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  • 1
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    Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress (2018)
    American Meteorological Society
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    Publication Date: 2018-04-01
    Description: The Warn-on-Forecast (WoF) program, driven by advanced data assimilation and ensemble design of numerical weather prediction (NWP) systems, seeks to advance 0–3-h NWP to aid National Weather Service warnings for thunderstorm-induced hazards. An early prototype of the WoF prediction system is the National Severe Storms Laboratory (NSSL) Experimental WoF System for ensembles (NEWSe), which comprises 36 ensemble members with varied initial conditions and parameterization suites. In the present study, real-time 3-h quantitative precipitation forecasts (QPFs) during spring 2016 from NEWSe members are compared against those from two real-time deterministic systems: the operational High Resolution Rapid Refresh (HRRR, version 1) and an upgraded, experimental configuration of the HRRR. All three model systems were run at 3-km horizontal grid spacing and differ in initialization, particularly in the radar data assimilation methods. It is the impact of this difference that is evaluated herein using both traditional and scale-aware verification schemes. NEWSe, evaluated deterministically for each member, shows marked improvement over the two HRRR versions for 0–3-h QPFs, especially at higher thresholds and smaller spatial scales. This improvement diminishes with forecast lead time. The experimental HRRR model, which became operational as HRRR version 2 in August 2016, also provides added skill over HRRR version 1.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 2
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    Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part II: Combined Radar and Satellite Data Experiments (2016)
    American Meteorological Society
    Details
    Publication Date: 2016-02-01
    Description: This research represents the second part of a two-part series describing the development of a prototype ensemble data assimilation system for the Warn-on-Forecast (WoF) project known as the NSSL Experimental WoF System for ensembles (NEWS-e). Part I describes the NEWS-e design and results from radar reflectivity and radial velocity data assimilation for six severe weather events occurring during 2013 and 2014. Part II describes the impact of assimilating satellite liquid and ice water path (LWP and IWP, respectively) retrievals from the GOES Imager along with the radar observations. Assimilating LWP and IWP observations may improve thermodynamic conditions at the surface over the storm-scale domain through better analysis of cloud coverage in the model compared to radar-only experiments. These improvements sometimes corresponded to an improved analysis of supercell storms leading to better forecasts of low-level vorticity. This positive impact was most evident for events where convection is not ongoing at the beginning of the radar and satellite data assimilation period. For more complex cases containing significant amounts of ongoing convection, only assimilating clear-sky satellite retrievals in place of clear-air reflectivity resulted in spurious regions of light precipitation compared to the radar-only experiments. The analyzed tornadic storms in these experiments are sometimes too weak and quickly diminished in intensity in the forecasts. The lessons learned as part of these experiments should lead to improved iterations of the NEWS-e system, building on the modestly successful results described here.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 3
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    Application of Two Spatial Verification Methods to Ensemble Forecasts of Low-Level Rotation (2016)
    American Meteorological Society
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    Publication Date: 2016-04-29
    Description: Two spatial verification methods are applied to ensemble forecasts of low-level rotation in supercells: a four-dimensional, object-based matching algorithm and the displacement and amplitude score (DAS) based on optical flow. Ensemble forecasts of low-level rotation produced using the National Severe Storms Laboratory (NSSL) Experimental Warn-on-Forecast System are verified against WSR-88D single-Doppler azimuthal wind shear values interpolated to the model grid. Verification techniques are demonstrated using four 60-min forecasts issued at 15-min intervals in the hour preceding development of the 20 May 2013 Moore, Oklahoma, tornado and compared to results from two additional forecasts of tornadic supercells occurring during the springs of 2013 and 2014. The object-based verification technique and displacement component of DAS are found to reproduce subjectively determined forecast characteristics in successive forecasts for the 20 May 2013 event, as well as to discriminate in subjective forecast quality between different events. Ensemble-mean, object-based measures quantify spatial and temporal displacement, as well as storm motion biases in predicted low-level rotation in a manner consistent with subjective interpretation. Neither method produces useful measures of the intensity of low-level rotation, owing to deficiencies in the verification dataset and forecast resolution.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 4
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    Sensitivity of Supercell Simulations to Initial-Condition Resolution (2016)
    American Meteorological Society
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    Publication Date: 2016-12-15
    Description: Observational and model resolution limitations currently preclude analysis of the smallest scales important to numerical prediction of convective storms. These missing scales can be recovered if the forecast model is integrated on a sufficiently fine grid, but not before errors are introduced that subsequently grow in scale and magnitude. This study is the first to systematically evaluate the impact of these initial-condition (IC) resolution errors on high-resolution forecasts of organized convection. This is done by comparing high-resolution supercell simulations generated using identical model settings but successively coarsened ICs. Consistent with the Warn-on-Forecast paradigm, the simulations are initialized with ongoing storms and integrated for 2 h. Both idealized and full-physics experiments are performed in order to examine how more realistic model settings modulate the error evolution. In all experiments, scales removed from the IC (wavelengths 〈 2, 4, 8, or 16 km) regenerate within 10–20 min of model integration. While the forecast errors arising from the initial absence of these scales become quantitatively large in many instances, the qualitative storm evolution is relatively insensitive to the IC resolution. It therefore appears that adopting much finer forecast (e.g., 250 m) than analysis (e.g., 3 km) grids for data assimilation and prediction would improve supercell forecasts given limited computational resources. This motivates continued development of mixed-resolution systems. The relative insensitivity to IC resolution further suggests that convective forecasting can be more readily advanced by improving model physics and numerics and expanding extrastorm observational coverage than by increasing intrastorm observational density.
    Print ISSN: 0022-4928
    Electronic ISSN: 1520-0469
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 5
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    Object-Based Verification of a Prototype Warn-on-Forecast System (2018)
    American Meteorological Society
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    Publication Date: 2018-09-17
    Description: An object-based verification methodology for the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e) has been developed and applied to 32 cases between December 2015 and June 2017. NEWS-e forecast objects of composite reflectivity and 30-min updraft helicity swaths are matched to corresponding reflectivity and rotation track objects in Multi-Radar Multi-Sensor system data on space and time scales typical of a National Weather Service warning. Object matching allows contingency-table-based verification statistics to be used to establish baseline performance metrics for NEWS-e thunderstorm and mesocyclone forecasts. NEWS-e critical success index (CSI) scores of reflectivity (updraft helicity) forecasts decrease from approximately 0.7 (0.4) to 0.4 (0.2) over 3 h of forecast time. CSI scores decrease through the forecast period, indicating that errors do not saturate during the 3-h forecast. Lower verification scores for rotation track forecasts are primarily a result of a high-frequency bias. Comparison of different system configurations used in 2016 and 2017 shows an increase in skill for 2017 reflectivity forecasts, attributable mainly to improvements in the forecast initial conditions. A small decrease in skill in 2017 rotation track forecasts is likely a result of sample differences between 2016 and 2017. Although large case-to-case variation is present, evidence is found that NEWS-e forecast skill improves with increasing object size and intensity.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 6
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    Radar and Damage Analysis of Severe Bow Echoes Observed during BAMEX (2006)
    American Meteorological Society
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    Publication Date: 2006-03-01
    Description: This study examines damaging-wind production by bow-shaped convective systems, commonly referred to as bow echoes. Recent idealized numerical simulations suggest that, in addition to descending rear inflow at the bow echo apex, low-level mesovortices within bow echoes can induce damaging straight-line surface winds. In light of these findings, detailed aerial and ground surveys of wind damage were conducted immediately following five bow echo events observed during the Bow Echo and Mesoscale Convective Vortex (MCV) Experiment (BAMEX) field phase. These damage locations were overlaid directly onto Weather Surveillance Radar-1988 Doppler (WSR-88D) images to (i) elucidate where damaging surface winds occurred within the bow-shaped convective system (in proximity to the apex, north of the apex, etc.), and then (ii) explain the existence of these winds in the context of the possible damaging-wind mechanisms. The results of this study provide clear observational evidence that low-level mesovortices within bow echoes can produce damaging straight-line winds at the ground. When present in the BAMEX dataset, mesovortex winds produced the most significant wind damage. Also in the BAMEX dataset, it was observed that smaller-scale bow echoes—those with horizontal scales of tens of kilometers or less—produced more significant wind damage than mature, extensive bow echoes (except when mesovortices were present within the larger-scale systems).
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 7
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    Application of a WRF Mesoscale Data Assimilation System to Springtime Severe Weather Events 2007–09 (2012)
    American Meteorological Society
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    Publication Date: 2012-05-01
    Description: An ensemble-based data assimilation system using the Weather Research and Forecasting Model (WRF) has been used to initialize forecasts of prolific severe weather events from springs 2007 to 2009. These experiments build on previous work that has shown the ability of ensemble Kalman filter (EnKF) data assimilation to produce realistic mesoscale features, such as drylines and convectively driven cold pools, which often play an important role in future convective development. For each event in this study, severe weather parameters are calculated from an experimental ensemble forecast started from EnKF analyses, and then compared to a control ensemble forecast in which no ensemble-based data assimilation is performed. Root-mean-square errors for surface observations averaged across all events are generally smaller for the experimental ensemble over the 0–6-h forecast period. At model grid points nearest to tornado reports, the ensemble-mean significant tornado parameter (STP) and the probability that STP 〉 1 are often greater in the experimental 0–6-h ensemble forecasts than in the control forecasts. Likewise, the probability of mesoscale convective system (MCS) maintenance probability (MMP) is often greater with the experimental ensemble at model grid points nearest to wind reports. Severe weather forecasts can be sharpened by coupling the respective severe weather parameter with the probability of measurable rainfall at model grid points. The differences between the two ensembles are found to be significant at the 95% level, suggesting that even a short period of ensemble data assimilation can yield improved forecast guidance for severe weather events.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 8
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    Storm-Scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama (2015)
    American Meteorological Society
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    Publication Date: 2015-08-01
    Description: As part of NOAA’s Warn-on-Forecast (WoF) initiative, a multiscale ensemble-based assimilation and prediction system is developed using the WRF-ARW model and DART assimilation software. To evaluate the capabilities of the system, retrospective short-range probabilistic storm-scale (convection allowing) ensemble analyses and forecasts are produced for the 27 April 2011 Alabama severe weather outbreak. Results indicate that the storm-scale ensembles are able to analyze the observed storms with strong low-level rotation at approximately the correct locations and to retain the supercell structures during the 0–1-h forecasts with reasonable accuracy. The system predicts the low-level mesocyclones of significant isolated tornadic supercells that align well with the locations of radar-derived rotation. For cases with multiple interacting storms in close proximity, the system tends to produce more variability in mesocyclone forecasts from one initialization time to the next until the observations show the dominance of one of the cells. The short-range ensemble probabilistic forecasts obtained from this continuous 5-min storm-scale 6-h-long update system demonstrate the potential of a frequently updated, high-resolution NWP system that could be used to extend severe weather warning lead times. This study also demonstrates the challenges associated with developing a WoF-type system. The results motivate future work to reduce model errors associated with storm motion and spurious cells, and to design storm-scale ensembles that better represent typical 1-h forecast errors.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 9
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    Buyer Beware: Some Words of Caution on the Use of Severe Wind Reports in Postevent Assessment and Research (2006)
    American Meteorological Society
    Details
    Publication Date: 2006-06-01
    Description: Postevent damage surveys conducted during the Bow Echo and Mesoscale Convective Vortex Experiment demonstrate that the severe thunderstorm wind reports in Storm Data served as a poor characterization of the actual scope and magnitude of the surveyed damage. Contrasting examples are presented in which a few reports grossly underrepresented a significant event (in terms of property damage and actual areal coverage of damage), while a large number of reports overrepresented a relatively less significant event. Explanations and further discussion of this problem are provided, as are some of the implications, which may include a skewed understanding of how and when systems of thunderstorms cause damage. A number of recommendations pertaining to severe wind reporting are offered.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 10
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    Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part I: Radar Data Experiments (2015)
    American Meteorological Society
    Details
    Publication Date: 2015-12-01
    Description: This first part of a two-part study on storm-scale radar and satellite data assimilation provides an overview of a multicase study conducted as part of the NOAA Warn-on-Forecast (WoF) project. The NSSL Experimental WoF System for ensembles (NEWS-e) is used to produce storm-scale analyses and forecasts of six diverse severe weather events from spring 2013 and 2014. In this study, only Doppler reflectivity and radial velocity observations (and, when available, surface mesonet data) are assimilated into a 36-member, storm-scale ensemble using an ensemble Kalman filter (EnKF) approach. A series of 1-h ensemble forecasts are then initialized from storm-scale analyses during the 1-h period preceding the onset of storm reports. Of particular interest is the ability of these 0–1-h ensemble forecasts to reproduce the low-level rotational characteristics of supercell thunderstorms, as well as other convective hazards. For the tornado-producing thunderstorms considered in this study, ensemble probabilistic forecasts of low-level rotation generally indicated a rotating thunderstorm approximately 30 min before the time of first observed tornado. Displacement errors (often to the north of tornado-affected areas) associated with vorticity swaths were greatest in those forecasts launched 30–60 min before the time of first tornado. Similar forecasts were produced for a tornadic mesovortex along the leading edge of a bow echo and, again, highlighted a well-defined vorticity swath as much as 30 min prior to the first tornado.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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