Search Results

You are looking at 1 - 10 of 35 items for

  • Author or Editor: Kevin W. Thomas x
  • Refine by Access: All Content x
Clear All Modify Search
Howard B. Bluestein
and
Kevin W. Thomas

Abstract

This is a case study of the synoptic and mesoscale aspects of a severe-weather outbreak in the Texas Panhandle. We offer circumstantial evidence that the rising branch of a thermally indirect circulation in the exit region of an unusually intense upper-level jet streak played a role in storm formation and sustenance. The jet streak's vertical circulation could not be accounted for by straight dynamics alone; curvature was important, especially along the right side of the exit region. The geostrophic momentum approximation leads to a reasonable qualitative explanation of the ageostrophic circulation, while quasi-geostrophic theory does not.

Full access
Kevin E. Trenberth
,
Thomas R. Karl
, and
Thomas W. Spence

There is compelling evidence that the climate is changing, for whatever reason. We discuss the degree, nature, and cause of the climate variations and whether there is in fact a change, but the only way to resolve the issue is with solid information. This requires improved global observations of the state variables and the variables causing change (the forcings), the means to process these and understand them, and the ability to set them in a coherent physical (as well as chemical and biological) framework with models for diagnostic and prognostic purposes. Meanwhile, the information that helps settle these arguments and reduces uncertainties is also extremely valuable for many other purposes, including a myriad of practical applications for business, industry, government, and the general public. The following is a list of strategic requirements necessary for a comprehensive climate observing system:

  • Climate observations from both space-based and in situ platforms are taken in ways that address climate needs and adhere to the 10 principles outlined by the NRC. The international framework for sharing data is vital.

  • A global telecommunications and satellite ground systems network and satellite data telemetry capacity to enable data and products from all observing platforms to be disseminated.

  • A climate observations analysis and tracking capability that produces global and regional analyses of various products for the atmosphere, oceans, land surface and hydrology, and the cryosphere.

  • Four-dimensional data assimilation and reanalysis capabilities that process the multivariate data in a physically consistent framework to enable production of the analyses, not just for the atmosphere, but also for the oceans, land surface, and cryosphere.

  • Global climate models that encompass all parts of the climate system and that are utilized in data assimilation and in making ensemble predictions originating from the initial observed state.

  • A climate observation oversight and observing system monitoring capability that tracks the performance of the observations, the gathering of the data, and the processing systems. This must also include the resources and influence to fix problems and the capability to communicate climate requirements when observational systems are being discussed and established, such as for weather purposes or in establishing requirements for instruments on satellites.

Although much has been learned about climate from past and present observing systems, we do not have an adequate climate observing system at present. Instead, we make do with an eclectic mix of observations mostly taken for other purposes. Nor are they adequately synthesized. Hence, in addition to making new observations, there is a strong rationale for building the system, and incorporating the management principles described here.

Full access
Kevin M. Grise
,
David W. J. Thompson
, and
Thomas Birner

Abstract

Static stability is a fundamental dynamical quantity that measures the vertical temperature stratification of the atmosphere. However, the magnitude and structure of finescale features in this field are difficult to discern in temperature data with low vertical resolution. In this study, the authors apply more than six years of high vertical resolution global positioning system radio occultation temperature profiles to document the long-term mean structure and variability of the global static stability field in the stratosphere and upper troposphere.

The most pronounced feature in the long-term mean static stability field is the well-known transition from low values in the troposphere to high values in the stratosphere. Superposed on this general structure are a series of finer-scale features: a minimum in static stability in the tropical upper troposphere, a broad band of high static stability in the tropical stratosphere, increases in static stability within the core of the stratospheric polar vortices, and a shallow but pronounced maximum in static stability just above the tropopause at all latitudes [i.e., the “tropopause inversion layer” (TIL)].

The results shown here provide the first global survey of static stability using high vertical resolution data and also uncover two novel aspects of the static stability field. In the tropical lower stratosphere, the results reveal a unique vertically and horizontally varying static stability structure, with maxima located at ∼17 and ∼19 km. The upper feature peaks during the NH cold season and has its largest magnitude between 10° and 15° latitude in both hemispheres; the lower feature exhibits a weaker seasonal cycle and is centered at the equator. The results also demonstrate that the strength of the TIL is closely tied to stratospheric dynamic variability. The magnitude of the TIL is enhanced following sudden stratospheric warmings in the polar regions and the easterly phase of the quasi-biennial oscillation in the tropics.

Full access
Jonathan Labriola
,
Nathan Snook
,
Ming Xue
, and
Kevin W. Thomas

Abstract

Day-ahead (20–22 h) 3-km grid spacing convection-allowing model forecasts are performed for a severe hail event that occurred in Denver, Colorado, on 8 May 2017 using six different multimoment microphysics (MP) schemes including: the Milbrandt–Yau double-moment (MY2), Thompson (THO), NSSL double-moment (NSSL), Morrison double-moment graupel (MOR-G) and hail (MOR-H), and Predicted Particle Properties (P3) schemes. Hail size forecasts diagnosed using the Thompson hail algorithm and storm surrogates predict hail coverage. For this case hail forecasts predict the coverage of hail with a high level of skill but underpredict hail size. The storm surrogate updraft helicity predicts the coverage of severe hail with the most skill for this case. Model data are analyzed to assess the effects of microphysical treatments related to rimed ice. THO uses diagnostic equations to increase the size of graupel within the hail core. MOR-G and MOR-H predict small rimed ice aloft; excessive size sorting and increased fall speeds cause MOR-H to predict more and larger surface hail than MOR-G. The MY2 and NSSL schemes predict large, dense rimed ice particles because both schemes predict separate hail and graupel categories. The NSSL scheme predicts relatively little hail for this case; however, the hail size forecast qualitatively improves when the maximum size of both hail and graupel is considered. The single ice category P3 scheme only predicts dense hail near the surface while above the melting layer large concentrations of low-density ice dominate.

Full access
Ming Xue
,
Jordan Schleif
,
Fanyou Kong
,
Kevin W. Thomas
,
Yunheng Wang
, and
Kefeng Zhu

Abstract

Twice-daily 48-h tropical cyclone (TC) forecasts were produced for the fall 2010 Atlantic hurricane season using the Advanced Research core of the Weather Research and Forecasting (WRF-ARW) model on a large 4-km grid covering much of the northern Atlantic. WRF forecasts initialized from operational Global Forecast System (GFS) analyses based on the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVAR) system and from experimental global ensemble Kalman filter (EnKF) analyses, and corresponding global GFS forecasts were intercompared. For the track, WRF forecasts show improvement over GFS forecasts using either set of initial conditions (ICs). The EnKF-initialized GFS and WRF are also better than the corresponding GSI-initialized forecasts, but the difference is not always statistically significant. At all lead times, the WRF track errors are comparable to or smaller than the National Hurricane Center (NHC) official track forecast error, with those of the EnKF WRF being smallest. For weaker TCs, more improvement comes from the model (resolution) than from the ICs. For hurricane intensity TCs, EnKF ICs produce better track forecasts than GSI ICs, with the best forecast coming from WRF at most lead times. For intensity, EnKF ICs consistently outperform GSI ICs in both models for weaker TCs. For hurricane-strength TCs, EnKF ICs produce forecasts statistically indistinguishable from GSI ICs in either model. For all TCs combined, WRF produces about half the error of the corresponding GFS simulation beyond 24 h, and at 36 and 48 h, the errors are smaller than those from NHC official forecasts. The improvement is even greater for hurricane-strength TCs. Overall, the WRF forecasts initialized with EnKF ICs have the smallest intensity error, and the difference is statistically significant compared to the GFS forecasts.

Full access
Gregory J. Stumpf
,
Arthur Witt
,
E. DeWayne Mitchell
,
Phillip L. Spencer
,
J. T. Johnson
,
Michael D. Eilts
,
Kevin W. Thomas
, and
Donald W. Burgess

Abstract

The National Severe Storms Laboratory (NSSL) has developed a mesocyclone detection algorithm (NSSL MDA) for the Weather Surveillance Radar-1988 Doppler (WSR-88D) system designed to automatically detect and diagnose the Doppler radar radial velocity patterns associated with storm-scale (1–10-km diameter) vortices in thunderstorms. The NSSL MDA is an enhancement to the current WSR-88D Build 9.0 Mesocyclone Algorithm (88D B9MA).

The recent abundance of WSR-88D observations indicates that a variety of storm-scale vortices are associated with severe weather and tornadoes, and not just those vortices meeting previously established criteria for mesocyclones observed during early Doppler radar studies in the 1970s and 1980s in the Great Plains region of the United States. The NSSL MDA’s automated vortex detection techniques differ from the 88D B9MA, such that instead of immediately thresholding one-dimensional shear segments for strengths comparable to predefined mesocyclone parameters, the initial strength thresholds are set much lower, and classification and diagnosis are performed on the properties of the four-dimensional detections. The NSSL MDA also includes multiple range-dependent strength thresholds, a more robust two-dimensional feature identifier, an improved three-dimensional vertical association technique, and the addition of time association and trends of vortex attributes. The goal is to detect a much broader spectrum of storm-scale vortices (so that few vortices are missed), and then diagnose them to determine their significance. The NSSL MDA is shown to perform better than the 88D B9MA at detecting storm-scale vortices and diagnosing significant vortices.

Operational implications of the NSSL MDA are also presented. In light of the new WSR-88D observations of storm-scale vortices and their association with severe weather and tornadoes, it is clear that the operational paradigms of automated vortex detection require changes.

Full access
Thomas J. Sullivan
,
James S. Ellis
,
Connee S. Foster
,
Kevin T. Foster
,
Ronald L. Baskett
,
John S. Nasstrom
, and
Walter W. Schalk III

The Atmospheric Release Advisory Capability (ARAC) at Lawrence Livermore National Laboratory is a centralized federal project for assessing atmospheric releases of hazardous materials in real time. Since ARAC began making assessments in 1974, the project has responded to over 60 domestic and international incidents. ARAC can model radiological accidents in the United States within 30 to 90 min, using its operationally robust, three-dimensional atmospheric transport and dispersion models, extensive geophysical and dose-factor databases, meteorological data acquisition systems, and experienced staff. Although it was originally conceived and developed as an emergency response and assessment service for providing dose-assessment calculations after nuclear accidents, it has proven to be an extremely adaptable system, capable of being modified to respond also to nonradiological hazardous releases. In 1991, ARAC responded to three major events: the oil fires in Kuwait, the eruption of Mt. Pinatubo in the Philippines, and an herbicide spill into the upper Sacramento River in California. Modeling the atmospheric effects of these events added significantly to the range of problems that ARAC can address and demonstrated that the system can be adapted to assess and respond to concurrent, multiple, unrelated events at different locations.

Full access
Thomas R. Karl
,
Philip D. Jones
,
Richard W. Knight
,
George Kukla
,
Neil Plummer
,
Vyacheslav Razuvayev
,
Kevin P. Gallo
,
Janette Lindseay
,
Robert J. Charlson
, and
Thomas C. Peterson

Monthly mean maximum and minimum temperatures for over 50% (10%) of the Northern (Southern) Hemisphere landmass, accounting for 37% of the global landmass, indicate that the rise of the minimum temperature has occurred at a rate three times that of the maximum temperature during the period 1951–90 (0.84°C versus 0.28°C). The decrease of the diurnal temperature range is approximately equal to the increase of mean temperature. The asymmetry is detectable in all seasons and in most of the regions studied.

The decrease in the daily temperature range is partially related to increases in cloud cover. Furthermore, a large number of atmospheric and surface boundary conditions are shown to differentially affect the maximum and minimum temperature. Linkages of the observed changes in the diurnal temperature range to large-scale climate forcings, such as anthropogenic increases in sulfate aerosols, greenhouse gases, or biomass burning (smoke), remain tentative. Nonetheless, the observed decrease of the diurnal temperature range is clearly important, both scientifically and practically.

Full access
Jidong Gao
,
Travis M. Smith
,
David J. Stensrud
,
Chenghao Fu
,
Kristin Calhoun
,
Kevin L. Manross
,
Jeffrey Brogden
,
Valliappa Lakshmanan
,
Yunheng Wang
,
Kevin W. Thomas
,
Keith Brewster
, and
Ming Xue

Abstract

A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system has been adapted for the NOAA Warn-on-Forecast (WoF) project to incorporate all available radar observations within a moveable analysis domain. The key features of the system include 1) incorporating radar observations from multiple Weather Surveillance Radars-1988 Doppler (WSR-88Ds) with NCEP forecast products as a background state, 2) the ability to automatically detect and analyze severe local hazardous weather events at 1-km horizontal resolution every 5 min in real time based on the current weather situation, and 3) the identification of strong circulation patterns embedded in thunderstorms. Although still in the early development stage, the system performed very well within the NOAA's Hazardous Weather Testbed (HWT) Experimental Warning Program during preliminary testing in spring 2010 when many severe weather events were successfully detected and analyzed. This study represents a first step in the assessment of this type of 3DVAR analysis for use in severe weather warnings. The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.

Full access
Aaron Johnson
,
Xuguang Wang
,
Ming Xue
,
Fanyou Kong
,
Gang Zhao
,
Yunheng Wang
,
Kevin W. Thomas
,
Keith A. Brewster
, and
Jidong Gao

Abstract

Multiscale convection-allowing precipitation forecast perturbations are examined for two forecasts and systematically over 34 forecasts out to 30-h lead time using Haar Wavelet decomposition. Two small-scale initial condition (IC) perturbation methods are compared to the larger-scale IC and physics perturbations in an experimental convection-allowing ensemble. For a precipitation forecast driven primarily by a synoptic-scale baroclinic disturbance, small-scale IC perturbations resulted in little precipitation forecast perturbation energy on medium and large scales, compared to larger-scale IC and physics (LGPH) perturbations after the first few forecast hours. However, for a case where forecast convection at the initial time grew upscale into a mesoscale convective system (MCS), small-scale IC and LGPH perturbations resulted in similar forecast perturbation energy on all scales after about 12 h. Small-scale IC perturbations added to LGPH increased total forecast perturbation energy for this case. Averaged over 34 forecasts, the small-scale IC perturbations had little impact on large forecast scales while LGPH accounted for about half of the error energy on such scales. The impact of small-scale IC perturbations was also less than, but comparable to, the impact of LGPH perturbations on medium scales. On small scales, the impact of small-scale IC perturbations was at least as large as the LGPH perturbations. The spatial structure of small-scale IC perturbations affected the evolution of forecast perturbations, especially at medium scales. There was little systematic impact of the small-scale IC perturbations when added to LGPH. These results motivate further studies on properly sampling multiscale IC errors.

Full access