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  • 1
    Publication Date: 2020-05-27
    Description: The NOAA Warn-on-Forecast System (WoFS) is an experimental rapidly updating convection-allowing ensemble designed to provide probabilistic operational guidance on high-impact thunderstorm hazards. The current WoFS uses physics diversity to help maintain ensemble spread. We assess the systematic impacts of the three WoFS PBL schemes—YSU, MYJ, and MYNN—using novel, object-based methods tailored to thunderstorms. Very short forecast lead times of 0–3 h are examined, which limits phase errors and thereby facilitates comparisons of observed and model storms that occurred in the same area at the same time. This evaluation framework facilitates assessment of systematic PBL scheme impacts on storms and storm environments. Forecasts using all three PBL schemes exhibit overly narrow ranges of surface temperature, dewpoint, and wind speed. The surface biases do not generally decrease at later forecast initialization times, indicating that systematic PBL scheme errors are not well mitigated by data assimilation. The YSU scheme exhibits the least bias of the three in surface temperature and moisture and in many sounding-derived convective variables. Interscheme environmental differences are similar both near and far from storms and qualitatively resemble the differences analyzed in previous studies. The YSU environments exhibit stronger mixing, as expected of nonlocal PBL schemes; are slightly less favorable for storm intensification; and produce correspondingly weaker storms than the MYJ and MYNN environments. On the other hand, systematic interscheme differences in storm morphology and storm location forecast skill are negligible. Overall, the results suggest that calibrating forecasts to correct for systematic differences between PBL schemes may modestly improve WoFS and other convection-allowing ensemble guidance at short lead times.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 2
    Publication Date: 2018-07-16
    Description: As convection-allowing ensembles are routinely used to forecast the evolution of severe thunderstorms, developing an understanding of storm-scale predictability is critical. Using a full-physics numerical weather prediction (NWP) framework, the sensitivity of ensemble forecasts of supercells to initial condition (IC) uncertainty is investigated using a perfect model assumption. Three cases are used from the real-time NSSL Experimental Warn-on-Forecast System for Ensembles (NEWS-e) from the 2016 NOAA Hazardous Weather Testbed Spring Forecasting Experiment. The forecast sensitivity to IC uncertainty is assessed by repeating the simulations with the initial ensemble perturbations reduced to 50% and 25% of their original magnitudes. The object-oriented analysis focuses on significant supercell features, including the mid- and low-level mesocyclone, and rainfall. For a comprehensive analysis, supercell location and amplitude predictability of the aforementioned features are evaluated separately. For all examined features and cases, forecast spread is greatly reduced by halving the IC spread. By reducing the IC spread from 50% to 25% of the original magnitude, forecast spread is still substantially reduced in two of the three cases. The practical predictability limit (PPL), or the lead time beyond which the forecast spread exceeds some prechosen threshold, is case and feature dependent. Comparing to past studies reveals that practical predictability of supercells is substantially improved by initializing once storms are well established in the ensemble analysis.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 3
    Publication Date: 2018-07-01
    Description: A goal of Warn-on-Forecast (WoF) is to develop forecasting systems that produce accurate analyses and forecasts of severe weather to be utilized in operational warning settings. Recent WoF-related studies have indicated the need to alleviate storm displacement errors in both analyses and forecasts. A potential solution to reduce these errors is the feature alignment technique (FAT), which mitigates displacement errors between observations and model fields while satisfying constraints. This study merges the FAT with a local ensemble transform Kalman filter (LETKF) and uses observing system simulation experiments (OSSEs) to vet the FAT as a potential alleviator of forecast errors arising from storm displacement errors. An idealized truth run of a supercell on a 250-m grid is used to generate pseudoradar observations, which are assimilated onto a 2-km grid using a 50-member ensemble to produce analyses and forecasts of the supercell. The FAT uses composite reflectivity to generate a 2D field of displacement vectors that is used to align the model variables with the observations prior to each analysis cycle. The FAT is tested by displacing the initial model background fields from the observations or modifying the environmental wind profile to create a storm motion bias in the forecast cycles. The FAT–LETKF performance is evaluated and compared to that of the LETKF alone. The FAT substantially reduces errors in storm intensity, location, and structure during data assimilation and subsequent forecasts. These supercell OSSEs provide the foundation for future experiments with real data and more complex events.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 4
    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
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  • 5
    Publication Date: 2018-12-28
    Description: The Storm Prediction Center (SPC) tornado database, generated from NCEI’s Storm Data publication, is indispensable for assessing U.S. tornado risk and investigating tornado–climate connections. Maximizing the value of this database, however, requires accounting for systemically lower reported tornado counts in rural areas owing to a lack of observers. This study uses Bayesian hierarchical modeling to estimate tornado reporting rates and expected tornado counts over the central United States during 1975–2016. Our method addresses a serious solution nonuniqueness issue that may have affected previous studies. The adopted model explains 73% (〉90%) of the variance in reported counts at scales of 50 km (〉100 km). Population density explains more of the variance in reported tornado counts than other examined geographical covariates, including distance from nearest city, terrain ruggedness index, and road density. The model estimates that approximately 45% of tornadoes within the analysis domain were reported. The estimated tornado reporting rate decreases sharply away from population centers; for example, while 〉90% of tornadoes that occur within 5 km of a city with population 〉 100 000 are reported, this rate decreases to
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
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  • 6
    Publication Date: 2018-08-24
    Description: In many instances, synchronization of Doppler radar data among multiple platforms for multiple-Doppler analysis is challenging. This study describes the production of dual-Doppler wind analyses from several case studies using data from a rapid-scanning, X-band, polarimetric, Doppler radar—the RaXPol radar—and data from nearby WSR-88Ds. Of particular interest is mitigating difficulties related to the drastic differences in scanning rates of the two radars. To account for differences in temporal resolution, a variational reflectivity tracking scheme [a spatially variable advection correction technique (SVAC)] has been employed to interpolate (in a Lagrangian sense) the coarser temporal resolution data (WSR-88D) to the times of the RaXPol volume scans. The RaXPol data and temporally interpolated WSR-88D data are then used to create quasi–rapid scan dual-Doppler analyses. This study focuses on the application of the SVAC technique to WSR-88D data to create dual-Doppler analyses of three tornadic supercells: the 19 May 2013 Edmond–Carney and Norman–Shawnee, Oklahoma, storms and the 24 May 2016 Dodge City, Kansas, storm. Results of the dual-Doppler analyses are briefly examined, including observations of the ZDR columns as a proxy for updrafts. Potential improvements to this technique are also discussed.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 7
    Publication Date: 2020-04-14
    Description: The bow echo, a mesoscale convective system (MCS) responsible for much hail and wind damage across the United States, is associated with poor skill in convection-allowing numerical model forecasts. Given the decrease in convection-allowing grid spacings within many operational forecasting systems, we investigate the effect of finer resolution on the character of bowing-MCS development in a real-data numerical simulation. Two ensembles were generated: one with a single domain of 3-km horizontal grid spacing, and another nesting a 1-km domain with two-way feedback. Ensemble members were generated from their control member with a stochastic kinetic-energy backscatter scheme, with identical initial and lateral-boundary conditions. Results suggest that resolution reduces hindcast skill of this MCS, as measured with an adaptation of the object-based Structure–Amplitude–Location method. The nested 1-km ensemble produces a faster system than in both the 3-km ensemble and observations. The nested 1-km simulation also produced stronger cold pools, which could be enhanced by the increased (fractal) cloud surface area with higher resolution, allowing more entrainment of dry air and hence increased evaporative cooling.
    Electronic ISSN: 2073-4433
    Topics: Geosciences
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  • 8
    Publication Date: 2020-10-21
    Description: Techniques to mitigate analysis errors arising from the non-simultaneity of data collections typically use advection-correction procedures based on the hypothesis (frozen turbulence) that the analyzed field can be represented as a pattern of unchanging form in horizontal translation. It is more difficult to advection correct the radial velocity than the reflectivity because even if the vector velocity field satisfies this hypothesis, its radial component does not – but that component does satisfy a second-derivative condition. We treat the advection correction of the radial velocity (vr) as a variational problem in which errors in that second-derivative condition are minimized subject to smoothness constraints on spatially variable pattern-translation components (U, V). The Euler- Lagrange equations are derived, and an iterative trajectory-based solution is developed in which U, V, and vr are analyzed together. The analysis code is first verified using analytical data, and then tested using Atmospheric Imaging Radar (AIR) data from a band of heavy rainfall on 4 September 2018 near El Reno, OK, and a decaying tornado on 27 May 2015 near Canadian, TX. In both cases, the analyzed vr field has smaller root-mean-square errors and larger correlation coefficients than in analyses based on persistence, linear time interpolation, or advection correction using constant U and V. As some experimentation is needed to obtain appropriate parameter values, the procedure is more suitable for non-real-time applications than use in an operational setting. In particular, the degree of spatial variability in U and V, and the associated errors in the analyzed vr field are strongly dependent on a smoothness parameter.
    Print ISSN: 0022-4928
    Electronic ISSN: 1520-0469
    Topics: Geography , Geosciences , Physics
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  • 9
    Publication Date: 2020-10-15
    Description: An improved understanding of common differences between tornadic and nontornadic supercells is sought using a large set of observations from the operational NEXRAD WSR-88D polarimetric radar network in the contiguous United States. In particular, data from 478 nontornadic and 294 tornadic supercells during a 7-year period (2011-2017) are used to produce probability-matched composite means of microphysical and kinematic variables. Means, which are centered on echo-top maxima and in a horizontal coordinate system rotated such that storm motion points in the positive x-dimension, are created in altitude relative to ground level at times of peak echo-top altitude and peak midlevel rotation for nontornadic supercells and times at and prior to the first tornado in tornadic supercells. Robust differences between supercell types are found, with consistent characteristics at and preceding tornadogenesis in tornadic storms. In particular, the mesocyclone is found to be vertically aligned in tornadic supercells and misaligned in nontornadic supercells. Microphysical differences found include a low-level radar reflectivity hook echo aligned with and ~10 km right of storm center in tornadic supercells and displaced 5-10 km down-motion in nontornadic supercells, a low-to-midlevel differential radar reflectivity dipole that is oriented more parallel to storm motion in tornadic supercells and more perpendicular in nontornadic supercells, and a separation between enhanced differential radar reflectivity and specific differential phase (with unique displacement-relative correlation coefficient reductions) at low levels that is more perpendicular to storm motion in tornadic supercells and more parallel in nontornadic supercells.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 10
    Publication Date: 2017-08-04
    Description: The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km  ×  100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with those from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s−1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s−1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. The results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.
    Print ISSN: 1867-1381
    Electronic ISSN: 1867-8548
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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