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

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

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers

Aerosol Data Sources and Their Roles within PARAGON

We briefly but systematically review major sources of aerosol data, emphasizing suites of measurements that seem most likely to contribute to assessments of global aerosol climate forcing. The strengths and limitations of existing satellite, surface, and aircraft remote sensing systems are described, along with those of direct sampling networks and ship-based stations. It is evident that an enormous number of aerosol-related observations have been made, on a wide range of spatial and temporal sampling scales, and that many of the key gaps in this collection of data could be filled by technologies that either exist or are expected to be available in the near future. Emphasis must be given to combining remote sensing and in situ active and passive observations and integrating them with aerosol chemical transport models, in order to create a more complete environmental picture, having sufficient detail to address current climate forcing questions. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative would provide an organizational framework to meet this goal

JMISR INteractive eXplorer

MISR (Multi-angle Imaging SpectroRadiometer) INteractive eXplorer (MINX) is an interactive visualization program that allows a user to digitize smoke, dust, or volcanic plumes in MISR multiangle images, and automatically retrieve height and wind profiles associated with those plumes. This innovation can perform 9-camera animations of MISR level-1 radiance images to study the 3D relationships of clouds and plumes. MINX also enables archiving MISR aerosol properties and Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power along with the heights and winds. It can correct geometric misregistration between cameras by correlating off-nadir camera scenes with corresponding nadir scenes and then warping the images to minimize the misregistration offsets. Plots of BRF (bidirectional reflectance factor) vs. camera angle for points clicked in an image can be displayed. Users get rapid access to map views of MISR path and orbit locations and overflight dates, and past or future orbits can be identified that pass over a specified location at a specified time. Single-camera, level-1 radiance data at 1,100- or 275- meter resolution can be quickly displayed in color using a browse option. This software determines the heights and motion vectors of features above the terrain with greater precision and coverage than previous methods, based on an algorithm that takes wind direction into consideration. Human interpreters can precisely identify plumes and their extent, and wind direction. Overposting of MODIS thermal anomaly data aids in the identification of smoke plumes. The software has been used to preserve graphical and textural versions of the digitized data in a Web-based database

Identification of Functional Toxin/Immunity Genes Linked to Contact-Dependent Growth Inhibition (CDI) and Rearrangement Hotspot (Rhs) Systems

Bacterial contact-dependent growth inhibition (CDI) is mediated by the CdiA/CdiB family of two-partner secretion proteins. Each CdiA protein exhibits a distinct growth inhibition activity, which resides in the polymorphic C-terminal region (CdiA-CT). CDI+ cells also express unique CdiI immunity proteins that specifically block the activity of cognate CdiA-CT, thereby protecting the cell from autoinhibition. Here we show that many CDI systems contain multiple cdiA gene fragments that encode CdiA-CT sequences. These “orphan” cdiA-CT genes are almost always associated with downstream cdiI genes to form cdiA-CT/cdiI modules. Comparative genome analyses suggest that cdiA-CT/cdiI modules are mobile and exchanged between the CDI systems of different bacteria. In many instances, orphan cdiA-CT/cdiI modules are fused to full-length cdiA genes in other bacterial species. Examination of cdiA-CT/cdiI modules from Escherichia coli EC93, E. coli EC869, and Dickeya dadantii 3937 confirmed that these genes encode functional toxin/immunity pairs. Moreover, the orphan module from EC93 was functional in cell-mediated CDI when fused to the N-terminal portion of the EC93 CdiA protein. Bioinformatic analyses revealed that the genetic organization of CDI systems shares features with rhs (rearrangement hotspot) loci. Rhs proteins also contain polymorphic C-terminal regions (Rhs-CTs), some of which share significant sequence identity with CdiA-CTs. All rhs genes are followed by small ORFs representing possible rhsI immunity genes, and several Rhs systems encode orphan rhs-CT/rhsI modules. Analysis of rhs-CT/rhsI modules from D. dadantii 3937 demonstrated that Rhs-CTs have growth inhibitory activity, which is specifically blocked by cognate RhsI immunity proteins. Together, these results suggest that Rhs plays a role in intercellular competition and that orphan gene modules expand the diversity of toxic activities deployed by both CDI and Rhs systems

MISR Global Aerosol Product Assessment by Comparison with AERONET

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

Response to "Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET"

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

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality