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PAUL M. WOLFF

Abstract

Error charts for the numerical barotropic forecasts prepared at the Joint Numerical Weather Prediction Unit since October 1957 have revealed retrogressive patterns of very long wavelength. These errors are shown to be due to changes in the large-scale components predicted by the numerical model. These components are actually quasi-stationary in the atmosphere. Forecasts prepared with an approximation to these components held unchanged show significantly increased accuracy. Finally, some of the difficulties in developing a more acceptable physical approach to this problem are outlined.

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Paul M. Wolff

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Paul M. Wolff
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Paul M. Wolff

Abstract

A method of space averaging is presented for separating long and short waves in the 500-mb geostrophic flow. The long-wave features are further identified as perturbations. Some of the forecasting characteristics noted in the application of these computations to six years of historical and one year of current hemispheric 500-mb charts are included.

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Capt. F. A. Berry, Lt. Cdrs. W. H. Haggard, and Paul M. Wolff

In support of several related applied meteorological research tasks at Project AROWA, studies are being made of pressure patterns at the 500-mb level. Preliminary results of investigations based on data from the period 1946 through 1951 are presented.

Examples of studies of the geostrophic wind profile, daily twenty-four-hour height-change charts, and tracks of the height-change centers are presented. A discussion of the preparation of composite charts for various types of blocking patterns is included. Some comments are made on the development of normal height charts, and the historical map program.

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Steven D. Miller, Courtney E. Weeks, Randy G. Bullock, John M. Forsythe, Paul A. Kucera, Barbara G. Brown, Cory A. Wolff, Philip T. Partain, Andrew S. Jones, and David B. Johnson

Abstract

Clouds pose many operational hazards to the aviation community in terms of ceilings and visibility, turbulence, and aircraft icing. Realistic descriptions of the three-dimensional (3D) distribution and temporal evolution of clouds in numerical weather prediction models used for flight planning and routing are therefore of central importance. The introduction of satellite-based cloud radar (CloudSat) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) sensors to the National Aeronautics and Space Administration A-Train is timely in light of these needs but requires a new paradigm of model-evaluation tools that are capable of exploiting the vertical-profile information. Early results from the National Center for Atmospheric Research Model Evaluation Toolkit (MET), augmented to work with the emergent satellite-based active sensor observations, are presented here. Existing horizontal-plane statistical evaluation techniques have been adapted to operate on observations in the vertical plane and have been extended to 3D object evaluations, leveraging blended datasets from the active and passive A-Train sensors. Case studies of organized synoptic-scale and mesoscale distributed cloud systems are presented to illustrate the multiscale utility of the MET tools. Definition of objects on the basis of radar-reflectivity thresholds was found to be strongly dependent on the model’s ability to resolve details of the cloud’s internal hydrometeor distribution. Contoured-frequency-by-altitude diagrams provide a useful mechanism for evaluating the simulated and observed 3D distributions for regional domains. The expanded MET provides a new dimension to model evaluation and positions the community to better exploit active-sensor satellite observing systems that are slated for launch in the near future.

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Greg M. McFarquhar, Christopher S. Bretherton, Roger Marchand, Alain Protat, Paul J. DeMott, Simon P. Alexander, Greg C. Roberts, Cynthia H. Twohy, Darin Toohey, Steve Siems, Yi Huang, Robert Wood, Robert M. Rauber, Sonia Lasher-Trapp, Jorgen Jensen, Jeffrey L. Stith, Jay Mace, Junshik Um, Emma Järvinen, Martin Schnaiter, Andrew Gettelman, Kevin J. Sanchez, Christina S. McCluskey, Lynn M. Russell, Isabel L. McCoy, Rachel L. Atlas, Charles G. Bardeen, Kathryn A. Moore, Thomas C. J. Hill, Ruhi S. Humphries, Melita D. Keywood, Zoran Ristovski, Luke Cravigan, Robyn Schofield, Chris Fairall, Marc D. Mallet, Sonia M. Kreidenweis, Bryan Rainwater, John D’Alessandro, Yang Wang, Wei Wu, Georges Saliba, Ezra J. T. Levin, Saisai Ding, Francisco Lang, Son C. H. Truong, Cory Wolff, Julie Haggerty, Mike J. Harvey, Andrew R. Klekociuk, and Adrian McDonald

Abstract

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

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