; Kacenelenbogen, M.; Russell, P.; LeBlanc, S.; Vaughan, M.; Ferrare, R.; Hostetler, C.; Rogers, R.;

Overview of ACE-Asia Spring 2001 Investigations on Aerosol Radiative Effects and Related Aerosol Properties

NASA Technical Reports Server (NTRS)

Russell, Philip B.; Valero, F. P. J.; Flatau, P. J.; Bergin, M.; Holben, B.; Nakajima, T.; Pilewskie, P.; Bergstrom, R.; Hipskind, R. Stephen (Technical Monitor)

2001-01-01

A primary, ACE-Asia objective was to quantify the interactions between aerosols and radiation in the Asia-Pacific region. Toward this end, radiometric and related aerosol measurements were made from ocean, land, air and space platforms. Models that predict aerosol fields guided the measurements and are helping integrate and interpret results. Companion overview's survey these measurement and modeling components. Here we illustrate how these components were combined to determine aerosol radiative. impacts and their relation to aerosol properties. Because clouds can obscure or change aerosol direct radiative effects, aircraft and ship sorties to measure these effects depended on predicting and finding cloud-free areas and times with interesting aerosols present. Pre-experiment satellite cloud climatologies, pre-flight aerosol and cloud forecasts, and in-flight guidance from satellite imagery all helped achieve this. Assessments of aerosol regional radiative impacts benefit from the spatiotemporal coverage of satellites, provided satellite-retrieved aerosol properties are accurate. Therefore, ACE-Asia included satellite retrieval tests, as part of many comparisons to judge the consistency (closure) among, diverse measurements. Early results include: (1) Solar spectrally resolved and broadband irradiances and optical depth measurements from the C-130 aircraft and at Kosan, Korea yielded aerosol radiative forcing efficiencies, permitting comparisons between efficiencies of ACE-Asia and INDOEX aerosols, and between dust and "pollution" aerosols. Detailed results will be presented in separate papers. (2) Based on measurements of wavelength dependent aerosol optical depth (AOD) and single scattering albedo the estimated 24-h a average aerosol radiative forcing efficiency at the surface for photosynthetically active radiation (400 - 700 nm) in Yulin, China is approx. 30 W sq m per AOD(500 nm). (3) The R/V Brown cruise from Honolulu to Sea of Japan sampled an aerosol optical depth gradient, with AOD(500 nm) extremes from 0.1 to 1.1. On the Pacific transit from Honolulu to Hachijo AOD(500 nm) averaged 0.2, including increases to 0.4 after several storms, suggesting the strong impact of wind-generated seasalt. The AOD maximum, found in the Sea of Japan, was influenced by dust and anthropogenic sources. (4) In Beijing, single scattering albedo retrieved from AERONET sun-sky radiometry yielded midvisible SSA=0.88 with strong wavelength dependence, suggesting a significant black carbon component. SSA retrieved during dust episodes was approx. 0.90 and variable but wavelength neutral reflecting the presence of urban haze with the dust. Downwind at Anmyon Island SSA was considerably higher, approx. 0.94, but wavelength neutral for dust episodes and spectrally dependent during non dust periods. (5) Satellite retrievals show major aerosol features moving from Asia over the Pacific; however, determining seasonal-average aerosol effects is hampered by sampling frequency and large-scale cloud systems that obscure key parts of aerosol patterns. Preliminary calculations using, satellite-retrieved AOD fields and initial ACE-Asia aerosol properties (including sulfates, soot, and dust) yield clear-sky aerosol radiative effects in the seasonal-average ACE-Asia plume exceeding those of manmade greenhouse gases. Quantifying all-sky direct aerosol radiative effects is complicated by the need to define the height of absorbing aerosols with respect to cloud decks.

Evaluating Nighttime CALIOP 0.532 micron Aerosol Optical Depth and Extinction Coefficient Retrievals

NASA Technical Reports Server (NTRS)

Campbell, J. R.; Tackett, J. L.; Reid, J. S.; Zhang, J.; Curtis, C. A.; Hyer, E. J.; Sessions, W. R.; Westphal, D. L.; Prospero, J. M.; Welton, E. J.;

Failure and Redemption of Multifilter Rotating Shadowband Radiometer (MFRSR)/Normal Incidence Multifilter Radiometer (NIMFR) Cloud Screening: Contrasting Algorithm Performance at Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) and Southern Great Plains (SGP) Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassianov, Evgueni I.; Flynn, Connor J.; Koontz, Annette S.

2013-09-11

Well-known cloud-screening algorithms, which are designed to remove cloud-contaminated aerosol optical depths (AOD) from AOD measurements, have shown great performance at many middle-to-low latitude sites around the world. However, they may occasionally fail under challenging observational conditions, such as when the sun is low (near the horizon) or when optically thin clouds with small spatial inhomogeneity occur. Such conditions have been observed quite frequently at the high-latitude Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) sites. A slightly modified cloud-screening version of the standard algorithm is proposed here with a focus on the ARM-supported Multifilter Rotating Shadowband Radiometer (MFRSR)more » and Normal Incidence Multifilter Radiometer (NIMFR) data. The modified version uses approximately the same techniques as the standard algorithm, but it additionally examines the magnitude of the slant-path line of sight transmittance and eliminates points when the observed magnitude is below a specified threshold. Substantial improvement of the multi-year (1999-2012) aerosol product (AOD and its Angstrom exponent) is shown for the NSA sites when the modified version is applied. Moreover, this version reproduces the AOD product at the ARM Southern Great Plains (SGP) site, which was originally generated by the standard cloud-screening algorithms. The proposed minor modification is easy to implement and its application to existing and future cloud-screening algorithms can be particularly beneficial for challenging observational conditions.« less

Aerosol algorithm evaluation within aerosol-CCI

NASA Astrophysics Data System (ADS)

Kinne, Stefan; Schulz, Michael; Griesfeller, Jan

Properties of aerosol retrievals from space are difficult. Even data from dedicated satellite sensors face contaminations which limit the accuracy of aerosol retrieval products. Issues are the identification of complete cloud-free scenes, the need to assume aerosol compositional features in an underdetermined solution space and the requirement to characterize the background at high accuracy. Usually the development of aerosol is a slow process, requiring continuous feedback from evaluations. To demonstrate maturity, these evaluations need to cover different regions and seasons and many different aerosol properties, because aerosol composition is quite diverse and highly variable in space and time, as atmospheric aerosol lifetimes are only a few days. Three years ago the ESA Climate Change Initiative started to support aerosol retrieval efforts in order to develop aerosol retrieval products for the climate community from underutilized ESA satellite sensors. The initial focus was on retrievals of AOD (a measure for the atmospheric column amount) and of Angstrom (a proxy for aerosol size) from the ATSR and MERIS sensors on ENVISAT. The goal was to offer retrieval products that are comparable or better in accuracy than commonly used NASA products of MODIS or MISR. Fortunately, accurate reference data of ground based sun-/sky-photometry networks exist. Thus, retrieval assessments could and were conducted independently by different evaluation groups. Here, results of these evaluations for the year 2008 are summarized. The capability of these newly developed retrievals is analyzed and quantified in scores. These scores allowed a ranking of competing efforts and also allow skill comparisons of these new retrievals against existing and commonly used retrievals.

Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.

2011-01-01

The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

Nighttime Aerosol Optical Depth Measurements Using a Ground-based Lunar Photometer

NASA Technical Reports Server (NTRS)

Berkoff, Tim; Omar, Ali; Haggard, Charles; Pippin, Margaret; Tasaddaq, Aasam; Stone, Tom; Rodriguez, Jon; Slutsker, Ilya; Eck, Tom; Holben, Brent;

Improving Calculation Accuracies of Accumulation-Mode Fractions Based on Spectral of Aerosol Optical Depths

NASA Astrophysics Data System (ADS)

Ying, Zhang; Zhengqiang, Li; Yan, Wang

2014-03-01

Anthropogenic aerosols are released into the atmosphere, which cause scattering and absorption of incoming solar radiation, thus exerting a direct radiative forcing on the climate system. Anthropogenic Aerosol Optical Depth (AOD) calculations are important in the research of climate changes. Accumulation-Mode Fractions (AMFs) as an anthropogenic aerosol parameter, which are the fractions of AODs between the particulates with diameters smaller than 1μm and total particulates, could be calculated by AOD spectral deconvolution algorithm, and then the anthropogenic AODs are obtained using AMFs. In this study, we present a parameterization method coupled with an AOD spectral deconvolution algorithm to calculate AMFs in Beijing over 2011. All of data are derived from AErosol RObotic NETwork (AERONET) website. The parameterization method is used to improve the accuracies of AMFs compared with constant truncation radius method. We find a good correlation using parameterization method with the square relation coefficient of 0.96, and mean deviation of AMFs is 0.028. The parameterization method could also effectively solve AMF underestimate in winter. It is suggested that the variations of Angstrom indexes in coarse mode have significant impacts on AMF inversions.

Near Real-Time Automatic Data Quality Controls for the AERONET Version 3 Database: An Introduction to the New Level 1.5V Aerosol Optical Depth Data Product

NASA Astrophysics Data System (ADS)

Giles, D. M.; Holben, B. N.; Smirnov, A.; Eck, T. F.; Slutsker, I.; Sorokin, M. G.; Espenak, F.; Schafer, J.; Sinyuk, A.

2015-12-01

The Aerosol Robotic Network (AERONET) has provided a database of aerosol optical depth (AOD) measured by surface-based Sun/sky radiometers for over 20 years. AERONET provides unscreened (Level 1.0) and automatically cloud cleared (Level 1.5) AOD in near real-time (NRT), while manually inspected quality assured (Level 2.0) AOD are available after instrument field deployment (Smirnov et al., 2000). The growing need for NRT quality controlled aerosol data has become increasingly important. Applications of AERONET NRT data include the satellite evaluation (e.g., MODIS, VIIRS, MISR, OMI), data synergism (e.g., MPLNET), verification of aerosol forecast models and reanalysis (e.g., GOCART, ICAP, NAAPS, MERRA), input to meteorological models (e.g., NCEP, ECMWF), and field campaign support (e.g., KORUS-AQ, ORACLES). In response to user needs for quality controlled NRT data sets, the new Version 3 (V3) Level 1.5V product was developed with similar quality controls as those applied by hand to the Version 2 (V2) Level 2.0 data set. The AERONET cloud screened (Level 1.5) NRT AOD database can be significantly impacted by data anomalies. The most significant data anomalies include AOD diurnal dependence due to contamination or obstruction of the sensor head windows, anomalous AOD spectral dependence due to problems with filter degradation, instrument gains, or non-linear changes in calibration, and abnormal changes in temperature sensitive wavelengths (e.g., 1020nm) in response to anomalous sensor head temperatures. Other less common AOD anomalies result from loose filters, uncorrected clock shifts, connection and electronic issues, and various solar eclipse episodes. Automatic quality control algorithms are applied to the new V3 Level 1.5 database to remove NRT AOD anomalies and produce the new AERONET V3 Level 1.5V AOD product. Results of the quality control algorithms are presented and the V3 Level 1.5V AOD database is compared to the V2 Level 2.0 AOD database.

Neural-Network Approach to Hyperspectral Data Analysis for Volcanic Ash Clouds Monitoring

NASA Astrophysics Data System (ADS)

Piscini, Alessandro; Ventress, Lucy; Carboni, Elisa; Grainger, Roy Gordon; Del Frate, Fabio

2015-11-01

In this study three artificial neural networks (ANN) were implemented in order to emulate a retrieval model and to estimate the ash Aerosol optical Depth (AOD), particle effective radius (reff) and cloud height from volcanic eruption using hyperspectral remotely sensed data. ANNs were trained using a selection of Infrared Atmospheric Sounding Interferometer (IASI) channels in Thermal Infrared (TIR) as inputs, and the corresponding ash parameters retrieved obtained using the Oxford retrievals as target outputs. The retrieval is demonstrated for the eruption of the Eyjafjallajo ̈kull volcano (Iceland) occurred in 2010. The results of validation provided root mean square error (RMSE) values between neural network outputs and targets lower than standard deviation (STD) of corresponding target outputs, therefore demonstrating the feasibility to estimate volcanic ash parameters using an ANN approach, and its importance in near real time monitoring activities, owing to its fast application. A high accuracy has been achieved for reff and cloud height estimation, while a decreasing in accuracy was obtained when applying the NN approach for AOD estimation, in particular for those values not well characterized during NN training phase.

10 Yr Spatial and Temporal Trends of PM2.5 Concentrations in the Southeastern US Estimated Using High-resolution Satellite Data

NASA Technical Reports Server (NTRS)

Hu, X.; Waller, L. A.; Lyapustin, A.; Wang, Y.; Liu, Y.

2013-01-01

Long-term PM2.5 exposure has been reported to be associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of the true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of spatiotemporally continuous distribution of PM2.5 concentrations are essential. Satellite-retrieved aerosol optical depth (AOD) has been widely used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, an inherent disadvantage of current AOD products is their coarse spatial resolutions. For instance, the spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) are 10 km and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5-AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US, centered at the Atlanta Metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted for each year individually, and we obtained model fitting R2 ranging from 0.71 to 0.85, MPE from 1.73 to 2.50 g m3, and RMSPE from 2.75 to 4.10 g m3. In addition, we found cross validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 g m3, and RMSPE from 3.12 to 5.00 g m3, indicating a good agreement between the estimated and observed values. Spatial trends show that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. A time series analysis was conducted to examine temporal trends of PM2.5 concentrations in the study area from 2001 to 2010. The results showed that the PM2.5 levels in the study area followed a generally declining trend from 2001 to 2010 and decreased about 20 during the period. However, there was an exception of an increase in year 2005, which is attributed to elevated sulfate concentrations in the study area in warm months of 2005. An investigation of the impact of wild and prescribed fires on PM2.5 levels in 2007 suggests a positive relationship between them.

Aerosol optical depth in a western Mediterranean site: An assessment of different methods

NASA Astrophysics Data System (ADS)

Sanchez-Romero, A.; González, J. A.; Calbó, J.; Sanchez-Lorenzo, A.; Michalsky, J.

2016-06-01

Column aerosol optical properties were derived from multifilter rotating shadowing radiometer (MFRSR) observations carried out at Girona (northeast Spain) from June 2012 to June 2014. We used a technique that allows estimating simultaneously aerosol optical depth (AOD) and Ångström exponent (AE) at high time-resolution. For the period studied, mean AOD at 500 nm was 0.14, with a noticeable seasonal pattern, i.e. maximum in summer and minimum in winter. Mean AE from 500 to 870 nm was 1.2 with a strong day-to-day variation and slightly higher values in summer. So, the summer increase in AOD seems to be linked with an enhancement in the number of fine particles. A radiative closure experiment, using the SMARTS2 model, was performed to confirm that the MFRSR-retrieved aerosol optical properties appropriately represent the continuously varying atmospheric conditions in Girona. Thus, the calculated broadband values of the direct flux show a mean absolute difference of less than 5.9 W m- 2 (0.77%) and R = 0.99 when compared to the observed fluxes. The sensitivity of the achieved closure to uncertainties in AOD and AE was also examined. We use this MFRSR-based dataset as a reference for other ground-based and satellite measurements that might be used to assess the aerosol properties at this site. First, we used observations obtained from a 100 km away AERONET station; despite a general similar behavior when compared with the in-situ MFRSR observations, certain discrepancies for AOD estimates in the different channels (R < 0.84 and slope < 1) appear. Second, AOD products from MISR and MODIS satellite observations were compared with our ground-based retrievals. Reasonable agreements are found for the MISR product (R = 0.92), with somewhat poorer agreement for the MODIS product (R = 0.70). Finally, we apply all these methods to study in detail the aerosol properties during two singular aerosol events related to a forest fire and a desert dust intrusion.

Evaluation of spatio-temporal variability of Hamburg Aerosol Climatology against aerosol datasets from MODIS and CALIOP

NASA Astrophysics Data System (ADS)

Pappas, V.; Hatzianastassiou, N.; Papadimas, C.; Matsoukas, C.; Kinne, S.; Vardavas, I.

2013-02-01

The new global aerosol climatology named HAC (Hamburg Aerosol Climatology) is compared against MODIS (MODerate resolution Imaging Spectroradiometer, Collection 5, 2000-2007) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization, Level 2-Version 3, 2006-2011) retrievals. The HAC aerosol optical depth (AOD) values are larger than MODIS in heavy aerosol load conditions (over land) and lower over oceans. Agreement between HAC and MODIS is better over land and for low AOD. Hemispherically, HAC has 16-17% smaller AOD values than MODIS. The discrepancy is slightly larger for the Southern Hemisphere (SH) than for the Northern Hemisphere (NH). Seasonally, the largest absolute differences are from March to August for NH and from September to February for SH. The spectral variability of HAC AOD is also evaluated against AERONET (1998-2007) data for sites representative of main aerosol types (pollutants, sea-salt, biomass and dust). The HAC has a stronger spectral dependence of AOD in the UV wavelengths, compared to AERONET and MODIS. For visible and near-infrared wavelengths, the spectral dependence is similar to AERONET. For specific sites, HAC AOD vertical distribution is compared to CALIOP data by looking at the fraction of columnar AOD at each altitude. The comparison suggests that HAC exhibits a smaller fraction of columnar AOD in the lowest 2-3 km than CALIOP, especially for sites with biomass burning smoke, desert dust and sea salt spray. For the region of the greater Mediterranean basin, the mean profile of HAC AOD is in very good agreement with CALIOP. The HAC AOD is very useful for distinguishing between natural and anthropogenic aerosols and provides high spectral resolution and vertically resolved information.

Global and Regional Evaluation of Over-Land Spectral Aerosol Optical Depth Retrievals from SeaWiFS

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M. J.; Holben, B. N.; Zhang, J.

2012-01-01

This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (Sea WiFS) measurements over land. First, the data are validated against Aerosol Robotic Network (AERONET) direct-sun AOD measurements, and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-year (1997-2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where Sea WiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record should be suitable for quantitative scientific use.

Regional Exploratory Analysis Between Atomospheric Aerosols and Precipitable Water in the Lower Troposhere via Inferential Statistics

NASA Astrophysics Data System (ADS)

Martinez, B. S.; Ye, H.; Levy, R. C.; Fetzer, E. J.; Remer, L.

2017-12-01

Atmospheric aerosols expose high levels of uncertainty in regard to Earth's changing atmospheric energy budget. Continued exploration and analysis is necessary to obtain more complete understanding in which, and to what degree, aerosols contribute within climate feedbacks and global climate change. With the advent of global satellite retrievals, along with specific aerosol optical depth (AOD) Dark Target and Deep Blue algorithms, aerosols can now be better measured and analyzed. Aerosol effect on climate depends primarily on altitude, the reflectance albedo of the underlying surface, along with the presence of clouds and the dynamics thereof. As currently known, the majority of aerosol distribution and mixing occur in the lower troposphere from the surface upwards to around 2km. Additionally, being a primary greenhouse gas contributor, water vapor is significant to climate feedbacks and Earth's radiation budget. Feedbacks are generally reported from the top of atmosphere (TOA). Therefore, little is known of the relationship between water vapor and aerosols; specifically, in regional areas of the globe known for aerosol loading such as anthropogenic biomass burning in South America and naturally occurring dust blowing off the deserts in the African and Arabian peninsulas. Statistical regression and timeseries analysis are used in determining significant probabilities suggesting trends of both regional precipitable water (PW) and AOD increase and decrease over a 13-year time period from 2003-2015. Regions with statistically significant positive or negative trends of AOD and PW are analyzed in determining correlations, or lack thereof. This initial examination helps to deduce and better understand how aerosols contribute to the radiation budget and assessing climate change.

Sensitivity of a radiative transfer model to the uncertainty in the aerosol optical depth used as input

NASA Astrophysics Data System (ADS)

Román, Roberto; Bilbao, Julia; de Miguel, Argimiro; Pérez-Burgos, Ana

2014-05-01

The radiative transfer models can be used to obtain solar radiative quantities in the Earth surface as the erythemal ultraviolet (UVER) irradiance, which is the spectral irradiance weighted with the erythemal (sunburn) action spectrum, and the total shortwave irradiance (SW; 305-2,8000 nm). Aerosol and atmospheric properties are necessary as inputs in the model in order to calculate the UVER and SW irradiances under cloudless conditions, however the uncertainty in these inputs causes another uncertainty in the simulations. The objective of this work is to quantify the uncertainty in UVER and SW simulations generated by the aerosol optical depth (AOD) uncertainty. The data from different satellite retrievals were downloaded at nine Spanish places located in the Iberian Peninsula: Total ozone column from different databases, spectral surface albedo and water vapour column from MODIS instrument, AOD at 443 nm and Angström Exponent (between 443 nm and 670 nm) from MISR instrument onboard Terra satellite, single scattering albedo from OMI instrument onboard Aura satellite. The obtained AOD at 443 nm data from MISR were compared with AERONET measurements in six Spanish sites finding an uncertainty in the AOD from MISR of 0.074. In this work the radiative transfer model UVSPEC/Libradtran (1.7 version) was used to obtain the SW and UVER irradiance under cloudless conditions for each month and for different solar zenith angles (SZA) in the nine mentioned locations. The inputs used for these simulations were monthly climatology tables obtained with the available data in each location. Once obtained the UVER and SW simulations, they were repeated twice but changing the AOD monthly values by the same AOD plus/minus its uncertainty. The maximum difference between the irradiance run with AOD and the irradiance run with AOD plus/minus its uncertainty was calculated for each month, SZA, and location. This difference was considered as the uncertainty on the model caused by the AOD uncertainty. The uncertainty in the simulated global SW and UVER varies with the location, but the behaviour is similar: high uncertainty in specific months. The averages of the uncertainty at the nine locations were calculated. Uncertainty in the global SW is lower than 5% for SZA values lower than 70º, and the uncertainty in global UVER is between 2 and 6%. The uncertainty in the direct and diffuse components is higher than in the global case for both SW and UVER irradiances, but a balance between the changes with AOD in direct and diffuse components provide a lower uncertainty in global SW and UVER irradiance. References Bilbao, J., Román, R., de Miguel, A., Mateos, D.: Long-term solar erythemal UV irradiance data reconstruction in Spain using a semiempirical method, J. Geophys. Res., 116, D22211, 2011. Kylling, A., Stamnes, K., Tsay, S. C.: A reliable and efficient two-stream algorithm for spherical radiative transfer: Documentation of acciracy in realistic layered media, J. Atmos. Chem, 21, 115-150, 1995. Ricchiazzi, P., Yang, S., Gautier, C., Sowle, D.: SBDART: A research and Teaching software tool for plane-parallel radiative transfer in the Earth's atmosphere, Bulletin of the American Meteorological

Comparison Between NPP-VIIRS Aerosol Data Products and the MODIS AQUA Deep Blue Collection 6 Dataset Over Land

NASA Technical Reports Server (NTRS)

Sayer, Andrew M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Kondragunta, S.

2013-01-01

Aerosols are small particles suspended in the atmosphere and have a variety of natural and man-made sources. Knowledge of aerosol optical depth (AOD), which is a measure of the amount of aerosol in the atmosphere, and its change over time, is important for multiple reasons. These include climate change, air quality (pollution) monitoring, monitoring hazards such as dust storms and volcanic ash, monitoring smoke from biomass burning, determining potential energy yields from solar plants, determining visibility at sea, estimating fertilization of oceans and rainforests by transported mineral dust, understanding changes in weather brought upon by the interaction of aerosols and clouds, and more. The Suomi-NPP satellite was launched late in 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine AOD. This study compares the VIIRS dataset to ground-based measurements of AOD, along with a state-of-the-art satellite AOD dataset (the new version of the Moderate Resolution Imaging Spectrometer Deep Blue algorithm) to assess its reliability. The Suomi-NPP satellite was launched late in 2011, carrying several instruments designed to continue the biogeophysical data records of current and previous satellite sensors. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine aerosol optical depth (AOD), and related activities since launch have been focused towards validating and understanding this new dataset through comparisons with other satellite and ground-based products. The operational VIIRS AOD product is compared over land with AOD derived from Moderate Resolution Imaging Spectrometer (MODIS) observations using the Deep Blue (DB) algorithm from the forthcoming Collection 6 of MODIS data

A Pure Marine Aerosol Model, for Use in Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Smirnov, A.; Hsu, N. C.; Holben, B. N.

2011-01-01

Retrievals of aerosol optical depth (AOD) and related parameters from satellite measurements typically involve prescribed models of aerosol size and composition, and are therefore dependent on how well these models are able to represent the radiative behaviour of real aerosols, This study uses aerosol volume size distributions retrieved from Sun-photometer measurements at 11 Aerosol Robotic Network (AERONET) island sites, spread throughout the world's oceans, as a basis to define such a model for unpolluted maritime aerosols. Size distributions are observed to be bimodal and approximately lognormal, although the coarse mode is skewed with a long tail on the low-radius end, The relationship of AOD and size distribution parameters to meteorological conditions is also examined, As wind speed increases, so do coarse-mode volume and radius, The AOD and Angstrom exponent (alpha) show linear relationships with wind speed, although there is considerable scatter in all these relationships, limiting their predictive power. Links between aerosol properties and near-surface relative humidity, columnar water vapor, and sea surface temperature are also explored. A recommended bimodal maritime model, which is able to reconstruct the AERONET AOD with accuracy of order 0.01-0.02, is presented for use in aerosol remote sensing applications. This accuracy holds at most sites and for wavelengths between 340 nm and 1020 nm. Calculated lidar ratios are also provided, and differ significantly from those currently used in Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) processing.

Remote sensing of PM2.5 from ground-based optical measurements

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.

2014-12-01

Remote sensing of particulate matter concentration with aerodynamic diameter smaller than 2.5 um(PM2.5) by using ground-based optical measurements of aerosols is investigated based on 6 years of hourly average measurements of aerosol optical properties, PM2.5, ceilometer backscatter coefficients and meteorological factors from Howard University Beltsville Campus facility (HUBC). The accuracy of quantitative retrieval of PM2.5 using aerosol optical depth (AOD) is limited due to changes in aerosol size distribution and vertical distribution. In this study, ceilometer backscatter coefficients are used to provide vertical information of aerosol. It is found that the PM2.5-AOD ratio can vary largely for different aerosol vertical distributions. The ratio is also sensitive to mode parameters of bimodal lognormal aerosol size distribution when the geometric mean radius for the fine mode is small. Using two Angstrom exponents calculated at three wavelengths of 415, 500, 860nm are found better representing aerosol size distributions than only using one Angstrom exponent. A regression model is proposed to assess the impacts of different factors on the retrieval of PM2.5. Compared to a simple linear regression model, the new model combining AOD and ceilometer backscatter can prominently improve the fitting of PM2.5. The contribution of further introducing Angstrom coefficients is apparent. Using combined measurements of AOD, ceilometer backscatter, Angstrom coefficients and meteorological parameters in the regression model can get a correlation coefficient of 0.79 between fitted and expected PM2.5.

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin

2013-01-01

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

An aerosol optical depth climatology for NOAA's national surface radiation budget network (SURFRAD)

NASA Astrophysics Data System (ADS)

Augustine, John A.; Hodges, Gary B.; Dutton, Ellsworth G.; Michalsky, Joseph J.; Cornwall, Christopher R.

2008-06-01

A series of algorithms developed to process spectral solar measurements for aerosol optical depth (AOD) for the National Oceanic and Atmospheric Administration's (NOAA) national surface radiation budget network (SURFRAD) is summarized, and decadal results are presented. AOD is a measure of the extinction of the Sun's beam due to aerosols. Daily files of AOD for five spectral measurements in the visible and near-infrared have been produced for 1997-2006. Comparisons of SURFRAD daily AOD averages to NASA's Aerosol Robotic Network product at two of the stations were generally good. An AOD climatology for each SURFRAD station is presented as an annual time series of composite monthly means that represents a typical intra-annual AOD variation. Results are similar to previous U.S. climatologies in that the highest AOD magnitude and greatest variability occur in summer, the lowest AOD levels are in winter, and geographically, the highest-magnitude AOD is in the eastern United States. Springtime Asian dust intrusions show up as a secondary maximum at the western stations. A time series of nationwide annual means shows that 500-nm AOD has decreased over the United States by about 0.02 AOD units over the 10-year period. However, this decline is not statistically significant nor geographically consistent within the country. The eastern U.S. stations and westernmost station at Desert Rock, Nevada, show decreasing AOD, whereas the other two western stations show an increase that is attributed to an upsurge in wildfire activity in the last half of the decade.

A Critical Examination of Spatial Biases Between MODIS and MISR Aerosol Products - Application for Potential AERONET Deployment

NASA Technical Reports Server (NTRS)

Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; Eck, T. F.; Holben, B. N.; Kahn, R. A.

2011-01-01

AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while side-stepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a km1 file.

Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model.

PubMed

Dai, Tie; Schutgens, Nick A J; Goto, Daisuke; Shi, Guangyu; Nakajima, Teruyuki

2014-12-01

A new global aerosol assimilation system adopting a more complex icosahedral grid configuration is developed. Sensitivity tests for the assimilation system are performed utilizing satellite retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the results over Eastern Asia are analyzed. The assimilated results are validated through independent Aerosol Robotic Network (AERONET) observations. Our results reveal that the ensemble and local patch sizes have little effect on the assimilation performance, whereas the ensemble perturbation method has the largest effect. Assimilation leads to significantly positive effect on the simulated AOD field, improving agreement with all of the 12 AERONET sites over the Eastern Asia based on both the correlation coefficient and the root mean square difference (assimilation efficiency). Meanwhile, better agreement of the Ångström Exponent (AE) field is achieved for 8 of the 12 sites due to the assimilation of AOD only. Copyright © 2014 Elsevier Ltd. All rights reserved.

Retrieving atmospheric dust opacity on Mars by imaging spectroscopy at large angles

NASA Astrophysics Data System (ADS)

Douté, S.; Ceamanos, X.; Appéré, T.

2013-09-01

We propose a new method to retrieve the optical depth of Martian aerosols (AOD) from OMEGA and CRISM hyperspectral imagery at a reference wavelength of 1 μm. Our method works even if the underlying surface is completely made of minerals, corresponding to a low contrast between surface and atmospheric dust, while being observed at a fixed geometry. Minimizing the effect of the surface reflectance properties on the AOD retrieval is the second principal asset of our method. The method is based on the parametrization of the radiative coupling between particles and gas determining, with local altimetry, acquisition geometry, and the meteorological situation, the absorption band depth of gaseous CO2. Because the last three factors can be predicted to some extent, we can define a new parameter β that expresses specifically the strength of the gas-aerosols coupling while directly depending on the AOD. Combining estimations of β and top of the atmosphere radiance values extracted from the observed spectra within the CO2 gas band at 2 μm, we evaluate the AOD and the surface reflectance by radiative transfer inversion. One should note that practically β can be estimated for a large variety of mineral or icy surfaces with the exception of CO2 ice when its 2 μm solid band is not sufficiently saturated. Validation of the proposed method shows that it is reliable if two conditions are fulfilled: (i) the observation conditions provide large incidence or/and emergence angles (ii) the aerosols are vertically well mixed in the atmosphere. Experiments conducted on OMEGA nadir looking observations as well as CRISM multi-angular acquisitions with incidence angles higher than 65° in the first case and 33° in the second case produce very satisfactory results. Finally in a companion paper the method is applied to monitoring atmospheric dust spring activity at high southern latitudes on Mars using OMEGA.

Aerosol optical depth in the European Brewer Network

NASA Astrophysics Data System (ADS)

López-Solano, Javier; Redondas, Alberto; Carlund, Thomas; Rodriguez-Franco, Juan J.; Diémoz, Henri; León-Luis, Sergio F.; Hernández-Cruz, Bentorey; Guirado-Fuentes, Carmen; Kouremeti, Natalia; Gröbner, Julian; Kazadzis, Stelios; Carreño, Virgilio; Berjón, Alberto; Santana-Díaz, Daniel; Rodríguez-Valido, Manuel; De Bock, Veerle; Moreta, Juan R.; Rimmer, John; Smedley, Andrew R. D.; Boulkelia, Lamine; Jepsen, Nis; Eriksen, Paul; Bais, Alkiviadis F.; Shirotov, Vadim; Vilaplana, José M.; Wilson, Keith M.; Karppinen, Tomi

2018-03-01

Aerosols play an important role in key atmospheric processes and feature high spatial and temporal variabilities. This has motivated scientific interest in the development of networks capable of measuring aerosol properties over large geographical areas in near-real time. In this work we present and discuss results of an aerosol optical depth (AOD) algorithm applied to instruments of the European Brewer Network. This network is comprised of close to 50 Brewer spectrophotometers, mostly located in Europe and adjacent areas, although instruments operating at, for example, South America and Australia are also members. Although we only show results for instruments calibrated by the Regional Brewer Calibration Center for Europe, the implementation of the AOD algorithm described is intended to be used by the whole network in the future. Using data from the Brewer intercomparison campaigns in the years 2013 and 2015, and the period in between, plus comparisons with Cimel sun photometers and UVPFR instruments, we check the precision, stability, and uncertainty of the Brewer AOD in the ultraviolet range from 300 to 320 nm. Our results show a precision better than 0.01, an uncertainty of less than 0.05, and, for well-maintained instruments, a stability similar to that of the ozone measurements. We also discuss future improvements to our algorithm with respect to the input data, their processing, and the characterization of the Brewer instruments for the measurement of AOD.

Hemispheric aerosol vertical profiles: anthropogenic impacts on optical depth and cloud nuclei.

PubMed

Clarke, Antony; Kapustin, Vladimir

2010-09-17

Understanding the effect of anthropogenic combustion upon aerosol optical depth (AOD), clouds, and their radiative forcing requires regionally representative aerosol profiles. In this work, we examine more than 1000 vertical profiles from 11 major airborne campaigns in the Pacific hemisphere and confirm that regional enhancements in aerosol light scattering, mass, and number are associated with carbon monoxide from combustion and can exceed values in unperturbed regions by more than one order of magnitude. Related regional increases in a proxy for cloud condensation nuclei (CCN) and AOD imply that direct and indirect aerosol radiative effects are coupled issues linked globally to aged combustion. These profiles constrain the influence of combustion on regional AOD and CCN suitable for challenging climate model performance and informing satellite retrievals.

A Climatology of Global Aerosol Mixtures to Support Sentinel-5P and Earthcare Mission Applications

NASA Astrophysics Data System (ADS)

Taylor, M.; Kazadzis, S.; Amaridis, V.; Kahn, R. A.

2015-11-01

Since constraining aerosol type with satellite remote sensing continues to be a challenge, we present a newly derived global climatology of aerosol mixtures to support atmospheric composition studies that are planned for Sentinel-5P and EarthCARE.The global climatology is obtained via application of iterative cluster analysis to gridded global decadal and seasonal mean values of the aerosol optical depth (AOD) of sulfate, biomass burning, mineral dust and marine aerosol as a proportion of the total AOD at 500nm output from the Goddard Chemistry Aerosol Radiation and Transport (GOCART). For both the decadal and seasonal means, the number of aerosol mixtures (clusters) identified is ≈10. Analysis of the percentage contribution of the component aerosol types to each mixture allowed development of a straightforward naming convention and taxonomy, and assignment of primary colours for the generation of true colour-mixing and easy-to-interpret maps of the spatial distribution of clusters across the global grid. To further help characterize the mixtures, aerosol robotic network (AERONET) Level 2.0 Version 2 inversion products were extracted from each cluster‟s spatial domain and used to estimate climatological values of key optical and microphysical parameters.The aerosol type climatology represents current knowledge that would be enhanced, possibly corrected, and refined by high temporal and spectral resolution, cloud-free observations produced by Sentinel-5P and EarthCARE instruments. The global decadal mean and seasonal gridded partitions comprise a preliminary reference framework and global climatology that can help inform the choice of components and mixtures in aerosol retrieval algorithms used by instruments such as TROPOMI and ATLID, and to test retrieval results.

Uncertainties of aerosol retrieval from neglecting non-sphericity of dust aerosols

NASA Astrophysics Data System (ADS)

Li, Chi; Xue, Yong; Yang, Leiku; Guang, Jie

2013-04-01

The Mie theory is conventionally applied to calculate aerosol optical properties in satellite remote sensing applications, while dust aerosols cannot be well modeled by the Mie calculation for their non-sphericity. It has been cited in Mishchenko et al. (1995; 1997) that neglecting non-sphericity can severely influence aerosol optical depth (AOD, ?) retrieval in case of dust aerosols because of large difference of phase functions under spherical and non-spherical assumptions, whereas this uncertainty has not been thoroughly studied. This paper aims at a better understanding of uncertainties on AOD retrieval caused by aerosol non-sphericity. A dust aerosol model with known refractive index and size distribution is generated from long-term AERONET observations since 1999 over China. Then aerosol optical properties, such as the extinction, phase function, single scattering albedo (SSA) are calculated respectively in the assumption of spherical and non-spherical aerosols. Mie calculation is carried out for spherical assumption, meanwhile for non-spherical aerosol modeling, we adopt the pre-calculated scattering kernels and software package presented by Dubovik et al. (2002; 2006), which describes dust as a shape mixture of randomly oriented polydisperse spheroids. Consequently we generate two lookup tables (LUTspheric and LUTspheroid) from simulated satellite received reflectance at top of atmosphere (TOA) under varieties of observing conditions and aerosol loadings using Second Simulation of a Satellite Signal in the Solar Spectrum - Vector (6SV) code. All the simulations are made at 550 nm, and for simplicity the Lambertian surface is assumed. Using the obtained LUTs we examine the differences of TOA reflectance (Δ?TOA = ?spheric - ?spheroid) under different surface reflectance and aerosol loadings. Afterwards AOD is retrieved using LUTspheric from the simulated TOA reflectance by LUTspheroid in order to detect the retrieval errors (Δ? = ?retreived -?input) induced by straightforwardly utilizing Mie theory in dust aerosol retrieval. As expected we find that the uncertainties mainly result from the obvious difference of phase functions (Pspheric and Pspheroid). Errors may be positive or negative, depending on the specific geometry. In scattering angle (θ) regions where Psphericis greater (30°~85° & 145°~180°), we generally get positive Δ?TOA and negative Δ?, and vice versa (85°~145°). For low aerosol loading (? ~0.25) and black surface, |Δ?TOA| could be greater than 0.004 and 0.012 around θ ~120° and θ ~170°, with |Δ?| of ~0.04 and ~0.12 respectively. In most back scattering cases (θ >100°), the magnitude of Δ? is about ten times that of Δ?TOA, while this ratio (|Δ?|/|Δ?TOA|) significantly reduces to as low as ~0.5 for forward scattering, and can reach ~20 at θ ~145°. Moreover, this errors and |Δ?|/|Δ?TOA| can increase more than ten times as aerosol loading gets higher and surface gets brighter. Therefore we conclude that the neglect of non-sphericity introduces substantial errors on radiative transfer simulation and AOD retrieval. As a result of this study, a representative aspheric aerosol model other than Mie calculation is recommended for inversion algorithms related with dust-like non-spherical aerosols. References Dubovik, O., Holben, B. N., Lapyonok, T., Sinyuk, A., Mishchenko, M. I., Yang, P., and Slutsker, I. (2002). Non-spherical aerosol retrieval method employing light scattering by spheroids. Geophyscal Research Letters, 29(10), 1415, doi:10.1029/2001GL014506. Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J.-F., Sorokin, M., and Slutsker, I. (2006). Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. Journal of Geophysical Research, 111, D11208, doi:10.1029/2005JD006619. Mishchenko, M. I., Lacis, A. A., Carlson, B. E., and Travis, L. D. (1995). Nonsphericity of dust-like aerosols: Implications for aerosol remote sensing and climate modeling, Geophyscal Research Letters, 22, 1077- 1080. Mishchenko, M. I., Travis, L. D., Kahn, R. A., and West, R. A. (1997). Modeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids, Journal of Geophysical Research, 102, 16831- 16847.

Construction of an Inexpensive Sun Photometer for Measuring Aerosols Optical Depth (AOD) and Comparison Between the Ground Based and Satellite Based Measurements

NASA Astrophysics Data System (ADS)

Mamun, M.; Mondol, P.

2012-12-01

Aerosols influence our weather and climate because they affect the amount of sunlight reaching Earth's surface. An important way of probing the atmosphere from the ground is to measure the effects of the atmosphere on sunlight transmitted through the atmosphere to Earth's surface. These indirect techniques provide information about the entire atmosphere above the observer, not just the atmosphere that can be sampled directly. In response to global issues of air quality and climate change, and to the need to improve the quality of science education, inexpensive atmosphere monitoring instruments have been developed. This paper describes a new kind of inexpensive two channels LED Sun Photometer for monitoring aerosols that provide much better long-term stability than instruments that use expensive interference filters. Here HAZE-SPAN TERC VHS-1 model has been used for constructing sun photometer with light emitting diode as detector. Monitoring Earth's atmosphere is a challenging task. As there is no facility in our country (Bangladesh) for ground based measurement for monitoring aerosol so, this type of study is very essential. This study compares the aerosol optical depth (AOD) retrieved from the Terra and Aqua MODerate Resolution Imaging Spectroradiometers (MODIS) with ground-based measurements from a handheld sun photometer over the region of Rajshahi, Bangladesh for The 15 days duration of June 2012. The results indicate that the Terra and Aqua MODIS AOD retrievals at 550 nm have good correlations with the measurements from the handheld sun photometer. The correlation coefficients r = 0.88 for Terra and r = 0.55 for Aqua where as r = 0.65 for Terra and Aqua themselves. AOD for another wavelength at 625 nm is documented in this study for finding out the relation of AOD at different wavelengths. In this paper it has been described and summarized briefly investigations for four important topics: LEDs used as light detectors, construction of sun photometer and its use, the measurements and monitoring of Aerosol Optical Depth (AOD) by using handheld sun photometer, and the comparison between satellite based and ground based measurements.

Development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia

NASA Astrophysics Data System (ADS)

Lee, Sojin; Song, Chul-han; Park, Rae Seol; Park, Mi Eun; Han, Kyung man; Kim, Jhoon; Choi, Myungje; Ghim, Young Sung; Woo, Jung-Hun

2016-04-01

To improve short-term particulate matter (PM) forecasts in South Korea, the initial distribution of PM composition, particularly over the upwind regions, is primarily important. To prepare the initial PM composition, the aerosol optical depth (AOD) data retrieved from a geostationary equatorial orbit (GEO) satellite sensor, GOCI (Geostationary Ocean Color Imager) which covers a part of Northeast Asia (113-146° E; 25-47° N), were used. Although GOCI can provide a higher number of AOD data in a semicontinuous manner than low Earth orbit (LEO) satellite sensors, it still has a serious limitation in that the AOD data are not available at cloud pixels and over high-reflectance areas, such as desert and snow-covered regions. To overcome this limitation, a spatiotemporal-kriging (STK) method was used to better prepare the initial AOD distributions that were converted into the PM composition over Northeast Asia. One of the largest advantages in using the STK method in this study is that more observed AOD data can be used to prepare the best initial AOD fields compared with other methods that use single frame of observation data around the time of initialization. It is demonstrated in this study that the short-term PM forecast system developed with the application of the STK method can greatly improve PM10 predictions in the Seoul metropolitan area (SMA) when evaluated with ground-based observations. For example, errors and biases of PM10 predictions decreased by ˜ 60 and ˜ 70{%}, respectively, during the first 6 h of short-term PM forecasting, compared with those without the initial PM composition. In addition, the influences of several factors on the performances of the short-term PM forecast were explored in this study. The influences of the choices of the control variables on the PM chemical composition were also investigated with the composition data measured via PILS-IC (particle-into-liquid sampler coupled with ion chromatography) and low air-volume sample instruments at a site near Seoul. To improve the overall performances of the short-term PM forecast system, several future research directions were also discussed and suggested.

Can a coupled meteorology–chemistry model reproduce the ...

EPA Pesticide Factsheets

The ability of a coupled meteorology–chemistry model, i.e., Weather Research and Forecast and Community Multiscale Air Quality (WRF-CMAQ), to reproduce the historical trend in aerosol optical depth (AOD) and clear-sky shortwave radiation (SWR) over the Northern Hemisphere has been evaluated through a comparison of 21-year simulated results with observation-derived records from 1990 to 2010. Six satellite-retrieved AOD products including AVHRR, TOMS, SeaWiFS, MISR, MODIS-Terra and MODIS-Aqua as well as long-term historical records from 11 AERONET sites were used for the comparison of AOD trends. Clear-sky SWR products derived by CERES at both the top of atmosphere (TOA) and surface as well as surface SWR data derived from seven SURFRAD sites were used for the comparison of trends in SWR. The model successfully captured increasing AOD trends along with the corresponding increased TOA SWR (upwelling) and decreased surface SWR (downwelling) in both eastern China and the northern Pacific. The model also captured declining AOD trends along with the corresponding decreased TOA SWR (upwelling) and increased surface SWR (downwelling) in the eastern US, Europe and the northern Atlantic for the period of 2000–2010. However, the model underestimated the AOD over regions with substantial natural dust aerosol contributions, such as the Sahara Desert, Arabian Desert, central Atlantic and northern Indian Ocean. Estimates of the aerosol direct radiative effect (DRE) at TOA a

AIR QUALITY FORECAST VERIFICATION USING SATELLITE DATA

EPA Science Inventory

NOAA 's operational geostationary satellite retrievals of aerosol optical depths (AODs) were used to verify National Weather Service (NWS) experimental (research mode) particulate matter (PM2.5) forecast guidance issued during the summer 2004 International Consortium for Atmosp...

Development of non-linear models predicting daily fine particle concentrations using aerosol optical depth retrievals and ground-based measurements at a municipality in the Brazilian Amazon region

NASA Astrophysics Data System (ADS)

Gonçalves, Karen dos Santos; Winkler, Mirko S.; Benchimol-Barbosa, Paulo Roberto; de Hoogh, Kees; Artaxo, Paulo Eduardo; de Souza Hacon, Sandra; Schindler, Christian; Künzli, Nino

2018-07-01

Epidemiological studies generally use particulate matter measurements with diameter less 2.5 μm (PM2.5) from monitoring networks. Satellite aerosol optical depth (AOD) data has considerable potential in predicting PM2.5 concentrations, and thus provides an alternative method for producing knowledge regarding the level of pollution and its health impact in areas where no ground PM2.5 measurements are available. This is the case in the Brazilian Amazon rainforest region where forest fires are frequent sources of high pollution. In this study, we applied a non-linear model for predicting PM2.5 concentration from AOD retrievals using interaction terms between average temperature, relative humidity, sine, cosine of date in a period of 365,25 days and the square of the lagged relative residual. Regression performance statistics were tested comparing the goodness of fit and R2 based on results from linear regression and non-linear regression for six different models. The regression results for non-linear prediction showed the best performance, explaining on average 82% of the daily PM2.5 concentrations when considering the whole period studied. In the context of Amazonia, it was the first study predicting PM2.5 concentrations using the latest high-resolution AOD products also in combination with the testing of a non-linear model performance. Our results permitted a reliable prediction considering the AOD-PM2.5 relationship and set the basis for further investigations on air pollution impacts in the complex context of Brazilian Amazon Region.

Expanding the Estimation of Surface PM2.5 from Aqua and Terra MODIS Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS

NASA Astrophysics Data System (ADS)

Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from MODIS AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove MODIS AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time MODIS AOD products from Terra and Aqua and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to MODIS, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to improve AQI. This presentation will focus on a description of ASDP, including an overview of the algorithm used to estimate surface PM2.5 using satellite data and examples of high resolution VIIRS AOD products and their value to the ASDP. Disclaimer: Although this work was reviewed by the U.S. Environmental Protection Agency and approved for publication, it may not necessarily reflect official Agency policy.

Development of IDEA product for GOES-R aerosol data

NASA Astrophysics Data System (ADS)

Zhang, Hai; Hoff, Raymond M.; Kondragunta, Shobha

2009-08-01

The NOAA GOES-R Advanced Baseline Imager (ABI) will have nearly the same capabilities as NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) to generate multi-wavelength retrievals of aerosol optical depth (AOD) with high temporal and spatial resolution, which can be used as a surrogate of surface particulate measurements such as PM2.5 (particulate matter with diameter less than 2.5 μm). To prepare for the launch of GOES-R and its application in the air quality forecasting, we have transferred and enhanced the Infusing satellite Data into Environmental Applications (IDEA) product from University of Wisconsin to NOAA NESDIS. IDEA was created through a NASA/EPA/NOAA cooperative effort. The enhanced IDEA product provides near-real-time imagery of AOD derived from multiple satellite sensors including MODIS Terra, MODIS Aqua, GOES EAST and GOES WEST imager. Air quality forecast guidance is produced through a trajectory model initiated at locations with high AOD retrievals and/or high aerosol index (AI) from OMI (Ozone Monitoring Instrument). The product is currently running at http://www.star.nesdis.noaa.gov/smcd/spb/aq/. The IDEA system will be tested using the GOES-R ABI proxy dataset, and will be ready to operate with GOES-R aerosol data when GOES-R is launched.

A new zenith-looking narrow-band radiometer-based system (ZEN) for dust aerosol optical depth monitoring

NASA Astrophysics Data System (ADS)

Almansa, A. Fernando; Cuevas, Emilio; Torres, Benjamín; Barreto, África; García, Rosa D.; Cachorro, Victoria E.; de Frutos, Ángel M.; López, César; Ramos, Ramón

2017-02-01

A new zenith-looking narrow-band radiometer based system (ZEN), conceived for dust aerosol optical depth (AOD) monitoring, is presented in this paper. The ZEN system comprises a new radiometer (ZEN-R41) and a methodology for AOD retrieval (ZEN-LUT). ZEN-R41 has been designed to be stand alone and without moving parts, making it a low-cost and robust instrument with low maintenance, appropriate for deployment in remote and unpopulated desert areas. The ZEN-LUT method is based on the comparison of the measured zenith sky radiance (ZSR) with a look-up table (LUT) of computed ZSRs. The LUT is generated with the LibRadtran radiative transfer code. The sensitivity study proved that the ZEN-LUT method is appropriate for inferring AOD from ZSR measurements with an AOD standard uncertainty up to 0.06 for AOD500 nm ˜ 0.5 and up to 0.15 for AOD500 nm ˜ 1.0, considering instrumental errors of 5 %. The validation of the ZEN-LUT technique was performed using data from AErosol RObotic NETwork (AERONET) Cimel Electronique 318 photometers (CE318). A comparison between AOD obtained by applying the ZEN-LUT method on ZSRs (inferred from CE318 diffuse-sky measurements) and AOD provided by AERONET (derived from CE318 direct-sun measurements) was carried out at three sites characterized by a regular presence of desert mineral dust aerosols: Izaña and Santa Cruz in the Canary Islands and Tamanrasset in Algeria. The results show a coefficient of determination (R2) ranging from 0.99 to 0.97, and root mean square errors (RMSE) ranging from 0.010 at Izaña to 0.032 at Tamanrasset. The comparison of ZSR values from ZEN-R41 and the CE318 showed absolute relative mean bias (RMB) < 10 %. ZEN-R41 AOD values inferred from ZEN-LUT methodology were compared with AOD provided by AERONET, showing a fairly good agreement in all wavelengths, with mean absolute AOD differences < 0.030 and R2 higher than 0.97.

What We are Learning from (and About) the 10 Plus Year MISR Aerosol Data Record

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2010-01-01

Having a 10+ year data record from the Multi-angle Imaging SpectroRadiometer (MISR) significantly improves our opportunities to validate the retrieved aerosol optical depth (AOD) and especially particle microphysical property products. It also begins to raise the possibility of using the data to look for changes or even trends, at least on a regional basis. Further, we have had the opportunity to expand the database of wildfire smoke plume heights derived from the multiangle observations. This presentation will review the latest aerosol validation results and algorithm upgrades under consideration by the MISR team, and will summarize the current status of MISR global aerosol air mass type, and regional dust transport and smoke injection height products. The strengths and limitations of these data for constraining aerosol transport model simulations will receive special emphasis.

New Shortwave Array Spectroradiometer-Hemispheric (SAS-He): Hyperspectral Design and Initial Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassianov, Evgueni I.; Flynn, Connor J M.; Barnard, James C.

2016-10-31

Aerosol optical depth (AOD) derived from hyperspectral measurements can serve as an invaluable input for simultaneous retrievals of particle size distributions and major trace gases. The required hyperspectral measurements are provided by a new ground-based radiometer, the so-called Shortwave Array Spectroradiometer-Hemispheric (SAS-He), recently developed with support from the Department of Energy (DOE) Office Atmospheric Radiation Measurement (ARM) Program. The SAS-He has wide spectral coverage (350-1700nm) and high spectral resolution: about 2.4 nm and 6 nm within 350-1000 nm and 970-1700 nm spectral ranges, respectively. To illustrate an initial performance of the SAS-He, we take advantage of integrated dataset collected duringmore » the ARM-supported Two-Column Aerosol Project (TCAP) over the US coastal region (Cape Cod, Massachusetts). This dataset includes AODs derived using data from Aerosol Robotic Network (AERONET) sunphotometer and Multi-Filter Rotating Shadowband Radiometer (MFRSR). We demonstrate that, on average, the SAS-He AODs closely match the MFRSR and AERONET AODs in the ultraviolet and visible spectral ranges for this area with highly variable AOD. Also, we discuss corrections of SAS-He total optical depth for gas absorption in the near-infrared spectral range and their operational implementation.« less

Aerosol Optical Depth Retrieval With AVIRIS Data: A Test of Tafkaa

DTIC Science & Technology

2002-09-01

the spatial resolution . Clearly there is a need for a method of AOD retrieval that can cover more of the globe in a...imagers lack sufficient spectral resolution for some scientific applications. The future of remote sensing is in the ability to collect and interpret...AVIRIS is by using a data cube with two axes for the spatial dimensions and the third axis representing the 224 channels that make up the spectral

The CAMS interim Reanalysis of Carbon Monoxide, Ozone and Aerosol for 2003-2015

NASA Astrophysics Data System (ADS)

Flemming, Johannes; Benedetti, Angela; Inness, Antje; Engelen, Richard J.; Jones, Luke; Huijnen, Vincent; Remy, Samuel; Parrington, Mark; Suttie, Martin; Bozzo, Alessio; Peuch, Vincent-Henri; Akritidis, Dimitris; Katragkou, Eleni

2017-02-01

A new global reanalysis data set of atmospheric composition (AC) for the period 2003-2015 has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). Satellite observations of total column (TC) carbon monoxide (CO) and aerosol optical depth (AOD), as well as several TC and profile observations of ozone, have been assimilated with the Integrated Forecasting System for Composition (C-IFS) of the European Centre for Medium-Range Weather Forecasting. Compared to the previous Monitoring Atmospheric Composition and Climate (MACC) reanalysis (MACCRA), the new CAMS interim reanalysis (CAMSiRA) is of a coarser horizontal resolution of about 110 km, compared to 80 km, but covers a longer period with the intent to be continued to present day. This paper compares CAMSiRA with MACCRA and a control run experiment (CR) without assimilation of AC retrievals. CAMSiRA has smaller biases than the CR with respect to independent observations of CO, AOD and stratospheric ozone. However, ozone at the surface could not be improved by the assimilation because of the strong impact of surface processes such as dry deposition and titration with nitrogen monoxide (NO), which were both unchanged by the assimilation. The assimilation of AOD led to a global reduction of sea salt and desert dust as well as an exaggerated increase in sulfate. Compared to MACCRA, CAMSiRA had smaller biases for AOD, surface CO and TC ozone as well as for upper stratospheric and tropospheric ozone. Finally, the temporal consistency of CAMSiRA was better than the one of MACCRA. This was achieved by using a revised emission data set as well as by applying careful selection and bias correction to the assimilated retrievals. CAMSiRA is therefore better suited than MACCRA for the study of interannual variability, as demonstrated for trends in surface CO.

Retrieval of aerosol optical and physical properties from ground-based measurements for Zanjan, a city in Northwest Iran

NASA Astrophysics Data System (ADS)

Masoumi, A.; Khalesifard, H. R.; Bayat, A.; Moradhaseli, R.

2013-02-01

A ground-based sun and sky scanning radiometer, CIMEL CE 318-2 sunphotometer, has been used to study the atmosphere of Zanjan, a city in Northwest Iran (36.70°N, 48.51°E, and 1800 m above the mean sea level) in the periods of October 2006-October 2008, and January-September 2010. Direct sun and solar principal plane sky radiance measurements by the sunphotometer have been used to retrieve the optical and physical properties of atmospheric aerosols, such as aerosol optical depth (AOD), Ångström exponent (α), single scattering albedo (SSA), refractive index, and volume size distributions. About 50 dusty days (daily averaged AOD (870) > 0.35, α < 0.5) have been recorded during the mentioned periods. Considering the different values obtained for SSA, real part of refractive index, and volume size distributions, it has been found that just dust and anthropogenic aerosols are making the atmospheric aerosols in this region. In these recordings it has been observed that AODs (Ångström exponents) were increasing (decreasing) during spring and early summer. This was accompanied by increase of SSA, real part of refractive index, and coarse mode part of volume size distributions of aerosols. This behavior could be due to transport of dust, mostly from Tigris-Euphrates basin or sometimes with lower probability from the region between Caspian and Aral seas and rarely from sources inside the Iran plateau like the Qom dry lake, especially in dry seasons. In this work NCEP/NCAR reanalysis, HYSPLIT model back trajectories, and MODIS Deep Blue AODs have been used to track the air masses and dust plumes during the recorded dust events.

Satellite-Based Evidence of Wavelength-Dependent Aerosol Absorption in Biomass Burning Smoke Inferred from Ozone Monitoring Instrument

NASA Technical Reports Server (NTRS)

Jethva, H.; Torres, O.

2012-01-01

We provide satellite-based evidence of the spectral dependence of absorption in biomass burning aerosols over South America using near-UV measurements made by the Ozone Monitoring Instrument (OMI) during 2005-2007. In the current near-UV OMI aerosol algorithm (OMAERUV), it is implicitly assumed that the only absorbing component in carbonaceous aerosols is black carbon whose imaginary component of the refractive index is wavelength independent. With this assumption, OMI-derived aerosol optical depth (AOD) is found to be significantly over-estimated compared to that of AERONET at several sites during intense biomass burning events (August-September). Other well-known sources of error affecting the near-UV method of aerosol retrieval do not explain the large observed AOD discrepancies between the satellite and the ground-based observations. A number of studies have revealed strong spectral dependence in carbonaceous aerosol absorption in the near-UV region suggesting the presence of organic carbon in biomass burning generated aerosols. A sensitivity analysis examining the importance of accounting for the presence of wavelength-dependent aerosol absorption in carbonaceous particles in satellite-based remote sensing was carried out in this work. The results convincingly show that the inclusion of spectrally-dependent aerosol absorption in the radiative transfer calculations leads to a more accurate characterization of the atmospheric load of carbonaceous aerosols.

A climatology of fine absorbing biomass burning, urban and industrial aerosols detected from satellites

NASA Astrophysics Data System (ADS)

Kalaitzi, Nikoleta; Hatzianastassiou, Nikos; Gkikas, Antonis; Papadimas, Christos D.; Torres, Omar; Mihalopoulos, Nikos

2017-04-01

Natural biomass burning (BB) along with anthropogenic urban and industrial aerosol particles, altogether labeled here as BU aerosols, contain black and brown carbon which both absorb strongly the solar radiation. Thus, BU aerosols warm significantly the atmosphere also causing adjustments to cloud properties, which traditionally are known as cloud indirect and semi-direct effects. Given the role of the effects of BU aerosols for contemporary and future climate change, and the uncertainty associated with BU, both ascertained by the latest IPCC reports, there is an urgent need for improving our knowledge on the spatial and temporal variability of BU aerosols all over the globe. Over the last few decades, thanks to the rapid development of satellite observational techniques and retrieval algorithms it is now possible to detect BU aerosols based on satellite measurements. However, care must be taken in order to ensure the ability to distinguish BU from other aerosol types usually co-existing in the Earth's atmosphere. In the present study, an algorithm is presented, based on a synergy of different satellite measurements, aiming to identify and quantify BU aerosols over the entire globe and during multiple years. The objective is to build a satellite-based climatology of BU aerosols intended for use for various purposes. The produced regime, namely the spatial and temporal variability of BU aerosols, emphasizes the BU frequency of occurrence and their intensity, in terms of aerosol optical depth (AOD). The algorithm is using the following aerosol optical properties describing the size and atmospheric loading of BU aerosols: (i) spectral AOD, (ii) Ångström Exponent (AE), (iii) Fine Fraction (FF) and (iv) Aerosol Index (AI). The relevant data are taken from Collection 006 MODIS-Aqua, except for AI which is taken from OMI-Aura. The identification of BU aerosols by the algorithm is based on a specific thresholding technique, with AI≥1.5, AE≥1.2 and FF≥0.6 threshold values. The study spans the 11-year period 2005-2015, which enables to examine the inter-annual variability and possible changes of BU aerosols. Emphasis is given on specific world areas known to be sources of BU emissions. An effort is also made to separate with the algorithm the BB from BU aerosols, aiming to create a satellite database of biomass burning aerosols. The results of the algorithm, as to BB aerosols and the ability to separate them, are evaluated through comparisons against the global satellite databases of MODIS active fire counts as well as AIRS carbon monoxide (CO), which is a key indicator of presence of biomass burning activities. The algorithm estimates frequencies of occurrence of BU aerosols reaching up to 10 days/year and AOD values up to 1.5 or even larger. The results indicate the existence of seasonal cycles of biomass burning in south and central Africa as well as in South America (Amazonia), with highest BU frequencies during June-September, December-February and August-October, respectively, whereas they successfully reproduce features like the export of African BB aerosols into the Atlantic Ocean.

High Resolution Trajectory-Based Smoke Forecasts Using VIIRS Aerosol Optical Depth and NUCAPS Carbon Monoxide Retrievals

NASA Astrophysics Data System (ADS)

Pierce, R. B.; Smith, N.; Barnet, C.; Barnet, C. D.; Kondragunta, S.; Davies, J. E.; Strabala, K.

2016-12-01

We use Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth (AOD) and combined Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) NOAA-Unique CrIS-ATMS Processing System (NUCAPS) carbon monoxide (CO) retrievals to initialize trajectory-based, high spatial resolution North American smoke dispersion forecasts during the May 2016 Fort McMurray wildfire in northern Alberta and the July 2016 Soberanes Fire in Northern California. These two case studies illustrate how long range transport of wild fire smoke can adversely impact surface air quality thousands of kilometers downwind and how local topographic flow can lead to complex transport patterns near the wildfire source region. The NUCAPS CO retrievals are shown to complement the high resolution VIIRS AOD retrievals by providing retrievals in partially cloudy scenes and also providing information on the vertical distribution of the wildfire smoke. This work addresses the need for low latency, web-based, high resolution forecasts of smoke dispersion for use by NWS Incident Meteorologists (IMET) to support on-site decision support services for fire incident management teams. The primary user community for the IDEA-I smoke forecasts is the Western regions of the NWS and US EPA due to the significant impacts of wildfires in these regions. Secondary users include Alaskan NWS offices and Western State and Local air quality management agencies such as the Western Regional Air Partnership (WRAP).

Intercomparison between CMIP5 model and MODIS satellite-retrieved data of aerosol optical depth, cloud fraction, and cloud-aerosol interactions

NASA Astrophysics Data System (ADS)

Sockol, Alyssa; Small Griswold, Jennifer D.

2017-08-01

Aerosols are a critical component of the Earth's atmosphere and can affect the climate of the Earth through their interactions with solar radiation and clouds. Cloud fraction (CF) and aerosol optical depth (AOD) at 550 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used with analogous cloud and aerosol properties from Historical Phase 5 of the Coupled Model Intercomparison Project (CMIP5) model runs that explicitly include anthropogenic aerosols and parameterized cloud-aerosol interactions. The models underestimate AOD by approximately 15% and underestimate CF by approximately 10% overall on a global scale. A regional analysis is then used to evaluate model performance in two regions with known biomass burning activity and absorbing aerosol (South America (SAM) and South Africa (SAF)). In SAM, the models overestimate AOD by 4.8% and underestimate CF by 14%. In SAF, the models underestimate AOD by 35% and overestimate CF by 13.4%. Average annual cycles show that the monthly timing of AOD peaks closely match satellite data in both SAM and SAF for all except the Community Atmosphere Model 5 and Geophysical Fluid Dynamics Laboratory (GFDL) models. Monthly timing of CF peaks closely match for all models (except GFDL) for SAM and SAF. Sorting monthly averaged 2° × 2.5° model or MODIS CF as a function of AOD does not result in the previously observed "boomerang"-shaped CF versus AOD relationship characteristic of regions with absorbing aerosols from biomass burning. Cloud-aerosol interactions, as observed using daily (or higher) temporal resolution data, are not reproducible at the spatial or temporal resolution provided by the CMIP5 models.

Sources, Sinks, and Transatlantic Transport of North African Dust Aerosol: A Multimodel Analysis and Comparison With Remote Sensing Data

NASA Technical Reports Server (NTRS)

Kim, Dongchul; Chin, Mian; Yu, Hongbin; Diehl, Thomas; Tan, Qian; Kahn, Ralph A.; Tsigaridis, Kostas; Bauer, Susanne E.; Takemura, Toshihiko; Pozzoli, Luca;

Co-variability of smoke and fire in the Amazon basin

NASA Astrophysics Data System (ADS)

Mishra, Amit Kumar; Lehahn, Yoav; Rudich, Yinon; Koren, Ilan

2015-05-01

The Amazon basin is a hot spot of anthropogenically-driven biomass burning, accounting for approximately 15% of total global fire emissions. It is essential to accurately measure these fires for robust regional and global modeling of key environmental processes. Here we have explored the link between spatio-temporal variability patterns in the Amazon basin's fires and the resulting smoke loading using 11 years (2002-2012) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Focusing on the peak burning season (July-October), our analysis shows strong inter-annual correlation between aerosol optical depth (AOD) and two MODIS fire products: fire radiative power (FRP) and fire pixel counts (FC). Among these two fire products, the FC better indicates the amount of smoke in the basin, as represented in remotely sensed AOD data. This fire product is significantly correlated both with regional AOD retrievals from MODIS and with point AOD measurements from the AERONET stations, pointing to spatial homogenization of the smoke over the basin on a seasonal time scale. However, MODIS AODs are found better than AERONET AODs observation for linking between smoke and fire. Furthermore, MODIS AOD measurements are strongly correlated with number of fires ∼10-20 to the east, most likely due to westward advection of smoke by the wind. These results can be rationalized by the regional topography and the wind regimes. Our analysis can improve data assimilation of satellite and ground-based observations into regional and global model studies, thus improving the assessment of the environmental and climatic impacts of frequency and distribution variability of the Amazon basin's fires. We also provide the optimal spatial and temporal scales for ground-based observations, which could be used for such applications.

Comparison and validation of the aerosol optical depth obtained with the Langley plot method in the UV-B from Brewer Ozone Spectrophotometer measurements

NASA Astrophysics Data System (ADS)

Cheymol, Anne; de Backer, Hugo; Josefsson, Weine; Stübi, René

2006-08-01

The Aerosol Optical Depths (AODs) retrieved from Brewer Ozone Spectrophotometer measurements with a method previously developed (Cheymol and De Backer, 2003) are now validated by comparisons between AODs from six Brewer spectrophotometers and two CSEM SPM2000 sunphotometers: two Brewer spectrophotometers 016 and 178 at Uccle in Belgium; one Brewer spectrophotometer 128 and one sunphotometer CSEM SPM2000 at Norrköping in Sweden; and three Brewer instruments 040, 072, 156 at Arosa and one CSEM SPM2000 sunphotometer at Davos in Switzerland. The comparison between AODs from Brewer spectrophotometer 128 at 320.1 nm and sunphotometer SPM2000 at 368 nm at Norrköping shows that the AODs obtained from the Brewer measurements with the Langley Plot Method (LPM) are very accurate if the neutral density filter spectral transmittances are well known: with the measured values of these filters, the correlation coefficient, the slope, and the intercept of the regression line are 0.98, 0.85 ± 0.004, and 0.02 ± 0.0014, respectively. The bias observed is mainly owing to the wavelength difference between the two instruments. The comparison between AODs from different Brewer spectrophotometers confirm that AODs will be in very good agreement if they are measured with several Brewer instruments at the same place: At Uccle, the correlation coefficient, slope, and intercept of the regression line are 0.98, 1.02 ± 0.003, and 0.06 ± 0.001, respectively; at Arosa, the comparisons between the AODs from three Brewer spectrophotometers 040, 072, and 156 give a correlation coefficient, a slope, and an intercept of the regression line above 0.94, 0.98 and below 0.04, respectively.

Evaluation of monthwise and overall trends of AOD over Indian cities using MODIS Aqua and Terra retrievals

NASA Astrophysics Data System (ADS)

Banerjee, Subhasis; Ghosh, Sanjay

2016-07-01

Atmospheric aerosols have been shown to have profound impact on climate system and human health. Regular and systematic monitoring of ambient air is thus necessary in order to asses its impact. There are several ground based stations worldwide employed in this service but still their numbers are inadequate and it is even almost impossible to have such stations at difficult geographical terrains and take measurement throughout the year. Aerosol optical depth or AOD, which is a measure of extinction of incoming solar radiation, serves as proxy to atmospheric aerosol loading. Various sensors onboard different satellites take routine measurement of AOD throughout the year. Satellite based AOD is used in many studies due to their wide coverage and availability for a longer time period. Satellite measures reflected solar radiation at the top of the atmosphere. Column integrated value of aerosol are routinely estimated from those measurements using suitable inversion algorithms. MODIS instrument onboard Aqua and Terra satellites of Earth Observing System takes routine measurement in wide spectral range. We used those data to evaluate trend of AOD over almost fifty Indian cities having population more than a million. The cities we have chosen spread over almost entire length and breadth of the country. Few such studies have already been conducted using MODIS data. They typically used level 3 data. Since Level 3 data comes in 1x 1 degree gridded form they provide average value over a vast geographical region. We used level 2 dataset to enable us taking smaller region(1/2 x 1/2 degree here) centering the region of our interest . We used seasonal Mann-Kendall (M-K) statistics coupled with Sen's non-parametric slope estimation procedure to estimate monthwise and overall(i.e., yearly trend taking seasonality into account) AOD trend. We used median AOD for each month of every year to discard very high AOD's which we often get due to cloud contamination. Seasonal M-K test takes care of seasonality in AOD values. Moreover we here used AQUA version 6 data set to compare with Terra 5.1. To our knowledge Aqua version 6 data set has yet not been used in any study over this region. In our study quality controlled "joint land and ocean" product (for almost one decade time) "Optical_Depth_Land_And_Ocean" (0.55 micron) has been used to estimate trend and only statistically significant trend (p=0.05 level) is only reported. We observed that thirty out of fifty cities show overall increasing trend in AOD by both the sensors whereas rest of the cities show increasing trend only by Aqua. Decadal increase in AOD value as reported by Terra is 2-10% whereas by Aqua 4-18%. Aqua consistently shows higher trend than Terra in all cases. After comparing data from both the sensors, we observed, for almost all the cities (except some cities lying in the southern part of the country) trend(increasing) is highest during the month of November, even in case of some north Indian cities November is the only month when significant trend is noticed. In case of most southern cities trend(increasing) is highest for the month of May. Strikingly, for most northern cities in the Indo-Gangetic plain Aqua shows significant overall trend whereas Terra shows no overall trend. But for southern cities both the sensors show similar trend. We also used AERONET level 2 data(0.50 micron) from Kanpur station to estimate trend using same method and found overall trend as estimated using Aqua (10 %) data is pretty close to that found using AERONET(9%)data.

Direct Aerosol Radiative Forcing from Combined A-Train Observations - Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-sky Estimates

NASA Astrophysics Data System (ADS)

Redemann, J.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Russell, P. B.; LeBlanc, S. E.; Vaughan, M.; Ferrare, R. A.; Hostetler, C. A.; Rogers, R. R.; Burton, S. P.; Torres, O.; Remer, L. A.; Stier, P.; Schutgens, N.

2014-12-01

We describe a technique for combining CALIOP aerosol backscatter, MODIS spectral AOD (aerosol optical depth), and OMI AAOD (absorption aerosol optical depth) retrievals for the purpose of estimating full spectral sets of aerosol radiative properties, and ultimately for calculating the 3-D distribution of direct aerosol radiative forcing. We present results using one year of data collected in 2007 and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the recently released MODIS Collection 6 data for aerosol optical depths derived with the dark target and deep blue algorithms has extended the coverage of the multi-sensor estimates towards higher latitudes. Initial calculations of seasonal clear-sky aerosol radiative forcing based on our multi-sensor aerosol retrievals compare well with over-ocean and top of the atmosphere IPCC-2007 model-based results, and with more recent assessments in the "Climate Change Science Program Report: Atmospheric Aerosol Properties and Climate Impacts" (2009). For the first time, we present comparisons of our multi-sensor aerosol direct radiative forcing estimates to values derived from a subset of models that participated in the latest AeroCom initiative. We discuss the major challenges that exist in extending our clear-sky results to all-sky conditions. On the basis of comparisons to suborbital measurements, we present some of the limitations of the MODIS and CALIOP retrievals in the presence of adjacent or underlying clouds. Strategies for meeting these challenges are discussed.

Spatial distribution of aerosol hygroscopicity and its effect on PM2.5 retrieval in East China

NASA Astrophysics Data System (ADS)

He, Qianshan; Zhou, Guangqiang; Geng, Fuhai; Gao, Wei; Yu, Wei

2016-03-01

The hygroscopic properties of aerosol particles have strong impact on climate as well as visibility in polluted areas. Understanding of the scattering enhancement due to water uptake is of great importance in linking dry aerosol measurements with relevant ambient measurements, especially for satellite retrievals. In this study, an observation-based algorithm combining meteorological data with the particulate matter (PM) measurement was introduced to estimate spatial distribution of indicators describing the integrated humidity effect in East China and the main factors impacting the hygroscopicity were explored. Investigation of 1 year data indicates that the larger mass extinction efficiency αext values (> 9.0 m2/g) located in middle and northern Jiangsu Province, which might be caused by particulate organic material (POM) and sulfate aerosol from industries and human activities. The high level of POM in Jiangsu Province might also be responsible for the lower growth coefficient γ value in this region. For the inland junction provinces of Jiangsu and Anhui, a considerable higher hygroscopic growth region in East China might be attributed to more hygroscopic particles mainly comprised of inorganic salts (e.g., sulfates and nitrates) from several large-scale industrial districts distributed in this region. Validation shows good agreement of calculated PM2.5 mass concentrations with in situ measurements in most stations with correlative coefficients of over 0.85, even if several defective stations induced by station location or seasonal variation of aerosol properties in this region. This algorithm can be used for more accurate surface level PM2.5 retrieval from satellite-based aerosol optical depth (AOD) with combination of the vertical correction for aerosol profile.

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

2010-01-01

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Understanding of the Regional Aerosol Characterization over the North-eastern part of the Indian Subcontinent: South-Asian Region

NASA Astrophysics Data System (ADS)

Dahutia, P.; Pathak, B.

2016-12-01

The north-eastern region (NER) of India is a part of Indian subcontinent owing a unique topography surrounded by three sides by high mountain and open in the west. The long-term characterization of aerosol and its effect on climate is carried out in 11 locations over NER of India along with two adjoining locations Dhaka (DAC) and Banmauk (BNK) (22-30°N and 88-98°E) using multiple satellite retrievals and model data. Quality assured monthly Level 3 Collection 6 data of MODerate Resolution Imaging Spectroradiometer (MODIS) data retrieved from both Aqua and Terra having 1°×1° resolution of columnar Aerosol Optical Depth (AOD) and its associated parameters for the period of 2001-2014. Investigation revealed a distinct spatio-temporal variation over all the locations with highest climatological mean AOD in Dhaka (0.66±0.19) and lowest in high altitude location Thimphu (0.17±0.1). The parameter Absorbing aerosols Index (AAI) from combine TOMS and OMI instrument is used to study absorbing aerosols during 1979-2014. The seasonal AOD and AAI are highest during pre-monsoon months while lowest in retreating monsoon in all the locations. The continuous wavelet transform (CWT) analysis of non-smoothen time-series of AOD revealed the strong annual oscillation (AO) of total columnar aerosol loading. The annual trend analysis of aerosol parameters shows a statistically significant (i.e., p<0.05) increasing trends of AOD ( 0.009-0.001year-1) as well as AAI ( 0.015-0.001year-1) over all locations. The simultaneous increase in Angtröm Exponent (AE) along with AOD and AAI indicates the enhancement of anthropogenic aerosols which might have a contribution to the climate change. The performed long-term (1979-2014) regression analysis of seasonal and annual mean of Net Surface Downward Shortwave Flux (NSDSF), Cloud Optical Depth (COD), rainfall and temperature shows a signature of climate change over this region. The opposite trend of COD (increasing) and NSDSF (decreasing) signifies the effect of clouds on reduction of surface reaching solar flux over the study locations. The increasing anthropogenic aerosols may have contributed to the decreasing trend of NSDSF directly or indirectly.

Light-absorbing aerosol properties retrieved from the sunphotometer observation over the Yangtze River Delta, China.

PubMed

Wang, Jing; Niu, Shengjie; Xu, Dan

2018-02-10

In this study, aerosol optical depth (AOD) and extinction Ångström exponent (EAE) are derived from ground-based sunphotometer observations between 2007 and 2014 at urban sites of Nanjing over the Yangtze River Delta. In addition, the present study aims to investigate aerosol light-absorbing properties such as single-scattering albedo (SSA), absorption Ångström exponent (AAE), and the aerosol-absorbing optical depth (AAOD). The retrieval of aerosol properties is compared with AERONET inversion products. The results demonstrate that the retrieved AOD has a good agreement with the AERONET Level 1.5 data, with the root mean square error being 0.068, 0.065, and 0.026 for total, fine mode, and coarse mode at 440 nm, respectively. The SSA values indicate similar accuracies in the results, which are about 0.003, -0.009, -0.008, and 0.010 different from AERONET at 440, 670, 870, and 1020 nm, respectively. The occurrence frequency of background level AOD (AOD<0.10) at 440 nm in this region is limited (1%). Monthly mean AOD, SSA, the effective radius (R eff ), and the volume concentration at 440 nm were 0.6-1.3, 0.85-0.92, 0.24-0.40 μm, and 0.18-0.28  μm 3  μm -2 , respectively. The mean value of AAOD at 440 nm (AAOD 440 ) was the highest in both summer (0.095±0.041) and autumn (0.094±0.042), but was the lowest in winter (0.079±0.036). It was also noted that SSA was found to be higher during summer (0.89±0.05). The spectral variation of SSA was observed to be strongly wavelength-dependent during all seasons. The seasonal mean AAE440-870 is the highest in winter (0.86±0.41) and lowest in spring (0.49±0.29). In winter, the cumulative frequency for AAE between 1.0 and 1.2 was about 87%. The peak in the AAE distribution was close to 1.0, indicating that the aerosol column was dominated by urban-industrial aerosols and absorption species other than black carbon. Analysis of the relationship between EAE and SSA showed that the aerosol populations could be classified as "mixed" aerosol, including a mixture of both anthropogenic particles and secondary organic aerosol with highly variable sphericity fraction.

Aerosols optical properties in dynamic atmosphere in the northwestern part of the Indian Himalaya: A comparative study from ground and satellite based observations

NASA Astrophysics Data System (ADS)

Guleria, Raj Paul; Kuniyal, Jagdish Chandra; Rawat, Pan Singh; Thakur, Harinder Kumar; Sharma, Manum; Sharma, Nand Lal; Singh, Mahavir; Chand, Kesar; Sharma, Priyanka; Thakur, Ajay Kumar; Dhyani, Pitamber Prasad; Bhuyan, Pradip Kumar

2011-08-01

The present study deals with the aerosol optical property which carried out during April 2006 to March 2007 over Mohal (31.9°N, 77.12°E) in the northwestern Indian Himalaya. The study was conducted using ground based Multi-wavelength Radiometer (MWR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The daily average aerosol optical depth (AOD) at 500 nm was found to be (mean ± standard deviation) 0.24 ± 0.10. The afternoon AOD values have been noticed to be higher than the forenoon AOD values. Spectral AOD values exhibited larger day-to-day variation in finer aerosols during the observation period. The daily average value of Ångström exponent 'α' and turbidity coefficient 'β' obtained was 1.10 ± 0.38 and 0.12 ± 0.08 respectively. Higher value of AOD ~ 0.39 ± 0.06 during summer associated with low α ~ 0.73 ± 0.28 has attributed to the increase in the relative dominance of coarse size particles. In winter α ~ 1.21 ± 0.32 indicating a considerable increase in fine size particles, attributed to the anthropogenic activities. The AOD spectra seem to be more wavelength dependent in winter as compared to summer. Comparison of MWR observation with MODIS observation indicates a good conformity between ground-based and satellite derived AOD. The root mean square deviation (RMSD), mean absolute bias deviation (MABD) and correlation coefficient have been found to be ~ 0.08, ~ 0.06 and ~ 0.77 respectively. These results suggest that the AOD retrieval through satellite can be able to characterize AOD distribution over Mohal. However, further efforts to eliminate systematic errors in the existing MODIS products are needed. During the observation period ~ 30%, ~ 47% and ~ 62% air parcels drawn at 4000, 5500 and 8000 m above ground level respectively reached at Mohal which passed through or originated from The Great Sahara. The maximum AOD at 500 nm occurred on 8 May 2006. This has caused a significant reduction in surface reaching solar irradiance by ~ 59 Wm -2. The back trajectory analysis suggested that the highest AOD during summer is due to high degree of human interference in the form of tourism and dust transport from the country lying in the northwestern part of India.

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

NASA Astrophysics Data System (ADS)

Liu, Yuqin; de Leeuw, Gerrit; Kerminen, Veli-Matti; Zhang, Jiahua; Zhou, Putian; Nie, Wei; Qi, Ximeng; Hong, Juan; Wang, Yonghong; Ding, Aijun; Guo, Huadong; Krüger, Olaf; Kulmala, Markku; Petäjä, Tuukka

2017-05-01

Aerosol effects on low warm clouds over the Yangtze River Delta (YRD, eastern China) are examined using co-located MODIS, CALIOP and CloudSat observations. By taking the vertical locations of aerosol and cloud layers into account, we use simultaneously observed aerosol and cloud data to investigate relationships between cloud properties and the amount of aerosol particles (using aerosol optical depth, AOD, as a proxy). Also, we investigate the impact of aerosol types on the variation of cloud properties with AOD. Finally, we explore how meteorological conditions affect these relationships using ERA-Interim reanalysis data. This study shows that the relation between cloud properties and AOD depends on the aerosol abundance, with a different behaviour for low and high AOD (i.e. AOD < 0.35 and AOD > 0.35). This applies to cloud droplet effective radius (CDR) and cloud fraction (CF), but not to cloud optical thickness (COT) and cloud top pressure (CTP). COT is found to decrease when AOD increases, which may be due to radiative effects and retrieval artefacts caused by absorbing aerosol. Conversely, CTP tends to increase with elevated AOD, indicating that the aerosol is not always prone to expand the vertical extension. It also shows that the COT-CDR and CWP (cloud liquid water path)-CDR relationships are not unique, but affected by atmospheric aerosol loading. Furthermore, separation of cases with either polluted dust or smoke aerosol shows that aerosol-cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust, which is ascribed to the higher absorption efficiency of smoke than dust. The variation of cloud properties with AOD is analysed for various relative humidity and boundary layer thermodynamic and dynamic conditions, showing that high relative humidity favours larger cloud droplet particles and increases cloud formation, irrespective of vertical or horizontal level. Stable atmospheric conditions enhance cloud cover horizontally. However, unstable atmospheric conditions favour thicker and higher clouds. Dynamically, upward motion of air parcels can also facilitate the formation of thicker and higher clouds. Overall, the present study provides an understanding of the impact of aerosols on cloud properties over the YRD. In addition to the amount of aerosol particles (or AOD), evidence is provided that aerosol types and ambient environmental conditions need to be considered to understand the observed relationships between cloud properties and AOD.

Spatial heterogeneity of aerosol optical and radiative properties obtained from multiple satellite retrievals over the Sub-Himalayan region of North-East India

NASA Astrophysics Data System (ADS)

Pathak, Binita; Bhuyan, Pradip; Biswas, Jhuma; Dahutia, Papori

North East India, nestled between the southeastern Tibetan Plateau on the north, the Indo Myanmar range of hills to the east, plains of Bangladesh to the south and the Indo-Gangetic plains (IGP) to the west has a unique topography and population inhabitation pattern. In recent decades, along with other parts of south Asia NE India has undergone rapid industrial and economic development. Lifestyle changes have increasingly added to the anthropogenic burden on the atmosphere in the plains while biomass burning due to shifting cultivation in the hills is a major source of particulate and gaseous pollution. Studies have suggested that during the Asian summer monsoon, boundary layer pollution from India, Southeast Asia and south China are lifted to the upper tropospheric region by convection followed by westward transport over the Middle East and the Mediterranean. The spatio-temporal variation of aerosol optical (viz. AOD, AAI, AAOD, AE, FMF, columnar mass concentration (CMC)) and radiative properties are studied using data from multiple satellite sensors: MODIS, OMI, TOMS, CERES at various locations within the NE India (22-30°N, 86-98°E) for the period 2000-2012. Significant spatio-temporal variation of aerosol optical and radiative properties is observed within the region. For example, Guwahati, the metropolitan city, shows maximum value of AOD, followed by Dhubri the location situated at the western corridor of north-east India. Minimum AOD is observed at the high altitude locations Thimphu and Tawang. Temporally AOD is overriding in March, April, May (MAM) at almost all the observation locations. The minimum AOD over the region in October-November (ON) is associated with the topography and local meteorology. AAI >0.5 at all the locations indicates presence of significant amount of absorbing aerosols. The peak AAI and AAOD in MAM at all the location is associated with the peak biomass burning activity and long range transportation from other locations of India and western Asia through the IGP. AE and FMF signify abundance of fine particles at high altitudes and coarse aerosols in pre-monsoon and monsoon seasons in the Brahmaputra valley. CMC shows similar spatio-temporal variability as AOD with maximum occurring at Guwahati and minimum at the high altitude locations. The GOCART model simulated data is used to evaluate the contribution of different aerosol types: sulfate, dust, sea-salt and carbonaceous (OC and BC) aerosols to composite AOD. The contribution of sulfate is overriding at all the locations followed by dust in pre-monsoon season and organic carbon in the rest of the seasons at all the locations. There is an increasing trend in anthropogenic component of aerosols over north east India. However, the GOCART model has not been able to simulate the observed magnitude and temporal variation of AOD except at a few high altitude locations. The instantaneous (SWARE) and diurnal average shortwave (SWARE24) Top of Atmosphere (TOA) Aerosol Radiative Effect (ARE) are retrieved from simultaneous CERES shortwave fluxes and AOD retrievals from the MODIS. The instantaneous TOA SWARE varies from -138 Wm-2 in JJAS over TWA to -12.27 Wm-2 in ON over Dibrugarh. The TOA SWARE24 is maximum in MAM at all the study locations in North-East India except at Aizwal, Thimphu and Tawang where it is maximum in JJAS. The minimum TOA SWARE24 occurs in ON months over all the study locations except at Agartala, Thimphu, Tawang where it is minimum in DJF months. The Instantaneous forcing efficiency varies from -395.38 Wm-2τ-1 in ON over Tawang to -11.26 Wm-2 τ-1 in DJF over Agartala.

Maintenance Manual for the Automated Airdrop Information Retrieval System; Human Factors Database

DTIC Science & Technology

1994-09-01

Sensorimotor Abilities Loss of Cognitive/Perceptual Abilities Treatment drug therapy physical therapy cognitive therapy biofeedback therapy 63 9...Device (AOD) Oxygen System oxygen mask oxygen hose oxygen cylinders on/off valve prebreather Floatation Devices life preserver Scuba Gear Ankle Braces

Comparison of Satellite Data with Ground-Based Measurements for Assessing Local Distributions of PM2.5 in Northeast Mexico.

NASA Astrophysics Data System (ADS)

Carmona, J.; Mendoza, A.; Lozano, D.; Gupta, P.; Mejia, G.; Rios, J.; Hernández, I.

2017-12-01

Estimating ground-level PM2.5 from satellite-derived Aerosol Optical Depth (AOD) through statistical models is a promising method to evaluate the spatial and temporal distribution of PM2.5 in regions where there are no or few ground-based observations, i.e. Latin America. Although PM concentrations are most accurately measured using ground-based instrumentation, the spatial coverage is too sparse to determine local and regional variations in PM. AOD satellite data offer the opportunity to overcome the spatial limitation of ground-based measurements. However, estimating PM surface concentrations from AOD satellite data is challenging, since multiple factors can affect the relationship between the total-column of AOD and the surface-concentration of PM. In this study, an Assembled Multiple Linear Regression Model (MLR) and a Neural Network Model (NN) were performed to estimate the relationship between the AOD and ground-concentrations of PM2.5 within the Monterrey Metropolitan Area (MMA). The MMA is located in northeast Mexico and is the third most populated urban area in the country. Episodes of high PM pollution levels are frequent throughout the year at the MMA. Daily averages of meteorological and air quality parameters were determined from data recorded at 5 monitoring sites of the MMA air quality monitoring network. Daily AOD data were retrieved from the MODIS sensor onboard the Aqua satellite. Overall, the best performance of the models was obtained using an AOD at 550 µm from the MYD04_3k product in combination with Temperature, Relative Humidity, Wind Speed and Wind Direction ground-based data. For the MLR performed, a correlation coefficient of R 0.6 and % bias of -6% were obtained. The NN showed a better performance than the MLR, with a correlation coefficient of R 0.75 and % bias -4%. The results obtained confirmed that satellite-derived AOD in combination with meteorological fields may allow to estimate PM2.5 local distributions.

Constructing An Event Based Aerosol Product Under High Aerosol Loading Conditions

NASA Astrophysics Data System (ADS)

Levy, R. C.; Shi, Y.; Mattoo, S.; Remer, L. A.; Zhang, J.

2016-12-01

High aerosol loading events, such as the Indonesia's forest fire in Fall 2015 or the persistent wintertime haze near Beijing, gain tremendous interests due to their large impact on regional visibility and air quality. Understanding the optical properties of these events and further being able to simulate and predict these events are beneficial. However, it is a great challenge to consistently identify and then retrieve aerosol optical depth (AOD) from passive sensors during heavy aerosol events. Some reasons include:1). large differences between optical properties of high-loading aerosols and those under normal conditions, 2) spectral signals of optically thick aerosols can be mistaken with surface depending on aerosol types, and 3) Extremely optically thick aerosol plumes can also be misidentified as clouds due to its high optical thickness. Thus, even under clear-sky conditions, the global distribution of extreme aerosol events is not well captured in datasets such as the MODIS Dark-Target (DT) aerosol product. In this study, with the synthetic use of OMI Aerosol Index, MODIS cloud product, and operational DT product, the heavy smoke events over the seven sea region are identified and retrieved over the dry season. An event based aerosol product that would compensate the standard "global" aerosol retrieval will be created and evaluated. The impact of missing high AOD retrievals on the regional aerosol climatology will be studied using this newly developed research product.

Airborne Sun Photometer Measurements of Aerosol Optical Depth during SOLVE II: Comparison with SAGE III and POAM III Measurements

NASA Technical Reports Server (NTRS)

Russell, P.; Livingston, J.; Schmid, B.; Eilers, J.; Kolyer, R.; Redemann, J.; Yee, J.-H.; Trepte, C.; Thomason, L.; Zawodny, J.

2003-01-01

The 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated aboard the NASA DC-8 during the Second SAGE III Ozone Loss and Validation Experiment (SOLVE II) and obtained successful measurements during the sunlit segments of eight science flights. These included six flights out of Kiruna, Sweden, one flight out of NASA Dryden Flight Research Center (DFRC), and the Kiruna-DFRC return transit flight. Values of spectral aerosol optical depth (AOD), columnar ozone and columnar water vapor have been derived from the AATS-14 measurements. In this paper, we focus on AATS-14 AOD data. In particular, we compare AATS-14 AOD spectra with temporally and spatially near-coincident measurements by the Stratospheric Aerosol and Gas Experiment III (SAGE III) and the Polar Ozone and Aerosol Measurement III (POAM III) satellite sensors. We examine the effect on retrieved AOD of uncertainties in relative optical airmass (the ratio of AOD along the instrument-to-sun slant path to that along the vertical path) at large solar zenith angles. Airmass uncertainties result fiom uncertainties in requisite assumed vertical profiles of aerosol extinction due to inhomogeneity along the viewing path or simply to lack of available data. We also compare AATS-14 slant path solar transmission measurements with coincident measurements acquired from the DC-8 by the NASA Langley Research Center Gas and Aerosol Measurement Sensor (GAMS).

Analysis of spatial-temporal heterogeneity in remotely sensed aerosol properties observed during 2005-2015 over three countries along the Gulf of Guinea Coast in Southern West Africa

NASA Astrophysics Data System (ADS)

Aklesso, Mangamana; Kumar, K. Raghavendra; Bu, Lingbing; Boiyo, Richard

2018-06-01

In the present study, the spatial-temporal distribution and estimation of trends of different aerosol optical properties, and related impact factors were investigated over three countries: Ghana, Togo, and Benin along the Gulf of Guinea Coast in Southern West Africa (SWA). For this purpose, long-term satellite derived aerosol optical properties (aerosol optical depth at 550 nm; AOD550, Ångström exponent at 470-660 nm; AE470-660, and absorption aerosol index; AAI) retrieved from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) during January 2005-December 2015 were utilized. The annual mean spatial distribution of AOD550 was found to be high (>0.55) over the southern coastal area, moderate-to-high (0.35-0.55) over the central, and low (<0.35) over northern parts of the study domain. The seasonal mean variations showed high (low) values of AOD550 and AAI during the Harmattan or dry (wet) season. Whereas, low (high) AE470-660 values were characterized during the Harmattan (wet) season. Linear trend analysis revealed a decreasing trend in AOD550 and AAI, and increasing trend in AE470-660. Further, an investigation on the potential drivers to AOD distribution over the SWA revealed that precipitation, NDVI, and terrain were negatively correlated with AOD. Finally, the HYSPLIT derived back trajectory analyses revealed diverse transport pathways originated from the North Atlantic Ocean, Sahara Desert, and Nigeria along with locally generated aerosols.

Assessing Surface BRDF-related Biases Using Target Mode Retrievals from the Orbiting Carbon Observatory-2 (OCO-2)

NASA Astrophysics Data System (ADS)

Natraj, V.; McDuffie, J. L.; O'Dell, C.; Eldering, A.; Fu, D.; Wunch, D.; Wennberg, P. O.

2015-12-01

The Orbiting Carbon Observatory-2 (OCO-2) is NASA's first dedicated Earth remote sensing satellite to study atmospheric carbon dioxide from space, and was launched successfully on July 2, 2014. In the target mode of observation, the Observatory will lock its view onto a specific surface location, and will scan back and forth over that target while flying overhead. A target track pass can last for up to 9 minutes. Over that time period, the Observatory can acquire as many as 12,960 samples at local zenith angles that vary between 0° and 85°. Here, we analyze target track measurements over several of the OCO-2 validation sites where ground-based solar-looking Fourier Transform Spectrometers are located. Preliminary analysis of target mode retrievals using the operational algorithm show biases that appear to be due to not accounting for bidirectional surface reflection (BRDF) effects, i.e., the non-isotropic nature of surface reflection. To address this issue, we implement a realistic BRDF model. The column averaged CO2 dry air mole fraction (XCO2) results using this new model show much less variation with scattering angle (or airmass). Further, the retrieved aerosol optical depth (AOD) is in much better agreement with coincident AERONET values. We also use information content analysis to evaluate the degrees of freedom with respect to BRDF parameters, and investigate cross-correlations between the parameters.

Use of the NASA GEOS-5 SEAC4RS Meteorological and Aerosol Reanalysis for assessing simulated aerosol optical properties as a function of smoke age

NASA Astrophysics Data System (ADS)

Randles, C. A.; da Silva, A. M., Jr.; Colarco, P. R.; Darmenov, A.; Buchard, V.; Govindaraju, R.; Chen, G.; Hair, J. W.; Russell, P. B.; Shinozuka, Y.; Wagner, N.; Lack, D.

2014-12-01

The NASA Goddard Earth Observing System version 5 (GEOS-5) Earth system model, which includes an online aerosol module, provided chemical and weather forecasts during the SEAC4RS field campaign. For post-mission analysis, we have produced a high resolution (25 km) meteorological and aerosol reanalysis for the entire campaign period. In addition to the full meteorological observing system used for routine NWP, we assimilate 550 nm aerosol optical depth (AOD) derived from MODIS (both Aqua and Terra satellites), ground-based AERONET sun photometers, and the MISR instrument (over bright surfaces only). Daily biomass burning emissions of CO, CO2, SO2, and aerosols are derived from MODIS fire radiative power retrievals. We have also introduced novel smoke "age" tracers, which provide, for a given time, a snapshot histogram of the age of simulated smoke aerosol. Because GEOS-5 assimilates remotely sensed AOD data, it generally reproduces observed (column) AOD compared to, for example, the airborne 4-STAR instrument. Constraining AOD, however, does not imply a good representation of either the vertical profile or the aerosol microphysical properties (e.g., composition, absorption). We do find a reasonable vertical structure for aerosols is attained in the model, provided actual smoke injection heights are not much above the planetary boundary layer, as verified with observations from DIAL/HRSL aboard the DC8. The translation of the simulated aerosol microphysical properties to total column AOD, needed in the aerosol assimilation step, is based on prescribed mass extinction efficiencies that depend on wavelength, composition, and relative humidity. Here we also evaluate the performance of the simulated aerosol speciation by examining in situ retrievals of aerosol absorption/single scattering albedo and scattering growth factor (f(RH)) from the LARGE and AOP suite of instruments. Putting these comparisons in the context of smoke age as diagnosed by the model helps us to revise assumed aerosol optical properties for an improved representation of aerosol radiative forcing.

Satellite constraints on surface concentrations of particulate matter

NASA Astrophysics Data System (ADS)

Ford Hotmann, Bonne

Because of the increasing evidence of the widespread adverse effects on human health from exposure to poor air quality and the recommendations of the World Health Organization to significantly reduce PM2.5 in order to reduce these risks, better estimates of surface air quality globally are required. However, surface measurements useful for monitoring particulate exposure are scarce, especially in developing countries which often experience the worst air pollution. Therefore, other methods are necessary to augment estimates in regions with limited surface observations. The prospect of using satellite observations to infer surface air quality is attractive; however, it requires knowledge of the complicated relationship between satellite-observed aerosol optical depth (AOD) and surface concentrations. This dissertation explores how satellite observations can be used in conjunction with a chemical transport model (GEOS-Chem) to better understand this relationship. First, we investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (factor 2-3 enhancement over wintertime AOD) is not present in surface mass concentrations (25-55% summertime enhancement). Goldstein et al. [2009] previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ~35% of PM2.5 mass and exhibits similar seasonality to total surface PM2.5. The GEOS-Chem model generally reproduces these surface aerosol measurements, but under represents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing; we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer. Next, we examine the usefulness of deriving premature mortality estimates from "satellite-based" PM2.5 concentrations. In particular, we examine how uncertainties in the model AOD-to-surface-PM2.5 relationship, satellite retrieved AOD, and particulars of the concentration-response function can impact these mortality estimates. We find that the satellite-based estimates suggest premature mortality due to chronic PM2.5 exposure is 2-16% higher in the U.S. and 4-13% lower in China compared to model-based estimates. However, this difference is overshadowed by the uncertainty in the methodology, which we quantify to be on order of 20% for the model-to- surface-PM2.5 relationship, 10% for the satellite AOD and 30-60% or greater with regards to the application of concentration response functions. Because there is a desire for acute exposure estimates, especially with regards to extreme events, we also examine how premature mortality due to acute exposure can be estimated from global models and satellite-observations. We find similar differences between model and satellite-based mortality estimates as with chronic exposure. However the range of uncertainty is much larger on these shorter timescales. This work suggests that although satellites can be useful for constraining model estimates of PM2.5, national mortality estimates from the two methods are not significantly different. In order to improve the efficacy of satellite-based PM2.5 mortality estimates, future work will need to focus on improving the model representation of the regional AOD-to-surface-PM2.5 relationship, reducing biases in satellite-retrieved AOD and advancing our understanding of personal and population-level responses to PM2.5 exposure.

Concept of a Fast and Simple Atmospheric Radiative Transfer Model for Aerosol Retrieval

NASA Astrophysics Data System (ADS)

Seidel, Felix; Kokhanovsky, Alexander A.

2010-05-01

Radiative transfer modelling (RTM) is an indispensable tool for a number of applications, including astrophysics, climate studies and quantitative remote sensing. It simulates the attenuation of light through a translucent medium. Here, we look at the scattering and absorption of solar light on its way to the Earth's surface and back to space or back into a remote sensing instrument. RTM is regularly used in the framework of the so-called atmospheric correction to find properties of the surface. Further, RTM can be inverted to retrieve features of the atmosphere, such as the aerosol optical depth (AOD), for instance. Present-day RTM, such as 6S, MODTRAN, SHARM, RT3, SCIATRAN or RTMOM have errors of only a few percent, however they are rather slow and often not easy to use. We present here a concept for a fast and simple RTM model in the visible spectral range. It is using a blend of different existing RTM approaches with a special emphasis on fast approximative analytical equations and parametrizations. This concept may be helpful for efficient retrieval algorithms, which do not have to rely on the classic look-up-tables (LUT) approach. For example, it can be used to retrieve AOD without complex inversion procedures including multiple iterations. Naturally, there is always a trade-off between speed and modelling accuracy. The code can be run therefore in two different modes. The regular mode provides a reasonable ratio between speed and accuracy, while the optional mode is very fast but less accurate. The normal mode approximates the diffuse scattered light by calculating the first (single scattering) and second order of scattering according to the classical method of successive orders of scattering. The very fast mode calculates only the single scattering approximation, which does not need any slow numerical integration procedure, and uses a simple correction factor to account for multiple scattering. This factor is a parametrization of MODTRAN results, which provide a typical ratio between single and multiple scattered light. A comparison of the presented RTM concept to the widely accepted 6S RTM reveals errors of up to 10% in standard mode. This is acceptable for certain applications. The very fast mode may lead to errors of up to 30%, but it is still able to reproduce qualitatively the results of 6S. An experimental implementation of this RTM concept is written in the common IDL language. It is therefore very flexible and straightforward to be implemented into custom retrieval algorithms of the remote sensing community. The code might also be used to add an atmosphere on top of an existing vegetation-canopy or water RTM. Due to the ease of use of the RTM code and the comprehensibility of the internal equations, the concept might be useful for educational purposes as well. The very fast mode could be of interest for a real-time applications, such as an in-flight instrument performance check for airborne optical sensors. In the future, the concept can be extended to account for scattering according to Mie theory, polarization and gaseous absorption. It is expected that this would reduce the model error to 5% or less.

The effect of cloud screening on MAX-DOAS aerosol retrievals.

NASA Astrophysics Data System (ADS)

Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim

2014-05-01

In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.

Validation of the National Solar Radiation Database (NSRDB) (2005-2012): Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Manajit; Weekley, Andrew; Habte, Aron

Publicly accessible, high-quality, long-term, satellite-based solar resource data is foundational and critical to solar technologies to quantify system output predictions and deploy solar energy technologies in grid-tied systems. Solar radiation models have been in development for more than three decades. For many years, the National Renewable Energy Laboratory (NREL) developed and/or updated such models through the National Solar Radiation Data Base (NSRDB). There are two widely used approaches to derive solar resource data from models: (a) an empirical approach that relates ground-based observations to satellite measurements and (b) a physics-based approach that considers the radiation received at the satellite andmore » creates retrievals to estimate clouds and surface radiation. Although empirical methods have been traditionally used for computing surface radiation, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal irradiance (GHI) using the visible and infrared channel measurements from the Geostationary Operational Environmental Satellites (GOES) system. GSIP uses a two-stage scheme that first retrieves cloud properties and then uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. NREL, the University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high temporal and spatial resolution data set. The product initially generates the cloud properties using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms [3], whereas the GHI is calculated using SASRAB. Then NREL implements accurate and high-resolution input parameters such as aerosol optical depth (AOD) and precipitable water vapor (PWV) to compute direct normal irradiance (DNI) using the DISC model. The AOD and PWV, temperature, and pressure data are also combined with the MMAC model to simulate solar radiation under clear-sky conditions. The current NSRDB update is based on a 4-km x 4-km resolution at a 30-minute time interval, which has a higher temporal and spatial resolution. This paper demonstrates the evaluation of the data set using ground-measured data and detailed evaluation statistics. The result of the comparison shows a good correlation to the NSRDB data set. Further, an outline of the new version of the NSRDB and future plans for enhancement and improvement are provided.« less

Probing into the aging dynamics of biomass burning aerosol by using satellite measurements of aerosol optical depth and carbon monoxide

NASA Astrophysics Data System (ADS)

Konovalov, Igor B.; Beekmann, Matthias; Berezin, Evgeny V.; Formenti, Paola; Andreae, Meinrat O.

2017-04-01

Carbonaceous aerosol released into the atmosphere from open biomass burning (BB) is known to undergo considerable chemical and physical transformations (aging). However, there is substantial controversy about the nature and observable effects of these transformations. A shortage of consistent observational evidence on BB aerosol aging processes under different environmental conditions and at various temporal scales hinders development of their adequate representations in chemistry transport models (CTMs). In this study, we obtain insights into the BB aerosol dynamics by using available satellite measurements of aerosol optical depth (AOD) and carbon monoxide (CO). The basic concept of our method is to consider AOD as a function of the BB aerosol photochemical age (that is, the time period characterizing the exposure of BB aerosol emissions to atmospheric oxidation reactions) predicted by means of model tracers. We evaluate the AOD enhancement ratio (ER) defined as the ratio of optical depth of actual BB aerosol with respect to that of a modeled aerosol tracer that is assumed to originate from the same fires as the real BB aerosol but that is not affected by any aging processes. To limit possible effects of model transport errors, the AOD measurements are normalized to CO column amounts that are also retrieved from satellite measurements. The method is applied to the analysis of the meso- and synoptic-scale evolution of aerosol in smoke plumes from major wildfires that occurred in Siberia in summer 2012. AOD and CO retrievals from MODIS and IASI measurements, respectively, are used in combination with simulations performed with the CHIMERE CTM. The analysis indicates that aging processes strongly affected the evolution of BB aerosol in the situation considered, especially in dense plumes (with spatial average PM2. 5 concentration exceeding 100 µg m-3). For such plumes, the ER is found to increase almost 2-fold on the scale of ˜ 10 h of daytime aerosol evolution (after a few first hours of the evolution that are not resolved in our analysis). The robustness of this finding is corroborated by sensitivity tests and Monte Carlo experiments. Furthermore, a simulation using the volatility basis set framework suggests that a large part of the increase in the ER can be explained by atmospheric processing of semi-volatile organic compounds. Our results are consistent with findings of a number of earlier studies reporting considerable underestimation of AOD by CTMs in which BB aerosol aging processes have either been disregarded or simulated in a highly simplified way. In general, this study demonstrates the feasibility of using satellite measurements of AOD in biomass burning plumes in combination with aerosol tracer simulations for the investigation of BB aerosol evolution and validation of BB aerosol aging schemes in atmospheric models.

Land Surface Reflectance Retrieval from Hyperspectral Data Collected by an Unmanned Aerial Vehicle over the Baotou Test Site

PubMed Central

Duan, Si-Bo; Li, Zhao-Liang; Tang, Bo-Hui; Wu, Hua; Ma, Lingling; Zhao, Enyu; Li, Chuanrong

2013-01-01

To evaluate the in-flight performance of a new hyperspectral sensor onboard an unmanned aerial vehicle (UAV-HYPER), a comprehensive field campaign was conducted over the Baotou test site in China on 3 September 2011. Several portable reference reflectance targets were deployed across the test site. The radiometric performance of the UAV-HYPER sensor was assessed in terms of signal-to-noise ratio (SNR) and the calibration accuracy. The SNR of the different bands of the UAV-HYPER sensor was estimated to be between approximately 5 and 120 over the homogeneous targets, and the linear response of the apparent reflectance ranged from approximately 0.05 to 0.45. The uniform and non-uniform Lambertian land surface reflectance was retrieved and validated using in situ measurements, with root mean square error (RMSE) of approximately 0.01–0.07 and relative RMSE of approximately 5%–12%. There were small discrepancies between the retrieved uniform and non-uniform Lambertian land surface reflectance over the homogeneous targets and under low aerosol optical depth (AOD) conditions (AOD = 0.18). However, these discrepancies must be taken into account when adjacent pixels had large land surface reflectance contrast and under high AOD conditions (e.g. AOD = 1.0). PMID:23785513

Big Data Tools as Applied to ATLAS Event Data

NASA Astrophysics Data System (ADS)

Vukotic, I.; Gardner, R. W.; Bryant, L. A.

2017-10-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Logfiles, database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and associated analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data. Such modes would simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning environments and tools like Spark, Jupyter, R, SciPy, Caffe, TensorFlow, etc. Machine learning challenges such as the Higgs Boson Machine Learning Challenge, the Tracking challenge, Event viewers (VP1, ATLANTIS, ATLASrift), and still to be developed educational and outreach tools would be able to access the data through a simple REST API. In this preliminary investigation we focus on derived xAOD data sets. These are much smaller than the primary xAODs having containers, variables, and events of interest to a particular analysis. Being encouraged with the performance of Elasticsearch for the ADC analytics platform, we developed an algorithm for indexing derived xAOD event data. We have made an appropriate document mapping and have imported a full set of standard model W/Z datasets. We compare the disk space efficiency of this approach to that of standard ROOT files, the performance in simple cut flow type of data analysis, and will present preliminary results on its scaling characteristics with different numbers of clients, query complexity, and size of the data retrieved.

Maritime Aerosol Network as a Component of AERONET - a Useful Tool for Evaluation of the Global Sea-Salt Aerosol Distribution

NASA Astrophysics Data System (ADS)

Smirnov, A.; Holben, B. N.; Kinne, S.; Nelson, N. B.; Stenchikov, G. L.; Broccardo, S. P.; Sowers, D.; Lobecker, E.; Ondrusek, M.; Zielinski, T. P.; Gray, L. M.; Frouin, R.; Radionov, V. F.; Smyth, T. J.; Zibordi, G.; Heller, M. I.; Slabakova, V.; Krüger, K.; Reid, E. A.; Istomina, L.; Vandermeulen, R. A.; O'Neill, N. T.; Levy, G.; Giles, D. M.; Slutsker, I.; Sorokin, M. G.; Eck, T. F.

2016-02-01

Sea-salt aerosol plays an important role in radiation balance and chemistry of marine atmosphere. Sea-salt production depends on various factors. There is a significant uncertainty in the parametrization of the sea-salt production and budget. Ship-based aerosol optical depth (AOD) measurements can be used as an important validation tool for various global models and in-situ measurements. The paper presents the current status of the Maritime Aerosol Network (MAN) which is a component of Aerosol Robotic Network. Since 2006 over 300 cruises were completed and data archive of more than 5500 measurement days is accessible at http://aeronet.gsfc.nasa.gov/new_web/maritime_aerosol_network.html . AOD measurements from ships of opportunity complemented island-based AERONET measurements and provided important reference points for satellite retrieved and modelled AOD climatology over the oceans. The program exemplifies mutually beneficial international, multi-agency effort in atmospheric aerosol optical studies over the oceans.

Daytime variations of absorbing aerosols above clouds in the southeast Atlantic

NASA Astrophysics Data System (ADS)

Chang, Y. Y.; Christopher, S. A.

2016-12-01

The daytime variation of aerosol optical depth (AOD) above maritime stratocumulus clouds in the southeast Atlantic is investigated by merging geostationary data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) with NASA A-Train data sets. SEVIRI's 15-minute above cloud AOD and below aerosol cloud optical depth (COD) retrieval provides the opportunity to assess their direct radiative forcing using actual cloud and aerosol properties instead of using fixed values from polar-orbiting measurements. The impact of overlying aerosols above clouds on the cloud mask products are compared with active spaceborne lidar to examine the performance of the product. Uncertainty analyses of aerosol properties on the estimation of optical properties and radiative forcing are addressed.

Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling

PubMed Central

Chang, Howard H.; Hu, Xuefei; Liu, Yang

2014-01-01

There has been a growing interest in the use of satellite-retrieved aerosol optical depth (AOD) to estimate ambient concentrations of PM2.5 (particulate matter <2.5 μm in aerodynamic diameter). With their broad spatial coverage, satellite data can increase the spatial–temporal availability of air quality data beyond ground monitoring measurements and potentially improve exposure assessment for population-based health studies. This paper describes a statistical downscaling approach that brings together (1) recent advances in PM2.5 land use regression models utilizing AOD and (2) statistical data fusion techniques for combining air quality data sets that have different spatial resolutions. Statistical downscaling assumes the associations between AOD and PM2.5 concentrations to be spatially and temporally dependent and offers two key advantages. First, it enables us to use gridded AOD data to predict PM2.5 concentrations at spatial point locations. Second, the unified hierarchical framework provides straightforward uncertainty quantification in the predicted PM2.5 concentrations. The proposed methodology is applied to a data set of daily AOD values in southeastern United States during the period 2003–2005. Via cross-validation experiments, our model had an out-of-sample prediction R2 of 0.78 and a root mean-squared error (RMSE) of 3.61 μg/m3 between observed and predicted daily PM2.5 concentrations. This corresponds to a 10% decrease in RMSE compared with the same land use regression model without AOD as a predictor. Prediction performances of spatial–temporal interpolations to locations and on days without monitoring PM2.5 measurements were also examined. PMID:24368510

Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling.

PubMed

Chang, Howard H; Hu, Xuefei; Liu, Yang

2014-07-01

There has been a growing interest in the use of satellite-retrieved aerosol optical depth (AOD) to estimate ambient concentrations of PM2.5 (particulate matter <2.5 μm in aerodynamic diameter). With their broad spatial coverage, satellite data can increase the spatial-temporal availability of air quality data beyond ground monitoring measurements and potentially improve exposure assessment for population-based health studies. This paper describes a statistical downscaling approach that brings together (1) recent advances in PM2.5 land use regression models utilizing AOD and (2) statistical data fusion techniques for combining air quality data sets that have different spatial resolutions. Statistical downscaling assumes the associations between AOD and PM2.5 concentrations to be spatially and temporally dependent and offers two key advantages. First, it enables us to use gridded AOD data to predict PM2.5 concentrations at spatial point locations. Second, the unified hierarchical framework provides straightforward uncertainty quantification in the predicted PM2.5 concentrations. The proposed methodology is applied to a data set of daily AOD values in southeastern United States during the period 2003-2005. Via cross-validation experiments, our model had an out-of-sample prediction R(2) of 0.78 and a root mean-squared error (RMSE) of 3.61 μg/m(3) between observed and predicted daily PM2.5 concentrations. This corresponds to a 10% decrease in RMSE compared with the same land use regression model without AOD as a predictor. Prediction performances of spatial-temporal interpolations to locations and on days without monitoring PM2.5 measurements were also examined.

Evaluation of 3-D Air Quality System Remotely-Sensed Aerosol Optical Depth for the Baltimore/Washington Metropolitan Air Shed

NASA Astrophysics Data System (ADS)

Weber, S. A.; Engel-Cox, J. A.; Hoff, R. M.; Prados, A.; Zhang, H.

2008-12-01

Integrating satellite- and ground-based aerosol optical depth (AOD) observations with surface total fine particulate (PM2.5) and sulfate concentrations allows for a more comprehensive understanding of local- and urban-scale air quality. This study evaluates the utility of integrated databases being developed for NOAA and EPA through the 3D-AQS project by examining the relationship between remotely-sensed AOD and PM2.5 concentrations for each platform for the summer of 2004 and the entire year of 2005. We compare results for the Baltimore, MD/Washington, DC metropolitan air shed, incorporating AOD products from the Terra and GOES-12 satellites, AERONET sunphotometer, and ground-based lidar, and PM2.5 concentrations from five surface monitoring sites. The satellite-derived products include AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR), as well as the GOES Aerosol/Smoke Product (GASP). The vertical profile of lidar backscatter is used to retrieve the planetary boundary layer (PBL) height in an attempt to capture only that fraction of the AOD arising from near surface aerosols. Adjusting the AOD data using platform- and season-specific ratios, calculated using the parameters of the regression equations, for two case studies resulted in a more accurate representation of surface PM2.5 concentrations when compared to a constant ratio that is currently being used in the NOAA IDEA product. This work demonstrates that quantitative relationships between remotely-sensed and in-situ aerosol observations in an integrated database can be computed and applied to improve the use of remotely-sensed observations for estimating surface concentrations.

Estimating ground-level PM2.5 in eastern China using aerosol optical depth determined from the GOCI satellite instrument

NASA Astrophysics Data System (ADS)

Xu, J.-W.; Martin, R. V.; van Donkelaar, A.; Kim, J.; Choi, M.; Zhang, Q.; Geng, G.; Liu, Y.; Ma, Z.; Huang, L.; Wang, Y.; Chen, H.; Che, H.; Lin, P.; Lin, N.

2015-11-01

We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of -1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5 / AOD ratio exhibits high consistency with ground-based measurements in Taiwan (MFB = -0.52 %) and Beijing (MFB = -8.0 %). We evaluate the satellite-derived PM2.5 versus the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in situ observations in both annual averages (r2 = 0.66, N = 494) and monthly averages (relative RMSE = 18.3 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical composition of GOCI-derived PM2.5 reveals that secondary inorganics (SO42-, NO3-, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating increase the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg m-3, with 400 million residents in regions that exceed the Interim Target-1 of the World Health Organization.

An Emerging Global Aerosol Climatology from the MODIS Satellite Sensors

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kleidman, Richard G.; Levy, Robert C.; Kaufman, Yoram J.; Tanre, Didier; Mattoo, Shana; Martins, J. Vandelei; Ichoku, Charles; Koren, Ilan; Hongbin, Yu;

Citizen-Enabled Aerosol Measurements for Satellites (CEAMS): A Network for High-Resolution Measurements of PM2.5 and Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Pierce, J. R.; Volckens, J.; Ford, B.; Jathar, S.; Long, M.; Quinn, C.; Van Zyl, L.; Wendt, E.

2017-12-01

Atmospheric particulate matter with diameter smaller than 2.5 μm (PM2.5) is a pollutant that contributes to the development of human disease. Satellite-derived estimates of surface-level PM2.5 concentrations have the potential to contribute greatly to our understanding of how particulate matter affects health globally. However, these satellite-derived PM2.5 estimates are often uncertain due to a lack of information about the ratio of surface PM2.5 to aerosol optical depth (AOD), which is the primary aerosol retrieval made by satellite instruments. While modelling and statistical analyses have improved estimates of PM2.5:AOD, large uncertainties remain in situations of high PM2.5 exposure (such as urban areas and in wildfire-smoke plumes) where the health impacts of PM2.5 may be the greatest. Surface monitoring networks for co-incident PM2.5 and AOD measurements are extremely rare, even in the North America. To provide constraints for the PM2.5:AOD relationship, we have developed a relatively low-cost (<$1000) monitor for citizen use that provides sun-photometer AOD measurements and filter-based PM2.5 measurements. The instrument is solar-powered, lightweight (< 1kg), and operated wirelessly via smartphone application (iOS and Android). Sun photometry is performed across 4 discrete wavelengths that match those reported by the Aerosol Robotic Network (AERONET). Aerosol concentration is reported using both time-integrated filter mass (analyzed in an academic laboratory and reported as a 24-48hr average) and a continuous PM sensor within the instrument. Citizen scientists use the device to report daily AOD and PM2.5 measurements made in their backyards to a central server for data display and download. In this presentation, we provide an overview of (1) AOD and PM2.5 measurement calibration; (2) citizen recruiting and training efforts; and (3) results from our pilot citizen-science measurement campaign.

Ship-borne measurements of aerosol optical depth over remote oceans and its dependence on wind speed

NASA Astrophysics Data System (ADS)

Smirnov, A.; Sayer, A. M.; Holben, B. N.; Hsu, N. C.; Sakerin, S. M.; Macke, A.; Nelson, N. B.; Courcoux, Y.; Smyth, T. J.; Croot, P. L.; Quinn, P.; Sciare, J.; Gulev, S. K.; Piketh, S.; Losno, R.; Kinne, S. A.; Radionov, V. F.

2011-12-01

Aerosol production sources over the World Ocean and various factors determining aerosol spatial and temporal distribution are important for understanding the Earth's radiation budget and aerosol-cloud interactions. Sea-salt aerosol production, being a major source of aerosol over remote oceans, depends on surface wind speed. Recently in a number of publications the effect of wind speed on aerosol optical depth (AOD) has been presented utilizing coastal, island-based and satellite-based AOD measurements. However, the influence of wind speed on the columnar optical depth is still poorly understood, because not all factors and precursors influencing AOD dependence can be accounted for. The Maritime Aerosol Network (a component of AERONET) data archive provides an excellent opportunity to analyze in depth a relationship between ship-based AOD measurements and wind speed. We considered only data presumably not influenced by urban/industrial continental sources, dust outbreaks, biomass burning, or glaciers and pack ice. Additional restrictions imposed on the data set were acceptance of only points taken not closer than two degrees from the nearest landmass. We present analyses on the effect of surface (deck-level) wind speed (acquired onboard, modeled by NCEP, measured from satellite) on AOD and its spectral dependence. Latitudinal comparison of measured onboard and modeled wind speeds showed relatively small bias, which was higher at high latitudes. Instantaneous AOD measurements and daily means yielded similar relationships with various wind speed subsets (instantaneous ship-based and NCEP, averaged over previous 24 hours, steady, satellite retrieved). We compared regression statistics of optical parameters versus wind speed presented in various papers and based on various satellite and sunphotometer measurements. Overall, despite certain scatter, the current work and a majority of publications showed consistent patterns, with the AOD versus wind speed (range 2-16 m/s) dependence close to linear.

Particulate matter pollution in the coal-producing regions of the Appalachian Mountains: Integrated ground-based measurements and satellite analysis.

PubMed

Aneja, Viney P; Pillai, Priya R; Isherwood, Aaron; Morgan, Peter; Aneja, Saurabh P

2017-04-01

This study integrates the relationship between measured surface concentrations of particulate matter 10 μm or less in diameter (PM 10 ), satellite-derived aerosol optical depth (AOD), and meteorology in Roda, Virginia, during 2008. A multiple regression model was developed to predict the concentrations of particles 2.5 μm or less in diameter (PM 2.5 ) at an additional location in the Appalachia region, Bristol, TN. The model was developed by combining AOD retrievals from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on board the EOS Terra and Aqua Satellites with the surface meteorological observations. The multiple regression model predicted PM 2.5 (r 2 = 0.62), and the two-variable (AOD-PM 2.5 ) model predicted PM 2.5 (r 2 = 0.4). The developed model was validated using particulate matter recordings and meteorology observations from another location in the Appalachia region, Hazard, Kentucky. The model was extrapolated to the Roda, VA, sampling site to predict PM 2.5 mass concentrations. We used 10 km x 10 km resolution MODIS 550 nm AOD to predict ground level PM 2.5 . For the relevant period in 2008, in Roda, VA, the predicted PM 2.5 mass concentration is 9.11 ± 5.16 μg m -3 (mean ± 1SD). This is the first study that couples ground-based Particulate Matter measurements with satellite retrievals to predict surface air pollution at Roda, Virginia. Roda is representative of the Appalachian communities that are commonly located in narrow valleys, or "hollows," where homes are placed directly along the roads in a region of active mountaintop mining operations. Our study suggests that proximity to heavy coal truck traffic subjects these communities to chronic exposure to coal dust and leads us to conclude that there is an urgent need for new regulations to address the primary sources of this particulate matter.

Inter-comparison of model-simulated and satellite-retrieved componential aerosol optical depths in China

NASA Astrophysics Data System (ADS)

Li, Shenshen; Yu, Chao; Chen, Liangfu; Tao, Jinhua; Letu, Husi; Ge, Wei; Si, Yidan; Liu, Yang

2016-09-01

China's large aerosol emissions have major impacts on global climate change as well as regional air pollution and its associated disease burdens. A detailed understanding of the spatiotemporal patterns of aerosol components is necessary for the calculation of aerosol radiative forcing and the development of effective emission control policy. Model-simulated and satellite-retrieved aerosol components can support climate change research, PM2.5 source appointment and epidemiological studies. This study evaluated the total and componential aerosol optical depth (AOD) from the GEOS-Chem model (GC) and the Global Ozone Chemistry Aerosol Radiation and Transport model (GOCART), and the Multiangle Imaging Spectroradiometer (MISR) from 2006 to 2009 in China. Linear regression analysis between the GC and AErosol RObotic NETwork (AERONET) in China yielded similar correlation coefficients (0.6 daily, 0.71 monthly) but lower slopes (0.41 daily, 0.58 monthly) compared with those in the U.S. This difference was attributed to GC's underestimation of water-soluble AOD (WAOD) west of the Heihe-Tengchong Line, the dust AOD (DAOD) in the fall and winter, and the soot AOD (SAOD) throughout the year and throughout the country. GOCART exhibits the strongest dust estimation capability among all datasets. However, the GOCART soot distribution in the Northeast and Southeast has significant errors, and its WAOD in the polluted North China Plain (NCP) and the South is underestimated. MISR significantly overestimates the water-soluble aerosol levels in the West, and does not capture the high dust loadings in all seasons and regions, and the SAOD in the NCP. These discrepancies can mainly be attributed to the uncertainties in the emission inventories of both models, the poor performance of GC under China's high aerosol loading conditions, the omission of certain aerosol tracers in GOCART, and the tendency of MISR to misidentify dust and non-dust mixtures.

Effects of Ocean Ecosystem on Marine Aerosol-Cloud Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meskhidze, Nicholas; Nenes, Athanasios

Using smore » atellite data for the surface ocean, aerosol optical depth (AOD), and cloud microphysical parameters, we show that statistically significant positive correlations exist between ocean ecosystem productivity, the abundance of submicron aerosols, and cloud microphysical properties over different parts of the remote oceans. The correlation coefficient for remotely sensed surface chlorophyll a concentration ([Chl- a ]) and liquid cloud effective radii over productive areas of the oceans varies between − 0.2 and − 0.6 . Special attention is given to identifying (and addressing) problems from correlation analysis used in the previous studies that can lead to erroneous conclusions. A new approach (using the difference between retrieved AOD and predicted sea salt aerosol optical depth, AOD diff ) is developed to explore causal links between ocean physical and biological systems and the abundance of cloud condensation nuclei (CCN) in the remote marine atmosphere. We have found that over multiple time periods, 550 nm AOD diff (sensitive to accumulation mode aerosol, which is the prime contributor to CCN) correlates well with [Chl- a ] over the productive waters of the Southern Ocean. Since [Chl- a ] can be used as a proxy of ocean biological productivity, our analysis demonstrates the role of ocean ecology in contributing CCN, thus shaping the microphysical properties of low-level marine clouds.« less

Impact of absorbing aerosol deposition on snow albedo reduction over the southern Tibetan plateau based on satellite observations

NASA Astrophysics Data System (ADS)

Lee, Wei-Liang; Liou, K. N.; He, Cenlin; Liang, Hsin-Chien; Wang, Tai-Chi; Li, Qinbin; Liu, Zhenxin; Yue, Qing

2017-08-01

We investigate the snow albedo variation in spring over the southern Tibetan Plateau induced by the deposition of light-absorbing aerosols using remote sensing data from moderate resolution imaging spectroradiometer (MODIS) aboard Terra satellite during 2001-2012. We have selected pixels with 100 % snow cover for the entire period in March and April to avoid albedo contamination by other types of land surfaces. A model simulation using GEOS-Chem shows that aerosol optical depth (AOD) is a good indicator for black carbon and dust deposition on snow over the southern Tibetan Plateau. The monthly means of satellite-retrieved land surface temperature (LST) and AOD over 100 % snow-covered pixels during the 12 years are used in multiple linear regression analysis to derive the empirical relationship between snow albedo and these variables. Along with the LST effect, AOD is shown to be an important factor contributing to snow albedo reduction. We illustrate through statistical analysis that a 1-K increase in LST and a 0.1 increase in AOD indicate decreases in snow albedo by 0.75 and 2.1 % in the southern Tibetan Plateau, corresponding to local shortwave radiative forcing of 1.5 and 4.2 W m-2, respectively.

Effects of Ocean Ecosystem on Marine Aerosol-Cloud Interaction

DOE PAGES

Meskhidze, Nicholas; Nenes, Athanasios

2010-01-01

Using smore » atellite data for the surface ocean, aerosol optical depth (AOD), and cloud microphysical parameters, we show that statistically significant positive correlations exist between ocean ecosystem productivity, the abundance of submicron aerosols, and cloud microphysical properties over different parts of the remote oceans. The correlation coefficient for remotely sensed surface chlorophyll a concentration ([Chl- a ]) and liquid cloud effective radii over productive areas of the oceans varies between − 0.2 and − 0.6 . Special attention is given to identifying (and addressing) problems from correlation analysis used in the previous studies that can lead to erroneous conclusions. A new approach (using the difference between retrieved AOD and predicted sea salt aerosol optical depth, AOD diff ) is developed to explore causal links between ocean physical and biological systems and the abundance of cloud condensation nuclei (CCN) in the remote marine atmosphere. We have found that over multiple time periods, 550 nm AOD diff (sensitive to accumulation mode aerosol, which is the prime contributor to CCN) correlates well with [Chl- a ] over the productive waters of the Southern Ocean. Since [Chl- a ] can be used as a proxy of ocean biological productivity, our analysis demonstrates the role of ocean ecology in contributing CCN, thus shaping the microphysical properties of low-level marine clouds.« less

An uncertainty analysis for satellite-based estimates of cloud condensation nuclei number concentrations

NASA Astrophysics Data System (ADS)

Shinozuka, Y.; Clarke, A. D.; Nenes, A.; Jefferson, A.; Wood, R.; McNaughton, C. S.; Ström, J.; Tunved, P.; Redemann, J.; Thornhill, K. L., II; Moore, R.; Lathem, T. L.; Lin, J.; Yoon, Y. J.

2017-12-01

Aerosol-cloud interactions (ACI) are the largest source of uncertainty in estimates of anthropogenic radiative forcing responsible for the on-going climate change. ACI for warm clouds depend on the number concentration of cloud condensation nuclei (CCN), not on aerosol optical properties. Yet, aerosol optical depth (AOD) and its variants weighted by the spectral dependence over visible and near infrared wavelengths are commonly substituted for CCN in ACI studies. The substitution is motivated by the wide availability in space and time of satellite retrievals, an advantage over the sparse CCN measurements. If satellite-based CCN estimates are to continue to complement purely model-based ones, what CCN-AOD relationship should we assume and how large is the associated uncertainty? Our 2015 paper examines airborne and ground-based observations of aerosols to address these questions, focusing on the relationship between CCN and light extinction, σ, of dried particles averaged over one-kilometer horizontal distance. That paper discusses the way the CCN-AOD relationship is influenced not only by the CCN-σ relationship but also by the humidity response of light extinction, the vertical profile, the horizontal-temporal variability and the AOD measurement error. In this presentation, we apply these findings to passive satellite data to analyze the uncertainty in satellite-based CCN estimates.

Ground based measurements on reflectance towards validating atmospheric correction algorithms on IRS-P6 AWiFS data

NASA Astrophysics Data System (ADS)

Rani Sharma, Anu; Kharol, Shailesh Kumar; Kvs, Badarinath; Roy, P. S.

In Earth observation, the atmosphere has a non-negligible influence on the visible and infrared radiation which is strong enough to modify the reflected electromagnetic signal and at-target reflectance. Scattering of solar irradiance by atmospheric molecules and aerosol generates path radiance, which increases the apparent surface reflectance over dark surfaces while absorption by aerosols and other molecules in the atmosphere causes loss of brightness to the scene, as recorded by the satellite sensor. In order to derive precise surface reflectance from satellite image data, it is indispensable to apply the atmospheric correction which serves to remove the effects of molecular and aerosol scattering. In the present study, we have implemented a fast atmospheric correction algorithm to IRS-P6 AWiFS satellite data which can effectively retrieve surface reflectance under different atmospheric and surface conditions. The algorithm is based on MODIS climatology products and simplified use of Second Simulation of Satellite Signal in Solar Spectrum (6S) radiative transfer code, which is used to generate look-up-tables (LUTs). The algorithm requires information on aerosol optical depth for correcting the satellite dataset. The proposed method is simple and easy to implement for estimating surface reflectance from the at sensor recorded signal, on a per pixel basis. The atmospheric correction algorithm has been tested for different IRS-P6 AWiFS False color composites (FCC) covering the ICRISAT Farm, Patancheru, Hyderabad, India under varying atmospheric conditions. Ground measurements of surface reflectance representing different land use/land cover, i.e., Red soil, Chick Pea crop, Groundnut crop and Pigeon Pea crop were conducted to validate the algorithm and found a very good match between surface reflectance and atmospherically corrected reflectance for all spectral bands. Further, we aggregated all datasets together and compared the retrieved AWiFS reflectance with aggregated ground measurements which showed a very good correlation of 0.96 in all four spectral bands (i.e. green, red, NIR and SWIR). In order to quantify the accuracy of the proposed method in the estimation of the surface reflectance, the root mean square error (RMSE) associated to the proposed method was evaluated. The analysis of the ground measured versus retrieved AWiFS reflectance yielded smaller RMSE values in case of all four spectral bands. EOS TERRA/AQUA MODIS derived AOD exhibited very good correlation of 0.92 and the data sets provides an effective means for carrying out atmospheric corrections in an operational way. Keywords: Atmospheric correction, 6S code, MODIS, Spectroradiometer, Sun-Photometer

Multi-sensor quantification of aerosol-induced variability in warm clouds over eastern China

NASA Astrophysics Data System (ADS)

Wang, Fu; Guo, Jianping; Zhang, Jiahua; Huang, Jingfeng; Min, Min; Chen, Tianmeng; Liu, Huan; Deng, Minjun; Li, Xiaowen

2015-07-01

Aerosol-cloud (AC) interactions remain uncharacterized due to difficulties in obtaining accurate aerosol and cloud observations. In this study, we quantified the aerosol indirect effects (AIE) on warm clouds over Eastern China based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO, and CPR/CLOUDSAT between June 2006 and December 2010. The seasonality of aerosols from ground-based PM10 (aerosol particles with diameter of 10 μm or less) significantly differed from that estimated using MODIS aerosol optical depth (AOD). This result was supported by the lower level frequency profile of aerosol occurrence from CALIOP, indicative of the significant role of CALIOP in the AC interaction. To focus on warm clouds, cloud layers with base (top) altitudes above 7 (10) km were excluded. The combination of CALIOP and CPR was applied to determine the exact position of warm clouds relative to aerosols out of the following six scenarios in terms of AC mixing states: 1) aerosol only (AO); 2) cloud only (CO); 3) single aerosol layer-single cloud layer (SASC); 4) single aerosol layer-double cloud layers (SADC); 5) double aerosol layers - single cloud layer (DASC); and 6) others. The cases with vertical distance between aerosol and cloud layer less (more) than 100 m (700 m) were marked mixed (separated), and the rest as uncertain. Results showed that only 8.95% (7.53%) belonged to the mixed (separated and uncertain) state among all of the collocated AC overlapping cases, including SASC, SADC, and DASC. Under mixed conditions, the cloud droplet effective radius (CDR) decreased with increasing AOD at moderate aerosol loading (AOD<0.4), and then became saturated at an AOD of around 0.5, followed by an increase in CDR with increasing AOD, known as boomerang shape. Under separated conditions, no apparent changes in CDR with AOD were observed. We categorized the AC dataset into summer- and winter-season subsets to determine how the boomerang shape varied with season. The response of CDR to AOD in summer exhibited similar but much more deepened boomerang shape, as compared with the all year round case. In contrast, CDR in winter did not follow the boomerang shape for its continued decreasing with increasing AOD, even after the saturation zone (AOD around 0.5) of a cloud droplet.

Spatial Surface PM2.5 Concentration Estimates for Wildfire Smoke Plumes in the Western U.S. Using Satellite Retrievals and Data Assimilation Techniques

NASA Astrophysics Data System (ADS)

Loria Salazar, S. M.; Holmes, H.

2015-12-01

Health effects studies of aerosol pollution have been extended spatially using data assimilation techniques that combine surface PM2.5 concentrations and Aerosol Optical Depth (AOD) from satellite retrievals. While most of these models were developed for the dark-vegetated eastern U.S. they are being used in the semi-arid western U.S. to remotely sense atmospheric aerosol concentrations. These models are helpful to understand the spatial variability of surface PM2.5concentrations in the western U.S. because of the sparse network of surface monitoring stations. However, the models developed for the eastern U.S. are not robust in the western U.S. due to different aerosol formation mechanisms, transport phenomena, and optical properties. This region is a challenge because of complex terrain, anthropogenic and biogenic emissions, secondary organic aerosol formation, smoke from wildfires, and low background aerosol concentrations. This research concentrates on the use and evaluation of satellite remote sensing to estimate surface PM2.5 concentrations from AOD satellite retrievals over California and Nevada during the summer months of 2012 and 2013. The aim of this investigation is to incorporate a spatial statistical model that uses AOD from AERONET as well as MODIS, surface PM2.5 concentrations, and land-use regression to characterize spatial surface PM2.5 concentrations. The land use regression model uses traditional inputs (e.g. meteorology, population density, terrain) and non-traditional variables (e.g. FIre Inventory from NCAR (FINN) emissions and MODIS albedo product) to account for variability related to smoke plume trajectories and land use. The results will be used in a spatially resolved health study to determine the association between wildfire smoke exposure and cardiorespiratory health endpoints. This relationship can be used with future projections of wildfire emissions related to climate change and droughts to quantify the expected health impact.

Development of improved wildfire smoke exposure estimates for health studies in the western U.S.

NASA Astrophysics Data System (ADS)

Ivey, C.; Holmes, H.; Loria Salazar, S. M.; Pierce, A.; Liu, C.

2016-12-01

Wildfire smoke exposure is a significant health concern in the western U.S. because large wildfires have increased in size and frequency over the past four years due to drought conditions. The transport phenomena in complex terrain and timing of the wildfire emissions make the smoke plumes difficult to simulate using conventional air quality models. Monitoring data can be used to estimate exposure metrics, but in rural areas the monitoring networks are too sparse to calculate wildfire exposure metrics for the entire population in a region. Satellite retrievals provide global, spatiotemporal air quality information and are used to track pollution plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Particulate matter (PM) exposures can be estimated using columnar aerosol optical depth (AOD), where satellite AOD retrievals serve as a spatial surrogate to simulate surface PM gradients. These exposure models have been successfully used in health effects studies in the eastern U.S. where complex mountainous terrain and surface reflectance do not limit AOD retrival from satellites. Using results from a chemical transport model (CTM) is another effective method to determine spatial gradients of pollutants. However, the CTM does not adequately capture the temporal and spatial distribution of wildfire smoke plumes. By combining the spatiotemporal pollutant fields from both satellite retrievals and CTM results with ground based pollutant observations the spatial wildfire smoke exposure model can be improved. This work will address the challenge of understanding the spatiotemporal distributions of pollutant concentrations to model human exposures of wildfire smoke in regions with complex terrain, where meteorological conditions as well as emission sources significantly influence the spatial distribution of pollutants. The focus will be on developing models to enhance exposure estimates of elevated PM and ozone concentrations from wildfire smoke plumes in the western U.S.

The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

NASA Astrophysics Data System (ADS)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

2017-04-01

We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse-resolution satellite products of air quality with the help of high-resolution model information. This will add value to existing earth observation products of air quality by bringing them to spatial scales that are more in line with what is generally required for studying urban and regional scale air quality. In a fifth activity, we implement robust and independent validation schemes for evaluating the quality of the generated products. Finally, in a sixth activity the consortium is working towards a pre-operational system for improved PM forecasts using observational (in situ and satellite) data assimilation. SAMIRA aims to maximize project benefits by liaison with national and regional environmental protection agencies and health institutions, as well as related ESA and European initiatives such as the Copernicus Atmosphere Monitoring Service (CAMS).

Characterizing the Vertical Profile of Aerosol Particle Extinction and Linear Depolarization over Southeast Asia and the Maritime Continent: The 2007-2009 View from CALIOP

NASA Technical Reports Server (NTRS)

Campbell, James R.; Reid, Jeffrey S.; Westphal, Douglas L.; Zhang, Jianglong; Tackett, Jason L.; Chew, Boon Ning; Welton, Ellsworth J.; Shimizu, Atsushi; Sugimoto, Nobuo; Aoki, Kazuma;

Validation of multi-angle imaging spectroradiometer aerosol products in China

Treesearch

J. Liu; X. Xia; Z. Li; P. Wang; M. Min; WeiMin Hao; Y. Wang; J. Xin; X. Li; Y. Zheng; Z. Chen

2010-01-01

Based on AErosol RObotic NETwork and Chinese Sun Hazemeter Network data, the Multi-angle Imaging SpectroRadiometer (MISR) level 2 aerosol optical depth (AOD) products are evaluated in China. The MISR retrievals depict well the temporal aerosol trend in China with correlation coefficients exceeding 0.8 except for stations located in northeast China and at the...

Fog and Cloud Induced Aerosol Modification Observed by AERONET

NASA Technical Reports Server (NTRS)

Eck, T. F.; Holben, B. N.; Reid, J. S.; Giles, D. M.; Rivas, M. A.; Singh, R. P.; Tripathi, S. N.; Bruegge, C. J.; Platnick, S. E.; Arnold, G. T.;

Aerosol Optical Depth spatiotemporal variability and contribution of different aerosol types over Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos; Zanis, Prodromos; Pöschl, Ulrich; Lelieveld, Jos; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios; Pozzer, Andrea

2015-04-01

In this work, we study the aerosol spatiotemporal variability over the region of Eastern Mediterranean, for the time period 2000-2012, using a 0.1-degree gridded dataset compiled from level-2 MODIS TERRA and MODIS AQUA AOD550 and FMR550 data. A detailed validation of the AOD550 data was implemented using ground-based observations from the AERONET, also showing that the gridding methodology we followed allows for the detection of several local hot spots that cannot be seen using lower resolutions or level-3 data. By combining the MODIS data with data from other satellite sensors (TOMS, OMI), data from a global chemical-aerosol-transport model (GOCART), and reanalysis data from MACC and ERA-interim, we quantify the relative contribution of different aerosol types to the total AOD550 for the period of interest. For this reason, we developed an optimized algorithm for regional studies based on results from previous global studies. Over land, anthropogenic, dust, and fine-mode natural aerosols contribute to the total AOD550, while anthropogenic, dust and maritime AODs are calculated over the ocean. The dust AOD550 over the region was compared against dust AODs from the LIVAS CALIPSO product, showing a similar seasonal variability. Finally, we also look into the aerosol load short-term trends over the region for each aerosol type separately, the results being strongly affected by the selected time period. The research leading to these results has received funding from the European Social Fund (ESF) and national resources under the operational programme Education and Lifelong Learning (EdLL) within the framework of the Action "Supporting Postdoctoral Researchers" (QUADIEEMS project) and from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 226144 (C8 project).

A comparison of uncertainties in the aerosol direct radiative effect in the SE U.S. calculated using satellite-based and ground-based aerosol properties

NASA Astrophysics Data System (ADS)

Sherman, J. P.

2017-12-01

Satellite-retrieved aerosol optical depth is typically used for measurement-based estimates of the aerosol direct radiative effect (DRE) on solar radiation, on both global and regional scales. The SE U.S. is one of only a few regions not to have warmed during the 20th century and is home to some of the highest summertime levels of biogenic and sulfate aerosols in the U.S. While decreases in aerosol optical depth over the past few decades have likely reduced the cooling effect of aerosols in the region, satellite-derived estimates of aerosol DRE alone may not be sufficient to study long-term DRE trends and the roles played by changing AOD and aerosol optical properties. Appalachian State University (APP) in Boone, NC is home to the only co-located NASA AERONET, NOAA ESRL, and (active) NASA MPLNET sites in the U.S. and is well-positioned to validate satellite-based aerosol retrievals and better constrain background aerosol DRE in regional climate models. As part of the first multi-year `ground truth' DRE study in the SE U.S., Sherman and McComiskey (2017) applied nearly four years of spectral AOD from the APP AERONET site, along with single-scattering albedo(SSA) and asymmetry parameter from the APP NOAA ESRL site, as inputs to the SBDART Radiative Transfer model to calculate seasonal dependence of aerosol DRE and DRE uncertainties at the top-of-atmosphere and at the surface. Clear sky aerosol DRE uncertainty at the TOA (surface) above APP ranges from 0.44 Wm-2 (0.73 Wm-2) for DEC to 0.90 Wm-2 (1.3 Wm-2) for JUN. Expressed as a fraction of seasonal-mean DRE, these uncertainties are 12-20% for all seasons except winter, when they are close to 50%. Use of MODIS or MISR AOD in place of AERONET increases these uncertainties by factors of 2.5 to 5 and DRE uncertainties are dominated by AOD uncertainty for all seasons. The use of SSA from OMI or MISR further increases the DRE uncertainties, especially during the higher AOD summer months, when DRE sensitivity to aerosol type (SSA, g) is highest. Seasonally-dependent sensitivities of aerosol DRE to AOD, SSA, and g above the regionally-representative APP site will be presented, along with current measurement uncertainties from MODIS, MISR, and OMI, to estimate uncertainties in satellite-based estimates of DRE and the degree to which they must be reduced if DRE uncertainty of 1 Wm-2 is to be achieved.

Near-surface and columnar measurements with a micro pulse lidar of atmospheric pollen in Barcelona, Spain

NASA Astrophysics Data System (ADS)

Sicard, Michaël; Izquierdo, Rebeca; Alarcón, Marta; Belmonte, Jordina; Comerón, Adolfo; Baldasano, José Maria

2016-06-01

We present for the first time continuous hourly measurements of pollen near-surface concentration and lidar-derived profiles of particle backscatter coefficients and of volume and particle depolarization ratios during a 5-day pollination event observed in Barcelona, Spain, between 27 and 31 March 2015. Daily average concentrations ranged from 1082 to 2830 pollen m-3. Platanus and Pinus pollen types represented together more than 80 % of the total pollen. Maximum hourly pollen concentrations of 4700 and 1200 m-3 were found for Platanus and Pinus, respectively. Every day a clear diurnal cycle caused by the vertical transport of the airborne pollen was visible on the lidar-derived profiles with maxima usually reached between 12:00 and 15:00 UT. A method based on the lidar polarization capabilities was used to retrieve the contribution of the pollen to the total aerosol optical depth (AOD). On average the diurnal (09:00-17:00 UT) pollen AOD was 0.05, which represented 29 % of the total AOD. Maximum values of the pollen AOD and its contribution to the total AOD reached 0.12 and 78 %, respectively. The diurnal means of the volume and particle depolarization ratios in the pollen plume were 0.08 and 0.14, with hourly maxima of 0.18 and 0.33, respectively. The diurnal mean of the height of the pollen plume was found at 1.24 km with maxima varying in the range of 1.47-1.78 km. A correlation study is performed (1) between the depolarization ratios and the pollen near-surface concentration to evaluate the ability of the former parameter to monitor pollen release and (2) between the depolarization ratios as well as pollen AOD and surface downward solar fluxes, which cause the atmospheric turbulences responsible for the particle vertical motion, to examine the dependency of the depolarization ratios and the pollen AOD upon solar fluxes. For the volume depolarization ratio the first correlation study yields to correlation coefficients ranging 0.00-0.81 and the second to correlation coefficients ranging 0.49-0.86.

Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

NASA Technical Reports Server (NTRS)

Xiao, Qingyang; Wang, Yujie; Chang, Howard H.; Meng, Xia; Geng, Guannan; Lyapustin, Alexei Ivanovich; Liu, Yang

2017-01-01

Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and pasture is not correlated with aerosol loading, supporting the assumption that temporal variation of column water vapor is primarily a function of the larger-scale meteorology. However, a difference in the response of cloud fraction to increasing AOD is observed between forest and pasture. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, are likely to have an impact on aerosol-cloud correlations between different land-cover types.

Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

NASA Astrophysics Data System (ADS)

Fernandes, A.; Riffler, M.; Ferreira, J.; Wunderle, S.; Borrego, C.; Tchepel, O.

2015-04-01

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.

Airborne Sunphotometry of Aerosol Optical Depth and Columnar Water Vapor During ACE-Asia

NASA Technical Reports Server (NTRS)

Redemann, Jens; Schmid, B.; Russell, P. B.; Livingston, J. M.; Eilers, J. A.; Ramirez, S. A.; Kahn, R.; Hipskind, R. Stephen (Technical Monitor)

2001-01-01

During the Intensive Field Campaign (IFC) of the Aerosol Characterization Experiment - Asia (ACE-Asia), March-May 2001, the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated during 15 of the 19 research flights aboard the NCAR C- 130, while its 14-channel counterpart (AATS- 14) was flown successfully on all 18 research flights of a Twin Otter aircraft operated by the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS), Monterey, CA. ACE-Asia was the fourth in a series of aerosol characterization experiments and focused on aerosol outflow from the Asian continent to the Pacific basin. Each ACE was designed to integrate suborbital and satellite measurements and models so as to reduce the uncertainty in calculations of the climate forcing due to aerosols. The Ames Airborne Tracking Sunphotometers measured solar beam transmission at 6 (380-1021 nm, AATS-6) and 14 wavelengths (353-1558 nm, AATS-14) respectively, yielding aerosol optical depth (AOD) spectra and column water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction and water vapor concentration. The wavelength dependence of AOD and extinction indicates that supermicron dust was often a major component of the aerosol. Frequently this dust-containing aerosol extended to high altitudes. For example, in data flights analyzed to date 34 +/- 13% of full-column AOD(525 nm) was above 3 km. In contrast, only 10 +/- 4% of CWV was above 3 km. In this paper, we will show first sunphotometer-derived results regarding the spatial variation of AOD and CWV, as well as the vertical distribution of aerosol extinction and water vapor concentration. Preliminary comparison studies between our AOD/aerosol extinction data and results from: (1) extinction products derived using in situ measurements and (2) AOD retrievals using the Multi-angle Imaging Spectro-Radiometer (MISR) aboard the TERRA satellite will also be presented.

Aerosol physical and chemical properties retrieved from ground-based remote sensing measurements during heavy haze days in Beijing winter

NASA Astrophysics Data System (ADS)

Li, Z.; Gu, X.; Wang, L.; Li, D.; Xie, Y.; Li, K.; Dubovik, O.; Schuster, G.; Goloub, P.; Zhang, Y.; Li, L.; Ma, Y.; Xu, H.

2013-10-01

With the increase in economic development over the past thirty years, many large cities in eastern and southwestern China are experiencing increased haze events and atmospheric pollution, causing significant impacts on the regional environment and even climate. However, knowledge on the aerosol physical and chemical properties in heavy haze conditions is still insufficient. In this study, two winter heavy haze events in Beijing that occurred in 2011 and 2012 were selected and investigated by using the ground-based remote sensing measurements. We used a CIMEL CE318 sun-sky radiometer to retrieve haze aerosol optical, physical and chemical properties, including aerosol optical depth (AOD), size distribution, complex refractive indices and aerosol fractions identified as black carbon (BC), brown carbon (BrC), mineral dust (DU), ammonium sulfate-like (AS) components and aerosol water content (AW). The retrieval results from a total of five haze days showed that the aerosol loading and properties during the two winter haze events were comparable. Therefore, average heavy haze property parameters were drawn to present a research case for future studies. The average AOD is about 3.0 at 440 nm, and the Ångström exponent is 1.3 from 440 to 870 nm. The fine-mode AOD is 2.8 corresponding to a fine-mode fraction of 0.93. The coarse particles occupied a considerable volume fraction of the bimodal size distribution in winter haze events, with the mean particle radius of 0.21 and 2.9 μm for the fine and coarse modes respectively. The real part of the refractive indices exhibited a relatively flat spectral behavior with an average value of 1.48 from 440 to 1020 nm. The imaginary part showed spectral variation, with the value at 440 nm (about 0.013) higher than the other three wavelengths (about 0.008 at 675 nm). The aerosol composition retrieval results showed that volume fractions of BC, BrC, DU, AS and AW are 1, 2, 49, 15 and 33%, respectively, on average for the investigated haze events. The preliminary uncertainty estimation and comparison of these remote sensing results with in situ BC and PM2.5 measurements are also presented in the paper.

Nocturnal aerosol optical depth measurements with a small-aperture automated photometer using the moon as a light source

USGS Publications Warehouse

Berkoff, T.A.; Sorokin, M.; Stone, T.; Eck, T.F.; Hoff, R.; Welton, E.; Holben, B.

2011-01-01

A method is described that enables the use of lunar irradiance to obtain nighttime aerosol optical depth (AOD) measurements using a small-aperture photometer. In this approach, the U.S. Geological Survey lunar calibration system was utilized to provide high-precision lunar exoatmospheric spectral irradiance predictions for a ground-based sensor location, and when combined with ground measurement viewing geometry, provided the column optical transmittance for retrievals of AOD. Automated multiwavelength lunar measurements were obtained using an unmodified Cimel-318 sunphotometer sensor to assess existing capabilities and enhancements needed for day/night operation in NASA's Aerosol Robotic Network (AERONET). Results show that even existing photometers can provide the ability for retrievals of aerosol optical depths at night near full moon. With an additional photodetector signal-to-noise improvement of 10-100, routine use over the bright half of the lunar phase and a much wider range of wavelengths and conditions can be achieved. Although the lunar cycle is expected to limit the frequency of observations to 30%-40% compared to solar measurements, nevertheless this is an attractive extension of AERONET capabilities. ?? 2011 American Meteorological Society.

Airborne Sunphotometry of African Dust and Marine Boundary Layer Aerosols in PRIDE

NASA Technical Reports Server (NTRS)

Livingston, John M.; Redemann, Jens; Russell, Philip; Schmid, Beat; Reid, Jeff; Pilewskie, Peter; Hipskind, R. Stephen (Technical Monitor)

2000-01-01

The Puerto Rico Dust Experiment (PRIDE) was conducted during summer 2000 to study the radiative, microphysical and transport properties of Saharan dust in the Caribbean region. During PRIDE, NASA Ames Research Center's six-channel airborne autotracking sunphotometer (AATS-6) was operated aboard a Piper Navajo airplane based at Roosevelt Roads Naval Station on the northeast coast of Puerto Rico. AATS-6 measurements were taken during 21 science flights off the coast of Puerto Rico in the western Caribbean. Data were acquired within and above the Marine Boundary Layer (MBL) and the Saharan Aerosol Layer (SAL) up to 5.5 km altitude tinder a wide range of dust loadings. Aerosol optical depth (AOD) spectra and columnar water vapor (CWV) values have been calculated from the AATS-6 measurements by using sunphotometer calibration data obtained at Mauna Loa Observatory (3A kin ASL) before (May) and after (October) PRIDE. Mid-visible AOD values measured near the surface during PRIDE ranged from 0.07 on the cleanest day to 0.55 on the most turbid day. Values measured above the MBL were as high as 0.35; values above the SAL were as low as 0.01. The fraction of total column AOD due to Saharan dust cannot be determined precisely from AATS-6 AOD data alone due to the uncertainty in the extent of vertical mixing of the dust down through the MBL. However, analyses of ground-based and airborne in-situ aerosol sampling measurements and ground-based aerosol lidar backscatter data should yield accurate characterization of the vertical mixing that will enable calculation of the Saharan dust AOD component from the sunphotometer data. Examples will be presented showing measured AATS-6 AOD spectra, calculated aerosol extinction and water vapor density vertical profiles, and aerosol size distributions retrieved by inversion of the AOD spectra. Near sea-surface AOD spectra acquired by AATS-6 during horizontal flight legs at 30 m ASL are available for validation of AOD derived from coincident satellite sensor (TOMS, MODIS, MISR) measurements. AATS-6 AOD data acquired during numerous aircraft ascents and descents through the MBL and the SAL should permit atmospheric column closure analyses with respect to aerosol optical depth, extinction, and size distribution by comparison with coincident aircraft-based in-situ particle size distribution measurements and ground-based (Cabras Island, Puerto Rico) micropulse lidar aerosol backscatter measurements. The aerosol information derived from the column closure analyses can be used subsequently to calculate radiative flux changes, which can then be compared with coincident spectral flux measurements taken from aboard the aircraft with a solar spectral flux radiometer.

Estimating PM2.5 in Xi'an , China Using Aerosol Optical Depth of Npp Viirs Data and Meteorological Measurements

NASA Astrophysics Data System (ADS)

Zhang, K.; Yang, Z.; Zheng, J.; Jiao, J.; Gao, W.

2018-04-01

In recent years, the air pollution is becoming more and more serious, which not only causes the decrease of the visibility, but also affects the human health. As the most important pollutant particulate matter, remote sensing satellite measurements have been widely used to estimate PM2.5 concentration on the ground. Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the instruments which is taken in the National Polar-orbiting Partnership (NPP) satellite. In this study, VIIRS was used to retrieve aerosol optical depth (AOD) with the way of dark pixels, and several other major meteorological variables (wind speed, relative humidity, NO2 concentration, ground surface relative humidity and planetary boundary layer height) were combined with AOD to construct a nonlinear multiple regression mode for establishing the relationship between AOD and PM2.5 concentration. The North Basin of Shaanxi province of China, which includes Xi'an, is located in the north of Qinling Mountains, south of the Loess Plateau, and in the central of Weihe basin, with special structure and other adverse weather conditions (static wind, less rain) to cause the frequent haze weather in Xi'an. Xi'an city was selected as the area of the experiment due to its particularity. This research obtained the AOD results from August 1, 2013 to October 30, 2013. The inversion results were compared with ground-based PM2.5 concentration date from air quality monitoring station of Xi'an. The result showed that there is a significant correlation between the two, and the correlation coefficient is 0.783. The inversion result verified that the model of VIIRS data agreed well AOD, which could be used to estimate the surface PM2.5 concentration and monitor the regional air quality.

Monitoring An Intensive Dust Event over Northern China Using Multi-satellite Observation

NASA Astrophysics Data System (ADS)

She, L.; Xue, Y.; Guang, J.; Mei, L.; Che, Y.; Fan, C.; Xie, Y.

2017-12-01

The deserts in western/northern China are one of the major mineral dust source regions of the world. Large amount of dust are emitted and blown east and southeast, especially in spring. An intensive dust event occurred over Northern China during May 3 - 8, 2017. The dust storms came from deserts in China and Mongolia. Due to the long-distance transport, more than ten provinces were affected by this dust event, several provinces occurred strong dust storm. In this study, multi-satellite data were employed to analyse the spatial-temporal evolution and dynamic transport behaviour of the dust plume, especially the geostationary satellite data - Himawari8 Advanced Himawari Imager (AHI) data. AHI data was used to estimate hourly Aerosol Optical Depth (AOD) to monitoring the aerosol distribution as well as the dust plume movements, as the dust storms often characterized by high AOD. A simple dust index was also calculated based on AHI VIS and TIR data to estimate the dust intensity. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data and the Ozone Monitoring Instrument (OMI) Aerosol Index were used as additional data sources to monitor the dust vertical distribution and provide independent information of dust presence. MODIS aerosol product and AERONET aerosol measurements were compared with the AHI retrieved AODs, the comparisons show a good agreement. The dust index was compared with the ground measurements as well as the corresponding RGB image. Simulations from HYSPLIT back-trajectory analysis shows similar temporal variation with the calculated AOD and dust index of the dust plume. Those comparisons with other satellite products and ground measurements suggested both the calculated AOD and dust index well depicted the dust events compared.

Two Methods to Derive Ground-level Concentrations of PM2.5 with Improved Accuracy in the North China, Calibrating MODIS AOD and CMAQ Model Predictions

NASA Astrophysics Data System (ADS)

Lyu, Baolei; Hu, Yongtao; Chang, Howard; Russell, Armistead; Bai, Yuqi

2016-04-01

Reliable and accurate characterizations of ground-level PM2.5 concentrations are essential to understand pollution sources and evaluate human exposures etc. Monitoring network could only provide direct point-level observations at limited locations. At the locations without monitors, there are generally two ways to estimate the pollution levels of PM2.5. One is observations of aerosol properties from the satellite-based remote sensing, such as Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD). The other one is from deterministic atmospheric chemistry models, such as the Community Multi-Scale Air Quality Model (CMAQ). In this study, we used a statistical spatio-temporal downscaler to calibrate the two datasets to monitor observations to derive fine-scale ground-level concentrations of PM2.5 with improved accuracy. We treated both MODIS AOD and CMAQ model predictions as biased proxy estimations of PM2.5 pollution levels. The downscaler proposed a Bayesian framework to model the spatially and temporally varying coefficients of the two types of estimations in the linear regression setting, in order to correct biases. Especially for calibrating MODIS AOD, a city-specific linear model was established to fill the missing AOD values, and a novel interpolation-based variable, i.e. PM2.5 Spatial Interpolator, was introduced to account for the spatial dependence among grid cells. We selected the heavy polluted and populated North China as our study area, in a grid setting of 81×81 12-km cells. For the evaluation of calibration performance for retrieved MODIS AOD, the R2 was 0.61 by the full model with PM2.5 Spatial Interpolator being presented, and was 0.48 with PM2.5 Spatial Interpolator not being presented. The constructed AOD values effectively predicted PM2.5 concentrations under our model structure, with R2=0.78. For the evaluation of calibrated CMAQ predictions, the R2 was 0.51, a little less than that of calibrated AOD. Finally we obtained two sets of calibrated estimations of ground-level PM2.5 concentrations with complete spatial coverage. By comparing the two datasets, we found that the prediction from AOD have a little smoother texture than that from CMAQ. The former also predicted larger heavy pollution area in the southern Hebei province than the latter, but in a small margin. In general, they have pretty similar spatial patterns, indicating the reliability of our data fusion method. In summary, the statistical spatio-temporal downscaler could provide improvements on MODIS AOD and CMAQ's predictions on PM2.5 pollution levels. Future work would focus on fusing three datasets, as aforementioned monitor observations, MODIS AOD and CMAQ predictions, to derive predictions of ground-level PM2.5 pollution levels with even increased accuracy.

Constraints on Global Aerosol Types: Past, Present, and Near-Future

NASA Astrophysics Data System (ADS)

Kahn, Ralph

2014-05-01

Although the recent IPCC fifth assessment report (AR5) suggests that confidence in estimated direct aerosol radiative forcing (DARF) is high, indications are that there is little agreement among current climate models about the global distribution of aerosol single-scattering albedo (SSA). SSA must be associated with specific surface albedo and aerosol optical depth (AOD) values to calculate DARF with confidence, and global-scale constraints on aerosol type, including SSA, are poor at present. Yet, some constraints on aerosol type have been demonstrated for several satellite instruments, including the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR). The time-series of approximately once-weekly, global MISR observations has grown to about 14 years. The MISR capability amounts to three-to-five bins in particle size, two-to-four bins in SSA, and spherical vs. non-spherical particle distinctions, under good retrieval conditions. As the record of coincident, suborbital validation data has increased steadily, it has become progressively more feasible to assess and to improve the operational algorithm constraints on aerosol type. This presentation will discuss planned refinements to the MISR operational algorithm, and will highlight recent efforts at using MISR results to help better represent wildfire smoke, volcanic ash, and urban pollution in climate models.

Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

PubMed

Reid, Colleen E; Jerrett, Michael; Petersen, Maya L; Pfister, Gabriele G; Morefield, Philip E; Tager, Ira B; Raffuse, Sean M; Balmes, John R

2015-03-17

Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event.

Impact of diurnal variability and meteorological factors on the PM2.5 - AOD relationship: Implications for PM2.5 remote sensing.

PubMed

Guo, Jianping; Xia, Feng; Zhang, Yong; Liu, Huan; Li, Jing; Lou, Mengyun; He, Jing; Yan, Yan; Wang, Fu; Min, Min; Zhai, Panmao

2017-02-01

PM 2.5 retrieval from space is still challenging due to the elusive relationship between PM 2.5 and aerosol optical depth (AOD), which is further complicated by meteorological factors. In this work, we investigated the diurnal cycle of PM 2.5 in China, using ground-based PM measurements obtained at 226 sites of China Atmosphere Watch Network during the period of January 2013 to December 2015. Results showed that nearly half of the sites witnessed a PM 2.5 maximum in the morning, in contrast to the least frequent occurrence (5%) in the afternoon when strong solar radiation received at the surface results in rapid vertical diffusion of aerosols and thus lower mass concentration. PM 2.5 tends to peak equally in the morning and evening in North China Plain (NCP) with an amplitude of nearly twice or three times that in the Pearl River Delta (PRD), whereas the morning PM 2.5 peak dominates in Yangtze River Delta (YRD) with a magnitude lying between those of NCP and PRD. The gridded correlation maps reveal varying correlations around each PM 2.5 site, depending on the locations and seasons. Concerning the impact of aerosol diurnal variation on the correlation, the averaging schemes of PM 2.5 using 3-h, 5-h, and 24-h time windows tend to have larger R biases, compared with the scheme of 1-h time window, indicating diurnal variation of aerosols plays a significant role in the establishment of explicit correlation between PM 2.5 and AOD. In addition, high cloud fraction and relative humidity tend to weaken the correlation, regardless of geographical location. Therefore, the impact of meteorology could be one of the most plausible alternatives in explaining the varying R values observed, due to its non-negligible effect on MODIS AOD retrievals. Our findings have implications for PM 2.5 remote sensing, as long as the aerosol diurnal cycle, along with meteorology, are explicitly considered in the future. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

An analysis of high fine aerosol loading episodes in north-central Spain in the summer 2013 - Impact of Canadian biomass burning episode and local emissions

NASA Astrophysics Data System (ADS)

Burgos, M. A.; Mateos, D.; Cachorro, V. E.; Toledano, C.; de Frutos, A. M.; Calle, A.; Herguedas, A.; Marcos, J. L.

2018-07-01

This work presents an evaluation of a surprising and unusual high turbidity summer period in 2013 recorded in the north-central Iberian Peninsula (IP). The study is made up of three main pollution episodes characterized by very high aerosol optical depth (AOD) values with the presence of fine aerosol particles: the strongest long-range transport Canadian Biomass Burning (BB) event recorded, one of the longest-lasting European Anthropogenic (A) episodes and an extremely strong regional BB. The Canadian BB episode was unusually strong with maximum values of AOD(440 nm) ∼ 0.8, giving rise to the highest value recorded by photometer data in the IP with a clearly established Canadian origin. The anthropogenic pollution episode originated in Europe is mainly a consequence of the strong impact of Canadian BB events over north-central Europe. As regards the local episode, a forest fire in the nature reserve near the Duero River (north-central IP) impacted on the population over 200 km away from its source. These three episodes exhibited fingerprints in different aerosol columnar properties retrieved by sun-photometers of the AErosol RObotic NETwork (AERONET) as well as in particle mass surface concentrations, PMx, measured by the European Monitoring and Evaluation Programme (EMEP). Main statistics, time series and scatterplots relate aerosol loads (aerosol optical depth, AOD and particulate matter, PM) with aerosol size quantities (Ångström Exponent and PM ratio). More detailed microphysical/optical properties retrieved by AERONET inversion products are analysed in depth to describe these events: contribution of fine and coarse particles to AOD and its ratio (the fine mode fraction), volume particle size distribution, fine volume fraction, effective radius, sphericity fraction, single scattering albedo and absorption optical depth. Due to its relevance in climate studies, the aerosol radiative effect has been quantified for the top and bottom of the atmosphere, obtaining mean daily values for this extraordinary summer period of -14.5 and -47.5 Wm-2, respectively.

Improving short-term air quality predictions over the U.S. using chemical data assimilation

NASA Astrophysics Data System (ADS)

Kumar, R.; Delle Monache, L.; Alessandrini, S.; Saide, P.; Lin, H. C.; Liu, Z.; Pfister, G.; Edwards, D. P.; Baker, B.; Tang, Y.; Lee, P.; Djalalova, I.; Wilczak, J. M.

2017-12-01

State and local air quality forecasters across the United States use air quality forecasts from the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. This project funded by the National Aeronautics and Space Administration (NASA) aims to enhance the decision-making process by improving the accuracy of NAQFC short-term predictions of ground-level particulate matter of less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The NAQFC is based on the Community Multiscale Air Quality (CMAQ) model. To improve the initialization of PM2.5 in CMAQ, we developed a new capability in the community Gridpoint Statistical Interpolation (GSI) system to assimilate Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals in CMAQ. Specifically, we developed new capabilities within GSI to read/write CMAQ data, a forward operator that calculates AOD at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that translates the changes in AOD to aerosol chemical composition. A generalized background error covariance program called "GEN_BE" has been extended to calculate background error covariance using CMAQ output. The background error variances are generated using a combination of both emissions and meteorological perturbations to better capture sources of uncertainties in PM2.5 simulations. The newly developed CMAQ-GSI system is used to perform daily 24-h PM2.5 forecasts with and without data assimilation from 15 July to 14 August 2014, and the resulting forecasts are compared against AirNOW PM2.5 measurements at 550 stations across the U. S. We find that the assimilation of MODIS AOD retrievals improves initialization of the CMAQ model in terms of improved correlation coefficient and reduced bias. However, we notice a large bias in nighttime PM2.5 simulations which is primarily associated with very shallow boundary layer in the model. The developments and results will be discussed in detail during the presentation.

Validation of MODIS Aerosol Optical Depth Retrievals over a Tropical Urban Site, Pune, India

NASA Technical Reports Server (NTRS)

More, Sanjay; Kuman, P. Pradeep; Gupta, Pawan; Devara, P. C. S.; Aher, G. R.

2011-01-01

In the present paper, MODIS (Terra and Aqua; level 2, collection 5) derived aerosoloptical depths (AODs) are compared with the ground-based measurements obtained from AERONET (level 2.0) and Microtops - II sun-photometer over a tropical urban station, Pune (18 deg 32'N; 73 deg 49'E, 559 m amsl). This is the first ever systematic validation of the MODIS aerosol products over Pune. Analysis of the data indicates that the Terra and Aqua MODIS AOD retrievals at 550 nm have good correlations with the AERONET and Microtops - II sun-photometer AOD measurements. During winter the linear regression correlation coefficients for MODIS products against AERONET measurements are 0.79 for Terra and 0.62 for Aqua; however for premonsoon, the corresponding coefficients are 0.78 and 0.74. Similarly, the linear regression correlation coefficients for Microtops measurements against MODIS products are 0.72 and 0.93 for Terra and Aqua data respectively during winter and are 0.78 and 0.75 during pre-monsoon. On yearly basis in 2008-2009, correlation coefficients for MODIS products against AERONET measurements are 0.80 and 0.78 for Terra and Aqua respectively while the corresponding coefficients are 0.70 and 0.73 during 2009-2010. The regressed intercepts with MODIS vs. AERONET are 0.09 for Terra and 0.05 for Aqua during winter whereas their values are 0.04 and 0.07 during pre-monsoon. However, MODIS AODs are found to underestimate during winter and overestimate during pre-monsoon with respect to AERONET and Microtops measurements having slopes 0.63 (Terra) and 0.74 (Aqua) during winter and 0.97 (Terra) and 0.94 (Aqua) during pre-monsoon. Wavelength dependency of Single Scattering Albedo (SSA) shows presence of absorbing and scattering aerosol particles. For winter, SSA decreases with wavelength with the values 0.86 +/- 0.03 at 440 nm and 0.82 +/- 0.04 at 1020nm. In pre-monsoon, it increases with wavelength (SSA is 0.87 +/- 0.02 at 440nm; and 0.88 +/-0.04 at 1020 nm).

Aerosols and lightning activity: The effect of vertical profile and aerosol type

NASA Astrophysics Data System (ADS)

Proestakis, E.; Kazadzis, S.; Lagouvardos, K.; Kotroni, V.; Amiridis, V.; Marinou, E.; Price, C.; Kazantzidis, A.

2016-12-01

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite has been utilized for the first time in a study regarding lightning activity modulation due to aerosols. Lightning activity observations, obtained by the ZEUS long range Lightning Detection Network, European Centre for Medium range Weather Forecasts (ECMWF) Convective Available Potential Energy (CAPE) data and Cloud Fraction (CF) retrieved by MODIS on board Aqua satellite have been combined with CALIPSO CALIOP data over the Mediterranean basin and for the period March to November, from 2007 to 2014. The results indicate that lightning activity is enhanced during days characterized by higher Aerosol Optical Depth (AOD) values, compared to days with no lightning. This study contributes to existing studies on the link between lightning activity and aerosols, which have been based just on columnar AOD satellite retrievals, by performing a deeper analysis into the effect of aerosol profiles and aerosol types. Correlation coefficients of R = 0.73 between the CALIPSO AOD and the number of lightning strikes detected by ZEUS and of R = 0.93 between ECMWF CAPE and lightning activity are obtained. The analysis of extinction coefficient values at 532 nm indicates that at an altitudinal range exists, between 1.1 km and 2.9 km, where the values for extinction coefficient of lightning-active and non-lightning-active cases are statistically significantly different. Finally, based on the CALIPSO aerosol subtype classification, we have investigated the aerosol conditions of lightning-active and non-lightning-active cases. According to the results polluted dust aerosols are more frequently observed during non-lightning-active days, while dust and smoke aerosols are more abundant in the atmosphere during the lightning-active days.

Aerosol and cloud properties derived from hyperspectral transmitted light in the southeast Atlantic sampled during field campaign deployments in 2016 and 2017

NASA Astrophysics Data System (ADS)

LeBlanc, S. E.; Redemann, J.; Flynn, C. J.; Segal-Rosenhaimer, M.; Kacenelenbogen, M. S.; Shinozuka, Y.; Pistone, K.; Karol, Y.; Schmidt, S.; Cochrane, S.; Chen, H.; Meyer, K.; Ferrare, R. A.; Burton, S. P.; Hostetler, C. A.; Hair, J. W.

2017-12-01

We present aerosol and cloud properties collected from airborne remote-sensing measurements in the southeast Atlantic during the recent NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign. During the biomass burning seasons of September 2016 and August 2017, we sampled aerosol layers which overlaid marine stratocumulus clouds off the southwestern coast of Africa. We sampled these aerosol layers and the underlying clouds from the NASA P3 airborne platform with the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). Aerosol optical depth (AOD), along with trace gas content in the atmospheric column (water vapor, NO2, and O3), is obtained from the attenuation in the sun's direct beam, measured at the altitude of the airborne platform. Using hyperspectral transmitted light measurements from 4STAR, in conjunction with hyperspectral hemispheric irradiance measurements from the Solar Spectral Flux Radiometers (SSFR), we also obtained aerosol intensive properties (asymmetry parameter, single scattering albedo), aerosol size distributions, cloud optical depth (COD), cloud particle effective radius, and cloud thermodynamic phase. Aerosol intensive properties are retrieved from measurements of angularly resolved skylight and flight level spectral albedo using the inversion used with measurements from AERONET (Aerosol Robotic Network) that has been modified for airborne use. The cloud properties are obtained from 4STAR measurements of scattered light below clouds. We show a favorable initial comparison of the above-cloud AOD measured by 4STAR to this same product retrieved from measurements by the MODIS instrument on board the TERRA and AQUA satellites. The layer AOD observed above clouds will also be compared to integrated aerosol extinction profile measurements from the High Spectral Resolution Lidar-2 (HSRL-2).

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

NASA Technical Reports Server (NTRS)

da Silva, Arlindo

2010-01-01

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

Retrieval, Inter-Comparison, and Validation of Above-Cloud Aerosol Optical Depth from A-train Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Bhartia, Pawan K.; Remer, Lorraine; Redemann, Jens; Dunagan, Stephen E.; Livingston, John; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal-Rosenbeimer, Michal;

A study of aerosol absorption and height retrievals with a hyperspectral (UV to NIR) passive sensor

NASA Astrophysics Data System (ADS)

Gasso, S.

2017-12-01

With the deployment of the first sensor (TOMS, in 1978) with capabilities to detect aerosol absorption (AA) from space, there has been a continuous evolution in hardware and algorithms used to measured this property. Although with TOMS and its more advanced successors (such as OMI) made significant progress in globally characterizing AA , there is room for improvement especially by taking advantage of sensors with extended spectral coverage (UV to NIR) and high spatial resolution (<1 km). While such unique sensor does not exist yet, the collocation of observations from different platforms that jointly fulfill those characteristics (e.g. A-Train, S-NPP) confirm that it is possible to fully retrieve all AA parameters that modulate absorption in the upwelling radiance (AOD, SSA and aerosol layer height). However, such combined approaches still have some drawbacks such as the difficulty to account for cloud contamination. The upcoming deployment of satellite detectors with the desired features all in one sensor (PACE, TropOMI, GEMS) prompt a revision of the AA retrieval technique used in past approaches. In particular,the TropOMI mission, a hyperspectral UV-to-NIR sensor with moderate ( 5km nadir pixel) spatial resolution to be launched in Fall 2017. In addition , the sensor will include sensing capabilities for the wavelength range of the Oxygen bands A and B at very high wavelength resolution. This study will be centered on the aerosol detection capabilities of TropOMI. Because the spectral range covered, it is theoretically possible to simultaneously retrieve the aerosol optical depth, the single scattering albedo and aerosol mean height without assuming any of them as it was the case with previous retrieval approaches. Specifically, we intend to present a theoretical study based on simulated radiances at selected UV, VIS and near-IR bands (including the Oxygen bands) and evaluate the sensitivity of this sensor to different levels of aerosol concentration, height and absorption properties (imaginary index) along with particle size distribution.

A Mesoscale Analysis of Column-Integrated Aerosol Properties in Northern India During the TIGERZ 2008 Pre-Monsoon Period and a Comparison to MODIS Retrievals

NASA Technical Reports Server (NTRS)

Giles, D. M.; Holben, B. N.; Tripathi, S. N.; Eck, T. F.; Newcomb, W. W.; Slutsker, I.; Dickerson, R. R.; Thompson, A. M.; Wang, S.-H.; Singh, R. P.;

Seasonal and inter-annual variability of aerosol optical properties during 2005-2010 over Red Mountain Pass and Impact on the Snow Cover of the San Juan Mountains

NASA Astrophysics Data System (ADS)

Singh, R. P.; Gautam, R.; Painter, T. H.

2011-12-01

Growing body of evidence suggests the significant role of aerosol solar absorption in accelerated seasonal snowmelt in the cryosphere and elevated mountain regions via snow contamination and radiative warming processes. Characterization of aerosol optical properties over seasonal snow cover and snowpacks is therefore important towards the better understanding of aerosol radiative effects and associated impact on snow albedo. In this study, we present seasonal variations in column-integrated aerosol optical properties retrieved from AERONET sunphotometer measurements (2005-2010) at Red Mountain Pass (37.90° N, 107.72° W, 3368 msl) in the San Juan Mountains, in the vicinity of the North American Great Basin and Colorado Plateau deserts. The aerosol optical depth (AOD) measured at 500nm is generally low (< 0.2) in the climatological monthly means but exhibits strong seasonal variability with very low background values of about 0.05 during winter season, but is found to significantly increase more than 5-6 times during summer months with values up to 0.3-0.4. Together with the spectral variations in AOD, the Angstrom Wavelength Exponent (α) typically varies in the range of 1-2 indicating the dominance of fine-mode particulates. However, during summer months, nearly 30% of α values are observed below 0.5 thus suggesting an increased influx of coarse-mode aerosols compared to other seasons. The higher AOD and lower α is most likely a result of the summer-time enhanced convection and upslope pollutant transport. In addition, the possibility of the observed increased coarse-mode influence associated with mineral dust influx cannot be ruled out, due to westerly-airmass driven transport from arid/desert regions as suggested by backward trajectory simulations. A meteorological coupling is also found in the summer season between AOD and column water vapor retrieved from AERONET with co-occurring enhanced water vapor and AOD. Based on column measurements, it is difficult to ascertain the aerosol composition, however, the summer-time enhanced aerosol loading as presented here is consistent with the increased dust deposition in the San Juan mountain snow cover as reported in recent studies. In summary, this study is expected to better understand the seasonal and inter-annual aerosol column variations and is an attempt to provide an insight into the effects of aerosol solar absorption on accelerated seasonal snowmelt in the San Juan mountains.

Joint Retrieval Of Surface Reflectance And Aerosol Properties: Application To MSG/SEVIRI in the framework of the aerosol_cci project

NASA Astrophysics Data System (ADS)

Luffarelli, Marta; Govaerts, Yves; Goossens, Cedric

2017-04-01

A new versatile algorithm for the joint retrieval of surface reflectance and aerosol properties has been developed and tested at Rayference. This algorithm, named Combined Inversion of Surface and Aerosols (CISAR), includes a fast physically-based Radiative Transfer Model (RTM) accounting for the surface reflectance anisotropy and its coupling with aerosol scattering. This RTM explicitly solves the radiative transfer equation during the inversion process, without relying on pre-calculated integrals stored in LUT, allowing for a continuous variation of the state variables in the solution space. The inversion is based on a Optimal Estimation (OE) approach, which seeks for the best balance between the information coming from the observation and the a priori information. The a priori information is any additional knowledge on the observed system and it can concern the magnitude of the state variable or constraints on temporal and spectral variability. Both observations and priori information are provided with the corresponding uncertainty. For each processed spectral band, CISAR delivers the surface Bidirectional Reflectance Factor (BRF) and aerosol optical thickness, discriminating the effects of small and large particles. It also provides the associated uncertainty covariance matrix for every processed pixels. In the framework of the ESA aerosol_cci project, CISAR is applied on TOA BRF acquired by SEVIRI onboard Meteosat Second Generation (MSG) in the VIS0.6, VIS0.8 and NIR1.6 spectral bands. SEVIRI observations are accumulated during several days to document the surface anisotropy and minimize the impact of clouds. While surface radiative properties are supposed constant during this accumulation period, aerosol properties are derived on an hourly basis. The information content of each MSG/SEVIRI band will be provided based on the analysis of the posterior uncertainty covariance matrix. The analysis will demonstrate in particular the capability of CISAR to decouple the fraction of TOA BRF signal coming from the surface from the one originating from the aerosols. The results of the algorithm are compared with independent data sets of AOD and surface reflectance. Comparison with ground observations from the AERONET network shows a good agreement between these data. The surface reflectance evaluation is performed comparing white-sky albedo retrieved by CISAR with the MODIS surface product. This evaluation shows a very good consistency. The retrieved aerosol optical depth is consistent also in term of spatial distribution, being comparable in terms of geographical location and intensity.

Evaluating the impact of above-cloud aerosols on cloud optical depth retrievals from MODIS

NASA Astrophysics Data System (ADS)

Alfaro, Ricardo

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.

Climatology analysis of cirrus cloud in ARM site: South Great Plain

NASA Astrophysics Data System (ADS)

Olayinka, K.

2017-12-01

Cirrus cloud play an important role in the atmospheric energy balance and hence in the earth's climate system. The properties of optically thin clouds can be determined from measurements of transmission of the direct solar beam. The accuracy of cloud optical properties determined in this way is compromised by contamination of the direct transmission by light that is scattered into the sensors field of view. With the forward scattering correction method developed by Min et al., (2004), the accuracy of thin cloud retrievals from MFRSR has been improved. Our result shows over 30% of cirrus cloud present in the atmosphere are within optical depth between (1-2). In this study, we do statistics studies on cirrus clouds properties based on multi-years cirrus cloud measurements from MFRSR at ARM site from the South Great Plain (SGP) site due to its relatively easy accessibility, wide variability of climate cloud types and surface flux properties, large seasonal variation in temperature and specific humidity. Through the statistic studies, temporal and spatial variations of cirrus clouds are investigated. Since the presence of cirrus cloud increases the effect of greenhouse gases, we will retrieve the aerosol optical depth in all the cirrus cloud regions using a radiative transfer model for atmospheric correction. Calculate thin clouds optical depth (COD), and aerosol optical depth (AOD) using a radiative transfer model algorithm, e.g.: MODTRAN (MODerate resolution atmospheric TRANsmission)

Contributions to the Understanding of Aerosol Microphysics Towards Improving the Assessment of Climate Radiative Forcing

NASA Astrophysics Data System (ADS)

Dawson, Kyle William

The study of climate and the associated impacts imposed by human activity has garnered the attention of scientists and policy makers since the 1950s. Research into the various atmospheric constituents that interact with solar radiation thus modulating Earth's radiative budget has been largely focused on the contributions from greenhouse gases and later focused on the role of atmospheric aerosol. The role of atmospheric aerosol, i.e. a solid or aqueous phase particulate, is complex and presents an opportunity for bettering the assessments of climate radiative forcing (i.e. the fraction of climate change due to anthropogenic, rather than natural, activities) in several ways. First, motivated to better understand the radiative effects of the Earth's background aerosol state to improve the assessment of anthropogenic effects, an experimental study on the water uptake ability of xanthan gum as a proxy for marine hydrogel, a component of natural primary emitted seaspray aerosol, is presented. Marine hydrogel comprises an organic component of the ocean surface microlayer that is released to the atmosphere via the bursting of bubbles generated by entrainment of air through crashing waves. This study investigates the water uptake ability (i.e. hygroscopicity) of these particles when exposed to a range of relative humidity (RH). The hydration characteristics of aerosolized pure xanthan gum as well as xanthan gum/salt mixtures were studied using a hygroscopic tandem differential mobility analyzer (HTDMA) and cloud condensation nuclei counter (CCNc). The hygroscopicity of the various solutions were compared to theoretical thermodynamic calculations accounting for the component volume fractions as a function of relative humidity. The data show that pure xanthan gum aerosol hygroscopicity behaves as other organic polysaccharides and, when combined with salts, is reasonably approximated by the volume fraction mixing rules above 90% RH. Deviations occur below 90% RH as well as for CCNc measured hygroscopicity and HTDMA measured hygroscopicity at 90% RH, and are discussed in terms of hydration regimes associated with structural changes imposed by polymer/salt crosslinks. Second, motivated by a necessity to provide better constraints for climate model assessments of radiative forcing, a computational study for developing a link between climate models and observations from remote sensing techniques is presented. The Creating Aerosol Types from CHemistry (CATCH) algorithm has been developed for providing atmospheric models with estimated aerosol types, analogous to those that are retrieved by remote sensing methods. To date, the link between models and remote sensing retrievals is crude and is based on the total column attenuation of radiation by aerosol called the aerosol optical depth (AOD). In this study, through multivariate clustering techniques, this link is expanded to produce model-calculated aerosol types of dusty mix, maritime, urban, smoke, and fresh smoke, that are analogous to those retrieved by remote sensing. The CATCH algorithm shows that vertically-resolved aerosol types compare well to those measured by aircraft-mounted High Spectral Resolution Lidar - version 1 (HSRL-1) during the Ship-Aircraft Bio-Optical Research (SABOR) field campaign during July/August of 2014. Flight-by-flight comparisons of the type-apportioned AOD and vertically-resolved aerosol extinction also compare well. The CATCH algorithm is then applied to a high-resolution nested grid domain over North America and found to produce encouraging results of spatially relevant aerosol types such as dusty mix aerosol over the Caribbean, maritime aerosol over oceans, urban aerosol over large cities, smoke aerosol over weak forest fires, and fresh smoke aerosol over strong forest fires.

Spatiotemporal variability and contribution of different aerosol types to the Aerosol Optical Depth over the Eastern Mediterranean

PubMed Central

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2018-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the Aerosol Optical Depth (AOD) over the Eastern Mediterranean as derived from MODIS Terra (3/2000–12/2012) and Aqua (7/2002–12/2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sunphotometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium sized cities, industrial zones, and power plant complexes, seasonal variabilities, and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ~ 0.22 ± 0.19 with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in Central and Eastern Europe, and transport of dust from the Sahara Desert and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine mode natural aerosols account for ~ 51 %, ~ 34 % and ~ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ~ 40 %, ~ 34 % and ~ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations. PMID:29755508

Spatiotemporal variability and contribution of different aerosol types to the aerosol optical depth over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-11-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ˜ 0.22 ± 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for ˜ 51, ˜ 34 and ˜ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ˜ 40, ˜ 34 and ˜ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Spatiotemporal Variability and Contribution of Different Aerosol Types to the Aerosol Optical Depth over the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Poeschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1deg × 0.1deg gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is approx. 0.22 +/- 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for approx. 51, approx. 34 and approx. 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account approx. 40, approx. 34 and approx. 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Spatiotemporal variability and contribution of different aerosol types to the Aerosol Optical Depth over the Eastern Mediterranean.

PubMed

Georgoulias, Aristeidis K; Alexandri, Georgia; Kourtidis, Konstantinos A; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the Aerosol Optical Depth (AOD) over the Eastern Mediterranean as derived from MODIS Terra (3/2000-12/2012) and Aqua (7/2002-12/2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sunphotometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium sized cities, industrial zones, and power plant complexes, seasonal variabilities, and decadal averages. The average AOD at 550 nm (AOD 550 ) for the entire region is ~ 0.22 ± 0.19 with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in Central and Eastern Europe, and transport of dust from the Sahara Desert and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD 550 . The spatial and temporal variability of anthropogenic, dust and fine mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD 550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine mode natural aerosols account for ~ 51 %, ~ 34 % and ~ 15 % of the total AOD 550 over land, while, anthropogenic aerosols, dust and marine aerosols account ~ 40 %, ~ 34 % and ~ 26 % of the total AOD 550 over the sea, based on MODIS Terra and Aqua observations.

Development and evaluation of a high-resolution aerosol optical depth product for the southern California region during the October 2007 wildfires

NASA Astrophysics Data System (ADS)

McCarthy, M. C.; Raffuse, S. M.; Dewinter, J. L.; Lurmann, F.; Craig, K. J.; Fruin, S.

2010-12-01

Current methods for estimating acute exposure to high levels of air pollution (e.g., particles, CO, NOx, aldehydes) during fire events require spatial interpolation over the study area using concentrations at central air quality monitors to represent the population of interest. This may inaccurately represent the magnitude of exposure because pollutant concentrations vary widely depending on the location of the fire plume, vertical mixing, and prevailing winds dispersing the pollutant. Remotely sensed datasets, such as aerosol optical depth (AOD) from the NASA MODIS instrument, can provide greater spatial coverage than ground-based air quality monitors. Past studies have shown positive correlations between AOD, a measure of aerosols in an atmospheric column, and ground-level measurements of PM2.5 and PM10 concentrations. However, current standard AOD products are not sufficient for assessing intra-urban variability due to the low spatial resolution (e.g., 10x10 km for MODIS) of datasets. In addition such products typically perform poorly with very dense smoke in the atmosphere and over reflective, semi-arid land surfaces such as southern California. A highly resolved AOD product (500m resolution) was developed for southern California during the October 2007 fires using radiance data obtained from the National Aeronautics and Space Administration (NASA) MODIS instrument. AOD was calculated at 0.55µm wavelength using a unique algorithm tailored to the southern California region and for an atmosphere dominated by biomass burning aerosols. The AOD product was compared with column measurements of AOD from surface-based AERONET sites. AOD was not predictive of surface PM during the October 2007 fires when compared to surface PM concentrations throughout southern California; R-square correlation coefficients were low. However, the relationship varied during the time period studied: correlations were weak early in the event (0.02) but improved during the later days of the event (0.3). Heavy dust episodes early in the fire event were poorly represented by the biomass-specific aerosol optical properties model. In addition, lofted smoke plumes from active fires did not mix down to the surface, resulting in high AOD column estimates and low surface PM concentrations. The aerosol was more dispersed later in the event; elevated surface PM concentrations were coincident with moderate AOD values. The case study demonstrates the challenges in using remote measurements in quantifying surface concentrations during active fire events in areas of complex terrain.

Refined Use of Satellite Aerosol Optical Depth Snapshots to Constrain Biomass Burning Emissions in the GOCART Model

NASA Astrophysics Data System (ADS)

Petrenko, Mariya; Kahn, Ralph; Chin, Mian; Limbacher, James

2017-10-01

Simulations of biomass burning (BB) emissions in global chemistry and aerosol transport models depend on external inventories, which provide location and strength for BB aerosol sources. Our previous work shows that to first order, satellite snapshots of aerosol optical depth (AOD) near the emitted smoke plume can be used to constrain model-simulated AOD, and effectively, the smoke source strength. We now refine the satellite-snapshot method and investigate where applying simple multiplicative emission adjustment factors alone to the widely used Global Fire Emission Database version 3 emission inventory can achieve regional-scale consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) AOD snapshots and the Goddard Chemistry Aerosol Radiation and Transport model. The model and satellite AOD are compared globally, over a set of BB cases observed by the MODIS instrument during the 2004, and 2006-2008 biomass burning seasons. Regional discrepancies between the model and satellite are diverse around the globe yet quite consistent within most ecosystems. We refine our approach to address physically based limitations of our earlier work (1) by expanding the number of fire cases from 124 to almost 900, (2) by using scaled reanalysis-model simulations to fill missing AOD retrievals in the MODIS observations, (3) by distinguishing the BB components of the total aerosol load from background aerosol in the near-source regions, and (4) by including emissions from fires too small to be identified explicitly in the satellite observations. The small-fire emission adjustment shows the complimentary nature of correcting for source strength and adding geographically distinct missing sources. Our analysis indicates that the method works best for fire cases where the BB fraction of total AOD is high, primarily evergreen or deciduous forests. In heavily polluted or agricultural burning regions, where smoke and background AOD values tend to be comparable, this approach encounters large uncertainties, and in some regions, other model- or measurement-related factors might contribute significantly to model-satellite discrepancies. This work sets the stage for a larger study within the Aerosol Comparison between Observations and Models (AeroCOM) multimodel biomass burning experiment. By comparing multiple model results using the refined technique presented here, we aim to separate BB inventory from model-specific contributions to the remaining discrepancies.

Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

NASA Technical Reports Server (NTRS)

Li, Jing; Li, Xichen; Carlson, Barbara E.; Kahn, Ralph A.; Lacis, Andrew A.; Dubovik, Oleg; Nakajima, Teruyuki

2016-01-01

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

Aerosol optical properties and radiative impacts in the Pearl River Delta region of China during the dry season

NASA Astrophysics Data System (ADS)

Mai, Boru; Deng, Xuejiao; Li, Zhanqing; Liu, Jianjun; Xia, Xiang'ao; Che, Huizheng; Liu, Xia; Li, Fei; Zou, Yu; Cribb, Maureen

2018-02-01

Aerosol optical properties and direct radiative effects on surface irradiance were examined using seven years (2006-2012) of Cimel sunphotometer data collected at Panyu—the main atmospheric composition monitoring station in the Pearl River Delta (PRD) region of China. During the dry season (October to February), mean values of the aerosol optical depth (AOD) at 550 nm, the Ångström exponent, and the single scattering albedo at 440 nm (SSA) were 0.54, 1.33 and 0.87, respectively. About 90% of aerosols were dominated by fine-mode strongly absorbing particles. The size distribution was bimodal, with fine-mode particles dominating. The fine mode showed a peak at a radius of 0.12 μm in February and October (˜ 0.10 μm3μm-2). The mean diurnal shortwave direct radiative forcing at the surface, inside the atmosphere ( F ATM), and at the top of the atmosphere, was -33.4±7.0, 26.1±5.6 and -7.3±2.7Wm-2, respectively. The corresponding mean values of aerosol direct shortwave radiative forcing per AOD were -60.0 ± 7.8, 47.3 ± 8.3 and -12.8 ± 3.1 W m-2, respectively. Moreover, during the study period, F ATM showed a significant decreasing trend ( p < 0.01) and SSA increased from 0.87 in 2006 to 0.91 in 2012, suggesting a decreasing trend of absorbing particles being released into the atmosphere. Optical properties and radiative impacts of the absorbing particles can be used to improve the accuracy of inversion algorithms for satellite-based aerosol retrievals in the PRD region and to better constrain the climate effect of aerosols in climate models.

Validating Above-cloud Aerosol Optical Depth Retrieved from MODIS using NASA Ames Airborne Sun-Tracking Photometric and Spectrometric (AATS and 4STAR) Measurements

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Remer, L. A.; Redemann, J.; Dunagan, S. E.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Segal-Rosenhaimer, M.

2014-12-01

Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay the lower level cloud decks as evident in the satellite images. In contrast to the cloud-free atmosphere, in which aerosols generally tend to cool the atmosphere, the presence of absorbing aerosols above cloud poses greater potential of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. In recent years, development of algorithms that exploit satellite-based passive measurements of ultraviolet (UV), visible, and polarized light as well as lidar-based active measurements constitute a major breakthrough in the field of remote sensing of aerosols. While the unprecedented quantitative information on aerosol loading above cloud is now available from NASA's A-train sensors, a greater question remains ahead: How to validate the satellite retrievals of above-cloud aerosols (ACA)? Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. In this study, we validate the ACA optical depth retrieved using the 'color ratio' (CR) method applied to the MODIS cloudy-sky reflectance by using the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS-2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (root-mean-square-error<0.1 for Aerosol Optical Depth (AOD) at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals (-10% to +50%). An extensive validation of satellite-based ACA retrievals requires equivalent field measurements particularly over the regions where ACA are often observed from satellites, i.e., south-eastern Atlantic Ocean, tropical Atlantic Ocean, northern Arabian Sea, South-East and North-East Asia.

Increased aerosol content in the atmosphere over Ukraine during summer 2010

NASA Astrophysics Data System (ADS)

Galytska, Evgenia; Danylevsky, Vassyl; Hommel, René; Burrows, John P.

2018-04-01

In this paper we assessed the influence of biomass burning during forest fires throughout summer (1 June-31 August) 2010 on aerosol abundance, dynamics, and its properties over Ukraine. We also considered influences and effects over neighboring countries: European Russia, Estonia, Belarus, Poland, Moldova, and Romania. We used MODIS satellite instrument data to study fire distribution. We also used ground-based remote measurements from the international sun photometer network AERONET plus MODIS and CALIOP satellite instrument data to determine the aerosol content and optical properties in the atmosphere over Eastern Europe. We applied the HYSPLIT model to investigate atmospheric dynamics and model pathways of particle transport. As with previous studies, we found that the highest aerosol content was observed over Moscow in the first half of August 2010 due to the proximity of the most active fires. Large temporal variability of the aerosol content with pronounced pollution peaks during 7-17 August was observed at the Ukrainian (Kyiv and Sevastopol), Belarusian (Minsk), Estonian (Toravere), and Romanian (Bucharest) AERONET sites. We analyzed aerosol spatiotemporal distribution over Ukraine using MODIS AOD 550 nm and further compared with the Kyiv AERONET site sun photometer measurements; we also compared CALIOP AOD 532 nm with MODIS AOD data. We analyzed vertical distribution of aerosol extinction at 532 nm, retrieved from CALIOP measurements, for the territory of Ukraine at locations where high AOD values were observed during intense fires. We estimated the influence of fires on the spectral single scattering albedo, size distribution, and complex refractive indices using Kyiv AERONET measurements performed during summer 2010. In this study we showed that the maximum AOD in the atmosphere over Ukraine recorded in summer 2010 was caused by particle transport from the forest fires in Russia. Those fires caused the highest AOD 500 nm over the Kyiv site, which in August 2010 exceeded multiannual monthly mean for the entire observational period (2008-2016, excluding 2010) by a factor of 2.2. Also, the influence of fires resulted in a change of the particle microphysics in the polluted regions.

Consistency of Global Modis Aerosol Optical Depths over Ocean on Terra and Aqua Ceres SSF Datasets

NASA Technical Reports Server (NTRS)

Ignatov, Alexander; Minnis, Patrick; Miller, Walter F.; Wielicki, Bruce A.; Remer, Lorraine

2006-01-01

Aerosol retrievals over ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side-by-side. The primary M product is generated by sub-setting and remapping the multi-spectral (0.47-2.1 micrometer) MODIS produced oceanic aerosol (MOD04/MYD04 for Terra/Aqua) onto CERES footprints. M*D04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary AVHRR-like A product is generated in only two MODIS bands 1 and 6 (on Aqua, bands 1 and 7). The A processing uses the CERES cloud screening algorithm, and NOAA/NESDIS glint identification, and single-channel aerosol retrieval algorithms. The M and A products have been documented elsewhere and preliminarily compared using 2 weeks of global Terra CERES SSF Edition 1A data in which the M product was based on MOD04 collection 3. In this study, the comparisons between the M and A aerosol optical depths (AOD) in MODIS band 1 (0.64 micrometers), tau(sub 1M) and tau(sub 1A) are re-examined using 9 days of global CERES SSF Terra Edition 2A and Aqua Edition 1B data from 13 - 21 October 2002, and extended to include cross-platform comparisons. The M and A products on the new CERES SSF release are generated using the same aerosol algorithms as before, but with different preprocessing and sampling procedures, lending themselves to a simple sensitivity check to non-aerosol factors. Both tau(sub 1M) and tau(sub 1A) generally compare well across platforms. However, the M product shows some differences, which increase with ambient cloud amount and towards the solar side of the orbit. Three types of comparisons conducted in this study - cross-platform, cross-product, and cross-release confirm the previously made observation that the major area for improvement in the current aerosol processing lies in a more formalized and standardized sampling (and most importantly, cloud screening) whereas optimization of the aerosol algorithm is deemed to be an important yet less critical element.

Influence of Desert Dust Intrusions on Ground-based and Satellite Derived Ultraviolet Irradiance in Southeastern Spain

NASA Technical Reports Server (NTRS)

Krotkov, Nickolay A.; Anton, Manuel; Valenzuela, Antonio; Roman, Roberto; Lyamani, Hassan; Arola, Antti; Olmo, Francisco J.; Alados-Arboledas

2012-01-01

The desert dust aerosols strongly affect propagation of solar radiation through the atmosphere, reducing surface irradiance available for photochemistry and photosynthesis. This paper evaluates effects of desert dust on surface UV erythemal irradiance (UVER), as measured by a ground-based broadband UV radiometer and retrieved from the satellite Ozone Monitoring Instrument (OMI) at Granada (southern Spain) from January 2006 to December 2010. The dust effects are characterized by the transmittance ra tio of the measured UVER to the corresponding modeled clear sky value. The transmittance has an exponential dependency on aerosol optical depth (AOD), with minimum values of approximately 0.6 (attenuation of approximately 40%). The OMI UVER algorithm does not account for UV aerosol absorption, which results in overestimation of the ground-based UVER especially during dust episodes with a mean relative difference up to 40%. The application of aerosol absorption post-correction method reduces OMI bias up to approximately 13%. The results highlight great effect of desert dust on the surface UV irradiance in regions like southern Spain, where dust intrusions from Sahara region are very frequent.

The Use of Aerosol Optical Depth in Estimating Trace Gas Emissions from Biomass Burning Plumes

NASA Astrophysics Data System (ADS)

Jones, N.; Paton-Walsh, C.; Wilson, S.; Meier, A.; Deutscher, N.; Griffith, D.; Murcray, F.

2003-12-01

We have observed significant correlations between aerosol optical depth (AOD) at 500 nm and column amounts of a number of biomass burning indicators (carbon monoxide, hydrogen cyanide, formaldehyde and ammonia) in bushfire smoke plumes over SE Australia during the 2001/2002 and 2002/2003 fire seasons from remote sensing measurements. The Department of Chemistry, University of Wollongong, operates a high resolution Fourier Transform Spectrometer (FTS), in the city of Wollongong, approximately 80 km south of Sydney. During the recent bushfires we collected over 1500 solar FTIR spectra directly through the smoke over Wollongong. The total column amounts of the biomass burning indicators were calculated using the profile retrieval software package SFIT2. Using the same solar beam, a small grating spectrometer equipped with a 2048 pixel CCD detector array, was used to calculate simultaneous aerosol optical depths. This dataset is therefore unique in its temporal sampling, location to active fires, and range of simultaneously measured constituents. There are several important applications of the AOD to gas column correlation. The estimation of global emissions from biomass burning currently has very large associated uncertainties. The use of visible radiances measured by satellites, and hence AOD, could significantly reduce these uncertainties by giving a direct estimate of global emissions of gases from biomass burning through application of the AOD to gas correlation. On a more local level, satellite-derived aerosol optical depth maps could be inverted to infer approximate concentration levels of smoke-related pollutants at the ground and in the lower troposphere, and thus can be used to determine the nature of any significant health impacts.

Near-Surface PM2.5 Concentrations Derived from Satellites, Simulation and Ground Monitors

NASA Astrophysics Data System (ADS)

van Donkelaar, A.; Martin, R.; Hsu, N. Y. C.; Kahn, R. A.; Levy, R. C.; Lyapustin, A.; Sayer, A. M.; Brauer, M.

2015-12-01

Exposure to fine particulate matter (PM2.5) is globally associated with 3.2 million premature deaths annually. Satellite retrievals of total column aerosol optical depth (AOD) from instruments such as MODIS, MISR and SeaWiFS are related to PM2.5 through local aerosol vertical profiles and optical properties. A globally applicable and geophysically-based AOD to PM2.5 relationship can be calculated from chemical transport model (CTM) simulations. This approach, while effective, ignores the wealth of ground monitoring data that exist in some regions of the world. We therefore use ground monitors to develop a geographically weighted regression (GWR) that predicts the residual bias in geophysically-based satellite-derived PM2.5. Predictors such as the AOD to PM2.5 relationship resolution, land cover type, and chemical composition are used to predict this bias, which can then be used to improve the initial PM2.5 estimates. This approach not only allows for direct bias correction, but also provides insight into factors biasing the initial CTM-derived AOD to PM2.5 relationship. Over North America, we find significant improvement in bias-corrected PM2.5 (r2=0.82 versus r2=0.62), with evidence that fine-scale variability in surface elevation and urban factors are major sources of error in the CTM-derived relationships. Agreement remains high (r2=0.78) even when a large fraction of ground monitors (70%) are withheld from the GWR, suggesting this technique may add value in regions with even sparse ground monitoring networks, and potentially worldwide.

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

2017-12-01

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

Temporal and spatial distributions of summer-time ground-level fine particulate matters in Baltimore-DC region

NASA Astrophysics Data System (ADS)

Liu, Y.; Greenwald, R.; Sarnat, J.; Hu, X.; Kewada, P.; Morales, Y.; Goldman, G.; Redman, J.; Russell, A. G.

2011-12-01

Environmental epidemiological studies have established a robust association between chronic exposure to ambient level fine particulate matters (PM2.5) and adverse health effects such as COPD, cardiorespiratory diseases, and premature death. Population exposure to PM2.5 has historically been estimated using ground measurements which are often sparse and unevenly distributed. There has been much interest as well as suspicion in both the air quality management and research communities regarding the value of satellite retrieved AOD as particle air pollution indicators. A critical step towards the future use of satellite aerosol products in air quality monitoring and management is to better understand the AOD-PM2.5 association. The existing EPA and IMPROVE networks are insufficient to validate AOD-estimated PM2.5 surface especially when higher resolution satellite products become available in the near future. As part of DISCOVER-AQ mission, we deployed 15 portable filter-based samplers alongside of ground-based sun photometers of the Distributed Regional Aerosol Gridded Observation Network (DRAGON) in July 2011. Gravimetric analyses were conducted to estimate 24h PM2.5 mass concentrations, using Teflon filters and Personal Environmental Monitors (PEMs) operated at a flow rate of 4 LPM. Pre- and post-sampling filters were weighed at our weigh room laboratory facilities at the Georgia Institute of Technology. Our objectives are (1) to examine if AOD measured by ground-based sun-photometers with the support from ground-based lidars can provide the fine scale spatial heterogeneity observed by ground PM monitors, and (2) whether PM2.5 levels estimated by satellite AOD agree with this true PM2.5 surface. Study design, instrumentation, and preliminary results of measured PM2.5 spatial patterns in July 2011 will be presented as well as discussion of further data analysis and model development.

Spatiotemporal characteristics of aerosols and their trends over mainland China with the recent Collection 6 MODIS and OMI satellite datasets.

PubMed

Hu, Kang; Kumar, Kanike Raghavendra; Kang, Na; Boiyo, Richard; Wu, Jinwen

2018-03-01

With the rapid development of China's economy and high rate of industrialization, environmental pollution has become a major challenge for the country. The present study is aimed at analyzing spatiotemporal heterogeneities and changes in trends of different aerosol optical properties observed over China. To achieve this, Collection 6 Level 3 data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS; 2002-2016) and Ozone Monitoring Instrument (OMI; 2005-2016) sensors were used to investigate aerosol optical depth (AOD 550 ), Ångstrӧm exponent (AE 470-660 ), and Absorption Aerosol Index (AAI). The spatial distribution of annual mean AOD 550 was noticed to be high over economically and industrialized regions of the east, south, and northeast of China, while low aerosol loadings were located over rural and less-developed areas of the west and northeast of China. High AE 470-660 (> 1.0) values were characterized by the abundance of fine-mode particles and vice versa, likely attributed to large anthropogenic activities. Similarly, high AOD with corresponding high AE and low AAI was characterized over the urban-industrialized regions of the central, east, and south of China during most of the months, being more pronounced in June and July. On seasonal scale, AOD values were found to be high during spring, followed by the summer and autumn, and low during the winter season. It is also evident that all aerosol parameters showed a single-peak frequency distribution in all seasons over entire China. Further, the annual, monthly, and seasonal spatial trends revealed a decreasing trend in AOD over most regions of China, except in the southwest of China, which showed a positive increasing trend. Significant increasing trends were noted in AAI for all the seasons, particularly during autumn and winter, resulting in a large amount of the absorbing type of aerosols produced from biomass burning and desert dust.

Aircraft- and ground-based assessment of the CCN-AOD relationship and implications on model analysis of ACI and underlying aerosol processes

NASA Astrophysics Data System (ADS)

Shinozuka, Y.; Clarke, A. D.; Nenes, A.; Lathem, T. L.; Redemann, J.; Jefferson, A.; Wood, R.

2014-12-01

Contrary to common assumptions in satellite-based modeling of aerosol-cloud interactions, ∂logCCN/∂logAOD is less than unity, i.e., the number concentration of cloud condensation nuclei (CCN) less than doubles as aerosol optical depth (AOD) doubles. This can be explained by omnipresent aerosol processes. Condensation, coagulation and cloud processing, for example, generally make particles scatter more light while hardly increasing their number. This paper reports on the relationship in local air masses between CCN concentration, aerosol size distribution and light extinction observed from aircraft and the ground at diverse locations. The CCN-to-local-extinction relationship, when averaged over ~1 km distance and sorted by the wavelength dependence of extinction, varies approximately by a factor of 2, reflecting the variability in aerosol intensive properties. This, together with retrieval uncertainties and the variability in aerosol spatio-temporal distribution and hygroscopic growth, challenges satellite-based CCN estimates. However, the large differences in estimated CCN may correspond to a considerably lower uncertainty in cloud drop number concentration (CDNC), given the sublinear response of CDNC to CCN. Overall, our findings from airborne and ground-based observations call for model-based reexamination of aerosol-cloud interactions and underlying aerosol processes.

A 4-D Climatology (1979-2009) of the Monthly Tropospheric Aerosol Optical Depth Distribution over the Mediterranean Region from a Comparative Evaluation and Blending of Remote Sensing and Model Products

NASA Technical Reports Server (NTRS)

Nabat, P.; Somot, S.; Mallet, M.; Chiapello, I; Morcrette, J. J.; Solomon, F.; Szopa, S.; Dulac, F; Collins, W.; Ghan, S.;

SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

NASA Astrophysics Data System (ADS)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

2016-04-01

Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the Czech Republic, and the Gorj County in Romania. All data products shall undergo a quality control, i.e. robust and independent validation. The SAMIRA consortium will further work towards a pre-operational system for improved PM10 forecasts using observational (in situ and satellite) data assimilation. SAMIRA aims to maximize project benefits by liaison with national and regional environmental protection agencies and health institutions, as well as related ESA and European initiatives such as the Copernicus Atmospheric Monitoring Services (CAMS).

Radiative characteristics of clouds embedded in smoke derived from airborne multiangular measurements

NASA Astrophysics Data System (ADS)

Gautam, Ritesh; Gatebe, Charles K.; Singh, Manoj K.; Várnai, Tamás.; Poudyal, Rajesh

2016-08-01

Clouds in the presence of absorbing aerosols result in their apparent darkening, observed at the top of atmosphere (TOA), which is associated with the radiative effects of aerosol absorption. Owing to the large radiative effect and potential impacts on regional climate, above-cloud aerosols have recently been characterized in multiple satellite-based studies. While satellite data are particularly useful in showing the radiative impact of above-cloud aerosols at the TOA, recent literature indicates large uncertainties in satellite retrievals of above-cloud aerosol optical depth (AOD) and single scattering albedo (SSA), which are among the most important parameters in the assessment of associated radiative effects. In this study, we analyze radiative characteristics of clouds in the presence of wildfire smoke using airborne data primarily from NASA's Cloud Absorption Radiometer, collected during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites campaign in Canada during the 2008 summer season. We found a strong positive reflectance (R) gradient in the UV-visible (VIS)-near infrared (NIR) spectrum for clouds embedded in dense smoke, as opposed to an (expected) negative gradient for cloud-free smoke and a flat spectrum for smoke-free cloud cover. Several cases of clouds embedded in thick smoke were found, when the aircraft made circular/spiral measurements, which not only allowed the complete characterization of angular distribution of smoke scattering but also provided the vertical distribution of smoke and clouds (within 0.5-5 km). Specifically, the largest darkening by smoke was found in the UV/VIS, with R0.34μm reducing to 0.2 (or 20%), in contrast to 0.8 at NIR wavelengths (e.g., 1.27 µm). The observed darkening is associated with large AODs (0.5-3.0) and moderately low SSA (0.85-0.93 at 0.53 µm), resulting in a significantly large instantaneous aerosol forcing efficiency of 254 ± 47 W m-2 τ-1. Our observations of smoke-cloud radiative interactions were found to be physically consistent with theoretical plane-parallel 1-D and Monte Carlo 3-D radiative transfer calculations, capturing the observed gradient across UV-VIS-NIR. Results from this study offer insights into aerosol-cloud radiative interactions and may help in better constraining satellite retrieval algorithms.

Radiative Characteristics of Clouds Embedded in Smoke Derived from Airborne Multiangular Measurements

NASA Technical Reports Server (NTRS)

Gautam, Ritesh; Gatebe, Charles K.; Singh, Manoj; Varnai, Tamas; Poudyal, Rajesh

2016-01-01

Clouds in the presence of absorbing aerosols result in their apparent darkening, observed at the top of atmosphere (TOA), which is associated with the radiative effects of aerosol absorption. Owing to the large radiative effect and potential impacts on regional climate, above-cloud aerosols have recently been characterized in multiple satellite-based studies. While satellite data are particularly useful in showing the radiative impact of above-cloud aerosols at the TOA, recent literature indicates large uncertainties in satellite retrievals of above-cloud aerosol optical depth (AOD) and single scattering albedo (SSA), which are among the most important parameters in the assessment of associated radiative effects. In this study, we analyze radiative characteristics of clouds in the presence of wildfire smoke using airborne data primarily from NASA's Cloud Absorption Radiometer, collected during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites campaign in Canada during the 2008 summer season. We found a strong positive reflectance (R) gradient in the UV-visible (VIS)-near infrared (NIR) spectrum for clouds embedded in dense smoke, as opposed to an (expected) negative gradient for cloud-free smoke and a flat spectrum for smoke-free cloud cover. Several cases of clouds embedded in thick smoke were found, when the aircraft made circular/spiral measurements, which not only allowed the complete characterization of angular distribution of smoke scattering but also provided the vertical distribution of smoke and clouds (within 0.5-5 km). Specifically, the largest darkening by smoke was found in the UV/VIS, with R(sub 0.34 microns) reducing to 0.2 (or 20%), in contrast to 0.8 at NIR wavelengths (e.g., 1.27 microns). The observed darkening is associated with large AODs (0.5-3.0) and moderately low SSA (0.85-0.93 at 0.53 microns), resulting in a significantly large instantaneous aerosol forcing efficiency of 254 +/- 47 W/sq m/t. Our observations of smoke-cloud radiative interactions were found to be physically consistent with theoretical plane-parallel 1-D and Monte Carlo 3-D radiative transfer calculations, capturing the observed gradient across UV-VIS-NIR. Results from this study offer insights into aerosol-cloud radiative interactions and may help in better constraining satellite retrieval algorithms.

Investigation of Panchromatic Satellite Imagery Sensor Low Bias in Shadow Method Aerosol Optical Depth Retrieval

DTIC Science & Technology

2009-03-01

value. While these instruments may be well suited for academic research, they are generally not useful for battlefield measurements. Airborne and...may be too generalized for use with current tactical decision aids in the high-resolution, high- precision environment of the modern battlefield...imager resolutions on the order of less than 1 meter, shadows from small features such as buildings can be used to effectively measure the AOD in the

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data.

PubMed

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C; Schwartz, Joel; Broday, David M

2015-12-01

Estimates of exposure to PM 2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM 2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM 2.5 and PM 10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM 2.5 and PM 10 over Israel. We later constructed daily predictions across Israel for 2003-2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R 2 values of 0.79 and 0.72 for PM 10 and PM 2.5 , respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM 2.5 and PM 10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM 2.5 and PM 10 in Israel, which could be used in the future for epidemiological studies.

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data

PubMed Central

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C.; Schwartz, Joel; Broday, David M.

2017-01-01

Estimates of exposure to PM2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM2.5 and PM10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM2.5 and PM10 over Israel. We later constructed daily predictions across Israel for 2003–2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R2 values of 0.79 and 0.72 for PM10 and PM2.5, respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM2.5 and PM10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM2.5 and PM10 in Israel, which could be used in the future for epidemiological studies. PMID:28966551

ACE-Asia Aerosol Optical Depth and Water Vapor Measured by Airborne Sunphotometers and Related to Other Measurements and Calculations

NASA Technical Reports Server (NTRS)

Livingston, John M.; Russell, P. B.; Schmid, B.; Redemann, J.; Eilers, J. A.; Ramirez, S. A.; Kahn, R.; Hegg, D.; Pilewskie, P.; Anderson, T.;

Identification of aerosol types over an urban site based on air-mass trajectory classification

NASA Astrophysics Data System (ADS)

Pawar, G. V.; Devara, P. C. S.; Aher, G. R.

2015-10-01

Columnar aerosol properties retrieved from MICROTOPS II Sun Photometer measurements during 2010-2013 over Pune (18°32‧N; 73°49‧E, 559 m amsl), a tropical urban station in India, are analyzed to identify aerosol types in the atmospheric column. Identification/classification is carried out on the basis of dominant airflow patterns, and the method of discrimination of aerosol types on the basis of relation between aerosol optical depth (AOD500 nm) and Ångström exponent (AE, α). Five potential advection pathways viz., NW/N, SW/S, N, SE/E and L have been identified over the observing site by employing the NOAA-HYSPLIT air mass back trajectory analysis. Based on AE against AOD500 nm scatter plot and advection pathways followed five major aerosol types viz., continental average (CA), marine continental average (MCA), urban/industrial and biomass burning (UB), desert dust (DD) and indeterminate or mixed type (MT) have been identified. In winter, sector SE/E, a representative of air masses traversed over Bay of Bengal and Eastern continental Indian region has relatively small AOD (τpλ = 0.43 ± 0.13) and high AE (α = 1.19 ± 0.15). These values imply the presence of accumulation/sub-micron size anthropogenic aerosols. During pre-monsoon, aerosols from the NW/N sector have high AOD (τpλ = 0.61 ± 0.21), and low AE (α = 0.54 ± 0.14) indicating an increase in the loading of coarse-mode particles over Pune. Dominance of UB type in winter season for all the years (i.e. 2010-2013) may be attributed to both local/transported aerosols. During pre-monsoon seasons, MT is the dominant aerosol type followed by UB and DD, while the background aerosols are insignificant.

Regional characteristics of the relationship between columnar AOD and surface PM2.5: Application of lidar aerosol extinction profiles over Baltimore-Washington Corridor during DISCOVER-AQ

NASA Astrophysics Data System (ADS)

Chu, D. Allen; Ferrare, Richard; Szykman, James; Lewis, Jasper; Scarino, Amy; Hains, Jennifer; Burton, Sharon; Chen, Gao; Tsai, Tzuchin; Hostetler, Chris; Hair, Johnathan; Holben, Brent; Crawford, James

2015-01-01

The first field campaign of DISCOVER-AQ (Deriving Information on Surface conditions from COlumn and VERtically resolved observations relevant to Air Quality) took place in July 2011 over Baltimore-Washington Corridor (BWC). A suite of airborne remote sensing and in-situ sensors was deployed along with ground networks for mapping vertical and horizontal distribution of aerosols. Previous researches were based on a single lidar station because of the lack of regional coverage. This study uses the unique airborne HSRL (High Spectral Resolution Lidar) data to baseline PM2.5 (particulate matter of aerodynamic diameter less than 2.5 μm) estimates and applies to regional air quality with satellite AOD (Aerosol Optical Depth) retrievals over BWC (∼6500 km2). The linear approximation takes into account aerosols aloft above AML (Aerosol Mixing Layer) by normalizing AOD with haze layer height (i.e., AOD/HLH). The estimated PM2.5 mass concentrations by HSRL AOD/HLH are shown within 2 RMSE (Root Mean Square Error ∼9.6 μg/m3) with correlation ∼0.88 with the observed over BWC. Similar statistics are shown when applying HLH data from a single location over the distance of 100 km. In other words, a single lidar is feasible to cover the range of 100 km with expected uncertainties. The employment of MPLNET-AERONET (MicroPulse Lidar NETwork - AErosol RObotic NETwork) measurements at NASA GSFC produces similar statistics of PM2.5 estimates as those derived by HSRL. The synergy of active and passive remote sensing aerosol measurements provides the foundation for satellite application of air quality on a daily basis. For the optimal range of 10 km, the MODIS-estimated PM2.5 values are found satisfactory at 27 (out of 36) sunphotometer locations with mean RMSE of 1.6-3.3 μg/m3 relative to PM2.5 estimated by sunphotometers. The remaining 6 of 8 marginal sites are found in the coastal zone, for which associated large RMSE values ∼4.5-7.8 μg/m3 are most likely due to overestimated AOD because of water-contaminated pixels.

Atmospheric correction over coastal waters using multilayer neural networks

NASA Astrophysics Data System (ADS)

Fan, Y.; Li, W.; Charles, G.; Jamet, C.; Zibordi, G.; Schroeder, T.; Stamnes, K. H.

2017-12-01

Standard atmospheric correction (AC) algorithms work well in open ocean areas where the water inherent optical properties (IOPs) are correlated with pigmented particles. However, the IOPs of turbid coastal waters may independently vary with pigmented particles, suspended inorganic particles, and colored dissolved organic matter (CDOM). In turbid coastal waters standard AC algorithms often exhibit large inaccuracies that may lead to negative water-leaving radiances (Lw) or remote sensing reflectance (Rrs). We introduce a new atmospheric correction algorithm for coastal waters based on a multilayer neural network (MLNN) machine learning method. We use a coupled atmosphere-ocean radiative transfer model to simulate the Rayleigh-corrected radiance (Lrc) at the top of the atmosphere (TOA) and the Rrs just above the surface simultaneously, and train a MLNN to derive the aerosol optical depth (AOD) and Rrs directly from the TOA Lrc. The SeaDAS NIR algorithm, the SeaDAS NIR/SWIR algorithm, and the MODIS version of the Case 2 regional water - CoastColour (C2RCC) algorithm are included in the comparison with AERONET-OC measurements. The results show that the MLNN algorithm significantly improves retrieval of normalized Lw in blue bands (412 nm and 443 nm) and yields minor improvements in green and red bands. These results indicate that the MLNN algorithm is suitable for application in turbid coastal waters. Application of the MLNN algorithm to MODIS Aqua images in several coastal areas also shows that it is robust and resilient to contamination due to sunglint or adjacency effects of land and cloud edges. The MLNN algorithm is very fast once the neural network has been properly trained and is therefore suitable for operational use. A significant advantage of the MLNN algorithm is that it does not need SWIR bands, which implies significant cost reduction for dedicated OC missions. A recent effort has been made to extend the MLNN AC algorithm to extreme atmospheric conditions (i.e. heavy polluted continental aerosols) over coastal areas by including additional aerosol and ocean models to generate the training dataset. Preliminary tests show very good results. Results of applying the extended MLNN algorithm to VIIRS images over the Yellow Sea and East China Sea areas with extreme atmospheric and marine conditions will be provided.

A novel image retrieval algorithm based on PHOG and LSH

NASA Astrophysics Data System (ADS)

Wu, Hongliang; Wu, Weimin; Peng, Jiajin; Zhang, Junyuan

2017-08-01

PHOG can describe the local shape of the image and its relationship between the spaces. The using of PHOG algorithm to extract image features in image recognition and retrieval and other aspects have achieved good results. In recent years, locality sensitive hashing (LSH) algorithm has been superior to large-scale data in solving near-nearest neighbor problems compared with traditional algorithms. This paper presents a novel image retrieval algorithm based on PHOG and LSH. First, we use PHOG to extract the feature vector of the image, then use L different LSH hash table to reduce the dimension of PHOG texture to index values and map to different bucket, and finally extract the corresponding value of the image in the bucket for second image retrieval using Manhattan distance. This algorithm can adapt to the massive image retrieval, which ensures the high accuracy of the image retrieval and reduces the time complexity of the retrieval. This algorithm is of great significance.

A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

NASA Astrophysics Data System (ADS)

Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

2011-12-01

The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

A 4-D Climatology (1979-2009) of the Monthly Tropospheric Aerosol Optical Depth Distribution over the Mediterranean Region from a Comparative Evaluation and Blending of Remote Sensing and Model Products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nabat, P.; Somot, S.; Mallet, M.

Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multiyear database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, seasalt, sulfate, black and organic carbon). We use 9 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS (2 products), TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDERmore » and MSG/SEVIRI, as well as 3 more historical datasets: NIMBUS7/CZCS, TOMS (onboard NIMBUS7 and Earth- Probe) and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, the multi-model mean coming from the ACCMIP exercise, and the reanalyses GEMS and MACC. Ground-based Level- 2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatiotemporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain datasets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data, but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences of vertical distribution between dust aerosols showing a large vertical spread, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003–2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology.We extend the 2003–2009 reconstruction to the past up to 1979 using the 2003–2009 average and applying the decreasing trend in sulfate aerosols from LMDz-OR-INCA, whose AOD trends over Europe and the Mediterranean are median among the ACCMIP models. Finally optical properties of the different aerosol types in this region are proposed from Mie calculations so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosolclimate studies.« less

Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

NASA Astrophysics Data System (ADS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-04-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOS-Chem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-01-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Response to "Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET"

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didier

2010-01-01

A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD) products, and reports much poorer agreement than that obtained by the instrument teams and others. We trace the reasons for the discrepancies primarily to differences in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account.

Arctic biomass burning aerosol event-microphysical property retrieval

NASA Astrophysics Data System (ADS)

Böckmann, Christine; Ritter, Christoph; Ortiz-Amezcua, Pablo

2018-04-01

An intense biomass-burning (BB) event from North America in July 2015 was observed over Ny-Ålesund (Spitsbergen, European Arctic). An extreme air pollution took place and aerosol optical depth (AOD) of more than 1 at 500nm occurs in middle and lower troposphere. We analyse data from the multi-wavelength Raman-lidar KARL of Alfred Wegener Institute to derive microphysical properties of the aerosol of one interesting layer from 3186 to 3306 m via regularization. We found credible and confidential microphysical parameters.

Improved estimation of PM2.5 using Lagrangian satellite-measured aerosol optical depth

NASA Astrophysics Data System (ADS)

Olivas Saunders, Rolando

Suspended particulate matter (aerosols) with aerodynamic diameters less than 2.5 mum (PM2.5) has negative effects on human health, plays an important role in climate change and also causes the corrosion of structures by acid deposition. Accurate estimates of PM2.5 concentrations are thus relevant in air quality, epidemiology, cloud microphysics and climate forcing studies. Aerosol optical depth (AOD) retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument has been used as an empirical predictor to estimate ground-level concentrations of PM2.5 . These estimates usually have large uncertainties and errors. The main objective of this work is to assess the value of using upwind (Lagrangian) MODIS-AOD as predictors in empirical models of PM2.5. The upwind locations of the Lagrangian AOD were estimated using modeled backward air trajectories. Since the specification of an arrival elevation is somewhat arbitrary, trajectories were calculated to arrive at four different elevations at ten measurement sites within the continental United States. A systematic examination revealed trajectory model calculations to be sensitive to starting elevation. With a 500 m difference in starting elevation, the 48-hr mean horizontal separation of trajectory endpoints was 326 km. When the difference in starting elevation was doubled and tripled to 1000 m and 1500m, the mean horizontal separation of trajectory endpoints approximately doubled and tripled to 627 km and 886 km, respectively. A seasonal dependence of this sensitivity was also found: the smallest mean horizontal separation of trajectory endpoints was exhibited during the summer and the largest separations during the winter. A daily average AOD product was generated and coupled to the trajectory model in order to determine AOD values upwind of the measurement sites during the period 2003-2007. Empirical models that included in situ AOD and upwind AOD as predictors of PM2.5 were generated by multivariate linear regressions using the least squares method. The multivariate models showed improved performance over the single variable regression (PM2.5 and in situ AOD) models. The statistical significance of the improvement of the multivariate models over the single variable regression models was tested using the extra sum of squares principle. In many cases, even when the R-squared was high for the multivariate models, the improvement over the single models was not statistically significant. The R-squared of these multivariate models varied with respect to seasons, with the best performance occurring during the summer months. A set of seasonal categorical variables was included in the regressions to exploit this variability. The multivariate regression models that included these categorical seasonal variables performed better than the models that didn't account for seasonal variability. Furthermore, 71% of these regressions exhibited improvement over the single variable models that was statistically significant at a 95% confidence level.

Satellite remote sensing of air quality in winter of Lanzhou

NASA Astrophysics Data System (ADS)

Wang, Dawei; Han, Tao; Jiang, Youyan; Li, Lili; Ren, Shuyuan

2018-03-01

Fine particulate matter (aerodynamic diameters of less than 2.5 μm, PM2.5) air pollution has become one of the global environmental problem, endangering the existence of residents living, climate, and public health. Estimation Particulate Matter (aerodynamic diameters of less than 10 μm, PM10) concentration and aerosol absorption was the key point in air quality and climate studies. In this study, we retrieve the Aerosol Optical Depth (AOD) from the Earth Observing System (EOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), and PM2.5, PM10 in winter on 2014 and 2015, using Extended Dense Dark Vegetation Algorithm and 6S radiation model to analysis the correlation. The result showed that at the condition of non-considering the influence of primary pollutants, the correlation of two Polynomials between aerosol optical depth and PM2.5 and PM10 was poor; taking the influence of the primary pollutants into consideration, the aerosol optical depth has a good correlation with PM2.5 and PM10. The version of PM10 by aerosol optical depth is higher than that of PM2.5, so the model can be used to realize the high precision inversion of winter PM10 in Lanzhou.

Evaluation of climate model aerosol seasonal and spatial variability over Africa using AERONET

NASA Astrophysics Data System (ADS)

Horowitz, Hannah M.; Garland, Rebecca M.; Thatcher, Marcus; Landman, Willem A.; Dedekind, Zane; van der Merwe, Jacobus; Engelbrecht, Francois A.

2017-11-01

The sensitivity of climate models to the characterization of African aerosol particles is poorly understood. Africa is a major source of dust and biomass burning aerosols and this represents an important research gap in understanding the impact of aerosols on radiative forcing of the climate system. Here we evaluate the current representation of aerosol particles in the Conformal Cubic Atmospheric Model (CCAM) with ground-based remote retrievals across Africa, and additionally provide an analysis of observed aerosol optical depth at 550 nm (AOD550 nm) and Ångström exponent data from 34 Aerosol Robotic Network (AERONET) sites. Analysis of the 34 long-term AERONET sites confirms the importance of dust and biomass burning emissions to the seasonal cycle and magnitude of AOD550 nm across the continent and the transport of these emissions to regions outside of the continent. In general, CCAM captures the seasonality of the AERONET data across the continent. The magnitude of modeled and observed multiyear monthly average AOD550 nm overlap within ±1 standard deviation of each other for at least 7 months at all sites except the Réunion St Denis Island site (Réunion St. Denis). The timing of modeled peak AOD550 nm in southern Africa occurs 1 month prior to the observed peak, which does not align with the timing of maximum fire counts in the region. For the western and northern African sites, it is evident that CCAM currently overestimates dust in some regions while others (e.g., the Arabian Peninsula) are better characterized. This may be due to overestimated dust lifetime, or that the characterization of the soil for these areas needs to be updated with local information. The CCAM simulated AOD550 nm for the global domain is within the spread of previously published results from CMIP5 and AeroCom experiments for black carbon, organic carbon, and sulfate aerosols. The model's performance provides confidence for using the model to estimate large-scale regional impacts of African aerosols on radiative forcing, but local feedbacks between dust aerosols and climate over northern Africa and the Mediterranean may be overestimated.

Column-integrated aerosol optical properties of coarse- and fine-mode particles over the Pearl River Delta region in China.

PubMed

Mai, B; Deng, X; Xia, X; Che, H; Guo, J; Liu, X; Zhu, J; Ling, C

2018-05-01

The sun-photometer data from 2011 to 2013 at Panyu site (Panyu) and from 2007 to 2013 at Dongguan site (Dg) in the Pearl River Delta region, were used for the retrieving of the aerosol optical depth (AOD), single scattering albedo (SSA), Ångström exponent (AE) and volume size distribution of coarse- and fine-mode particles. The coarse-mode particles presented low AOD (ranging from 0.05±0.03 to 0.08±0.05) but a strong absorption property (SSA ranged from 0.70±0.03 to 0.90±0.02) for the wavelengths between 440 and 1020nm. However, these coarse particles accounted for <10% of the total particles. The AOD of fine particles (AODf) was over 3 times as large as that of coarse particles (AODc). The fine particles SSA (SSAf) generally decreased as a function of wavelength, and the relatively lower SSAf value in summer was likely to be due to the stronger solar radiation and higher temperature. More than 70% of the aerosols at Panyu site were dominated by fine-mode absorbing particles, whereas about 70% of the particles at Dg site were attributed to fine-mode scattering particles. The differences of the aerosol optical properties between the two sites are likely associated with local emissions of the light-absorbing carbonaceous aerosols and the scattering aerosols (e.g., sulfate and nitrate particles) caused by the gas-phase oxidation of gaseous precursors (e.g., SO 2 and NO 2 ). The size distribution exhibited bimodal structures in which the accumulation mode was predominant. The fine-mode volume showed positive dependence on AOD (500nm), and the growth of peak value of the fine-mode volume was higher than that of the coarse volume. Both the AOD and SSA increased with increasing relative humidity (RH), while the AE decreased with increasing RH. These correlations imply that the aerosol properties are greatly modified by condensation growth. Copyright © 2017 Elsevier B.V. All rights reserved.

Results from the Fourth WMO Filter Radiometer Comparison for aerosol optical depth measurements

NASA Astrophysics Data System (ADS)

Kazadzis, Stelios; Kouremeti, Natalia; Diémoz, Henri; Gröbner, Julian; Forgan, Bruce W.; Campanelli, Monica; Estellés, Victor; Lantz, Kathleen; Michalsky, Joseph; Carlund, Thomas; Cuevas, Emilio; Toledano, Carlos; Becker, Ralf; Nyeki, Stephan; Kosmopoulos, Panagiotis G.; Tatsiankou, Viktar; Vuilleumier, Laurent; Denn, Frederick M.; Ohkawara, Nozomu; Ijima, Osamu; Goloub, Philippe; Raptis, Panagiotis I.; Milner, Michael; Behrens, Klaus; Barreto, Africa; Martucci, Giovanni; Hall, Emiel; Wendell, James; Fabbri, Bryan E.; Wehrli, Christoph

2018-03-01

This study presents the results of the Fourth Filter Radiometer Comparison that was held in Davos, Switzerland, between 28 September and 16 October 2015. Thirty filter radiometers and spectroradiometers from 12 countries participated including reference instruments from global aerosol networks. The absolute differences of all instruments compared to the reference have been based on the World Meteorological Organization (WMO) criterion defined as follows: 95% of the measured data has to be within 0.005 ± 0.001/m (where m is the air mass). At least 24 out of 29 instruments achieved this goal at both 500 and 865 nm, while 12 out of 17 and 13 out of 21 achieved this at 368 and 412 nm, respectively. While searching for sources of differences among different instruments, it was found that all individual differences linked to Rayleigh, NO2, ozone, water vapor calculations and related optical depths and air mass calculations were smaller than 0.01 in aerosol optical depth (AOD) at 500 and 865 nm. Different cloud-detecting algorithms used have been compared. Ångström exponent calculations showed relatively large differences among different instruments, partly because of the high calculation uncertainty of this parameter in low AOD conditions. The overall low deviations of these AOD results and the high accuracy of reference aerosol network instruments demonstrated a promising framework to achieve homogeneity, compatibility and harmonization among the different spectral AOD networks in the near future.

NCEP Global Aerosols Forecast. NOAA/NWS/NCEP/EMC

Science.gov Websites

Documentations Select Domain Global Regional Year: 2016 2017 2018 Month: Jan Feb Mar Apr May Jun Jul Aug Sep Oct 31 Select Field: Total AOD Total AOD Dust AOD Sea salt AOD Black carbon AOD POM AOD Sulfate AOD Get

The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm: theoretical basis

NASA Astrophysics Data System (ADS)

Loughman, Robert; Bhartia, Pawan K.; Chen, Zhong; Xu, Philippe; Nyaku, Ernest; Taha, Ghassan

2018-05-01

The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss-Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

A retrieval algorithm of hydrometer profile for submillimeter-wave radiometer

NASA Astrophysics Data System (ADS)

Liu, Yuli; Buehler, Stefan; Liu, Heguang

2017-04-01

Vertical profiles of particle microphysics perform vital functions for the estimation of climatic feedback. This paper proposes a new algorithm to retrieve the profile of the parameters of the hydrometeor(i.e., ice, snow, rain, liquid cloud, graupel) based on passive submillimeter-wave measurements. These parameters include water content and particle size. The first part of the algorithm builds the database and retrieves the integrated quantities. Database is built up by Atmospheric Radiative Transfer Simulator(ARTS), which uses atmosphere data to simulate the corresponding brightness temperature. Neural network, trained by the precalculated database, is developed to retrieve the water path for each type of particles. The second part of the algorithm analyses the statistical relationship between water path and vertical parameters profiles. Based on the strong dependence existing between vertical layers in the profiles, Principal Component Analysis(PCA) technique is applied. The third part of the algorithm uses the forward model explicitly to retrieve the hydrometeor profiles. Cost function is calculated in each iteration, and Differential Evolution(DE) algorithm is used to adjust the parameter values during the evolutionary process. The performance of this algorithm is planning to be verified for both simulation database and measurement data, by retrieving profiles in comparison with the initial one. Results show that this algorithm has the ability to retrieve the hydrometeor profiles efficiently. The combination of ARTS and optimization algorithm can get much better results than the commonly used database approach. Meanwhile, the concept that ARTS can be used explicitly in the retrieval process shows great potential in providing solution to other retrieval problems.

A multi-spectral approach to simultaneously retrieve above-cloud smoke optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds using MODIS

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2013-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into the standard MODIS cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 μm (effective particle size retrievals are derived from the short and mid-wave IR channels at 1.6, 2.1, and 3.7 μm). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple MODIS spectral channels in the visible and near- and shortwave-infrared. Preliminary retrieval results are shown, as are comparisons with other A-Train sensors.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

Steps Toward an EOS-Era Aerosol Air Mass Type Climatology

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2012-01-01

We still have a way to go to develop a global climatology of aerosol type from the EOS-era satellite data record that currently spans more than 12 years of observations. We have demonstrated the ability to retrieve aerosol type regionally, providing a classification based on the combined constraints on particle size, shape, and single-scattering albedo (SSA) from the MISR instrument. Under good but not necessarily ideal conditions, the MISR data can distinguish three-to-five size bins, two-to-four bins in SSA, and spherical vs. non-spherical particles. However, retrieval sensitivity varies enormously with scene conditions. So, for example, there is less information about aerosol type when the mid-visible aerosol optical depth (AOD) is less that about 0.15 or 0.2.

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

DOE Office of Scientific and Technical Information (OSTI.GOV)

Misra, Amit; Kanawade, Vijay P.; Tripathi, Sachchida Nand

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD andmore » MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.« less

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

DOE PAGES

Misra, Amit; Kanawade, Vijay P.; Tripathi, Sachchida Nand

2016-08-03

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD andmore » MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.« less

Physical state and temporal evolution of icy surfaces in the Mars South Pole

NASA Astrophysics Data System (ADS)

Douté, S.; Pilorget, C.

2017-09-01

On Mars H2O and CO2 ices can be found as seasonal or perennial deposits notably in the polar regions. Their bidirectional reflectance factor (BRF) is a tracer of their evolution which is still not completely understood. It is a key parameter for characterizing the composition and the physical state, as well as for calculating the bolometric albedo, the energy balance of the icy surfaces, and thus their impact on the martian climate. The BRF is potentially accessible thanks to the near-simultaneous multi-angle, hyperspectral observations of the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) implying 11 viewing angles in visible and infrared ranges. In previous research (Ceamanos2013, Doute2015) we put forward the Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO), an algorithm that characterizes and corrects the aerosol scattering effects. The aerosol optical depth (AOD) and the BRF of surface materials are retrieved conjointly and coherently as a function of wavelength. In this work, we apply MARS-ReCO on time series of CRISM sequences over different regions of interest in the outskirts of the south permanent polar cap. The time series span from mid-spring to late summer (Ls=210-320*) during which the CO2 ice sublimates sometimes revealing H2O frost and defrosted terrains. Thanks to the atmospheric correction, we are able to identify various classes of spectrophotometric behavior. We also note a regular increase of the directional-hemispherical surface albedo during the period of the time.

Pulse retrieval algorithm for interferometric frequency-resolved optical gating based on differential evolution.

PubMed

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-10-01

A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely, differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove the robustness of the algorithm against experimental artifacts and noise. These tests show that the integrated error-correction mechanisms of the iFROG method can be successfully used to remove the effect from timing errors and spectrally varying efficiency in the detection. Moreover, the accuracy and noise resilience of the new algorithm are shown to outperform retrieval based on the generalized projections algorithm, which is widely used as the standard method in FROG retrieval. The differential evolution algorithm is further validated with experimental data, measured with unamplified three-cycle pulses from a mode-locked Ti:sapphire laser. Additionally introducing group delay dispersion in the beam path, the retrieval results show excellent agreement with independent measurements with a commercial pulse measurement device based on spectral phase interferometry for direct electric-field retrieval. Further experimental tests with strongly attenuated pulses indicate resilience of differential-evolution-based retrieval against massive measurement noise.

Fire and Smoke Monitoring at NOAA' Satellite Service; Applications to Smoke Forecasting

NASA Astrophysics Data System (ADS)

Stephens, G.; Ruminski, M.

2005-12-01

The Hazard Mapping System (HMS), developed and run operationally by NOAA's Satellite Services Division (SSD), is a multiplatform remote sensing approach to detecting fires and smoke over the US and adjacent areas of Canada and Mexico. The system utilizes sensors on 7 different NOAA and NASA satellites. Automated detection algorithms are employed for each of the satellites for the fire detects while smoke is delineated by an image analyst. Analyses are quality control by an analyst who inspects all available imagery and automated fire detects, deleting suspected false detects and adding fires that the automated routines miss. Graphical, text, and GIS compatible analyses are posted to a web site as soon as updates are performed, and a final product for a given day is posted early the following morning. All products are archived at NOAA's National Geophysical Data Center. Areal extent of detectable smoke is outlined using animated visible imagery, for input to a dispersion and transport model, the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), developed by NOAA's Air Resources Laboratory (ARL). Resulting smoke forecasts will soon be used as input to NOAA's Air Quality forecasts. The GOES Aerosol and Smoke Product (GASP) is an experimental GOES imagery based aerosol optical depth (AOD) product developed by the NESDIS Office of Research and Applications, being implemented for evaluation by the NESDIS Satellite Analysis Branch for use in smoke and volcanic ash monitoring. Currently, research is underway in NESDIS' Office of Research and Applications to objectivize smoke delineation using GASP and MODIS AOD retrievals. NOAA's Operational Significant Event Imagery (OSEI) program processes satellite imagery of environmentally significant events, including fire, smoke and volcanic ash, visible in operational satellite data. This imagery is often referred to by fire managers and air quality agencies. Future plans include the integration of high resolution global data from the European Space Agency's MetOp satellite and global geostationary satellites.

Resolving the Aerosol Piece of the Global Climate Picture

NASA Astrophysics Data System (ADS)

Kahn, R. A.

2017-12-01

Factors affecting our ability to calculate climate forcing and estimate model predictive skill include direct radiative effects of aerosols and their indirect effects on clouds. Several decades of Earth-observing satellite observations have produced a global aerosol column-amount (AOD) record, but an aerosol microphysical property record required for climate and many air quality applications is lacking. Surface-based photometers offer qualitative aerosol-type classification, and several space-based instruments map aerosol air-mass types under favorable conditions. However, aerosol hygroscopicity, mass extinction efficiency (MEE), and quantitative light absorption, must be obtained from in situ measurements. Completing the aerosol piece of the climate picture requires three elements: (1) continuing global AOD and qualitative type mapping from space-based, multi-angle imagers and aerosol vertical distribution from near-source stereo imaging and downwind lidar, (2) systematic, quantitative in situ observations of particle properties unobtainable from space, and (3) continuing transport modeling to connect observations to sources, and extrapolate limited sampling in space and time. At present, the biggest challenges to producing the needed aerosol data record are: filling gaps in particle property observations, maintaining global observing capabilities, and putting the pieces together. Obtaining the PDFs of key particle properties, adequately sampled, is now the leading observational deficiency. One simplifying factor is that, for a given aerosol source and season, aerosol amounts often vary, but particle properties tend to be repeatable. SAM-CAAM (Systematic Aircraft Measurements to Characterize Aerosol Air Masses), a modest aircraft payload deployed frequently could fill this gap, adding value to the entire satellite data record, improving aerosol property assumptions in retrieval algorithms, and providing MEEs to translate between remote-sensing optical constraints and aerosol mass book-kept in climate models [Kahn et al., BAMS 2017]. This will also improve connections between remote-sensing particle types and those defined in models. The third challenge, maintaining global observing capabilities, requires continued community effort and good budgetary fortune.

Aplication of LIRIC algorithm to study aerosol transport over Belsk, Poland

NASA Astrophysics Data System (ADS)

Pietruczuk, Aleksander; Posyniak, Michał

2015-04-01

In this work synergy of measurements done by of a LIDAR and a sun-sky scanning photometer is presented. The LIdar-Radiometer Inversion Code (LIRIC) was applied to study periodic events of increased values of the aerosol optical depth (AOD) observed at Belsk (Poland). Belsk is a background site located in a rural area around 50 km south from Warsaw. Events of increased AOD occur mainly during spring and they coincide with events of elevated concentrations of particulate matter (PM10). This phenomenon is observed in all eastern Europe, e.g. in Minsk, and is caused by long range aerosol transport. Our previous work showed aerosol transport from the border between Belarus, Ukraine and Russia in the planetary boundary layer (PBL), and from north Africa in the free troposphere. The LIRIC algorithm, which uses optical and microphysical properties of the aerosol derived from photometric measurements and LIDAR profiles, was applied to study vertical distribution of fine and coarse modes of aerosol. The analysis of the airmass backward trajectories and models results (DREAM and NAAPS)was also used to determine a possible aerosol type and its source region. This study proved our previous findings. Most of events with increased AODs are observed during spring. In this season the fine mode aerosol is mainly present in the PBL. On the basis of the trajectory analysis and the NAAPS results we presume that it is the absorbing aerosol originating from the regions of seasonal biomass burning in eastern Europe, i.e. the area mentioned above. The events with increased AODs were also found during summer. In this case the fine mode aerosol is transported in the PBL a like to spring season. However, our analysis of trajectories and model results indicated western Europe as a source region. It is probably urban/industrial aerosol. The coarse mode aerosol is transported mainly in the free troposphere as separate layers. The analysis of backward trajectories indicates northern Africa as a possible source region regardless the season. DREAM and NAAPS results suggest presence of mineral dust in this case over Belsk.

Aerosol Indirect Effect on Warm Clouds over Eastern China Using Combined CALIOP and MODIS Observations

NASA Astrophysics Data System (ADS)

Guo, Jianping; Wang, Fu; Huang, Jingfeng; Li, Xiaowen

2015-04-01

Aerosol, one of key components of the climate system, is highly variable, both temporally and spatially. It often exerts great influences on the cloud-precipitation chain processes by serving as CCN/IN, altering cloud microphysics and its life cycle. Yet, the aerosol indirect effect on clouds remains largely unknown, because the initial changes in clouds due to aerosols may be enhanced or dampened by such feedback processes as modified cloud dynamics, or evaporation of the smaller droplets due to the competition for water vapor. In this study, we attempted to quantify the aerosol effects on warm cloud over eastern China, based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO and CPR/CLOUDSAT during the period 2006 to 2010. The seasonality of aerosol from ground-based PM10 is quite different from that estimated from MODIS AOD. This result is corroborated by lower level profile of aerosol occurrence frequency from CALIOP, indicating the significant role CALIOP could play in aerosol-cloud interaction. The combined use of CALIOP and CPR facilitate the process to exactly determine the (vertical) position of warm cloud relative to aerosol, out of six scenarios in terms of aerosol-cloud mixing status in terms of aerosol-cloud mixing status, which shows as follows: AO (Aerosol only), CO (Cloud only), SASC (Single aerosol-single cloud), SADC (single aerosol-double cloud), DASC (double aerosol-single cloud), and others. Results shows that about 54% of all the cases belong to mixed status, among all the collocated aerosol-cloud cases. Under mixed condition, a boomerang shape is observed, i.e., reduced cloud droplet radius (CDR) is associated with increasing aerosol at moderate aerosol pollution (AOD<0.4), becoming saturated at AOD of 0.5, followed by an increase in CDR with aerosol. In contrast, there is no such boomerang shape found for (aerosol-cloud) separated cases. We categorize dataset into warm-season and cold-season subsets to figure out how the boomerang shape varies with season. For moderate aerosol loading (AOD<0.4), the effect on the droplet size for the "Mixed" cases is greater during cold season (denoted by a large slope), as compared with that during warm season. It is likely associated with an increase in the emission of light absorbing aerosol like smoke (black carbon), mainly caused by coal-fired heating during the cold season in China. As expected, the sensitivity of CDR to AOD is much weaker for "Separated" cases, irrespective of warm or cold seasons, indicating no real aerosol indirect effect occurring in this case. In contrast, for heavy aerosol loading (AOD>0.4), an increasing CDR with AOD can be seen in "Mixed" scenario during the warm season. Conversely, a closer look at the responses of CDR during the cold season shows that CDR decreases with AOD, although the strength is not much large. Therefore, we argue that cloud droplet size decreases with aerosol loading during cold season, irrespective of moderate or heavy atmospheric pollution. Finally, we discuss the possible factors that may influence the aerosol indirect effects on warm clouds investigated here. For instance, aerosol-cloud interaction conundrum might be affected by aerosol humidification, which is the case for MODIS AOD during warm seasons. But this issue can be partly overcome by categorizing dataset into warm-season and cold-season subsets, representing different ambient humidity condition in the atmosphere. The different boomerang shapes observed during various seasons, particularly after transition zone due to droplet saturation effect, have great implications for climate forcing by aerosol in eastern China.

Enhancements in Deriving Smoke Emission Coefficients from Fire Radiative Power Measurements

NASA Technical Reports Server (NTRS)

Ellison, Luke; Ichoku, Charles

2011-01-01

Smoke emissions have long been quantified after-the-fact by simple multiplication of burned area, biomass density, fraction of above-ground biomass, and burn efficiency. A new algorithm has been suggested, as described in Ichoku & Kaufman (2005), for use in calculating smoke emissions directly from fire radiative power (FRP) measurements such that the latency and uncertainty associated with the previously listed variables are avoided. Application of this new, simpler and more direct algorithm is automatic, based only on a fire's FRP measurement and a predetermined coefficient of smoke emission for a given location. Attaining accurate coefficients of smoke emission is therefore critical to the success of this algorithm. In the aforementioned paper, an initial effort was made to derive coefficients of smoke emission for different large regions of interest using calculations of smoke emission rates from MODIS FRP and aerosol optical depth (AOD) measurements. Further work had resulted in a first draft of a 1 1 resolution map of these coefficients. This poster will present the work done to refine this algorithm toward the first production of global smoke emission coefficients. Main updates in the algorithm include: 1) inclusion of wind vectors to help refine several parameters, 2) defining new methods for calculating the fire-emitted AOD fractions, and 3) calculating smoke emission rates on a per-pixel basis and aggregating to grid cells instead of doing so later on in the process. In addition to a presentation of the methodology used to derive this product, maps displaying preliminary results as well as an outline of the future application of such a product into specific research opportunities will be shown.

Evaluating Satellite Retrievals of Smoke Aerosol above Clouds using Airborne High Spectral Resolution Lidar Measurements during ORACLES

NASA Astrophysics Data System (ADS)

Ferrare, R. A.; Burton, S. P.; Cook, A. L.; Harper, D. B.; Hostetler, C. A.; Hair, J. W.; Vaughan, M.; Hu, Y.; Fenn, M. A.; Clayton, M.; Scarino, A. J.; Jethva, H. T.; Sayer, A. M.; Meyer, K.; Torres, O.; Josset, D. B.; Redemann, J.

2017-12-01

The NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL-2) provided extensive measurements of smoke above shallow marine clouds while deployed from the NASA ER-2 aircraft during the NASA EV-S Observations of Aerosols above Clouds and their Interactions (ORACLES) mission. During the first ORACLES field campaign in September 2016, the ER-2 was deployed from Walvis Bay, Namibia and conducted flights over the southeastern Atlantic Ocean. HSRL-2 measured profiles of aerosol backscattering, extinction and aerosol optical depth (AOD) at 355 and 532 nm and aerosol backscattering and depolarization at 1064 nm and so provided an excellent characterization of the widespread smoke layers above shallow marine clouds. OMI, MODIS, and CALIOP satellite retrievals of above cloud AOD (ACAOD) are compared to the HSRL-2 measurements. The OMI above-cloud aerosols data product (OMACA) ACAOD product relies on the spectral contrast produced by aerosol absorption in two near-UV measurements (354 and 388 nm) to derive ACAOD. Two MODIS ACAOD products are examined; the first ("multichannel') relies on the spectral contrast in aerosol absorption derived from reflectance measurements at six MODIS channels from the visible to the shortwave infrared (swIR). The second method is an extension of the "Deep Blue" method and differs from the multichannel method in that it does not use swIR channels. The CALIOP V4 operational and "depolarization ratio (DR)" methods of retrieving ACAOD are also examined. The MODIS and OMI ACAOD values were well correlated (r2>0.6) with the HSRL-2 ACAOD values; bias differences were generally less than about 0.1 at 532 nm (10-30%). The CALIOP operational retrievals missed a significant amount of aerosol and so were biased low by 50-75% compared to HSRL-2. In contrast, the CALIOP DR method produced ACAOD values in excellent agreement (bias differences less than 0.03 (5%)) with HSRL-2. Aerosol extinction profiles computed for the smoke layer using the CALIOP attenuated backscatter profiles and constrained by the CALIOP DR ACAOD retrievals are also found to agree well on average with coincident HSRL-2 extinction profiles. These constrained CALIOP extinction profiles are used to characterize the smoke distribution over this region.

Trans-Pacific transport and evolution of aerosols: evaluation of quasi-global WRF-Chem simulation with multiple observations

NASA Astrophysics Data System (ADS)

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; Leung, L. Ruby; Qian, Yun; Yu, Hongbin; Huang, Lei; Kalashnikova, Olga V.

2016-05-01

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010-2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols. The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010-2014 averaged over three Pacific sub-regions. The evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.

Algorithms and sensitivity analyses for Stratospheric Aerosol and Gas Experiment II water vapor retrieval

NASA Technical Reports Server (NTRS)

Chu, W. P.; Chiou, E. W.; Larsen, J. C.; Thomason, L. W.; Rind, D.; Buglia, J. J.; Oltmans, S.; Mccormick, M. P.; Mcmaster, L. M.

1993-01-01

The operational inversion algorithm used for the retrieval of the water-vapor vertical profiles from the Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation data is presented. Unlike the algorithm used for the retrieval of aerosol, O3, and NO2, the water-vapor retrieval algorithm accounts for the nonlinear relationship between the concentration versus the broad-band absorption characteristics of water vapor. Problems related to the accuracy of the computational scheme, the accuracy of the removal of other interfering species, and the expected uncertainty of the retrieved profile are examined. Results are presented on the error analysis of the SAGE II water vapor retrieval, indicating that the SAGE II instrument produced good quality water vapor data.

Comparative Results of AIRS AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2016-01-01

The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

Air quality and human health improvements from reduced deforestation in Brazil

NASA Astrophysics Data System (ADS)

Reddington, C.; Butt, E. W.; Ridley, D. A.; Artaxo, P.; Morgan, W.; Coe, H.; Spracklen, D. V.

2015-12-01

Significant areas of the Brazilian Amazon have been deforested over the past few decades, with fire being the dominant method through which forests and vegetation are cleared. Fires emit large quantities of particulate matter into the atmosphere, degrading air quality and negatively impacting human health. Since 2004, Brazil has achieved substantial reductions in deforestation rates and associated deforestation fires. Here we assess the impact of this reduction on air quality and human health. We show that dry season (August - October) aerosol optical depth (AOD) retrieved by satellite over southwest Brazil and Bolivia is positively related to Brazil's annual deforestation rate (r=0.96, P<0.001). Observed dry season AOD is more than a factor two greater in years with high deforestation rates compared to years with low deforestation rates, suggesting regional air quality is degraded substantially by fire emissions associated with deforestation. This link is further demonstrated by the positive relationship between observed AOD and satellite-derived particulate emissions from deforestation fires (r=0.89, P<0.01). Using a global aerosol model with satellite-derived fire emissions, we show that reductions in fires associated with reduced deforestation have reduced regional dry season mean surface particulate matter concentrations by ~30%. Using concentration response functions we estimate that this reduction in particulate matter may be preventing 1060 (388-1721) premature adult mortalities annually across South America. Future increases in Brazil's deforestation rates and associated fires may threaten the improved air quality reported here.

Optimisation of Ferrochrome Addition Using Multi-Objective Evolutionary and Genetic Algorithms for Stainless Steel Making via AOD Converter

NASA Astrophysics Data System (ADS)

Behera, Kishore Kumar; Pal, Snehanshu

2018-03-01

This paper describes a new approach towards optimum utilisation of ferrochrome added during stainless steel making in AOD converter. The objective of optimisation is to enhance end blow chromium content of steel and reduce the ferrochrome addition during refining. By developing a thermodynamic based mathematical model, a study has been conducted to compute the optimum trade-off between ferrochrome addition and end blow chromium content of stainless steel using a predator prey genetic algorithm through training of 100 dataset considering different input and output variables such as oxygen, argon, nitrogen blowing rate, duration of blowing, initial bath temperature, chromium and carbon content, weight of ferrochrome added during refining. Optimisation is performed within constrained imposed on the input parameters whose values fall within certain ranges. The analysis of pareto fronts is observed to generate a set of feasible optimal solution between the two conflicting objectives that provides an effective guideline for better ferrochrome utilisation. It is found out that after a certain critical range, further addition of ferrochrome does not affect the chromium percentage of steel. Single variable response analysis is performed to study the variation and interaction of all individual input parameters on output variables.

Creating a consistent dark-target aerosol optical depth record from MODIS and VIIRS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Holz, R.

2014-12-01

To answer fundamental questions about our changing climate, we must quantify how aerosols are changing over time. This is a global question that requires regional characterization, because in some places aerosols are increasing and in others they are decreasing. Although NASA's Moderate resolution Imaging Spectrometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, the creation of an aerosol climate data record (CDR) requires consistent multi-decadal data. With the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, there is potential to continue the MODIS aerosol time series. Yet, since the operational VIIRS aerosol product is produced by a different algorithm, it is not suitable to continue MODIS to create an aerosol CDR. Therefore, we have applied the MODIS Dark-target (DT) algorithm to VIIRS observations, taking into account the slight differences in wavelengths, resolutions and geometries between the two sensors. More specifically, we applied the MODIS DT algorithm to a dataset known as the Intermediate File Format (IFF), created by the University of Wisconsin. The IFF is produced for both MODIS and VIIRS, with the idea that a single (MODIS-like or ML) algorithm can be run either dataset, which can in turn be compared to the MODIS Collection 6 (M6) retrieval that is run on standard MODIS data. After minimizing or characterizing remaining differences between ML on MODIS-IFF (or ML-M) and M6, we have performed apples-to-apples comparison between ML-M and ML on VIIRS IFF (ML-V). Examples of these comparisons include time series of monthly global mean, monthly and seasonal global maps at 1° resolution, and collocations as compared to AERONET. We concentrate on the overlapping period January 2012 through June 2014, and discuss some of the remaining discrepancies between the ML-V and ML-M datasets.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

NASA Astrophysics Data System (ADS)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China

NASA Astrophysics Data System (ADS)

Che, Huizheng; Qi, Bing; Zhao, Hujia; Xia, Xiangao; Eck, Thomas F.; Goloub, Philippe; Dubovik, Oleg; Estelles, Victor; Cuevas-Agulló, Emilio; Blarel, Luc; Wu, Yunfei; Zhu, Jun; Du, Rongguang; Wang, Yaqiang; Wang, Hong; Gui, Ke; Yu, Jie; Zheng, Yu; Sun, Tianze; Chen, Quanliang; Shi, Guangyu; Zhang, Xiaoye

2018-01-01

Aerosol pollution in eastern China is an unfortunate consequence of the region's rapid economic and industrial growth. Here, sun photometer measurements from seven sites in the Yangtze River Delta (YRD) from 2011 to 2015 were used to characterize the climatology of aerosol microphysical and optical properties, calculate direct aerosol radiative forcing (DARF) and classify the aerosols based on size and absorption. Bimodal size distributions were found throughout the year, but larger volumes and effective radii of fine-mode particles occurred in June and September due to hygroscopic growth and/or cloud processing. Increases in the fine-mode particles in June and September caused AOD440 nm > 1.00 at most sites, and annual mean AOD440 nm values of 0.71-0.76 were found at the urban sites and 0.68 at the rural site. Unlike northern China, the AOD440 nm was lower in July and August (˜ 0.40-0.60) than in January and February (0.71-0.89) due to particle dispersion associated with subtropical anticyclones in summer. Low volumes and large bandwidths of both fine-mode and coarse-mode aerosol size distributions occurred in July and August because of biomass burning. Single-scattering albedos at 440 nm (SSA440 nm) from 0.91 to 0.94 indicated particles with relatively strong to moderate absorption. Strongly absorbing particles from biomass burning with a significant SSA wavelength dependence were found in July and August at most sites, while coarse particles in March to May were mineral dust. Absorbing aerosols were distributed more or less homogeneously throughout the region with absorption aerosol optical depths at 440 nm ˜ 0.04-0.06, but inter-site differences in the absorption Angström exponent indicate a degree of spatial heterogeneity in particle composition. The annual mean DARF was -93 ± 44 to -79 ± 39 W m-2 at the Earth's surface and ˜ -40 W m-2 at the top of the atmosphere (for the solar zenith angle range of 50 to 80°) under cloud-free conditions. The fine mode composed a major contribution of the absorbing particles in the classification scheme based on SSA, fine-mode fraction and extinction Angström exponent. This study contributes to our understanding of aerosols and regional climate/air quality, and the results will be useful for validating satellite retrievals and for improving climate models and remote sensing algorithms.

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

NASA Technical Reports Server (NTRS)

Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr;

Substance use by same sex attracted young people: Prevalence, perceptions and homophobia.

PubMed

Kelly, John; Davis, Cassandra; Schlesinger, Carla

2015-07-01

Research highlights that lesbian, gay, bisexual and transgender (LGBT) people use alcohol and drugs (AOD) more than heterosexual people; however, the incidence of AOD use by LGBT youth is less understood. The purpose of the current study was to ascertain AOD prevalence rates for LGBT youth compared with the Australian youth population; perceptions of AOD use within the LGBT community; and the impact of homophobia on AOD use. The study surveyed a cross-sectional sample of LGBT youth (13-24 years) (n = 161) who attended a LGBT festival in Brisbane, Australia, in 2012. The Alcohol Use Disorders Identification Test-Consumption, Fagerström Test for Nicotine Dependence and Drug Check Assessment Tool were utilised to examine patterns of AOD use, with items developed to explore perceptions of AOD use and homophobia. AOD use was common among the LGBT sample, with higher prevalence rates compared with the general Australian youth population (2010 National Drug Strategy Household Survey). AOD use by under 18-year-olds, and gender diverse youth was markedly higher. The majority misperceived AOD use to be the same in the LGBT and heterosexual communities. Those who believed homophobia impacted on AOD use were significantly more likely to use AOD. The higher prevalence of AOD use strongly suggests the need for AOD agencies to better respond to LGBT youth by not only screening sexuality and gender identity but also exploring young people's perceptions of AOD use in the LGBT community and their experiences of homophobia in order to provide effective AOD clinical treatment. © 2014 Australasian Professional Society on Alcohol and other Drugs.

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2016-01-01

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

Retrieving Liquid Water Path and Precipitable Water Vapor from the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, David D.; Clough, Shepard A.; Liljegren, James C.

2007-11-01

Ground-based two-channel microwave radiometers have been used for over 15 years by the Atmospheric Radiation Measurement (ARM) program to provide observations of downwelling emitted radiance from which precipitable water vapor (PWV) and liquid water path (LWP) – twp geophysical parameters critical for many areas of atmospheric research – are retrieved. An algorithm that utilizes two advanced retrieval techniques, a computationally expensive physical-iterative approach and an efficient statistical method, has been developed to retrieve these parameters. An important component of this Microwave Retrieval (MWRRET) algorithm is the determination of small (< 1K) offsets that are subtracted from the observed brightness temperaturesmore » before the retrievals are performed. Accounting for these offsets removes systematic biases from the observations and/or the model spectroscopy necessary for the retrieval, significantly reducing the systematic biases in the retrieved LWP. The MWRRET algorithm provides significantly more accurate retrievals than the original ARM statistical retrieval which uses monthly retrieval coefficients. By combining the two retrieval methods with the application of brightness temperature offsets to reduce the spurious LWP bias in clear skies, the MWRRET algorithm provides significantly better retrievals of PWV and LWP from the ARM 2-channel microwave radiometers compared to the original ARM product.« less

Aerosol Properties Derived from Airborne Sky Radiance and Direct Beam Measurements in Recent NASA and DoE Field Campaigns

NASA Technical Reports Server (NTRS)

Redemann, J.; Flynn, C. J.; Shinozuka, Y.; Russell, P. B.; Kacenelenbogen, M.; Segal-Rosenheimer, M.; Livingston, J. M.; Schmid, B.; Dunagan, S. E.; Johnson, R. R.;

Seasonal, interannual, and long-term variabilities in biomass burning activity over South Asia.

PubMed

Bhardwaj, P; Naja, M; Kumar, R; Chandola, H C

2016-03-01

The seasonal, interannual, and long-term variations in biomass burning activity and related emissions are not well studied over South Asia. In this regard, active fire location retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), the retrievals of aerosol optical depth (AOD) from MODIS Terra, and tropospheric column NO2 from Ozone Monitoring Instrument (OMI) are used to understand the effects of biomass burning on the tropospheric pollution loadings over South Asia during 2003-2013. Biomass burning emission estimates from Global Fire Emission Database (GFED) and Global Fire Assimilation System (GFAS) are also used to quantify uncertainties and regional discrepancies in the emissions of carbon monoxide (CO), nitrogen oxide (NOx), and black carbon (BC) due to biomass burning in South Asia. In the Asian continent, the frequency of fire activity is highest over Southeast Asia, followed by South Asia and East Asia. The biomass burning activity in South Asia shows a distinct seasonal cycle that peaks during February-May with some differences among four (north, central, northeast, and south) regions in India. The annual biomass burning activity in north, central, and south regions shows an increasing tendency, particularly after 2008, while a decrease is seen in northeast region during 2003-2013. The increase in fire counts over the north and central regions contributes 24 % of the net enhancement in fire counts over South Asia. MODIS AOD and OMI tropospheric column NO2 retrievals are classified into high and low fire activity periods and show that biomass burning leads to significant enhancement in tropospheric pollution loading over both the cropland and forest regions. The enhancement is much higher (110-176 %) over the forest region compared to the cropland (34-62 %) region. Further efforts are required to understand the implications of biomass burning on the regional air quality and climate of South Asia.

Combined neural network/Phillips-Tikhonov approach to aerosol retrievals over land from the NASA Research Scanning Polarimeter

NASA Astrophysics Data System (ADS)

Di Noia, Antonio; Hasekamp, Otto P.; Wu, Lianghai; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John E.

2017-11-01

In this paper, an algorithm for the retrieval of aerosol and land surface properties from airborne spectropolarimetric measurements - combining neural networks and an iterative scheme based on Phillips-Tikhonov regularization - is described. The algorithm - which is an extension of a scheme previously designed for ground-based retrievals - is applied to measurements from the Research Scanning Polarimeter (RSP) on board the NASA ER-2 aircraft. A neural network, trained on a large data set of synthetic measurements, is applied to perform aerosol retrievals from real RSP data, and the neural network retrievals are subsequently used as a first guess for the Phillips-Tikhonov retrieval. The resulting algorithm appears capable of accurately retrieving aerosol optical thickness, fine-mode effective radius and aerosol layer height from RSP data. Among the advantages of using a neural network as initial guess for an iterative algorithm are a decrease in processing time and an increase in the number of converging retrievals.

The Complexity of Bit Retrieval

DOE PAGES

Elser, Veit

2018-09-20

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

The Complexity of Bit Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elser, Veit

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

Optimization of the GSFC TROPOZ DIAL retrieval using synthetic lidar returns and ozonesondes - Part 1: Algorithm validation

NASA Astrophysics Data System (ADS)

Sullivan, J. T.; McGee, T. J.; Leblanc, T.; Sumnicht, G. K.; Twigg, L. W.

2015-10-01

The main purpose of the NASA Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZ DIAL) is to measure the vertical distribution of tropospheric ozone for science investigations. Because of the important health and climate impacts of tropospheric ozone, it is imperative to quantify background photochemical ozone concentrations and ozone layers aloft, especially during air quality episodes. For these reasons, this paper addresses the necessary procedures to validate the TROPOZ retrieval algorithm and confirm that it is properly representing ozone concentrations. This paper is focused on ensuring the TROPOZ algorithm is properly quantifying ozone concentrations, and a following paper will focus on a systematic uncertainty analysis. This methodology begins by simulating synthetic lidar returns from actual TROPOZ lidar return signals in combination with a known ozone profile. From these synthetic signals, it is possible to explicitly determine retrieval algorithm biases from the known profile. This was then systematically performed to identify any areas that need refinement for a new operational version of the TROPOZ retrieval algorithm. One immediate outcome of this exercise was that a bin registration error in the correction for detector saturation within the original retrieval was discovered and was subsequently corrected for. Another noticeable outcome was that the vertical smoothing in the retrieval algorithm was upgraded from a constant vertical resolution to a variable vertical resolution to yield a statistical uncertainty of <10 %. This new and optimized vertical-resolution scheme retains the ability to resolve fluctuations in the known ozone profile, but it now allows near-field signals to be more appropriately smoothed. With these revisions to the previous TROPOZ retrieval, the optimized TROPOZ retrieval algorithm (TROPOZopt) has been effective in retrieving nearly 200 m lower to the surface. Also, as compared to the previous version of the retrieval, the TROPOZopt had an overall mean improvement of 3.5 %, and large improvements (upwards of 10-15 % as compared to the previous algorithm) were apparent between 4.5 and 9 km. Finally, to ensure the TROPOZopt retrieval algorithm is robust enough to handle actual lidar return signals, a comparison is shown between four nearby ozonesonde measurements. The ozonesondes are mostly within the TROPOZopt retrieval uncertainty bars, which implies that this exercise was quite successful.

Weekday AOD smaller than weekend AOD in eastern China on the basis of the MODIS AOD product

NASA Astrophysics Data System (ADS)

Song, Jingjing; Xia, Xiangao; Zhang, Xiaoling; Che, Huizheng; Li, Xiaojing

2018-05-01

A weekly cycle of surface particulate matter (PM) characterized by smaller values during weekends and larger values during weekdays was reported in eastern China. Whether column-integrated aerosol optical depth (AOD) showed similar weekly cycling as that of PM was debated. The weekly variation of AOD in eastern China was further studied by using the latest MODIS aerosol product (collection 6) with a fine spatial resolution (0.1°) from 2002 to 2015. We used three statistical methods to determine whether the weekly cycle of AOD was significant. AOD during weekdays (Wednesday to Friday) was lower than that during weekends. The maximum and minimum AOD was generally observed on Monday and Wednesday, respectively. This weekly pattern of AOD was in good agreement with previous results based on satellite aerosol products with a coarse spatial resolution, but it was in contrast to that of PM. Further analysis of the AOD weekly variability in 19 provincial cities suggested that AOD during weekdays was smaller than that during weekends in urban regions. Potential causes for the different weekly cycle of PM and AOD in eastern China were discussed.

Answering the Call for Model-Relevant Observations of Aerosols and Clouds

NASA Technical Reports Server (NTRS)

Redemann, J.; Shinozuka, Y.; Kacenelenbogen, M.; Segal-Rozenhaimer, M.; LeBlanc, S.; Vaughan, M.; Stier, P.; Schutgens, N.

2017-01-01

We describe a technique for combining multiple A-Train aerosol data sets, namely MODIS spectral AOD (aerosol optical depth), OMI AAOD (absorption aerosol optical depth) and CALIOP aerosol backscatter retrievals (hereafter referred to as MOC retrievals) to estimate full spectral sets of aerosol radiative properties, and ultimately to calculate the 3-D distribution of direct aerosol radiative effects (DARE). We present MOC results using almost two years of data collected in 2007 and 2008, and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. We compare the spatio-temporal distribution of the MOC retrievals and MOC-based calculations of seasonal clear-sky DARE to values derived from four models that participated in the Phase II AeroCom model intercomparison initiative. Comparisons of seasonal aerosol property to AeroCom Phase II results show generally good agreement best agreement with forcing results at TOA is found with GMI-MerraV3.We discuss the challenges in making observations that really address deficiencies in models, with some of the more relevant aspects being representativeness of the observations for climatological states, and whether a given model-measurement difference addresses a sampling or a model error.

Influence of Aerosols And Surface Reflectance On NO2 Retrieval Over China From 2005 to 2015

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.

2016-12-01

Satellite observation is a powerful way to analysis annual and seasonal variations of nitrogen dioxide (NO2). However, much retrieval of vertical column densities (VCDs) of normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. In traditional retrieval, aerosols' effects are often considered as cloud. However, China has complicated aerosols type and aerosol loading. Their optical properties may be very different from the cloud. Furthermore, China has undergone big changes in land use type in recent 10 years. Traditional climatology surface reflectance data may not have representation. In order to study spatial-temporal variation of and influences of these two factors on variations and trends, we use an improved retrieval method of VCDs over China, called the POMINO, based on measurements from the Ozone Monitoring Instrument (OMI), and we compare the results of without aerosol, without surface reflectance treatments and without both to the original POMINO product from 2005 to 2015. Furthermore, we will study correspondent spatial-temporal variations of aerosols, represented by MODIS aerosol optical depth (AOD) data and CALIOP extinction data; surface reflectance, represented by MODIS bidirectional reflectance distribution function (BRDF) data.

An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

NASA Astrophysics Data System (ADS)

Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

2016-09-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

System engineering approach to GPM retrieval algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, C. R.; Chandrasekar, V.

2004-01-01

System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Groundmore » validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do calculated at each bin, the rain rate can then be calculated based on a suitable rain-rate model. This paper develops a system engineering interface to the retrieval algorithms while remaining cognizant of system engineering issues so that it can be used to bridge the divide between algorithm physics an d overall mission requirements. Additionally, in line with the systems approach, a methodology is developed such that the measurement requirements pass through the retrieval model and other subsystems and manifest themselves as measurement and other system constraints. A systems model has been developed for the retrieval algorithm that can be evaluated through system-analysis tools such as MATLAB/Simulink.« less

The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor

NASA Astrophysics Data System (ADS)

Loyola, Diego G.; Gimeno García, Sebastián; Lutz, Ronny; Argyrouli, Athina; Romahn, Fabian; Spurr, Robert J. D.; Pedergnana, Mattia; Doicu, Adrian; Molina García, Víctor; Schüssler, Olena

2018-01-01

This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV) and visible (VIS) spectral regions, and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR). Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME) on board the second European Remote-Sensing Satellite (ERS-2) over 20 years ago. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI) and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN.

Long-term observation of aerosol cloud relationships in the Mid-Atlantic region

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.; Yin, B.

2013-12-01

Long-term ground-based observations of aerosol and cloud properties derived from measurements of Multifilter Rotating Shadow Band Radiometer and microwave radiometer at an atmospheric measurement field station in the Baltimore-Washington corridor operated by Howard University are used to examine the temporal variation of aerosol and cloud properties and moreover aerosol indirect effect on clouds. Through statistical analysis of five years (from 2006 to 2010) of these observations, the proportion of polluted cases is found larger in 2006 and 2007 and the proportion of optically thick clouds cases is also larger in 2006 and 2007 than that in 2008, 2009 and 2010. Both the mean aerosol optical depth (AOD) and cloud optical depth (COD) are observed decreasing from 2006 to 2010 but there is no obvious trend observed on cloud liquid water path (LWP). Because of the limit of AOD retrievals under cloudy conditions surface measurements of fine particle particulate matter 2.5 (PM2.5) were used for assessing aerosol indirect effect. A positive relationship between LWP and cloud droplets effective radius (Re) and a negative relationship between PM2.5 and Re are observed based on a stringent case selection method which is used to reduce the uncertainties from retrieval and meteorological impacts. The total 5 years summer time observations are segregated according to the value of PM2.5. Examination of distributions of COD, cloud condensation nuclei (CCN), cloud droplets effective radius and LWP under polluted and pristine conditions further confirm that the high aerosol loading decreases cloud droplets effective radius and increases cloud optical depth.

Study of Desert Dust Events over the Southwestern Iberian Peninsula in Year 2000: Two Case Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cachorro, V. E.; Vergaz, R.; de Frutos, A. M.

2006-03-07

Strong desert dust events occurring in 2000 over the southwestern Atlantic coast of the Iberian Peninsula are detected and evaluated by means of the TOMS Aerosol Index (A.I.) at three different sites, Funchal (Madeira Island, Portugal), Lisboa (Portugal), and El Arenosillo (Huelva, Spain). At the El Arenosillo station, measurements from an AERONET Cimel sunphotometer allow more retrieval of the spectral AOD and the derived alpha ''angstrom'' coefficient. After using different threshold values of these parameters, we conclude that it is difficult to establish reliable and robust criteria for an automatic estimation of the number of dust episodes and the totalmore » number of dusty days per year. As a result, additional information, such as airmass trajectories, were used to improve the estimation, from which reasonable results were obtained (although some manual editing was still needed). A detailed characterization of two selected desert dust episodes, a strong event in winter and another of less intensity in summer, was carried out using AOD derived from Brewer spectrometer measurements. Size distribution parameters and radiative properties, such as refractive index and the aerosol single scattering albedo derived from Cimel data, were analyzed in detail for one of these two case studies. Although specific to this dust episode, the retrieved range of values of these parameters clearly reflect the characteristics of desert aerosols. Back-trajectory analysis, synoptic weather maps and satellite images were also considered together, as supporting data to assess the aerosol desert characterization in this region of study.« less

Consistency of two global MODIS aerosol products over ocean on Terra and Aqua CERES SSF datasets

NASA Astrophysics Data System (ADS)

Ignatov, Alexander; Minnis, Patrick; Wielicki, Bruce; Loeb, Norman G.; Remer, Lorraine A.; Kaufman, Yoram J.; Miller, Walter F.; Sun-Mack, Sunny; Laszlo, Istvan; Geier, Erika B.

2004-12-01

MODIS aerosol retrievals over ocean from Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side by side. The primary M product is generated by subsetting and remapping the multi-spectral (0.44 - 2.1 μm) MOD04 aerosols onto CERES footprints. MOD04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary (AVHRR-like) A product is generated in only two MODIS bands: 1 and 6 on Terra, and ` and 7 on Aqua. The A processing uses NASA/LaRC cloud-screening and NOAA/NESDIS single channel aerosol algorthm. The M and A products have been documented elsewhere and preliminarily compared using two weeks of global Terra CERES SSF (Edition 1A) data in December 2000 and June 2001. In this study, the M and A aerosol optical depths (AOD) in MODIS band 1 and (0.64 μm), τ1M and τ1A, are further checked for cross-platform consistency using 9 days of global Terra CERES SSF (Edition 2A) and Aqua CERES SSF (Edition 1A) data from 13 - 21 October 2002.

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE PAGES

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

2014-12-01

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

An Uncertainty Quantification Framework for Remote Sensing Retrievals

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Hobbs, J.

2017-12-01

Remote sensing data sets produced by NASA and other space agencies are the result of complex algorithms that infer geophysical state from observed radiances using retrieval algorithms. The processing must keep up with the downlinked data flow, and this necessitates computational compromises that affect the accuracies of retrieved estimates. The algorithms are also limited by imperfect knowledge of physics and of ancillary inputs that are required. All of this contributes to uncertainties that are generally not rigorously quantified by stepping outside the assumptions that underlie the retrieval methodology. In this talk we discuss a practical framework for uncertainty quantification that can be applied to a variety of remote sensing retrieval algorithms. Ours is a statistical approach that uses Monte Carlo simulation to approximate the sampling distribution of the retrieved estimates. We will discuss the strengths and weaknesses of this approach, and provide a case-study example from the Orbiting Carbon Observatory 2 mission.

Microphysical characterization of long-range transported biomass burning particles from North America at three EARLINET stations

NASA Astrophysics Data System (ADS)

Ortiz-Amezcua, Pablo; Guerrero-Rascado, Juan Luis; José Granados-Muñoz, María; Benavent-Oltra, José Antonio; Böckmann, Christine; Samaras, Stefanos; Stachlewska, Iwona S.; Janicka, Łucja; Baars, Holger; Bohlmann, Stephanie; Alados-Arboledas, Lucas

2017-05-01

Strong events of long-range transported biomass burning aerosol were detected during July 2013 at three EARLINET (European Aerosol Research Lidar Network) stations, namely Granada (Spain), Leipzig (Germany) and Warsaw (Poland). Satellite observations from MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instruments, as well as modeling tools such as HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) and NAAPS (Navy Aerosol Analysis and Prediction System), have been used to estimate the sources and transport paths of those North American forest fire smoke particles. A multiwavelength Raman lidar technique was applied to obtain vertically resolved particle optical properties, and further inversion of those properties with a regularization algorithm allowed for retrieving microphysical information on the studied particles. The results highlight the presence of smoke layers of 1-2 km thickness, located at about 5 km a.s.l. altitude over Granada and Leipzig and around 2.5 km a.s.l. at Warsaw. These layers were intense, as they accounted for more than 30 % of the total AOD (aerosol optical depth) in all cases, and presented optical and microphysical features typical for different aging degrees: color ratio of lidar ratios (LR532 / LR355) around 2, α-related ångström exponents of less than 1, effective radii of 0.3 µm and large values of single scattering albedos (SSA), nearly spectrally independent. The intensive microphysical properties were compared with columnar retrievals form co-located AERONET (Aerosol Robotic Network) stations. The intensity of the layers was also characterized in terms of particle volume concentration, and then an experimental relationship between this magnitude and the particle extinction coefficient was established.

A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

PubMed

Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

2012-04-01

We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

Measurement-based climatology of aerosol direct radiative effect, its sensitivities, and uncertainties from a background southeast US site

NASA Astrophysics Data System (ADS)

Sherman, James P.; McComiskey, Allison

2018-03-01

Aerosol optical properties measured at Appalachian State University's co-located NASA AERONET and NOAA ESRL aerosol network monitoring sites over a nearly four-year period (June 2012-Feb 2016) are used, along with satellite-based surface reflectance measurements, to study the seasonal variability of diurnally averaged clear sky aerosol direct radiative effect (DRE) and radiative efficiency (RE) at the top-of-atmosphere (TOA) and at the surface. Aerosol chemistry and loading at the Appalachian State site are likely representative of the background southeast US (SE US), home to high summertime aerosol loading and one of only a few regions not to have warmed during the 20th century. This study is the first multi-year ground truth DRE study in the SE US, using aerosol network data products that are often used to validate satellite-based aerosol retrievals. The study is also the first in the SE US to quantify DRE uncertainties and sensitivities to aerosol optical properties and surface reflectance, including their seasonal dependence.Median DRE for the study period is -2.9 W m-2 at the TOA and -6.1 W m-2 at the surface. Monthly median and monthly mean DRE at the TOA (surface) are -1 to -2 W m-2 (-2 to -3 W m-2) during winter months and -5 to -6 W m-2 (-10 W m-2) during summer months. The DRE cycles follow the annual cycle of aerosol optical depth (AOD), which is 9 to 10 times larger in summer than in winter. Aerosol RE is anti-correlated with DRE, with winter values 1.5 to 2 times more negative than summer values. Due to the large seasonal dependence of aerosol DRE and RE, we quantify the sensitivity of DRE to aerosol optical properties and surface reflectance, using a calendar day representative of each season (21 December for winter; 21 March for spring, 21 June for summer, and 21 September for fall). We use these sensitivities along with measurement uncertainties of aerosol optical properties and surface reflectance to calculate DRE uncertainties. We also estimate uncertainty in calculated diurnally-averaged DRE due to diurnal aerosol variability. Aerosol DRE at both the TOA and surface is most sensitive to changes in AOD, followed by single-scattering albedo (ω0). One exception is under the high summertime aerosol loading conditions (AOD ≥ 0.15 at 550 nm), when sensitivity of TOA DRE to ω0 is comparable to that of AOD. Aerosol DRE is less sensitive to changes in scattering asymmetry parameter (g) and surface reflectance (R). While DRE sensitivity to AOD varies by only ˜ 25 to 30 % with season, DRE sensitivity to ω0, g, and R largely follow the annual AOD cycle at APP, varying by factors of 8 to 15 with season. Since the measurement uncertainties of AOD, ω0, g, and R are comparable at Appalachian State, their relative contributions to DRE uncertainty are largely influenced by their (seasonally dependent) DRE sensitivity values, which suggests that the seasonal dependence of DRE uncertainty must be accounted for. Clear sky aerosol DRE uncertainty at the TOA (surface) due to measurement uncertainties ranges from 0.45 (0.75 W m-2) for December to 1.1 (1.6 W m-2) for June. Expressed as a fraction of DRE computed using monthly median aerosol optical properties and surface reflectance, the DRE uncertainties at TOA (surface) are 20 to 24 % (15 to 22 %) for March, June, and September and 49 (50 %) for DEC. The relatively low DRE uncertainties are largely due to the low uncertainty in AOD measured by AERONET. Use of satellite-based AOD measurements by MODIS in the DRE calculations increases DRE uncertainties by a factor of 2 to 5 and DRE uncertainties are dominated by AOD uncertainty for all seasons. Diurnal variability in AOD (and to a lesser extent g) contributes to uncertainties in DRE calculated using daily-averaged aerosol optical properties that are slightly larger (by ˜ 20 to 30 %) than DRE uncertainties due to measurement uncertainties during summer and fall, with comparable uncertainties during winter and spring.

Analysis of the weekly cycle of aerosol optical depth using AERONET and MODIS data

NASA Astrophysics Data System (ADS)

Xia, Xiangao; Eck, Tom F.; Holben, Brent N.; Phillippe, Goloub; Chen, Hongbin

2008-07-01

Multi-year Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data are used to study AOD weekly variations at the global scale. A clear weekly cycle of AOD is observed in the United States (U.S.) and Central Europe. AOD during the weekday is larger than that during the weekend in 36 out of 43 AERONET sites in the U.S. The average U.S. weekend effect (the percent difference in AOD during the weekday and the weekend) is 3.8%. A weekly periodicity with lower AODs on Sunday and Monday and higher AODs from Wednesday until Saturday is revealed over Central Europe and the average weekend effect there is 4.0%. The weekly cycle in urban sites is greater than that in rural sites. AOD during the weekday is also significantly larger than that during the weekend in urban AERONET sites in South America and South Korea. However, a reversed AOD weekly cycle is observed in the Middle East and India. AODs on Thursday and Friday, the "weekend" for Middle East cultures, are relatively lower than AODs on other days. There is no clear weekly variation of AOD over eastern China. The striking feature in this region is the occurrence of much higher AOD on Sunday and this phenomenon is independent of season. The analysis of MODIS aerosol data is in good agreement with that of AERONET data.

Development of a remote sensing algorithm to retrieve atmospheric aerosol properties using multiwavelength and multipixel information

NASA Astrophysics Data System (ADS)

Hashimoto, Makiko; Nakajima, Teruyuki

2017-06-01

We developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using satellite-received radiances for multiple wavelengths and pixels. Our algorithm utilizes spatial inhomogeneity of surface reflectance to retrieve aerosol properties, and the main target is urban aerosols. This algorithm can simultaneously retrieve aerosol optical thicknesses (AOT) for fine- and coarse-mode aerosols, soot volume fraction in fine-mode aerosols (SF), and surface reflectance over heterogeneous surfaces such as urban areas that are difficult to obtain by conventional pixel-by-pixel methods. We applied this algorithm to radiances measured by the Greenhouse Gases Observing Satellite/Thermal and Near Infrared Sensor for Carbon Observations-Cloud and Aerosol Image (GOSAT/TANSO-CAI) at four wavelengths and were able to retrieve the aerosol parameters in several urban regions and other surface types. A comparison of the retrieved AOTs with those from the Aerosol Robotic Network (AERONET) indicated retrieval accuracy within ±0.077 on average. It was also found that the column-averaged SF and the aerosol single scattering albedo (SSA) underwent seasonal changes as consistent with the ground surface measurements of SSA and black carbon at Beijing, China.

North Atlantic Aerosol Properties for Radiative Impact Assessments. Derived from Column Closure Analyses in TARFOX and ACE-2

NASA Technical Reports Server (NTRS)

Russell, Philip A.; Bergstrom, Robert A.; Schmid, Beat; Livingston, John M.

2000-01-01

Aerosol effects on atmospheric radiative fluxes provide a forcing function that can change the climate in potentially significant ways. This aerosol radiative forcing is a major source of uncertainty in understanding the climate change of the past century and predicting future climate. To help reduce this uncertainty, the 1996 Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) and the 1997 Aerosol Characterization Experiment (ACE-2) measured the properties and radiative effects of aerosols over the Atlantic Ocean. Both experiments used remote and in situ measurements from aircraft and the surface, coordinated with overpasses by a variety of satellite radiometers. TARFOX focused on the urban-industrial haze plume flowing from the United States over the western Atlantic, whereas ACE-2 studied aerosols over the eastern Atlantic from both Europe and Africa. These aerosols often have a marked impact on satellite-measured radiances. However, accurate derivation of flux changes, or radiative forcing, from the satellite measured radiances or retrieved aerosol optical depths (AODs) remains a difficult challenge. Here we summarize key initial results from TARFOX and ACE-2, with a focus on closure analyses that yield aerosol microphysical models for use in improved assessments of flux changes. We show how one such model gives computed radiative flux sensitivities (dF/dAOD) that agree with values measured in TARFOX and preliminary values computed for the polluted marine boundary layer in ACE-2. A companion paper uses the model to compute aerosol-induced flux changes over the North Atlantic from AVHRR-derived AOD fields.

Global View of Aerosol Vertical Distributions from CALIPSO Lidar Measurements and GOCART Simulations: Regional and Seasonal Variations

NASA Technical Reports Server (NTRS)

Yu, Hongbin; Chin, Mian; Winker, David M.; Omar, Ali H.; Liu, Zhaoyan; Kittaka, Chieko; Diehl, Thomas

2010-01-01

This study examines seasonal variations of the vertical distribution of aerosols through a statistical analysis of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations from June 2006 to November 2007. A data-screening scheme is developed to attain good quality data in cloud-free conditions, and the polarization measurement is used to separate dust from non-dust aerosol. The CALIPSO aerosol observations are compared with aerosol simulations from the Goddard Chemistry Aerosol Radiation Transport (GOCART) model and aerosol optical depth (AOD) measurements from the MODerate resolution Imaging Spectroradiometer (MODIS). The CALIPSO observations of geographical patterns and seasonal variations of AOD are generally consistent with GOCART simulations and MODIS retrievals especially near source regions, while the magnitude of AOD shows large discrepancies in most regions. Both the CALIPSO observation and GOCART model show that the aerosol extinction scale heights in major dust and smoke source regions are generally higher than that in industrial pollution source regions. The CALIPSO aerosol lidar ratio also generally agrees with GOCART model within 30% on regional scales. Major differences between satellite observations and GOCART model are identified, including (1) an underestimate of aerosol extinction by GOCART over the Indian sub-continent, (2) much larger aerosol extinction calculated by GOCART than observed by CALIPSO in dust source regions, (3) much weaker in magnitude and more concentrated aerosol in the lower atmosphere in CALIPSO observation than GOCART model over transported areas in midlatitudes, and (4) consistently lower aerosol scale height by CALIPSO observation than GOCART model. Possible factors contributing to these differences are discussed.

The validation of the Yonsei CArbon Retrieval algorithm with improved aerosol information using GOSAT measurements

NASA Astrophysics Data System (ADS)

Jung, Yeonjin; Kim, Jhoon; Kim, Woogyung; Boesch, Hartmut; Goo, Tae-Young; Cho, Chunho

2017-04-01

Although several CO2 retrieval algorithms have been developed to improve our understanding about carbon cycle, limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. Based on an optimal estimation method, the Yonsei CArbon Retrieval (YCAR) algorithm was developed to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) using the Greenhouse Gases Observing SATellite (GOSAT) measurements with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) are the most important factors in CO2 retrievals since AOPs are assumed as fixed parameters during retrieval process, resulting in significant XCO2 retrieval error up to 2.5 ppm. In this study, to reduce these errors caused by inaccurate aerosol optical information, the YCAR algorithm improved with taking into account aerosol optical properties as well as aerosol vertical distribution simultaneously. The CO2 retrievals with two difference aerosol approaches have been analyzed using the GOSAT spectra and have been evaluated throughout the comparison with collocated ground-based observations at several Total Carbon Column Observing Network (TCCON) sites. The improved YCAR algorithm has biases of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, with smaller biases and higher correlation coefficients compared to the GOSAT operational algorithm. In addition, the XCO2 retrievals will be validated at other TCCON sites and error analysis will be evaluated. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties. This study would be expected to provide useful information in estimating carbon sources and sinks.

Updates on the development of Deep Blue aerosol algorithm for constructing consistent long-term data records from MODIS to VIIRS

NASA Astrophysics Data System (ADS)

Hsu, N. Y. C.; Sayer, A. M.; Lee, J.; Kim, W. V.

2017-12-01

The impacts of natural and anthropogenic sources of air pollution on climate and human health have continued to gain attention from the scientific community. In order to facilitate these effects, high quality consistent long-term global aerosol data records from satellites are essential. Several EOS-era instruments (e.g., SeaWiFS, MODIS, and MISR) are able to provide such information with a high degree of fidelity. However, with the aging MODIS sensors and the launch of the VIIRS instrument on Suomi NPP in late 2011, the continuation of long-term aerosol data records suitable for climate studies from MODIS to VIIRS is needed urgently. Recently, we have successfully modified our MODIS Deep Blue algorithm to process the VIIRS data. Extensive works were performed in refining the surface reflectance determination scheme to account for the wavelength differences between MODIS and VIIRS. Better aerosol models (including non-spherical dust) are also now implemented in our VIIRS algorithm compared to the MODIS C6 algorithm. We will show the global (land and ocean) distributions of various aerosol products from Version 1 of the VIIRS Deep Blue data set. The preliminary validation results of these new VIIRS Deep Blue aerosol products using data from AERONET sunphotometers over land and ocean will be discussed. We will also compare the monthly averaged Deep Blue aerosol optical depth (AOD) from VIIRS with the MODIS C6 products to investigate if any systematic biases may exist between MODIS C6 and VIIRS AOD. The Version 1 VIIRS Deep Blue aerosol products are currently scheduled to be released to the public in 2018.

Satellite Remote Sensing for Developing Time and Space Resolved Estimates of Ambient Particulate in Cleveland, OH.

PubMed

Kumar, Naresh; Chu, Allen D; Foster, Andrew D; Peters, Thomas; Willis, Robert

2011-09-01

This article empirically demonstrates the use of fine resolution satellite-based aerosol optical depth (AOD) to develop time and space resolved estimates of ambient particulate matter (PM) ≤2.5 µm and ≤10 µm in aerodynamic diameters (PM(2.5) and PM(10), respectively). AOD was computed at three different spatial resolutions, i.e., 2 km (means 2 km × 2 km area at nadir), 5 km, and 10 km, by using the data from MODerate Resolution Imaging Spectroradiometer (MODIS), aboard the Terra and Aqua satellites. Multiresolution AOD from MODIS (AOD(MODIS)) was compared with the in situ measurements of AOD by NASA's AErosol RObotic NETwork (AERONET) sunphotometer (AOD(AERONET)) at Bondville, IL, to demonstrate the advantages of the fine resolution AOD(MODIS) over the 10-km AOD(MODIS), especially for air quality prediction. An instrumental regression that corrects AOD(MODIS) for meteorological conditions was used for developing a PM predictive model.The 2-km AOD(MODIS) aggregated within 0.025° and 15-min intervals shows the best association with the in situ measurements of AOD(AERONET). The 2-km AOD(MODIS) seems more promising to estimate time and space resolved estimates of ambient PM than the 10-km AOD(MODIS), because of better location precision and a significantly greater number of data points across geographic space and time. Utilizing the collocated AOD(MODIS) and PM data in Cleveland, OH, a regression model was developed for predicting PM for all AOD(MODIS) data points. Our analysis suggests that the slope of the 2-km AOD(MODIS) (instrumented on meteorological conditions) is close to unity with the PM monitored on the ground. These results should be interpreted with caution, because the slope of AOD(MODIS) ranges from 0.52 to 1.72 in the site-specific models. In the cross validation of the overall model, the root mean square error (RMSE) of PM(10) was smaller (2.04 µg/m(3) in overall model) than that of PM(2.5) (2.5 µg/m(3)). The predicted PM in the AOD(MODIS) data (∼2.34 million data points) was utilized to develop a systematic grid of daily PM at 5-km spatial resolution with the aid of spatiotemporal Kriging.

Variation in MERRA-2 aerosol optical depth over the Yangtze River Delta from 1980 to 2016

NASA Astrophysics Data System (ADS)

Sun, Enwei; Che, Huizheng; Xu, Xiaofeng; Wang, Zhenzhu; Lu, Chunsong; Gui, Ke; Zhao, Hujia; Zheng, Yu; Wang, Yaqiang; Wang, Hong; Sun, Tianze; Liang, Yuanxin; Li, Xiaopan; Sheng, Zhizhong; An, Linchang; Zhang, Xiaoye; Shi, Guangyu

2018-05-01

In this study, 765 instantaneous MERRA-2 (second Modern-Era Retrospective analysis for Research and Applications) aerosol optical depth (AOD) values at 550 nm were compared with those of a sky radiometer in Hefei (31.90° N, 117.17° E) for the different seasons from March 2007 to February 2010. The correlation coefficients (R) were 0.88, 0.83, 0.88, and 0.80 in spring, summer, autumn, and winter, respectively. The MERRA-2 AOD is also compared with MODIS Aqua AOD in the entire Yangtze River Delta, and good agreement has been obtained. The MERRA-2 AOD product was used to analyze the spatial distribution and temporal variation of the annual, seasonal and monthly means of the AOD over the Yangtze River Delta region from 1980 to 2016 (37 years). The mean values of the MERRA-2 AOD during the study period show that the AOD (between 0.45 and 0.55) in the northern area of the Yangtze River Delta was higher than that (between 0.30 and 0.45) of the southern area. The northwest part of the Yangtze River Delta had the highest mean AOD values (between 0.50 and 0.55). The AOD increased slowly in the 1980s and 1990s, followed by a rapid increase between 2001 and 2010. An AOD decrease can be seen from 2011 to 2016. The mean AOD in each month is discussed. High AOD was observed in March, April, and June, while low AOD could be seen in September, October, November, and December. Three different area types (large cities, medium-sized cities, and remote areas) had nearly the same annual AOD variation. Large cities had the highest AOD (about 0.48), while remote areas had the lowest (about 0.42). In summer, the AOD in remote areas was much lower than that in cities. The AOD variational trend over the Yangtze River Delta was studied during two periods. The increasing trend could be seen over the entire Yangtze River Delta in each month from 1980 to 2009. A decreasing trend was found all over the Yangtze River Delta in January, February, March, July, October, and November, whereas in other months, some parts witnessed increasing AOD while others saw a decreasing trend between 2010 and 2016.

A New Inversion-Based Algorithm for Retrieval of Over-Water Rain Rate from SSM/I Multichannel Imagery

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Stettner, David R.

1994-01-01

This paper discusses certain aspects of a new inversion based algorithm for the retrieval of rain rate over the open ocean from the special sensor microwave/imager (SSM/I) multichannel imagery. This algorithm takes a more detailed physical approach to the retrieval problem than previously discussed algorithms that perform explicit forward radiative transfer calculations based on detailed model hydrometer profiles and attempt to match the observations to the predicted brightness temperature.

Are perceptions of social norms regarding peer alcohol and other drug use associated with personal use in Danish adolescents?

PubMed

Vallentin-Holbech, Lotte; Rasmussen, Birthe Marie; Stock, Christiane

2017-12-01

This study aims to describe norm perceptions among Danish pupils aged 13-17 years related to the prevalence of personal lifetime use of alcohol and other drugs (AODs). Further we examined if norm perceptions were associated with personal lifetime AOD use. The data were collected as baseline data in the trial The GOOD Life. A total of 2601 pupils from 42 public schools in the Region of Southern Denmark completed an online questionnaire measuring personal lifetime AOD use and personal approval of use. Additionally the perceived frequency of AOD use and approval of use among peers of their own grade were measured. Lifetime AOD outcome variables were alcohol consumption (at least one drink, being drunk and had five or more drinks on one occasion), smoking, and cannabis use. Pupils' perceptions of peer approval were significantly higher than pupils' personal approval of AOD use among adolescents for all outcomes. With the exception of cannabis use the estimated AOD prevalence among peers (median) were higher than the actual prevalence of personal lifetime use. Multilevel logistic regression models showed a significantly increased risk of personal AOD use for pupils that overestimated their peers' AOD use and also for pupils that perceived peers to approve of AOD use. The findings highlight that pupils' exaggerated perceptions regarding their peers' use and approval of AOD use are related to personal experience with AODs.

NCEP Air Quality Forecast(AQF) Verification. NOAA/NWS/NCEP/EMC

Science.gov Websites

average Select forecast four: Day 1 AOD skill for all thresholds Day 1 Time series for AOD GT 0 Day 2 AOD skill for all thresholds Day 2 Time series for AOD GT 0 Diurnal plots for AOD GT 0 Select statistic type

Introducing MISR Version 23: Resolution and Content Improvements to MISR Aerosol and Land Surface Product

NASA Astrophysics Data System (ADS)

Garay, M. J.; Bull, M. A.; Witek, M. L.; Diner, D. J.; Seidel, F.

2017-12-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing operational Level 2 (swath-based) aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution and atmospherically corrected land surface products at 1.1 km resolution. A major, multi-year development effort has led to the release of updated operational MISR Level 2 aerosol and land surface retrieval products. The spatial resolution of the aerosol product has been increased to 4.4 km, allowing more detailed characterization of aerosol spatial variability, especially near local sources and in urban areas. The product content has been simplified and updated to include more robust measures of retrieval uncertainty and other fields to benefit users. The land surface product has also been updated to incorporate the Version 23 aerosol product as input and to improve spatial coverage, particularly over mountainous terrain and snow/ice-covered surfaces. We will describe the major upgrades incorporated in Version 23, present validation of the aerosol product, and describe some of the applications enabled by these product updates.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

Retrieving Atmospheric Profiles Data in the Presence of Clouds from Hyperspectral Remote Sensing Data

NASA Technical Reports Server (NTRS)

Liu, Xu; Larar, Allen M.; Zhou, Daniel K.; Kizer, Susan H.; Wu, Wan; Barnet, Christopher; Divakarla, Murty; Guo, Guang; Blackwell, Bill; Smith, William L.;

Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns

NASA Technical Reports Server (NTRS)

Redemann, J.; Flynn, C. J.; Shinozuka, Y.; Kacenelenbogen, M.; Segal-Rosenheimer, M.; LeBlanc, S.; Russell, P. B.; Livingston, J. M.; Schmid, B.; Dunagan, S. E.;

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands.

PubMed

Salem, Salem Ibrahim; Higa, Hiroto; Kim, Hyungjun; Kobayashi, Hiroshi; Oki, Kazuo; Oki, Taikan

2017-07-31

Numerous algorithms have been proposed to retrieve chlorophyll- a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m -3 , 16.25 mg·m -3 , and 19.05 mg·m -3 , respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll- a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the algorithms that incorporate the 665-nm band outperform other algorithms for measured dataset (RMSE = 36.84 mg·m -3 ), while algorithms that incorporate the band tuning approach provide the highest retrieval accuracy for the simulated dataset (RMSE = 25.05 mg·m -3 ).

Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands

PubMed Central

Higa, Hiroto; Kobayashi, Hiroshi; Oki, Kazuo

2017-01-01

Numerous algorithms have been proposed to retrieve chlorophyll-a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m−3, 16.25 mg·m−3, and 19.05 mg·m−3, respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll-a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the algorithms that incorporate the 665-nm band outperform other algorithms for measured dataset (RMSE = 36.84 mg·m−3), while algorithms that incorporate the band tuning approach provide the highest retrieval accuracy for the simulated dataset (RMSE = 25.05 mg·m−3). PMID:28758984

Validation of YCAR algorithm over East Asia TCCON sites

NASA Astrophysics Data System (ADS)

Kim, W.; Kim, J.; Jung, Y.; Lee, H.; Goo, T. Y.; Cho, C. H.; Lee, S.

2016-12-01

In order to reduce the retrieval error of TANSO-FTS column averaged CO2 concentration (XCO2) induced by aerosol, we develop the Yonsei university CArbon Retrieval (YCAR) algorithm using aerosol information from TANSO-Cloud and Aerosol Imager (TANSO-CAI), providing simultaneous aerosol optical depth properties for the same geometry and optical path along with the FTS. Also we validate the retrieved results using ground-based TCCON measurement. Particularly this study first utilized the measurements at Anmyeondo, the only TCCON site located in South Korea, which can improve the quality of validation in East Asia. After the post screening process, YCAR algorithms have higher data availability by 33 - 85 % than other operational algorithms (NIES, ACOS, UoL). Although the YCAR algorithm has higher data availability, regression analysis with TCCON measurements are better or similar to other algorithms; Regression line of YCAR algorithm is close to linear identity function with RMSE of 2.05, bias of - 0.86 ppm. According to error analysis, retrieval error of YCAR algorithm is 1.394 - 1.478 ppm at East Asia. In addition, spatio-temporal sampling error of 0.324 - 0.358 ppm for each single sounding retrieval is also analyzed with Carbon Tracker - Asia data. These results of error analysis reveal the reliability and accuracy of latest version of our YCAR algorithm. Both XCO2 values retrieved using YCAR algorithm on TANSO-FTS and TCCON measurements show the consistent increasing trend about 2.3 - 2.6 ppm per year. Comparing to the increasing rate of global background CO2 amount measured in Mauna Loa, Hawaii (2 ppm per year), the increasing trend in East Asia shows about 30% higher trend due to the rapid increase of CO2 emission from the source region.

An advanced retrieval algorithm for greenhouse gases using polarization information measured by GOSAT TANSO-FTS SWIR I: Simulation study

NASA Astrophysics Data System (ADS)

Kikuchi, N.; Yoshida, Y.; Uchino, O.; Morino, I.; Yokota, T.

2016-11-01

We present an algorithm for retrieving column-averaged dry air mole fraction of carbon dioxide (XCO2) and methane (XCH4) from reflected spectra in the shortwave infrared (SWIR) measured by the TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) sensor on board the Greenhouse gases Observing SATellite (GOSAT). The algorithm uses the two linear polarizations observed by TANSO-FTS to improve corrections to the interference effects of atmospheric aerosols, which degrade the accuracy in the retrieved greenhouse gas concentrations. To account for polarization by the land surface reflection in the forward model, we introduced a bidirectional reflection matrix model that has two parameters to be retrieved simultaneously with other state parameters. The accuracy in XCO2 and XCH4 values retrieved with the algorithm was evaluated by using simulated retrievals over both land and ocean, focusing on the capability of the algorithm to correct imperfect prior knowledge of aerosols. To do this, we first generated simulated TANSO-FTS spectra using a global distribution of aerosols computed by the aerosol transport model SPRINTARS. Then the simulated spectra were submitted to the algorithms as measurements both with and without polarization information, adopting a priori profiles of aerosols that differ from the true profiles. We found that the accuracy of XCO2 and XCH4, as well as profiles of aerosols, retrieved with polarization information was considerably improved over values retrieved without polarization information, for simulated observations over land with aerosol optical thickness greater than 0.1 at 1.6 μm.

Development of a generalized algorithm of satellite remote sensing using multi-wavelength and multi-pixel information (MWP method) for aerosol properties by satellite-borne imager

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Morimoto, S.; Takenaka, H.

2014-12-01

We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-wavelength and multi-pixel information of satellite imagers (MWP method). In this algorithm, the inversion method is a combination of maximum a posteriori (MAP) method (Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, with the progress of computing technique, this method has being combined with the direct radiation transfer calculation numerically solved by each iteration step of the non-linear inverse problem, without using LUT (Look Up Table) with several constraints.Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area.We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode, soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Then, we applied this algorithm to GOSAT/CAI imager data, and we compared retrieved and surface-observed AOTs at the CAI pixel closest to an AERONET (Aerosol Robotic Network) or SKYNET site in each region. Comparison at several sites in urban area indicated that AOTs retrieved by our method are in agreement with surface-observed AOT within ±0.066.Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

DOE PAGES

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; ...

2016-05-10

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

NASA Technical Reports Server (NTRS)

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-01-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Aerosol climatology over the Mexico City basin: Characterization of optical properties

NASA Astrophysics Data System (ADS)

Carabali, Giovanni; Estévez, Héctor Raúl; Valdés-Barrón, Mauro; Bonifaz-Alfonzo, Roberto; Riveros-Rosas, David; Velasco-Herrera, Víctor Manuel; Vázquez-Gálvez, Felipe Adrián

2017-09-01

Climatology of Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and aerosol particle-size distribution were analyzed using a 15-year (1999-2014) dataset from AErosol RObotic NETwork (AERONET) observations over the Mexico City (MC) basin. The atmosphere over this site is dominated by two main aerosol types, represented by urban/industrial pollution and biomass-burning particles. Due to the specific meteorological conditions within the basin, seasons are usually classified into three as follows: Dry Winter (DW) (November-February); Dry Spring (DS) (March-April), and the RAiny season (RA) (May-October), which are mentioned throughout this article. Using a CIMEL sun photometer, we conducted continuous observations over the MC urban area from January 1999 to December 2014. Aerosol Optical Depth (AOD), Ångström exponent (α440-870), Single Scattering Albedo (SSA), and aerosol particle-size distribution were derived from the observational data. The overall mean AOD500 during the 1999-2014 period was 0.34 ± 0.07. The monthly mean AOD reached a maximal value of 0.49 in May and a minimal value of 0.27 in February and March. The average α440-870 value for the period studied was 1.50 ± 0.16. The monthly average of α440-870 reached a minimal value of 1.32 in August and a maximal value of 1.61 in May. Average SSA at 440 nm was 0.89 throughout the observation period, indicating that aerosols over Mexico City are composed mainly of absorptive particles. Concentrations of fine- and coarse-mode aerosols over MC were highest in DS season compared with other seasons, especially for particles with radii measuring between 0.1 and 0.2 μm. Results from the Spectral De-convolution Algorithm (SDA) show that fine-mode aerosols dominated AOD variability in MC. In the final part of this article, we present a classification of aerosols in MC by using the graphical method proposed by Gobbi et al. (2007), which is based on the combined analysis of α and its spectral curvature δα.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data.

PubMed

Kloog, Itai; Chudnovsky, Alexandra A; Just, Allan C; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-10-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 2.5 ) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM 2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM 2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 2 =0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

PubMed Central

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2017-01-01

Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region. PMID:28966552

A multi-model evaluation of aerosols over South Asia: common problems and possible causes

NASA Astrophysics Data System (ADS)

Pan, X.; Chin, M.; Gautam, R.; Bian, H.; Kim, D.; Colarco, P. R.; Diehl, T. L.; Takemura, T.; Pozzoli, L.; Tsigaridis, K.; Bauer, S.; Bellouin, N.

2015-05-01

Atmospheric pollution over South Asia attracts special attention due to its effects on regional climate, water cycle and human health. These effects are potentially growing owing to rising trends of anthropogenic aerosol emissions. In this study, the spatio-temporal aerosol distributions over South Asia from seven global aerosol models are evaluated against aerosol retrievals from NASA satellite sensors and ground-based measurements for the period of 2000-2007. Overall, substantial underestimations of aerosol loading over South Asia are found systematically in most model simulations. Averaged over the entire South Asia, the annual mean aerosol optical depth (AOD) is underestimated by a range 15 to 44% across models compared to MISR (Multi-angle Imaging SpectroRadiometer), which is the lowest bound among various satellite AOD retrievals (from MISR, SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra). In particular during the post-monsoon and wintertime periods (i.e., October-January), when agricultural waste burning and anthropogenic emissions dominate, models fail to capture AOD and aerosol absorption optical depth (AAOD) over the Indo-Gangetic Plain (IGP) compared to ground-based Aerosol Robotic Network (AERONET) sunphotometer measurements. The underestimations of aerosol loading in models generally occur in the lower troposphere (below 2 km) based on the comparisons of aerosol extinction profiles calculated by the models with those from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Furthermore, surface concentrations of all aerosol components (sulfate, nitrate, organic aerosol (OA) and black carbon (BC)) from the models are found much lower than in situ measurements in winter. Several possible causes for these common problems of underestimating aerosols in models during the post-monsoon and wintertime periods are identified: the aerosol hygroscopic growth and formation of secondary inorganic aerosol are suppressed in the models because relative humidity (RH) is biased far too low in the boundary layer and thus foggy conditions are poorly represented in current models, the nitrate aerosol is either missing or inadequately accounted for, and emissions from agricultural waste burning and biofuel usage are too low in the emission inventories. These common problems and possible causes found in multiple models point out directions for future model improvements in this important region.