A22A-01
Multi-Sensor Characterization of Aerosol Events
Recent developments in surface and satellite sensing along with new information technologies now allow real- time, 'just-in-time' data analysis for the characterization and partial explanation of the of major air pollution events. The data from surface-based air pollution monitoring networks now provides routinely high grade, spatio-temporal and chemical patterns throughout the US for PM25 and ozone. Satellite sensors with global coverage and kilometer-scale spatial resolution now provide real-time snapshots which depict the pattern of haze, smoke and dust in stunning detail. The instantaneous 'horizontal' diffusion of information via the Internet now permits, in principle, the delivery of the right information to the right people at the right place and time. The resulting "data deluge" problem is especially acute for aerosol pollution, since aerosol systems are inherently complex and since there are so many different kinds of relevant data. Atmospheric aerosols are a 6-D system (x, y, z, t, size, composition) and full characterization requires 'filling' (observing or modeling) the entire 6D data-space. However, each sensor samples a small subset of the aerosol data space, while some sensors, like satellites provide only integral measures of the 6D aerosol pattern. Clearly, characterization requires the combination of the multi- sensory data and 6D models outputs. Complete aerosol chemical composition data are available only for limited sampling locations in few regions of the world but over the US, rich aerosol chemistry datasets are available from the IMPROVE aerosol chemistry network and from the EPA Speciation Trends Network. There is also an increasing array of Satellite data from MODIS, OMI, CALIPSO, GOES, AVHRR sensors. Aerosol characterization using the combination of these sensors over the US is in progress and will be reported. Recently, the multi-sensory characterization of aerosols during events has provided support to the air quality managers. The current challenge is to incorporate such support into the air quality management process in a more regular and robust way. Event analyses were performed as part of FASTNET (Poirot, et al, 2005), a data acquisition and analysis facility with particular emphasis on detailed real-time and post-analysis of major aerosol events including forest fire smoke and windblown dust. These have large emission rates over short periods of time, continental and global-scale impacts, and unpredictable sporadic occurrence.
A22A-02
What do fully compatible MODIS and MISR aerosol pixels tell us?
Direct and, especially, indirect effects of aerosols on climate are widely recognized as being quite significant and yet poorly understood and quantified. Because of the global nature of aerosol effects on climate, satellite observations have been and will be an indispensable source of information about aerosol characteristics for use in various assessments of climate and climate change. While the ability to retrieve aerosol parameters from TOMS and AVHRR radiance measurements has been quite limited, our knowledge of the global distribution of aerosol properties has been expected to improve dramatically owing to the launch of more advanced satellite instruments such as POLDER, MODIS, and MISR. The MODIS and MISR aerosol products have been especially popular, and their use has been increasingly frequent. There have been parallel claims of unprecedented accuracy of aerosol retrievals with MODIS and MISR. These claims have been based on limited comparisons with ground-based observations which, however, are not necessarily indicative of the actual global performance of these satellite sensors. Fortunately, both instruments have been flown for many years on the same Terra platform, which provides a unique opportunity to compare fully collocated pixel- level MODIS and MISR aerosol retrievals directly and globally. This presentation will focus on an extensive analysis of ~8 years of the MODIS and MISR aerosol records, including pixel-level results and several types of time and area averages. In this analysis we use only fully compatible MODIS and MISR aerosol pixels defined as follows. A MODIS-Terra level-2 aerosol pixel and a MISR level-2 aerosol pixel are considered "fully compatible" if they (i) are located within the narrower MISR swath; (ii) have been collocated spatially to ±3.3 km and temporally to ±3 min; (iii) have been determined to be "cloud-free" by both cloud-screening procedures; and (iv) have been identified as suitable for aerosol retrieval and have been taken through the standard MODIS and MISR retrieval routines, thereby resulting in specific AOT and AE values. Both datasets seem to indicate that there has been a weak increasing tendency in the globally averaged aerosol optical thickness (AOT) over the land and no long-term AOT tendency over the oceans. Also, both datasets appear to exhibit long-term regional tendencies in the AOT distribution, such as a significant AOT increase over much of Brazil and Southern Asia as well over much of the Equatorial Atlantic Ocean and Equatorial Africa. They also show a significant AOT decrease over much of Europe and the Former Soviet Union.
A22A-03
MISR and MODIS Aerosol Product Attributes That Matter for Aerosol Radiative Forcing Calculations
The NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) and MODerate
resolution Imaging Spectroradiometer (MODIS) have produced data records nearly nine years long, widely
recognized and used due to their frequent, global coverage, radiometric stability, spatial resolution down to
250 m, and taken together, their broad spectral and angular coverage. Aerosol column optical depth and
particle type information derived from the MISR and MODIS radiances have been evaluated both statistically
and for individual cases of special interest, and the products have been used with success in many
applications.
However, when calculating aerosol direct radiative forcing with these data sets, both individually and
especially in combination, it is tempting to push the accuracy limits the MISR and MODIS products offer. As a
result, this is one key application that demands a thorough understanding of the assumptions and
compromises that are made in the operational algorithms so they can handle the diversity of conditions,
globally, and efficiently enough to process all the data. We have re-examined and compared the MISR and
MODIS aerosol products from this perspective, and will provide a summary of results, including explanations
of limiting assumptions, and prospects for upgrades to these and next-generation algorithms.
http://www-misr.jpl.nasa.gov
A22A-04 INVITED
Observing Aerosol Radiative Processes from Passive and Active Instruments
Improved understanding of the radiative effects of aerosols in climate requires the synergistic use of a broad range of different types of observations and models. This presentation will highlight recent studies that use multiple instruments (passive and active) to improve our understanding of both the direct and indirect radiative effects of aerosols. Measurements of aerosols, clouds and radiation from MODIS, CALIPSO, HSRL and CERES will be presented with special focus on aerosols in the vicinity of clouds, arguably amongst the most poorly understood and observationally challenging areas in aerosol science.
A22A-05 INVITED
Global and regional aerosol variations during the EOS satellite era 2000-2007: An analysis using multiple satellite sensors and the global model GOCART
We present here a global model (GOCART) analysis of variations of atmospheric aerosols from 2000 to 2007 using data from satellite sensors of MODIS, MISR, and AVHRR, and ground-based sunphotometer network AERONET. We compare the model results with observations over 7 land and 7 ocean regions that are dominated by anthropogenic, dust, biomass burning, and transported aerosols. We will analyze the observed change of aerosols in terms of change of emission, transport, and other factors and try to explain the differences in satellite retrieved aerosol optical depth from different sensors during the 8-year time period.
A22A-06
Analysis of Interannual Variability of MODIS Terra and Aqua Aerosols and Clouds
We study sensitivity of MODIS Level 3 Aerosol Optical Thickness (AOT) interannual variability to various
factors: temporal aggregation (daily vs. monthly); spatial sampling; weighting by quality, pixel count weighting
vs. non-weighting. We also study sensitivity of the results to interannual changes in cloud properties globally
and locally. We address differences between MODIS Terra and Aqua measurements.
http://giovanni.gsfc.nasa.gov
A22A-07
Aerosol Climatologies for AOD, Absorption, Size and CCN
A proper representation of aerosol properties is an essential first step in addressing potential impacts of aerosols on climate and on clouds. In the context of temporal and spatial variability to concentration, size and composition of aerosols maps of aerosol properties are usually based on insufficiently evaluated data-sets of model simulations or satellite retrievals. Here a new approach is offered: Quality data from ground-based remote sensing networks are merged into multi-model median background fields for global monthly maps on aerosol optical depth (AOD), single scattering albedo (w0) and Ångstrom parameter (AnP). Adopting the commonly observed distinction into fine sizes (radii: .05-.50um) and coarse sizes (radii >.50um) and assumptions for the composition of coarse sizes, the mid-visible optical properties are spectrally extended so that aerosol single scattering properties at all solar and infrared wavelengths are defined. Modeling is applied to define AOD anthropogenic (fine-size) fraction and AOD vertical distribution. Applying a recent result, that aerosol humidification is well constrained, the critical size (of aerosols for cloud droplet formation) becomes a function of the environment (e.g. supersaturation and temperature). Applying the optical properties and associated aerosol concentrations of the aerosol climatology, monthly global monthly maps are provided for cloud condensation nuclei (CCN) concentrations and regional CCN enhancements from anthropogenic activity.