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  • Author or Editor: J. Bösenberg x
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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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The Arm Program's Water Vapor Intensive Observation Periods

Overview, Initial Accomplishments, and Future Challenges

H. E. Revercomb, D. D. Turner, D. C. Tobin, R. O. Knuteson, W. F. Feltz, J. Barnard, J. Bösenberg, S. Clough, D. Cook, R. Ferrare, J. Goldsmith, S. Gutman, R. Halthore, B. Lesht, J. Liljegren, H. Linné, J. Michalsky, V. Morris, W. Porch, S. Richardson, B. Schmid, M. Splitt, T. Van Hove, E. Westwater, and D. Whiteman

A series of water vapor intensive observation periods (WVIOPs) were conducted at the Atmospheric Radiation Measurement (ARM) site in Oklahoma between 1996 and 2000. The goals of these WVIOPs are to characterize the accuracy of the operational water vapor observations and to develop techniques to improve the accuracy of these measurements.

The initial focus of these experiments was on the lower atmosphere, for which the goal is an absolute accuracy of better than 2% in total column water vapor, corresponding to ~1 W m−2 of infrared radiation at the surface. To complement the operational water vapor instruments during the WVIOPs, additional instrumentation including a scanning Raman lidar, microwave radiometers, chilled-mirror hygrometers, a differential absorption lidar, and ground-based solar radiometers were deployed at the ARM site. The unique datasets from the 1996, 1997, and 1999 experiments have led to many results, including the discovery and characterization of a large (> 25%) sonde-to-sonde variability in the water vapor profiles from Vaisala RS-80H radiosondes that acts like a height-independent calibration factor error. However, the microwave observations provide a stable reference that can be used to remove a large part of the sonde-to-sonde calibration variability. In situ capacitive water vapor sensors demonstrated agreement within 2% of chilled-mirror hygrometers at the surface and on an instrumented tower. Water vapor profiles retrieved from two Raman lidars, which have both been calibrated to the ARM microwave radiometer, showed agreement to within 5% for all altitudes below 8 km during two WVIOPs. The mean agreement of the total precipitable water vapor from different techniques has converged significantly from early analysis that originally showed differences up to 15%. Retrievals of total precipitable water vapor (PWV) from the ARM microwave radiometer are now found to be only 3% moister than PWV derived from new GPS results, and about 2% drier than the mean of radiosonde data after a recently defined sonde dry-bias correction is applied. Raman lidar profiles calibrated using tower-mounted chilled-mirror hygrometers confirm the expected sensitivity of microwave radiometer data to water vapor changes, but it is drier than the microwave radiometer (MWR) by 0.95 mm for all PWV amounts. However, observations from different collocated microwave radiometers have shown larger differences than expected and attempts to resolve the remaining inconsistencies (in both calibration and forward modeling) are continuing.

The paper concludes by outlining the objectives of the recent 2000 WVIOP and the ARM–First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX), the latter of which switched the focus to characterizing upper-tropospheric humidity measurements.

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H.-T. Mengelkamp, F. Beyrich, G Heinemann, F Ament, J Bange, F Berger, J Bösenberg, T Foken, B Hennemuth, C. Heret, S Huneke, K.-P. Johnsen, M. Kerschgens, W. Kohsiek, J.-P. Leps, C. Liebethal, H. Lohse, M. Mauder, W. Meijninger, S. Raasch, C. Simmer, T. Spieß, A. Tittebrand, J. Uhlenbrock, and P. Zittel

The representation of subgrid-scale surface heterogeneities in numerical weather and climate models has been a challenging problem for more than a decade. The Evaporation at Grid and Pixel Scale (EVA-GRIPS) project adds to the numerous studies on vegetation-atmosphere interaction processes through a comprehensive field campaign and through simulation studies with land surface schemes and mesoscale models. The mixture of surface types in the test area in eastern Germany is typical for larger parts of northern Central Europe. The spatial scale considered corresponds to the grid scale of a regional atmospheric weather prediction or climate model and to the pixel scale of satellite images. Area-averaged fluxes derived from point measurements, scintillometer measurements, and a helicopter-borne turbulence probe were widely consistent with respect to the sensible heat flux. The latent heat flux from the scintillometer measurements is systematically higher than the eddy covariance data. Fluxes derived from numerical simulations proved the so-called mosaic approach to be an appropriate parameterization for subgrid heterogeneity.

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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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