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At least 181 records · Page 10

EOS Science Plan and EOS Science Plan Executive Summary

Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper, we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sunphotometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

King, Michael D.↗

How Well Will MODIS Measure Top of Atmosphere Aerosol Direct Radiative Forcing?

The new generation of satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) will be able to detect and characterize global aerosols with an unprecedented accuracy. The question remains whether this accuracy will be sufficient to narrow the uncertainties in our estimates of aerosol radiative forcing at the top of the atmosphere. Satellite remote sensing detects aerosol optical thickness with the least amount of relative error when aerosol loading is high. Satellites are less effective when aerosol loading is low. We use the monthly mean results of two global aerosol transport models to simulate the spatial distribution of smoke aerosol in the Southern Hemisphere during the tropical biomass burning season. This spatial distribution allows us to determine that 87-94% of the smoke aerosol forcing at the top of the atmosphere occurs in grid squares with sufficient signal to noise ratio to be detectable from space. The uncertainty of quantifying the smoke aerosol forcing in the Southern Hemisphere depends on the uncertainty introduced by errors in estimating the background aerosol, errors resulting from uncertainties in surface properties and errors resulting from uncertainties in assumptions of aerosol properties. These three errors combine to give overall uncertainties of 1.5 to 2.2 Wm-2 (21-56%) in determining the Southern Hemisphere smoke aerosol forcing at the top of the atmosphere. The range of values depend on which estimate of MODIS retrieval uncertainty is used, either the theoretical calculation (upper bound) or the empirical estimate (lower bound). Strategies that use the satellite data to derive flux directly or use the data in conjunction with ground-based remote sensing and aerosol transport models can reduce these uncertainties.

Remer, Lorraine A.↗

The NASA Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Mission: an Emerging Era of Global, Hyperspectral Earth System Remote Sensing

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents NASA's next investment in satellite ocean color and the study of Earth's ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere.

Gorman, Eric T.↗

Aerosol Properties in Cloudy Environments from Remote Sensing Observations: A Review of the Current State of Knowledge

Aerosol properties are fundamentally different near clouds than away from clouds. This paper reviews the current state of knowledge of aerosol properties in the near-low-cloud environment and quantitatively compares them with aerosols far from clouds, according to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft, and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote sensing retrievals. This study is timely in view of science definition studies for NASA’s Aerosol, Cloud, Convection and Precipitation (ACCP) mission, which will also seek to directly link aerosol properties to nearby clouds.

A. Marshak↗

The relative importance of aerosol scattering and absorption in remote sensing

Previous attempts to explain the effect of aerosols on satellite measurements of surface properties for the visible and near-infrared spectrum have emphasized the amount of aerosols without consideration of their absorption properties. In order to estimate the importance of absorption, the radiances of the sunlight scattered from models of the earth-atmosphere system are computed as functions of the aerosol optical thickness and absorption. The absorption effect is small where the surface reflectance is weak, but is important for strong reflectance. These effects on classification of surface features, measuring vegetation index, and measuring surface reflectance are presented.

Fraser, R. S.↗

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Petrenko, Maksym↗

Aerosol Sources, Absorption, and Intercontinental Transport: Synergies among Models, Remote Sensing, and Atmospheric Measurements

Aerosol climate forcing is one of the largest uncertainties in assessing the anthropogenic impact on the global climate system. This uncertainty arises from the poorly quantified aerosol sources, especially black carbon emissions, our limited knowledge of aerosol mixing state and optical properties, and the consequences of intercontinental transport of aerosols and their precursors. Here we use a global model GOCART to simulate atmospheric aerosols, including sulfate, black carbon, organic carbon, dust, and sea salt, from anthropogenic, biomass burning, and natural sources. We compare the model calculated aerosol extinction and absorption with those quantities from the ground-based sun photometer measurements from AERONET at several different wavelengths and the field observations from ACE-Asia, and model calculated total aerosol optical depth and fine mode fractions with the MODIS satellite retrieval. We will also estimate the intercontinental transport of pollution and dust aerosols from their source regions to other areas in different seasons.

Chin, Mian↗

Aerosol Sources, Absorption, and Intercontinental Transport: Synergies Among Models, Remote Sensing, and Atmospheric Measurements

Aerosol climate forcing is one of the largest uncertainties in assessing the anthropogenic impact on the global climate system. This uncertainty arises from the poorly quantified aerosol sources, especially black carbon emissions, our limited knowledge of aerosol mixing state and optical properties, and the consequences of intercontinental transport of aerosols and their precursors. Here we use a global model GOCART to simulate atmospheric aerosols, including sulfate, black carbon, organic carbon, dust, and sea salt, from anthropogenic, .biomass burning, and natural sources. We compare the model calculated aerosol extinction and absorption with those quantities from the ground-based sun photometer measurements from AERON" at several different wavelengths and the field observations from ACE-Asia, and model calculated total aerosol optical depth and fine mode fractions with the MODIS satellite retrieval. We will also estimate the intercontinental transport of pollution and dust aerosols from their source regions to other areas in different seasons.

Chin, Mian↗

Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing

Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) datahas shown that major aerosol pollution events with very highfine mode AOD (>1.0 in midvisible) in theChina/Korea/Japan region are often observed to be associated with significant cloud cover. This makesremote sensing of these events difficult even for high temporal resolution Sun photometer measurements.Possible physical mechanisms for these events that have high AOD include a combination of aerosolhumidification, cloud processing, and meteorological covariation with atmospheric stability andconvergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloudscreening algorithms now allow for unprecedented ability to monitor these extremefine mode pollutionevents. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening)provides an even more comprehensive assessment offine mode AOD than L2 in current and previous dataversions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA dailyaveragefine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remotesensing of AOD often did not retrieve and/or identify some of the highestfine mode AOD events in thisregion. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDAfinemode AOD was significantly higher in magnitude, particularly for the highest AOD events that were oftenassociated with significant cloudiness.

Eck, T. F.↗

Remote sensing of the atmospheric aerosols and noctilucent clouds from space

The method for the determination of the optical density of tropospheric and mesospheric aerosols and for the estimation of the scattering phase function in the forward directions (0 to 30 deg) is proposed. The method is based on measurements of the brightness of the twilight horizon with the high resolution limb camera having five separated fields of view. In some detail the features of the camera are described and the mathematical aspects of remote sensing data inversion are discussed.

Avaste, O.↗

Temporal and spatial variability of aerosol optical depth in the Sahel region in relation to vegetation remote sensing

In order to monitor the aerosol characteristics needed for atmospheric correction of remotely sensed data, a network of sun photometers was established in the Sahel region of Senegal, Mali, and Niger. Data analysis suggests that there is a high spatial variability of the aerosol optical thickness tau(a) in the western Sahel region. At a 67 percent confidence level the instantaneous values of tau(a) can be extrapolated approximately 270-400 km with an error tolerance of 50 percent. Spatial variability in the dry season is found to be of a similar magnitude. The ranges of variations in the NDVI in the Sahel region are shown to be approximately 0.02 and 0.01, respectively, due to commonly observed fluctuations in the aerosol optical thickness and aerosol size distribution.

Holben, B. N.↗

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: 1. an EOF Approach to the Spatial-Temporal Variability of Aerosol Optical Depth Using Multiple Remote Sensing Data Sets

Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Niño over Indonesia and central South America is also captured with the EOF technique.

variability↗

Satellite aerosols retrieval over land surfaces using the structure functions

Remote sensing of aerosol optical thickness from space is difficult over continental surfaces. There are two retrieval algorithms, one based on the use of dark targets and a second based on contrast reduction between selected pixels. Improvements in the contrast reduction method are reported. A procedure is developed for using the satellite image to evaluate whether conditions for applying the structure method are met. The theoretical background is discussed, and the usefulness of the structure functions is demonstrated. The method is applied to NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery where simultaneous ground measurements are used for validation.

Tanre, D.↗

The Atmospheric Channels of GLAS: Near Real-Time Global Lidar Remote Sensing of Clouds and Aerosols from Space

The Geoscience Laser Altimeter System (GLAS) will be placed into orbit in 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESat). From its nearly polar orbit (94 degree inclination), GLAS will provide continuous global measurements of the vertical distribution of clouds and aerosols while simultaneously providing high accuracy topographic profiling of surface features. During the mission, which is slated to last 3 to 5 years, the data collected by GLAS will be in near-real time to produce level 1 and 2 data products at the NASA GLAS Science Computing Facility (SCF) at Goddard Space Flight Center in Greenbelt, Maryland. The atmospheric products include cloud and aerosol layer heights, planetary boundary layer depth, polar stratospheric clouds and thin cloud and aerosol optical depth. These products will be made available to the science community within days of their creation. The processing algorithms must be robust, adaptive, efficient, and clever enough to run autonomously for the widely varying atmospheric conditions that will be encountered. This paper presents an overview of the GLAS atmospheric data products and briefly discusses the design of the processing algorithms.

Palm, Stephen P.↗

Remote Sensing of Non-Aerosol (anomalous) Absorption in Cloud Free Atmosphere

The interaction of sunlight with atmospheric gases, aerosols and clouds is fundamental to the understanding of climate and its variation. Several studies questioned our understanding of atmospheric absorption of sunlight in cloudy or in cloud free atmospheres. Uncertainty in instruments' accuracy and in the analysis methods makes this problem difficult to resolve. Here we use several years of measurements of sky and sun spectral brightness by selected instruments of the Aerosol Robotic Network (AERONET), that have known and high measurement accuracy. The measurements taken in several locations around the world show that in the atmospheric windows 0.44, 0.06, 0.86 and 1.02 microns the only significant absorbers in cloud free atmosphere is aerosol and ozone. This conclusions is reached using a method developed to distinguish between absorption associated with the presence of aerosol and absorption that is not related to the presence of aerosol. Non-aerosol absorption, defined as spectrally independent or smoothly variable, was found to have an optical thickness smaller than 0.002 corresponding to absorption of sunlight less than 1W/sq m, or essentially zero.

Kaufman, Yoram J.↗

TPSAS-NF1676L-27355-DND

Systematic and concurrent observation of column-integrated, surface, and vertically-resolved distributions of aerosols and trace gases relevant to air quality as they evolve throughout the day. Three major observational components: - NASA King Air (Remote sensing) Continuous mapping of aerosols with HSRL and trace gas columns with ACAM - NASA P-3B (in situ meas.) In situ profiling of aerosols and trace gases over surface measurement sites - Ground sites In situ trace gases and aerosols Remote sensing of trace gas and aerosol columns (Pandora and Aeronet) Ozonesondes Lidar observations of aerosol (and ozone).

Jay Al-Saadi↗

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.↗