Search Results

You are looking at 1 - 10 of 12 items for :

  • Author or Editor: Barbara G. Brown x
  • Bulletin of the American Meteorological Society x
  • Refine by Access: All Content x
Clear All Modify Search
Allan H. Murphy
and
Barbara G. Brown

This paper reports some results of a study in which two groups of individuals—undergraduate students and professional meteorologists at Oregon State University—completed a short questionnaire concerning their interpretations of terminology commonly used in public weather forecasts. The questions related to terms and phrases associated with three elements: 1) cloudiness—fraction of sky cover; 2) precipitation—spatial and/or temporal variations; and 3) temperature—specification of intervals.

The students' responses indicate that cloudiness terms are subject to wide and overlapping ranges of interpretation, although the interpretations of these terms correspond quite well to National Weather Service definitions. Their responses to the precipitation and temperature questions reveal that some confusion exists concerning the meaning of spatial and temporal modifiers in precipitation forecasts and that some individuals interpret temperature ranges in terms of asymmetric intervals. When compared to the students' responses, the meteorologists' responses exhibit narrower ranges of interpretation of the cloudiness terms and less confusion about the meaning of spatial/temporal precipitation modifiers.

The study was not intended to be a definitive analysis of public understanding of forecast terminology. Instead, it should be viewed as a primitive form of the type of forecast-terminology study that must be undertaken in the future. Some implications of this investigation for future work in the area are discussed briefly.

Full access
Allan H. Murphy
and
Barbara G. Brown

Worded forecasts, which generally consist of both verbal and numerical expressions, play an important role in the communication of weather information to the general public. However, relatively few studies of the composition and interpretation of such forecasts have been conducted. Moreover, the studies that have been undertaken to date indicate that many expressions currently used in public forecasts are subject to wide ranges of interpretation (and to misinterpretation) and that the ability of individuals to recall the content of worded forecasts is quite limited. This paper focuses on forecast terminology and the understanding of such terminology in the context of short-range public weather forecasts.

The results of previous studies of forecast terminology (and related issues) are summarized with respect to six basic aspects or facets of worded forecasts. These facets include: 1) events (the values of the meteorological variables): 2) terminology (the words used to describe the events); 3) words versus numbers (the use of verbal and/or numerical expressions); 4) uncertainty (the mode of expression of uncertainty); 5) amount of information (the number of items of information); and 6) content and format (the selection of items of information and their placement). In addition, some related topics are treated briefly, including the impact of verification systems, the role of computer-worded forecasts, the implications of new modes of communication, and the use of weather forecasts.

Some conclusions and inferences that can be drawn from this review of previous work are discussed briefly, and a set of recommendations are presented regarding steps that should be taken to raise the level of understanding and enhance the usefulness of worded forecasts. These recommendations are organized under four headings: 1) studies of public understanding, interpretation, and use; 2) management practices; 3) forecaster training and education; and 4) public education.

Full access
Barbara G. Brown
,
Richard W. Katz
, and
Allan H. Murphy

The so-called fallowing/planting problem is an example of a decision-making situation that is potentially sensitive to meteorological information. In this problem, wheat farmers in the drier, western portions of the northern Great Plains must decide each spring whether to plant a crop or to let their land lie fallow. Information that could be used to make this decision includes the soil moisture at planting time and a forecast of growing-season precipitation. A dynamic decision-making model is employed to investigate the economic value of such forecasts in the fallowing/planting situation.

Current seasonal-precipitation forecasts issued by the National Weather Service are found to have minimal economic value in this decision-making problem. However, relatively modest improvements in the quality of the forecasts would lead to quite large increases in value, and perfect information would possess considerable value. In addition, forecast value is found to be sensitive to changes in crop price and precipitation climatology. In particular, the shape of the curve relating forecast value to forecast quality is quite dependent on the amount of growing-season precipitation.

Full access
Eric Gilleland
,
David A. Ahijevych
,
Barbara G. Brown
, and
Elizabeth E. Ebert

Numerous new methods have been proposed for using spatial information to better quantify and diagnose forecast performance when forecasts and observations are both available on the same grid. The majority of the new spatial verification methods can be classified into four broad categories (neighborhood, scale separation, features based, and field deformation), which themselves can be further generalized into two categories of filter and displacement. Because the methods make use of spatial information in widely different ways, users may be uncertain about what types of information each provides, and which methods may be most beneficial for particular applications. As an international project, the Spatial Forecast Verification Methods Inter-Comparison Project (ICP; www.ral.ucar.edu/projects/icp) was formed to address these questions. This project was coordinated by NCAR and facilitated by the WMO/World Weather Research Programme (WWRP) Joint Working Group on Forecast Verification Research. An overview of the methods involved in the project is provided here with some initial guidelines about when each of the verification approaches may be most appropriate. Future spatial verification methods may include hybrid methods that combine aspects of filter and displacement approaches.

Full access
Manfred Dorninger
,
Eric Gilleland
,
Barbara Casati
,
Marion P. Mittermaier
,
Elizabeth E. Ebert
,
Barbara G. Brown
, and
Laurence J. Wilson

Abstract

Recent advancements in numerical weather prediction (NWP) and the enhancement of model resolution have created the need for more robust and informative verification methods. In response to these needs, a plethora of spatial verification approaches have been developed in the past two decades. A spatial verification method intercomparison was established in 2007 with the aim of gaining a better understanding of the abilities of the new spatial verification methods to diagnose different types of forecast errors. The project focused on prescribed errors for quantitative precipitation forecasts over the central United States. The intercomparison led to a classification of spatial verification methods and a cataloging of their diagnostic capabilities, providing useful guidance to end users, model developers, and verification scientists. A decade later, NWP systems have continued to increase in resolution, including advances in high-resolution ensembles. This article describes the setup of a second phase of the verification intercomparison, called the Mesoscale Verification Intercomparison over Complex Terrain (MesoVICT). MesoVICT focuses on the application, capability, and enhancement of spatial verification methods to deterministic and ensemble forecasts of precipitation, wind, and temperature over complex terrain. Importantly, this phase also explores the issue of analysis uncertainty through the use of an ensemble of meteorological analyses.

Full access
Rebecca E. Morss
,
Jeffrey K. Lazo
,
Barbara G. Brown
,
Harold E. Brooks
,
Philip T. Ganderton
, and
Brian N. Mills

Despite the meteorological community's long-term interest in weather-society interactions, efforts to understand socioeconomic aspects of weather prediction and to incorporate this knowledge into the weather prediction system have yet to reach critical mass. This article aims to reinvigorate interest in societal and economic research and applications (SERA) activities within the meteorological and social science communities by exploring key SERA issues and proposing SERA priorities for the next decade.

The priorities were developed by the authors, building on previous work, with input from a diverse group of social scientists and meteorologists who participated in a SERA workshop in August 2006. The workshop was organized to provide input to the North American regional component of THORPEX: A Global Atmospheric Research Programme, but the priorities identified are broadly applicable to all weather forecast research and applications.

To motivate and frame SERA activities, we first discuss the concept of high-impact weather forecasts and the chain from forecast creation to value realization. Next, we present five interconnected SERA priority themes—use of forecast information in decision making, communication of forecast uncertainty, user-relevant verification, economic value of forecasts, and decision support— and propose research integrated across the themes.

SERA activities can significantly improve understanding of weather-society interactions to the benefit of the meteorological community and society. However, reaching this potential will require dedicated effort to bring together and maintain a sustainable interdisciplinary community.

Full access
Steven V. Vasiloff
,
Dong-Jun Seo
,
Kenneth W. Howard
,
Jian Zhang
,
David H. Kitzmiller
,
Mary G. Mullusky
,
Witold F. Krajewski
,
Edward A. Brandes
,
Robert M. Rabin
,
Daniel S. Berkowitz
,
Harold E. Brooks
,
John A. McGinley
,
Robert J. Kuligowski
, and
Barbara G. Brown

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

Full access
Edward I. Tollerud
,
Brian Etherton
,
Zoltan Toth
,
Isidora Jankov
,
Tara L. Jensen
,
Huiling Yuan
,
Linda S. Wharton
,
Paula T. McCaslin
,
Eugene Mirvis
,
Bill Kuo
,
Barbara G. Brown
,
Louisa Nance
,
Steven E. Koch
, and
F. Anthony Eckel
Full access
Annmarie G. Carlton
,
Joost de Gouw
,
Jose L. Jimenez
,
Jesse L. Ambrose
,
Alexis R. Attwood
,
Steven Brown
,
Kirk R. Baker
,
Charles Brock
,
Ronald C. Cohen
,
Sylvia Edgerton
,
Caroline M. Farkas
,
Delphine Farmer
,
Allen H. Goldstein
,
Lynne Gratz
,
Alex Guenther
,
Sherri Hunt
,
Lyatt Jaeglé
,
Daniel A. Jaffe
,
John Mak
,
Crystal McClure
,
Athanasios Nenes
,
Thien Khoi Nguyen
,
Jeffrey R. Pierce
,
Suzane de Sa
,
Noelle E. Selin
,
Viral Shah
,
Stephanie Shaw
,
Paul B. Shepson
,
Shaojie Song
,
Jochen Stutz
,
Jason D. Surratt
,
Barbara J. Turpin
,
Carsten Warneke
,
Rebecca A. Washenfelder
,
Paul O. Wennberg
, and
Xianling Zhou

Abstract

The Southeast Atmosphere Studies (SAS), which included the Southern Oxidant and Aerosol Study (SOAS); the Southeast Nexus (SENEX) study; and the Nitrogen, Oxidants, Mercury and Aerosols: Distributions, Sources and Sinks (NOMADSS) study, was deployed in the field from 1 June to 15 July 2013 in the central and eastern United States, and it overlapped with and was complemented by the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. SAS investigated atmospheric chemistry and the associated air quality and climate-relevant particle properties. Coordinated measurements from six ground sites, four aircraft, tall towers, balloon-borne sondes, existing surface networks, and satellites provide in situ and remotely sensed data on trace-gas composition, aerosol physicochemical properties, and local and synoptic meteorology. Selected SAS findings indicate 1) dramatically reduced NOx concentrations have altered ozone production regimes; 2) indicators of “biogenic” secondary organic aerosol (SOA), once considered part of the natural background, were positively correlated with one or more indicators of anthropogenic pollution; and 3) liquid water dramatically impacted particle scattering while biogenic SOA did not. SAS findings suggest that atmosphere–biosphere interactions modulate ambient pollutant concentrations through complex mechanisms and feedbacks not yet adequately captured in atmospheric models. The SAS dataset, now publicly available, is a powerful constraint to develop predictive capability that enhances model representation of the response and subsequent impacts of changes in atmospheric composition to changes in emissions, chemistry, and meteorology.

Full access
David C. Leon
,
Jeffrey R. French
,
Sonia Lasher-Trapp
,
Alan M. Blyth
,
Steven J. Abel
,
Susan Ballard
,
Andrew Barrett
,
Lindsay J. Bennett
,
Keith Bower
,
Barbara Brooks
,
Phil Brown
,
Cristina Charlton-Perez
,
Thomas Choularton
,
Peter Clark
,
Chris Collier
,
Jonathan Crosier
,
Zhiqiang Cui
,
Seonaid Dey
,
David Dufton
,
Chloe Eagle
,
Michael J. Flynn
,
Martin Gallagher
,
Carol Halliwell
,
Kirsty Hanley
,
Lee Hawkness-Smith
,
Yahui Huang
,
Graeme Kelly
,
Malcolm Kitchen
,
Alexei Korolev
,
Humphrey Lean
,
Zixia Liu
,
John Marsham
,
Daniel Moser
,
John Nicol
,
Emily G. Norton
,
David Plummer
,
Jeremy Price
,
Hugo Ricketts
,
Nigel Roberts
,
Phil D. Rosenberg
,
David Simonin
,
Jonathan W. Taylor
,
Robert Warren
,
Paul I. Williams
, and
Gillian Young

Abstract

The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

Full access