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Slutsker, Ilya

Publications and source records attributed to Slutsker, Ilya.

15 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Intercomparison of Aerosol Volume Size Distributions Derived from AERONET Ground-Based Remote Sensing and LARGE in Situ Aircraft Profiles During the 2011–2014 DRAGON and DISCOVER-AQ Experiments

Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH< 20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0:0330:035 μm (ambient AERONET values were 15.8% larger than dried LARGE values), and the average difference in widthpeak_conc was 0:0420:039 μm (AERONET values were 25.7% larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0:0110:019 μm (AERONET values were 5.2% larger) and widthpeak_conc average differences equal to 0:0300:037 μm (AERONET values were 15.8% larger).

Schafer, Joel S.↗
NASA NTRS2019

The Impact of Neglecting Ice Phase on Cloud Optical Depth Retrievals from AERONET Cloud Mode Observations

Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world. Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid. This assumption has the potential to introduce errors into long term statistics of retrieved optical depth for clouds that also contain ice. Using a set of idealized cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence of ice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55% to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2– 4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10% and surface flux to about 15 %.

Shonk, Jonathan K. P.↗
NASA NTRS2019

Global Validation of Columnar Water Vapor Derived from EOS MODIS-MAIAC Algorithm Against the Ground-Based AERONET Observations

The water vapor is a relevant greenhouse gas in the Earth's climate system, and satellite products become one of the most effective way to characterize and monitor the columnar water vapor (CWV) content at global scale. Recently, a new product (MCD19) was released as part of MODIS (Moderate Resolution Imaging Spectroradiometer) Collection 6 (C6). This operational product from the Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm includes a high 1-kilometer resolution CWV retrievals. This study presents the first global validation of MAIAC C6 CWV obtained from MODIS MCD19A2 product. This evaluation was performed using Aerosol Robotic Network (AERONET) observations at 265 sites (2000-2017). Overall, the results show a good agreement between MAIAC/AERONET CWV retrievals, with correlation coefficient higher than 0.95 and RMS (Root Mean Square) error lower than 0.250 centimeters. The binned error analysis revealed an underestimation (approximately 10 percent) of Aqua CWV retrievals with negative bias for CWV higher than 3.0 centimeters. In contrast, Terra CWV retrievals show a slope of regression close to unity and a low mean bias of 0.075 centimeters. While the accuracy is relatively similar between 1.0 and 5.0 centimeters for both sensor products, Terra dataset is more reliable for applications in humid tropical areas (less than 5.0 centimeters). The expected error was defined as plus or minus 15 percent, with less than 68 percent of retrievals falling within this envelope. However, the accuracy is regionally dependent, and lower error should be expected in some regions, such as South America and Oceania. Since MODIS instruments have exceeded their design lifetime, time series analysis was also presented for both sensor products. The temporal analysis revealed a systematic offset of global average between Terra and Aqua CWV records. We also found an upward trend (approximately 0.2 centimeters per decade) in Terra CWV retrievals, while Aqua CWV retrievals remain stable over time. The sensor degradation influences the ability to detect climate signals, and this study indicates the need for revisiting calibration of the MODIS bands 17-19, mainly for Terra instrument, to assure the quality of the MODIS water vapor product. Finally, this study presents a comprehensive validation analysis of MAIAC CWV over land, raising the understanding of its overall quality.

MAIAC↗
NASA NTRS2018

An Overview of Mesoscale Aerosol Processes, Comparisons, and Validation Studies from DRAGON Networks

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Holben, Brent N.↗
NASA NTRS2015

A42A-04: Determination of Cloud Thermodynamic Phase with Ground Based, Polarimetrically Sensitive, Passive Sky Radiometers

When observed from the ground, optically thick clouds minimally polarize light, while the linear polarization direction (angle) of optically thin clouds contains information about thermodynamic phase. For instruments such at the Cimel radiometers that comprise the AErosol RObotic NEtwork (AERONET), these properties can also be exploited to aid cloud optical property retrievals. Using vector radiative transfer simulations, we explore the conditions most favorable to cloud thermodynamic phase determination, then test with actual AERONET data. Results indicate that this technique may be appropriate for some, but not all, conditions, and motivate a deeper investigation about the polarization direction measurement capability of Cimel instruments, which to date have been primarily used to determine degree of polarization. Recent work explores these measurement issues using a newly installed instrument at the NASA Ames Research Center in Moffett Field, California.

Knobelspiesse, Kirk↗
NASA NTRS2015

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

In recent years it was proposed to combine AERONET network photometer capabilities with a high precision lunar model used for satellite calibration to retrieve columnar nighttime AODs. The USGS lunar model can continuously provide pre-atmosphere high precision lunar irradiance determinations for multiple wavelengths at ground sensor locations. When combined with measured irradiances from a ground-based AERONET photometer, atmospheric column transmissions can determined yielding nighttime column aerosol AOD and Angstrom coefficients. Additional demonstrations have utilized this approach to further develop calibration methods and to obtain data in polar regions where extended periods of darkness occur. This new capability enables more complete studies of the diurnal behavior of aerosols, and feedback for models and satellite retrievals for the nighttime behavior of aerosols. It is anticipated that the nighttime capability of these sensors will be useful for comparisons with satellite lidars such as CALIOP and CATS in additional to ground-based lidars in MPLNET at night, when the signal-to-noise ratio is higher than daytime and more precise AOD comparisons can be made.

Berkoff, Tim↗
NASA NTRS2012

An Analysis of AERONET Aerosol Absorption Properties and Classifications Representative of Aerosol Source Regions

Partitioning of mineral dust, pollution, smoke, and mixtures using remote sensing techniques can help improve accuracy of satellite retrievals and assessments of the aerosol radiative impact on climate. Spectral aerosol optical depth (tau) and single scattering albedo (omega (sub 0) ) from Aerosol Robotic Network (AERONET) measurements are used to form absorption [i.e., omega (sub 0) and absorption Angstrom exponent (alpha(sub abs))] and size [i.e., extinction Angstrom exponent (alpha(sub ext)) and fine mode fraction of tau] relationships to infer dominant aerosol types. Using the long-term AERONET data set (1999-2010), 19 sites are grouped by aerosol type based on known source regions to: (1) determine the average omega (sub 0) and alpha(sub abs) at each site (expanding upon previous work); (2) perform a sensitivity study on alpha(sub abs) by varying the spectral omega (sub 0); and (3) test the ability of each absorption and size relationship to distinguish aerosol types. The spectral omega (sub 0) averages indicate slightly more aerosol absorption (i.e., a 0.0 < delta omega (sub 0) <= 0.02 decrease) than in previous work and optical mixtures of pollution and smoke with dust show stronger absorption than dust alone. Frequency distributions of alpha(sub abs) show significant overlap among aerosol type categories and at least 10% of the alpha(sub abs) retrievals in each category are below 1.0. Perturbing the spectral omega (sub 0) by +/- 0.03 induces significant alpha(sub abs) changes from the unperturbed value by at least approx. +/- 0.6 for Dust, approx. +/-0.2 for Mixed, and approx. +/-0.1 for Urban/Industrial and Biomass Burning. The omega (sub 0)440nm and alpha(sub ext) 440-870nm relationship shows the best separation among aerosol type clusters, providing a simple technique for determining aerosol type from surface- and future space-based instrumentation.

Giles, David M.↗
NASA NTRS2011

Aerosol Properties over the Indo-Gangetic Plain: A Mesoscale Perspective from the TIGERZ Experiment

High aerosol loading over the northern Indian subcontinent can result in poor air quality leading to human health consequences and climate perturbations. The international 2008 TIGERZ experiment intensive operational period (IOP) was conducted in the Indo \Gangetic Plain (IGP) around the industrial city of Kanpur (26.51degN, 80.23deg E), India, during the premonsoon (April-June). Aerosol Robotic Network (AERONET) Sun photometers performed frequent measurements of aerosol properties at temporary sites distributed within an area covering 50 sq km around Kanpur to characterize pollution and dust in a region where complex aerosol mixtures and semi \bright surface effects complicate satellite retrieval algorithms. TIGERZ IOP Sun photometers quantified aerosol optical depth (AOD) increases up to 0.10 within and downwind of the city, with urban emissions accounting for 10 C20% of the IGP aerosol loading on deployment days. TIGERZ IOP area \averaged volume size distribution and single scattering albedo retrievals indicated spatially homogeneous, uniformly sized, spectrally absorbing pollution and dust particles. Aerosol absorption and size relationships were used to categorize black carbon and dust as dominant absorbers and to identify a third category in which both black carbon and dust dominate absorption.Moderate Resolution Imaging Spectroradiometer (MODIS) AOD retrievals with the lowest quality assurance (QA > or = 0) flags were biased high with respect to TIGERZ IOP area \averaged measurements. MODIS AOD retrievals with QA 0 had moderate correlation (R(sup 2) = 0.52-69) with the Kanpur AERONET site, whereas retrievals with QA > 0 were limited in number. Mesoscale \distributed Sun photometers quantified temporal and spatial variability of aerosol properties, and these results were used to validate satellite retrievals.

Giles, David M.↗
NASA NTRS2008

AERONET-OC: Strengths and Weaknesses of a Network for the Validation of Satellite Coastal Radiometric Products

The Ocean Color component of the Aerosol Robotic Network (AERONET-OC) has been implemented to support long-term satellite ocean color investigations through cross-site consistent and accurate measurements collected by autonomous radiometer systems deployed on offshore fixed platforms. The ultimate purpose of AERONET-OC is the production of standardized measurements performed at different sites with identical measuring systems and protocols, calibrated using a single reference source and method, and processed with the same code. The AERONET-OC primary data product is the normalized water leaving radiance determined at center-wavelengths of interest for satellite ocean color applications, with an uncertainty lower than 5% in the blue-green spectral regions and higher than 8% in the red. Measurements collected at 6 sites counting the northern Adriatic Sea, the Baltic Proper, the Gulf of Finland, the Persian Gulf, and, the northern and southern margins of the Middle Atlantic Bay, have shown the capability of producing quality assured data over a wide range of bio-optical conditions including Case-2 yellow substance- and sedimentdominated waters. This work briefly introduces network elements like: deployment sites, measurement method, instrument calibration, processing scheme, quality-assurance, uncertainties, data archive and products accessibility. Emphases is given to those elements which underline the network strengths (i.e., mostly standardization of any network element) and its weaknesses (i.e., the use of consolidated, but old-fashioned technology). The work also addresses the application of AERONET-OC data to the validation of primary satellite radiometric products over a variety of complex coastal waters and finally provides elements for the identification of new deployment sites most suitable to support satellite ocean color missions.

Zibordi, Giuseppe↗
NASA NTRS2007

Characterizing Aerosols over Southeast Asia using the AERONET Data Synergy Tool

Biomass burning, urban pollution and dust aerosols have significant impacts on the radiative forcing of the atmosphere over Asia. In order to better quanti@ these aerosol characteristics, the Aerosol Robotic Network (AERONET) has established over 200 sites worldwide with an emphasis in recent years on the Asian continent - specifically Southeast Asia. A total of approximately 15 AERONET sun photometer instruments have been deployed to China, India, Pakistan, Thailand, and Vietnam. Sun photometer spectral aerosol optical depth measurements as well as microphysical and optical aerosol retrievals over Southeast Asia will be analyzed and discussed with supporting ground-based instrument, satellite, and model data sets, which are freely available via the AERONET Data Synergy tool at the AERONET web site (http://aeronet.gsfc.nasa.gov). This web-based data tool provides access to groundbased (AERONET and MPLNET), satellite (MODIS, SeaWiFS, TOMS, and OMI) and model (GOCART and back trajectory analyses) databases via one web portal. Future development of the AERONET Data Synergy Tool will include the expansion of current data sets as well as the implementation of other Earth Science data sets pertinent to advancing aerosol research.

Giles, David M.↗
NASA NTRS2006

A Network for Standardized Ocean Color Validation Measurements

The Aerosol Robotic Network (AERONET) was developed to support atmospheric studies at various scales with measurements from worldwide distributed autonomous sunphotometers [Holben et al. 1998]. AERONET has now extended its support to marine applications through the additional capability of measuring the radiance emerging from the sea with modified sun-photometers installed on offshore platforms like lighthouses, navigation aids, oceanographic and oil towers. The functionality of this added network component called AERONET - Ocean Color (AERONET-OC), has been verified at different sites and deployment structures over a four year testing phase. Continuous or occasional deployment platforms (see Fig. 1) included: the Acqua Alta Oceanographic Tower (AAOT) of the Italian National Research Council in the northern Adriatic Sea since spring 2002; the Martha s Vineyard Coastal Observatory (MVCO) tower of the Woods Hole Oceanographic Institution in the Atlantic off the Massachusetts coast for different periods since spring 2004; the TOTAL Abu-Al-Bukhoosh oil Platform (AABP, shown through an artistic rendition in Fig. 1) in the Persian (Arabian) Gulf in fall 2004; the Gustaf Dal n Lighthouse Tower (GDLT) of the Swedish Maritime Administration in the Baltic Sea in summer 2005; and the platform at the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) site located in the Atlantic Ocean off the Virginia coast since fall 2005. Data collected during the network testing phase, confirm the capability of AERONET-OC to support the validation of marine optical remote sensing products through standardized measurements of normalized water-leaving radiance, LWN, and aerosol optical thickness, a, at multiple coastal sites.

Zibordi, Giuseppe↗
NASA NTRS2001

Techniques of Validation of Aerosol and Water Vapor Retrievals From MODIS

Aerosols are extremely important for global climate studies and modeling in the quest to characterize the global radiation budget and forcing. The physical characteristics, composition, abundance, and spatial distribution and dynamics of aerosols are still very poorly known. Aerosol column optical thickness and other parameters as well as column precipitable water vapor amount are some of the main atmospheric parameters retrieved from the MODIS instrument on board the Terra satellite. To ensure the reliability of these parameters, we have embarked on a very massive validation effort. This involves cross correlation between the retrievals from the satellite data and those obtained from sunphotometer measurements at a large number of ground stations spread throughout the globe. Notable among these ground stations is a large network of over 100 stations coordinated under the Aerosol Robotic Network (AERONET) project. Whereas MODIS retrieves the aerosol parameters throughout the globe once or twice a day during the daytime, the ground measurements cover only discrete locations of the earth, though the retrievals are done several times a day. We have devised a method to. match the MODIS and ground retrievals through spatial statistics for the MODIS data and temporal statistics for the ground data. This has produced good comparisons and has enabled the validation of MODIS aerosol and water vapor retrievals at over 100 discrete locations in various parts of the earth both over the land and over the ocean. Currently, the validation statistical data is produced routinely by the MODIS aerosol group and is even available not only for validation but also for use by the science community for short and long term studies at various parts of the earth. One important advantage is that the system can be expanded to incorporate more locations where ground measurements and other studies may be conducted at any time during the lifetime of MODIS.

Ichoku, Charles↗
NASA NTRS2001

A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products

With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.

Ichoku, Charles↗
NASA NTRS2001

Analysis of the Performance Characteristics of the Five-Channel Microtops II Sun Photometer for Measuring Aerosol Optical Thickness and Precipitable Water Vapor

Five Microtops II sun photometers were studied in detail at the NASA Goddard Space Flight Center (GSFC) to determine their performance in measuring aerosol optical thickness (AOT or Tau(sub alphalambda) and precipitable column water vapor (W). Each derives Tau(sub alphalambda) from measured signals at four wavelengths lambda (340, 440, 675, and 870 nm), and W from the 936 nm signal measurements. Accuracy of Tau(sub alphalambda) and W determination depends on the reliability of the relevant channel calibration coefficient (V(sub 0)). Relative calibration by transfer of parameters from a more accurate sun photometer (such as the Mauna-Loa-calibrated AERONET master sun photometer at GSFC) is more reliable than Langley calibration performed at GSFC. It was found that the factory-determined value of the instrument constant for the 936 nm filter (k= 0.7847) used in the Microtops' internal algorithm is unrealistic, causing large errors in V(sub 0(936)), Tau(sub alpha936), and W. Thus, when applied for transfer calibration at GSFC, whereas the random variation of V(aub 0) at 340 to 870 nm is quite small, with coefficients of variation (CV) in the range of 0 to 2.4%, at 936 nm the CV goes up to 19%. Also, the systematic temporal variation of V(sub 0) at 340 to 870 nm is very slow, while at 936 nm it is large and exhibits a very high dependence on W. The algorithm also computes Tau(sub alpha936) as 0.91Tau(sub alpha870), which is highly simplistic. Therefore, it is recommended to determine Tau(sub alpha936) by logarithmic extrapolation from Tau(sub alpha675) and Tau(sub alpha 870. From the operational standpoint of the Microtops, apart from errors that may result from unperceived cloud contamination, the main sources of error include inaccurate pointing to the Sun, neglecting to clean the front quartz window, and neglecting to calibrate correctly. If these three issues are adequately taken care of, the Microtops can be quite accurate and stable, with root mean square (rms) differences between corresponding retrievals from clean calibrated Microtops and the AERONET sun photometer being about +/-0.02 at 340 nm, decreasing down to about +/-0.01 at 870 nm.

Ichoku, Charles↗