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Timothy J. Beatty, Chris A. Hostetler, and Chester S. Gardner

Abstract

The UIUC CEDAR Rayleigh/Na lidar was operated for approximately 160 h on 30 nights in January, March, and April 1989 at the Arecibo Observatory (18°N, 67°W) as part of the AIDA Act '89 Campaign. During this period 38 quasi-monochromatic gravity waves were observed in the stratopause region (25-55 km) and 62 waves were observed in the mesopause region (80–105 km). The event rates in both regions are approximately half those observed at the midlatitude site of Urbana. The characteristics of the waves in both regions are similar. Measured vertical wavelengths range from 1.1 to 17 km, vertical phase velocities from −6 to −270 cm s−1, observed periods from 5 min to 65 h, and amplitudes (relative atmospheric density variations) 0.4% to 17%. The wave amplitudes in the stratopause region are on average half the values for waves in the mesopause region with similar periods and vertical wavelengths. Vertical wavenumber spectra of density perturbations in both regions exhibit power-law dependencies with slopes near −3. The magnitudes of the spectra in the stratopause region are typically a factor of 5 to 10 times smaller than the magnitudes of the mesopause region spectra, which is in significant disagreement with the predictions of linear saturation theory. Temporal frequency spectra of density perturbations in the mesopause region also exhibit power-law dependencies with slopes between −1.5 and −2.0 (mean slope = 1.85 ± 0.38) for frequencies smaller than the Brunt-Väisälä frequency and slopes near −3 for frequencies larger than the Brunt-Väisälä frequency. The rms density perturbations averaged 1.2% in the stratopause region and 5.2% in the mesopause region. These results are compared with other radar and lidar observations.

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Mark A. Vaughan, Kathleen A. Powell, David M. Winker, Chris A. Hostetler, Ralph E. Kuehn, William H. Hunt, Brian J. Getzewich, Stuart A. Young, Zhaoyan Liu, and Matthew J. McGill

Abstract

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth’s atmosphere is critical in assessing the planet’s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars.

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Kathleen A. Powell, Chris A. Hostetler, Mark A. Vaughan, Kam-Pui Lee, Charles R. Trepte, Raymond R. Rogers, David M. Winker, Zhaoyan Liu, Ralph E. Kuehn, William H. Hunt, and Stuart A. Young

Abstract

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission was launched in April 2006 and has continuously acquired collocated multisensor observations of the spatial and optical properties of clouds and aerosols in the earth’s atmosphere. The primary payload aboard CALIPSO is the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), which makes range-resolved measurements of elastic backscatter at 532 and 1064 nm and linear depolarization ratios at 532 nm. CALIOP measurements are important in reducing uncertainties that currently limit understanding of the global climate system, and it is essential that these measurements be accurately calibrated. This work describes the procedures used to calibrate the 532-nm measurements acquired during the nighttime portions of the CALIPSO orbits. Accurate nighttime calibration of the 532-nm parallel-channel data is fundamental to the success of the CALIOP measurement scheme, because the nighttime calibration is used to infer calibration across the day side of the orbits and all other channels are calibrated relative to the 532-nm parallel channel. The theoretical basis of the molecular normalization technique as applied to space-based lidar measurements is reviewed, and a comprehensive overview of the calibration algorithm implementation is provided. Also included is a description of a data filtering procedure that detects and removes spurious high-energy events that would otherwise introduce large errors into the calibration. Error estimates are derived and comparisons are made to validation data acquired by the NASA airborne high–spectral resolution lidar. Similar analyses are also presented for the 532-nm perpendicular-channel calibration technique.

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Larry K. Berg, Carl M. Berkowitz, John A. Ogren, Chris A. Hostetler, Richard A. Ferrare, Manvendra K. Dubey, Elisabeth Andrews, Richard L. Coulter, Johnathan W. Hair, John M. Hubbe, Yin-Nan Lee, Claudio Mazzoleni, Jason Olfert, and Stephen R. Springston

The primary goal of the Cumulus Humilis Aerosol Processing Study (CHAPS) was to characterize and contrast freshly emitted aerosols below, within, and above fields of cumuli, and to study changes to the cloud microphysical structure within these same cloud fields in the vicinity of Oklahoma City during June 2007. CHAPS is one of few studies that have had an aerosol mass spectrometer (AMS) sampling downstream of a counterflow virtual impactor (CVI) inlet on an aircraft, allowing the examination of the chemical composition of activated aerosols within the cumuli. The results from CHAPS provide insights into changes in the aerosol chemical and optical properties as aerosols move through shallow cumuli downwind of a moderately sized city. Three instrument platforms were employed during CHAPS, including the U.S. Department of Energy Gulfstream-1 aircraft, which was equipped for in situ sampling of aerosol optical and chemical properties; the NASA Langley King Air B200, which carried the downward-looking NASA Langley High Spectral Resolution Lidar (HSRL) to measure profiles of aerosol backscatter, extinction, and depolarization between the King Air and the surface; and a surface site equipped for continuous in situ measurements of aerosol optical properties, profiles of aerosol backscatter, and meteorological conditions, including total sky cover and thermodynamic profiles of the atmosphere. In spite of record precipitation over central Oklahoma, a total of 8 research flights were made by the G-l and 18 by the B200, including special satellite verification flights timed to coincide with NASA satellite A-Train overpasses.

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Ali H. Omar, David M. Winker, Mark A. Vaughan, Yongxiang Hu, Charles R. Trepte, Richard A. Ferrare, Kam-Pui Lee, Chris A. Hostetler, Chieko Kittaka, Raymond R. Rogers, Ralph E. Kuehn, and Zhaoyan Liu

Abstract

Descriptions are provided of the aerosol classification algorithms and the extinction-to-backscatter ratio (lidar ratio) selection schemes for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol products. One year of CALIPSO level 2 version 2 data are analyzed to assess the veracity of the CALIPSO aerosol-type identification algorithm and generate vertically resolved distributions of aerosol types and their respective optical characteristics. To assess the robustness of the algorithm, the interannual variability is analyzed by using a fixed season (June–August) and aerosol type (polluted dust) over two consecutive years (2006 and 2007). The CALIPSO models define six aerosol types: clean continental, clean marine, dust, polluted continental, polluted dust, and smoke, with 532-nm (1064 nm) extinction-to-backscatter ratios Sa of 35 (30), 20 (45), 40 (55), 70 (30), 65 (30), and 70 (40) sr, respectively. This paper presents the global distributions of the CALIPSO aerosol types, the complementary distributions of integrated attenuated backscatter, and the volume depolarization ratio for each type. The aerosol-type distributions are further partitioned according to surface type (land/ocean) and detection resolution (5, 20, and 80 km) for optical and spatial context, because the optically thick layers are found most often at the smallest spatial resolution. Except for clean marine and polluted continental, all the aerosol types are found preferentially at the 80-km resolution. Nearly 80% of the smoke cases and 60% of the polluted dust cases are found over water, whereas dust and polluted continental cases are found over both land and water at comparable frequencies. Because the CALIPSO observables do not sufficiently constrain the determination of the aerosol, the surface type is used to augment the selection criteria. Distributions of the total attenuated color ratios show that the use of surface type in the typing algorithm does not result in abrupt and artificial changes in aerosol type or extinction.

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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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David J. Diner, Thomas P. Ackerman, Theodore L. Anderson, Jens Bösenberg, Amy J. Braverman, Robert J. Charlson, William D. Collins, Roger Davies, Brent N. Holben, Chris A . Hostetler, Ralph A. Kahn, John V. Martonchik, Robert T. Menzies, Mark A. Miller, John A. Ogren, Joyce E. Penner, Philip J. Rasch, Stephen E. Schwartz, John H. Seinfeld, Graeme L. Stephens, Omar Torres, Larry D. Travis, Bruce A . Wielicki, and Bin Yu

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 longterm 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, interagency, 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.

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Armin Sorooshian, Bruce Anderson, Susanne E. Bauer, Rachel A. Braun, Brian Cairns, Ewan Crosbie, Hossein Dadashazar, Glenn Diskin, Richard Ferrare, Richard C. Flagan, Johnathan Hair, Chris Hostetler, Haflidi H. Jonsson, Mary M. Kleb, Hongyu Liu, Alexander B. MacDonald, Allison McComiskey, Richard Moore, David Painemal, Lynn M. Russell, John H. Seinfeld, Michael Shook, William L. Smith Jr, Kenneth Thornhill, George Tselioudis, Hailong Wang, Xubin Zeng, Bo Zhang, Luke Ziemba, and Paquita Zuidema

Abstract

We report on a multiyear set of airborne field campaigns (2005–16) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE; 2019–23). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (>500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and ii) quantification of model-relevant metrics associated with aerosol–cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual-aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms.

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