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Anthony R. Dobrovolskis and David J. Diner

Abstract

Infrared images of Venus reveal a curious double-lobed hot spot in the polar region. Elson has suggested that this “dipole” represents a barotropic instability associated with a high-latitude jet. Unfortunately, the classical theory of barotropic instability cannot predict temperature variations. This paper generalizes the theory to include horizontal divergence, vertical motions, and temperature variations, and applies it to the stratosphere of Venus. The fastest-growing barotropic instability in the nominal model matches the observed dipole in period and horizontal temperature pattern. The accompanying wind variations are comparable to the speed of the mean jet indicating strong nonlinear effects. We conclude that the Venus dipole may represent the self-limited stage of a barotropic instability with divergence.

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Carol J. Bruegge, David J. Diner, and Valerie G. Duval

Abstract

The Multiangle Imaging SpectroRadiometer (MISR) is currently under development for NASA's Earth Observing System. The instrument consists of nine pushbroom cameras, each with four spectral bands in the visible and near-infrared. The cameras point in different view directions to provide measurements from nadir to highly oblique view angles in the along-track plant. Multiple view-angle observations provide a unique resource for studies of clouds, aerosols, and the surface. MISR is built to challenging radiometric and geometric performance specifications. Radiometric accuracy, for example, must be within ±3%/1σ, and polarization insensitivity must be better than ±1%. An onboard calibrator (OBC) provides monthly updates to the instrument gain coefficients. Spectralon diffuse panels we used within the OBC to provide a uniform target for the cameras to view. The absolute radiometric scale is established both preflight and in orbit through the use of detector standards. During the mission, ground data processing to accomplish radiometric calibration, geometric rectification and registration of the nine view-angle imagery, and geophysical retrievals will proceed in an automated fashion. A global dataset is produced every 9 days. This paper details the preflight characterization of the MISR instrument, the design of the OBC, and the radiance product processing.

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Linda Forster, Anthony B. Davis, David J. Diner, and Bernhard Mayer

Abstract

For passive satellite imagers, current retrievals of cloud optical thickness and effective particle size fail for convective clouds with 3D morphology. Indeed, being based on 1D radiative transfer (RT) theory, they work well only for horizontally homogeneous clouds. A promising approach for treating clouds as fully 3D objects is cloud tomography, which has been demonstrated for airborne observations. However, more efficient forward 3D RT solvers are required for cloud tomography from space. Here, we present a path forward by acknowledging that optically thick clouds have “veiled cores” (VCs). Sunlight scattered into and out of this deep region does not contribute significant information about the inner structure of the cloud to the spatially detailed imagery. We investigate the VC location for the MISR and MODIS imagers. While MISR provides multiangle imagery in the visible and near-infrared (IR), MODIS includes channels in the shortwave IR, albeit at a single view angle. This combination will enable future 3D retrievals to disentangle the cloud’s effective particle size and extinction fields. We find that, in practice, the VC is located at an optical distance of ~5, starting from the cloud boundary along the line of sight. For MODIS’s absorbing wavelengths the VC covers a larger volume, starting at smaller optical distances. This concept will not only lead to a reduction in the number of unknowns for the tomographic reconstruction but also significantly increase the speed and efficiency of the 3D RT solver at the heart of the algorithm by applying, say, the photon diffusion approximation inside the VC.

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Kevin J. Mueller, Dong L. Wu, Ákos Horváth, Veljko M. Jovanovic, Jan-Peter Muller, Larry Di Girolamo, Michael J. Garay, David J. Diner, Catherine M. Moroney, and Steve Wanzong

Abstract

Cloud motion vector (CMV) winds retrieved from the Multiangle Imaging SpectroRadiometer (MISR) instrument on the polar-orbiting Terra satellite from 2003 to 2008 are compared with collocated atmospheric motion vectors (AMVs) retrieved from Geostationary Operational Environmental Satellite (GOES) imagery over the tropics and midlatitudes and from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery near the poles. MISR imagery from multiple view angles is exploited to jointly retrieve stereoscopic cloud heights and motions, showing advantages over the AMV heights assigned by radiometric means, particularly at low heights (<3 km) that account for over 95% of MISR CMV sampling. MISR–GOES wind differences exhibit a standard deviation ranging with increasing height from 3.3 to 4.5 m s−1 for a high-quality [quality indicator (QI) ≥ 80] subset where height differences are <1.5 km. Much of the observed difference can be attributed to the less accurately retrieved component of CMV motion along the direction of satellite motion. MISR CMV retrieval is subject to correlation between error in retrieval of this along-track component and of height. This manifests as along-track bias varying with height to magnitudes as large as 2.5 m s−1. The cross-track component of MISR CMVs shows small (<0.5 m s−1) bias and standard deviation of differences (1.7 m s−1) relative to GOES AMVs. Larger differences relative to MODIS are attributed to the tracking of cloud features at heights lower than MODIS in multilayer cloud scenes.

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John H. Seinfeld, Ralph A. Kahn, Theodore L. Anderson, Robert J. Charlson, Roger Davies, David J. Diner, John A. Ogren, Stephen E. Schwartz, and Bruce A. Wielicki

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.

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David J. Diner, Gregory P. Asner, Roger Davies, Yuri Knyazikhin, Jan-Peter Muller, Anne W. Nolin, Bernard Pinty, Crystal B. Schaaf, and Julienne Stroeve

The physical interpretation of simultaneous multiangle observations represents a relatively new approach to remote sensing of terrestrial geophysical and biophysical parameters. Multiangle measurements enable retrieval of physical scene characteristics, such as aerosol type, cloud morphology and height, and land cover (e.g., vegetation canopy type), providing improved albedo accuracies as well as compositional, morphological, and structural information that facilitates addressing many key climate, environmental, and ecological issues. While multiangle data from wide field-of-view scanners have traditionally been used to build up directional “signatures” of terrestrial scenes through multitemporal compositing, these approaches either treat the multiangle variation as a problem requiring correction or normalization or invoke statistical assumptions that may not apply to specific scenes. With the advent of a new generation of global imaging spectroradiometers capable of acquiring simultaneous visible/near-IR multiangle observations, namely, the Along-Track Scanning Radiometer-2, the Polarization and Directionality of the Earth's Reflectances instrument, and the Multiangle Imaging SpectroRadiometer, both qualitatively new approaches as well as quantitative improvements in accuracy are achievable that exploit the multiangle signals as unique and rich sources of diagnostic information. This paper discusses several applications of this technique to scientific problems in terrestrial atmospheric and surface geophysics and biophysics.

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Thomas P. Ackerman, Amy J. Braverman, David J. Diner, Theodore L. Anderson, Ralph A. Kahn, John V. Martonchik, Joyce E. Penner, Philip J. Rasch, Bruce A. Wielicki, and Bin Yu

Given the breadth and complexity of available data, constructing a measurement-based description of global tropospheric aerosols that will effectively confront and constrain global three-dimensional models is a daunting task. Because data are obtained from multiple sources and acquired with nonuniform spatial and temporal sampling, scales, and coverage, protocols need to be established that will organize this vast body of knowledge. Currently, there is no capability to assemble the existing aerosol data into a unified, interoperable whole. Technology advancements now being pursued in high-performance distributed computing initiatives can accomplish this objective. Once the data are organized, there are many approaches that can be brought to bear upon the problem of integrating data from different sources. These include data-driven approaches, such as geospatial statistics formulations, and model-driven approaches, such as assimilation or chemical transport modeling. Establishing a data interoperability framework will stimulate algorithm development and model validation and will facilitate the exploration of synergies between different data types. Data summarization and mining techniques can be used to make statistical inferences about climate system relationships and interpret patterns of aerosol-induced change. Generating descriptions of complex, nonlinear relationships among multiple parameters is critical to climate model improvement and validation. Finally, determining the role of aerosols in past and future climate change ultimately requires the use of fully coupled climate and chemistry models, and the evaluation of these models is required in order to trust their results. The set of recommendations presented here address one component of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative. Implementing them will produce the most accurate four-dimensional representation of global aerosols, which can then be used for testing, constraining, and validating models. These activities are critical components of a sustained program to quantify aerosol effects on global climate.

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Ralph Kahn, Wen-Hao Li, John V. Martonchik, Carol J. Bruegge, David J. Diner, Barbara J. Gaitley, Wedad Abdou, Oleg Dubovik, Brent Holben, Alexander Smirnov, Zhonghai Jin, and Dennis Clark

Abstract

Studying aerosols over ocean is one goal of the Multiangle Imaging Spectroradiometer (MISR) and other spaceborne imaging systems. But top-of-atmosphere equivalent reflectance typically falls in the range of 0.03 to 0.12 at midvisible wavelengths and can be below 0.01 in the near-infrared, when an optically thin aerosol layer is viewed over a dark ocean surface. Special attention must be given to radiometric calibration if aerosol optical thickness, and any information about particle microphysical properties, are to be reliably retrieved from such observations. MISR low-light-level vicarious calibration is performed in the vicinity of remote islands hosting Aerosol Robotic Network (AERONET) sun- and sky-scanning radiometers, under low aerosol loading, low wind speed, relatively cloud free conditions. MISR equivalent reflectance is compared with values calculated from a radiative transfer model constrained by coincident, AERONET-retrieved aerosol spectral optical thickness, size distribution, and single scattering albedo, along with in situ wind measurements. Where the nadir view is not in sun glint, MISR equivalent reflectance is also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance. The authors push the limits of the vicarious calibration method’s accuracy, aiming to assess absolute, camera-to-camera, and band-to-band radiometry. Patterns repeated over many well-constrained cases lend confidence to the results, at a few percent accuracy, as do additional vicarious calibration tests performed with multiplatform observations taken during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. Conclusions are strongest in the red and green bands, but are too uncertain to accept for the near-infrared. MISR nadir-view and MODIS low-light-level absolute reflectances differ by about 4% in the blue and green bands, with MISR reporting higher values. In the red, MISR agrees with MODIS band 14 to better than 2%, whereas MODIS band 1 is significantly lower. Compared to the AERONET-constrained model, the MISR aft-viewing cameras report reflectances too high by several percent in the blue, green, and possibly the red. Better agreement is found in the nadir- and the forward-viewing cameras, especially in the blue and green. When implemented on a trial basis, calibration adjustments indicated by this work remove 40% of a 0.05 bias in retrieved midvisible aerosol optical depth over dark water scenes, produced by the early postlaunch MISR algorithm. A band-to-band correction has already been made to the MISR products, and the remaining calibration adjustments, totaling no more than a few percent, are planned.

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Ralph A. Kahn, John A. Ogren, Thomas P. Ackerman, Jens Bösenberg, Robert J. Charlson, David J. Diner, Brent N. Holben, Robert T. Menzies, Mark A. Miller, and John H. Seinfeld

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.

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David J. Diner, Robert T. Menzies, Ralph A. Kahn, Theodore L. Anderson, Jens Bösenberg, Robert J. Charlson, Brent N. Holben, Chris A. Hostetler, Mark A. Miller, John A. Ogren, Graeme L. Stephens, Omar Torres, Bruce A. Wielicki, Philip J. Rasch, Larry D. Travis, and William D. Collins

A comprehensive and cohesive aerosol measurement record with consistent, well-understood uncertainties is a prerequisite to understanding aerosol impacts on long-term climate and environmental variability. Objectives to attaining such an understanding include improving upon the current state-of-the-art sensor calibration and developing systematic validation methods for remotely sensed microphysical properties. While advances in active and passive remote sensors will lead to needed improvements in retrieval accuracies and capabilities, ongoing validation is essential so that the changing sensor characteristics do not mask atmospheric trends. Surface-based radiometer, chemical, and lidar networks have critical roles within an integrated observing system, yet they currently undersample key geographic regions, have limitations in certain measurement capabilities, and lack stable funding. In situ aircraft observations of size-resolved aerosol chemical composition are necessary to provide important linkages between active and passive remote sensing. A planned, systematic approach toward a global aerosol observing network, involving multiple sponsoring agencies and surface-based, suborbital, and spaceborne sensors, is required to prioritize trade-offs regarding capabilities and costs. This strategy is a key ingredient of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) framework. A set of recommendations is presented.

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