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Peter A. Stamus, Frederick H. Carr, and David P. Baumhefner

Abstract

A scale-separation technique based on two-dimensional Fourier decomposition is applied to the comparison and verification of analyses and forecasts produced by regional numerical weather prediction systems. A major emphasis of this study is the verification of secondary or derived parameters in addition to the evaluation of primary model variables. Two prediction models are used to illustrate the technique for a variety of forecast fields separated into three separate wavenumber bands. Three different sets of analyses, one from each model system and an independent set, are used for both analysis intercomparison and model verification. The comparison of the analyses is essential to establishing the level of uncertainty for each variable as a function of scale. The synoptic-scale database used to produce the analyses for this study does not allow the verification of scales 800 km or less, no matter how fine the resolution of the model.

Examining the spectra of difference fields with time allows one to study the evolution of model error (or differences between two models) as a function of wavenumber. In some instances where traditional statistical measures of skill indicated good agreement between two forecasts, spectral scale selection of the difference fields shows that the spatial distribution of the errors was quite different, pointing to different error-growth characteristics of the models. The technique allows one to partially separate phase and amplitude errors and, hence, barotropic-versus baroclinic-type error structure. It was found, as expected, that forecast skill decreases more rapidly with time for smaller scales, but this is not true for all parameters examined. The presence of lateral boundary conditions strongly influences the evaluation of skill in a regional model for the primary variables, but not as much for some secondary variables. Verification of secondary variables nearly always indicates significant errors in the forecast before serious problems in the primary variables are detected.

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Carl E. Hane, John A. Haynes, David L. Andra Jr., and Frederick H. Carr

Abstract

Mesoscale convective systems that affect a limited area within the southern plains of the United States during late morning hours during the warm season are investigated. A climatological study over a 5-yr period documents the initiation locations and times, tracks, associated severe weather, and relation to synoptic features over the lifetimes of 145 systems. An assessment is also made of system evolution in each case during the late morning. For a subset of 48 systems, vertical profiles of basic variables from Rapid Update Cycle (RUC) model analyses are used to characterize the environment of each system. Scatter diagrams and discriminant analyses are used to assess which environmental variables are most promising in helping to determine which of two classes of evolutionary character each system will follow.

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Frederick H. Carr, Phillip L. Spencer, Charles A. Doswell III, and Jeffrey D. Powell

Abstract

Two methods for objective analysis of wind profiler data in time-height space are proposed and compared. One is a straightforward adaptation of a procedure developed by Doswell for introducing time continuity into a sequence of spatial analyses. The second technique, named the correlation method, introduces a new rationale for selection of the Barnes filter parameter that is based on knowledge of the statistical structure of wind profiler data. The advantages and disadvantages of each method are discussed. It is noted that the correlation method, in principle, allows the deduction of consistent sampling intervals in time and space for the most dominant phenomena resolved by the data provided by a given atmospheric observing system. It is recommended that an objective analysis of wind profiler data be performed before single- or multiprofiler kinematic calculations are made.

In addition, it is shown that the positions of extrema in kinematic quantities computed from profiler triangles are relatively insensitive to the number of passes used in the analysis procedures. In fact, it is demonstrated that multipass Barnes-type schemes can overfit the original data, suggesting that a one-pass method may be preferable provided that the filter parameter is selected properly.

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Nicholas A. Gasperoni, Xuguang Wang, Keith A. Brewster, and Frederick H. Carr

Abstract

The Nationwide Network of Networks (NNoN) concept was introduced by the National Research Council to address the growing need for a national mesoscale observing system and the continued advancement toward accurate high-resolution numerical weather prediction. The research test bed known as the Dallas–Fort Worth (DFW) Urban Demonstration Network was created to experiment with many kinds of mesoscale observations that could be used in a data assimilation system. Many nonconventional observations, including Earth Networks and Citizen Weather Observer Program surface stations, are combined with conventional operational data to form the test bed network. A principal component of the NNoN effort is the quantification of observation impact from several different sources of information. In this study, the GSI-based EnKF system was used together with the WRF-ARW Model to examine impacts of observations assimilated for forecasting convection initiation (CI) in the 3 April 2014 hail storm case. Data denial experiments tested the impact of high-frequency (5 min) assimilation of nonconventional data on the timing and location of CI and subsequent storm evolution. Results showed nonconventional observations were necessary to capture details in the dryline structure causing localized enhanced convergence and leading to CI. Diagnosis of denial-minus-control fields showed the cumulative influence each observing network had on the resulting CI forecast. It was found that most of this impact came from the assimilation of thermodynamic observations in sensitive areas along the dryline gradient. Accurate metadata were found to be crucial toward the future application of nonconventional observations in high-resolution assimilation and forecast systems.

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Carl E. Hane, Jill D. Watts, David L. Andra Jr., John A. Haynes, Edward Berry, Robert M. Rabin, and Frederick H. Carr

Abstract

The factors that influence the evolution of convective systems during the late morning over much of the Great Plains are not understood well. It is known that in this region the majority of such systems dissipate or decrease in intensity during this period. With this fact in mind, a summary is given of comments made during the occurrence of morning convective systems by forecasters at two National Weather Service (NWS) offices relating to factors that were most important in determining their forecasts of system evolution. In addition, results of a preliminary climatological study covering eight summer months for 181 summer precipitation systems affecting the county warning areas of the two NWS offices during late morning are presented. Revealed among the significant system characteristics is that approximately two-thirds of the included systems either decreased in intensity or dissipated during the late morning.

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Richard J. Reed, Robert M. White, Edward S. Epstein, Richard A. Craig, Harry Hamilton, Robert E. Livezey, David Houghton, and Frederick Carr
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Erik N. Rasmussen, Jerry M. Straka, Robert Davies-Jones, Charles A. Doswell III, Frederick H. Carr, Michael D. Eilts, and Donald R. MacGorman

This paper describes the Verification of the Origins of Rotation in Tornadoes Experiment planned for 1994 and 1995 to evaluate a set of hypotheses pertaining to tornadogenesis and tornado dynamics. Observations of state variables will be obtained from five mobile mesonet vehicles, four mobile ballooning laboratories, three movie photography teams, portable Doppler radar teams, two in situ tornado instruments deployment teams, and the T-28 and National Atmospheric and Oceanic Administration P-3 aircraft. In addition, extensive use will be made of the new generation of observing systems, including the WSR-88D Doppler radars, demonstration wind profiler network, and National Weather Service rawinsondes.

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Walter F. Dabberdt, Thomas W. Schlatter, Frederick H. Carr, Elbert W. Joe Friday, David Jorgensen, Steven Koch, Maria Pirone, F. Martin Ralph, Juanzhen Sun, Patrick Welsh, James W. Wilson, and Xiaolei Zou

More than 120 scientists, engineers, administrators, and users met on 8–10 December 2003 in a workshop format to discuss the needs for enhanced three-dimensional mesoscale observing networks. Improved networks are seen as being critical to advancing numerical and empirical modeling for a variety of mesoscale applications, including severe weather warnings and forecasts, hydrology, air-quality forecasting, chemical emergency response, transportation safety, energy management, and others. The participants shared a clear and common vision for the observing requirements: existing two-dimensional mesoscale measurement networks do not provide observations of the type, frequency, and density that are required to optimize mesoscale prediction and nowcasts. To be viable, mesoscale observing networks must serve multiple applications, and the public, private, and academic sectors must all actively participate in their design and implementation, as well as in the creation and delivery of value-added products. The mesoscale measurement challenge can best be met by an integrated approach that considers all elements of an end-to-end solution—identifying end users and their needs, designing an optimal mix of observations, defining the balance between static and dynamic (targeted or adaptive) sampling strategies, establishing long-term test beds, and developing effective implementation strategies. Detailed recommendations are provided pertaining to nowcasting, numerical prediction and data assimilation, test beds, and implementation strategies.

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Xubin Zeng, Robert Atlas, Ronald J. Birk, Frederick H. Carr, Matthew J. Carrier, Lidia Cucurull, William H. Hooke, Eugenia Kalnay, Raghu Murtugudde, Derek J. Posselt, Joellen L. Russell, Daniel P. Tyndall, Robert A. Weller, and Fuqing Zhang

Abstract

The NOAA Science Advisory Board appointed a task force to prepare a white paper on the use of observing system simulation experiments (OSSEs). Considering the importance and timeliness of this topic and based on this white paper, here we briefly review the use of OSSEs in the United States, discuss their values and limitations, and develop five recommendations for moving forward: national coordination of relevant research efforts, acceleration of OSSE development for Earth system models, consideration of the potential impact on OSSEs of deficiencies in the current data assimilation and prediction system, innovative and new applications of OSSEs, and extension of OSSEs to societal impacts. OSSEs can be complemented by calculations of forecast sensitivity to observations, which simultaneously evaluate the impact of different observation types in a forecast model system.

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David McLaughlin, David Pepyne, V. Chandrasekar, Brenda Philips, James Kurose, Michael Zink, Kelvin Droegemeier, Sandra Cruz-Pol, Francesc Junyent, Jerald Brotzge, David Westbrook, Nitin Bharadwaj, Yanting Wang, Eric Lyons, Kurt Hondl, Yuxiang Liu, Eric Knapp, Ming Xue, Anthony Hopf, Kevin Kloesel, Alfred DeFonzo, Pavlos Kollias, Keith Brewster, Robert Contreras, Brenda Dolan, Theodore Djaferis, Edin Insanic, Stephen Frasier, and Frederick Carr

Dense networks of short-range radars capable of mapping storms and detecting atmospheric hazards are described. Composed of small X-band (9.4 GHz) radars spaced tens of kilometers apart, these networks defeat the Earth curvature blockage that limits today s long-range weather radars and enables observing capabilities fundamentally beyond the operational state-of-the-art radars. These capabilities include multiple Doppler observations for mapping horizontal wind vectors, subkilometer spatial resolution, and rapid-update (tens of seconds) observations extending from the boundary layer up to the tops of storms. The small physical size and low-power design of these radars permits the consideration of commercial electronic manufacturing approaches and radar installation on rooftops, communications towers, and other infrastructure elements, leading to cost-effective network deployments. The networks can be architected in such a way that the sampling strategy dynamically responds to changing weather to simultaneously accommodate the data needs of multiple types of end users. Such networks have the potential to supplement, or replace, the physically large long-range civil infrastructure radars in use today.

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