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  • Author or Editor: W. R. Young x
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W.R. Moninger
,
J. Bullas
,
B. de Lorenzis
,
E. Ellison
,
J. Flueck
,
J.C. McLeod
,
C. Lusk
,
P.D. Lampru
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R.S. Phillips
,
W.F. Roberts
,
R. Shaw
,
T.R. Stewart
,
J. Weaver
,
K.C. Young
, and
S.M. Zubrick

During the summer of 1989, the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration sponsored an evaluation of artificial-intelligence-based systems that forecast severe convective storms. The evaluation experiment, called Shootout-89, took place in Boulder, Colorado, and focused on storms over the northeastern Colorado foothills and plains.

Six systems participated in Shootout-89: three traditional expert systems, a hybrid system including a linear model augmented by a small expert system, an analogue-based system, and a system developed using methods from the cognitive science/judgment analysis tradition.

Each day of the exercise, the systems generated 2–9-h forecasts of the probabilities of occurrence of nonsignificant weather, significant weather, and severe weather in each of four regions in northeastern Colorado. A verification coordinator working at the Denver Weather Service Forecast Office gathered ground-truth data from a network of observers.

The systems were evaluated on several measures of forecast skill, on timeliness, on ease of learning, and on ease of use. They were generally easy to operate; however, they required substantially different levels of meteorological expertise on the part of their users, reflecting the various operational environments for which they had been designed. The systems varied in their statistical behavior, but on this difficult forecast problem, they generally showed a skill approximately equal to that of persistence forecasts and climatological forecasts.

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David A. R. Kristovich
,
Richard D. Clark
,
Jeffrey Frame
,
Bart Geerts
,
Kevin R. Knupp
,
Karen A. Kosiba
,
Neil F. Laird
,
Nicholas D. Metz
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Justin R. Minder
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Todd D. Sikora
,
W. James Steenburgh
,
Scott M. Steiger
,
Joshua Wurman
, and
George S. Young

Abstract

Intense lake-effect snowstorms regularly develop over the eastern Great Lakes, resulting in extreme winter weather conditions with snowfalls sometimes exceeding 1 m. The Ontario Winter Lake-effect Systems (OWLeS) field campaign sought to obtain unprecedented observations of these highly complex winter storms.

OWLeS employed an extensive and diverse array of instrumentation, including the University of Wyoming King Air research aircraft, five university-owned upper-air sounding systems, three Center for Severe Weather Research Doppler on Wheels radars, a wind profiler, profiling cloud and precipitation radars, an airborne lidar, mobile mesonets, deployable weather Pods, and snowfall and particle measuring systems. Close collaborations with National Weather Service Forecast Offices during and following OWLeS have provided a direct pathway for results of observational and numerical modeling analyses to improve the prediction of severe lake-effect snowstorm evolution. The roles of atmospheric boundary layer processes over heterogeneous surfaces (water, ice, and land), mixed-phase microphysics within shallow convection, topography, and mesoscale convective structures are being explored.

More than 75 students representing nine institutions participated in a wide variety of data collection efforts, including the operation of radars, radiosonde systems, mobile mesonets, and snow observation equipment in challenging and severe winter weather environments.

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Edwin F. Harrison
,
David R. Brooks
,
Patrick Minnis
,
Bruce A. Wielicki
,
W. Frank Staylor
,
Gary G. Gibson
,
David F. Young
,
Frederick M. Denn
, and
the ERBE Science Team

First results for diurnal cycles derived from the Earth Radiation Budget Experiment (ERBE) are presented for the combined Earth Radiation Budget Satellite (ERBS) and NOAA-9 spacecraft for April 1985. Regional scale longwave (LW) radiation data are analyzed to determine diurnal variations for the total scene (including clouds) and for clear-sky conditions. The LW diurnal range was found to be greatest for clear desert regions (up to about 70 W · m−2) and smallest for clear oceans (less than 5 W · m−2). Local time of maximum longwave radiation occurs at a wide range of times throughout the day and night over oceans, but generally occurs from noon to early afternoon over land and desert regions.

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Russell S. Vose
,
Scott Applequist
,
Mark A. Bourassa
,
Sara C. Pryor
,
Rebecca J. Barthelmie
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Brian Blanton
,
Peter D. Bromirski
,
Harold E. Brooks
,
Arthur T. DeGaetano
,
Randall M. Dole
,
David R. Easterling
,
Robert E. Jensen
,
Thomas R. Karl
,
Richard W. Katz
,
Katherine Klink
,
Michael C. Kruk
,
Kenneth E. Kunkel
,
Michael C. MacCracken
,
Thomas C. Peterson
,
Karsten Shein
,
Bridget R. Thomas
,
John E. Walsh
,
Xiaolan L. Wang
,
Michael F. Wehner
,
Donald J. Wuebbles
, and
Robert S. Young

This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.

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Bruce A. Wielicki
,
D. F. Young
,
M. G. Mlynczak
,
K. J. Thome
,
S. Leroy
,
J. Corliss
,
J. G. Anderson
,
C. O. Ao
,
R. Bantges
,
F. Best
,
K. Bowman
,
H. Brindley
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J. J. Butler
,
W. Collins
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J. A. Dykema
,
D. R. Doelling
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D. R. Feldman
,
N. Fox
,
X. Huang
,
R. Holz
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Y. Huang
,
Z. Jin
,
D. Jennings
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D. G. Johnson
,
K. Jucks
,
S. Kato
,
D. B. Kirk-Davidoff
,
R. Knuteson
,
G. Kopp
,
D. P. Kratz
,
X. Liu
,
C. Lukashin
,
A. J. Mannucci
,
N. Phojanamongkolkij
,
P. Pilewskie
,
V. Ramaswamy
,
H. Revercomb
,
J. Rice
,
Y. Roberts
,
C. M. Roithmayr
,
F. Rose
,
S. Sandford
,
E. L. Shirley
,
Sr. W. L. Smith
,
B. Soden
,
P. W. Speth
,
W. Sun
,
P. C. Taylor
,
D. Tobin
, and
X. Xiong

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

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David A. R. Kristovich
,
George S. Young
,
Johannes Verlinde
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Peter J. Sousounis
,
Pierre Mourad
,
Donald Lenschow
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Robert M. Rauber
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Mohan K. Ramamurthy
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Brian F. Jewett
,
Kenneth Beard
,
Elen Cutrim
,
Paul J. DeMott
,
Edwin W. Eloranta
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Mark R. Hjelmfelt
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Sonia M. Kreidenweis
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Jon Martin
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James Moore
,
Harry T. Ochs III
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David C Rogers
,
John Scala
,
Gregory Tripoli
, and
John Young

A severe 5-day lake-effect storm resulted in eight deaths, hundreds of injuries, and over $3 million in damage to a small area of northeastern Ohio and northwestern Pennsylvania in November 1996. In 1999, a blizzard associated with an intense cyclone disabled Chicago and much of the U.S. Midwest with 30–90 cm of snow. Such winter weather conditions have many impacts on the lives and property of people throughout much of North America. Each of these events is the culmination of a complex interaction between synoptic-scale, mesoscale, and microscale processes.

An understanding of how the multiple size scales and timescales interact is critical to improving forecasting of these severe winter weather events. The Lake-Induced Convection Experiment (Lake-ICE) and the Snowband Dynamics Project (SNOWBAND) collected comprehensive datasets on processes involved in lake-effect snowstorms and snowbands associated with cyclones during the winter of 1997/98. This paper outlines the goals and operations of these collaborative projects. Preliminary findings are given with illustrative examples of new state-of-the-art research observations collected. Analyses associated with Lake-ICE and SNOWBAND hold the promise of greatly improving our scientific understanding of processes involved in these important wintertime phenomena.

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C. M. Platt
,
S. A. Young
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A. I. Carswell
,
S. R. Pal
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M. P. McCormick
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D. M. Winker
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M. DelGuasta
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L. Stefanutti
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W. L. Eberhard
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M. Hardesty
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P. H. Flamant
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R. Valentin
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B. Forgan
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G. G. Gimmestad
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H. Jäger
,
S. S. Khmelevtsov
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I. Kolev
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B. Kaprieolev
,
Da-ren Lu
,
K. Sassen
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V. S. Shamanaev
,
O. Uchino
,
Y. Mizuno
,
U. Wandinger
,
C. Weitkamp
,
A. Ansmann
, and
C. Wooldridge

The Experimental Cloud Lidar Pilot Study (ECLIPS) was initiated to obtain statistics on cloud-base height, extinction, optical depth, cloud brokenness, and surface fluxes. Two observational phases have taken place, in October–December 1989 and April–July 1991, with intensive 30-day periods being selected within the two time intervals. Data are being archived at NASA Langley Research Center and, once there, are readily available to the international scientific community.

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S. I. Bohnenstengel
,
S. E. Belcher
,
A. Aiken
,
J. D. Allan
,
G. Allen
,
A. Bacak
,
T. J. Bannan
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J. F. Barlow
,
D. C. S. Beddows
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W. J. Bloss
,
A. M. Booth
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C. Chemel
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O. Coceal
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C. F. Di Marco
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M. K. Dubey
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K. H. Faloon
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Z. L. Fleming
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M. Furger
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J. K. Gietl
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R. R. Graves
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D. C. Green
,
C. S. B. Grimmond
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C. H. Halios
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J. F. Hamilton
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R. M. Harrison
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M. R. Heal
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D. E. Heard
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C. Helfter
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S. C. Herndon
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R. E. Holmes
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J. R. Hopkins
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A. M. Jones
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F. J. Kelly
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S. Kotthaus
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B. Langford
,
J. D. Lee
,
R. J. Leigh
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A. C. Lewis
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R. T. Lidster
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F. D. Lopez-Hilfiker
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J. B. McQuaid
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C. Mohr
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P. S. Monks
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E. Nemitz
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N. L. Ng
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C. J. Percival
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A. S. H. Prévôt
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H. M. A. Ricketts
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R. Sokhi
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D. Stone
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J. A. Thornton
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A. H. Tremper
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A. C. Valach
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S. Visser
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L. K. Whalley
,
L. R. Williams
,
L. Xu
,
D. E. Young
, and
P. Zotter

Abstract

Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.

Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

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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.

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