Impact of the Environmental Low-Level Wind Profile on Ensemble Forecasts of the 4 May 2007 Greensburg, Kansas, Tornadic Storm and Associated Mesocyclones

The early tornadic phase of the Greensburg, Kansas, supercell on the evening of 4 May 2007 is simulated using a set of storm-scale (1-km horizontal grid spacing) 30-member ensemble Kalman filter (EnKF) data assimilation and forecast experiments. The Next Generation Weather Radar (NEXRAD) level-II radar data from the Dodge City, Kansas (KDDC), Weather Surveillance Radar-1988 Doppler (WSR-88D) are assimilated into the National Severe Storms Laboratory (NSSL) Collaborative Model for Multiscale Atmospheric Simulation (COMMAS). The initially horizontally homogeneous environments are initialized from one of three reconstructed soundings representative of the early tornadic phase of the storm, when a low-level jet (LLJ) was intensifying. To isolate the impact of the low-level wind profile, 0–3.5-km AGL wind profiles from Vance Air Force Base, Oklahoma (KVNX), WSR-88D velocity-azimuth display (VAD) analyses at 0130, 0200, and 0230 UTC are used. A sophisticated, double-moment bulk ice microphysics scheme is employed. For each of the three soundings, ensemble forecast experiments are initiated from EnKF analyses at various times prior to and shortly after the genesis of the Greensburg tornado (0200 UTC). Probabilistic forecasts of the mesocyclone-scale circulation(s) are generated and compared to the observed Greensburg tornado track. Probabilistic measures of significant rotation and observation-space diagnostic statistics are also calculated. It is shown that, in general, the track of the Greensburg tornado is well predicted, and forecasts improve as forecast lead time decreases. Significant variability is also seen across the experiments using different VAD wind profiles. Implications of these results regarding the choice of initial mesoscale environment, as well as for the “Warn-on-Forecast” paradigm for probabilistic numerical prediction of severe thunderstorms and tornadoes, are discussed.

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Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part I: Radar Data Experiments

Weather and Forecasting ◽

10.1175/waf-d-15-0043.1 ◽

2015 ◽

Vol 30 (6) ◽

pp. 1795-1817 ◽

Cited By ~ 61

Author(s):

Dustan M. Wheatley ◽

Kent H. Knopfmeier ◽

Thomas A. Jones ◽

Gerald J. Creager

Keyword(s):

Data Assimilation ◽

Leading Edge ◽

Radar Data ◽

Ensemble Forecasts ◽

Low Level ◽

The North ◽

Weather Events ◽

Probabilistic Forecasts ◽

Bow Echo ◽

System Part

Abstract 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.

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Short-Term Probabilistic Forecasts of the 31 May 2013 Oklahoma Tornado and Flash Flood Event Using a Continuous-Update-Cycle Storm-Scale Ensemble System

Weather and Forecasting ◽

10.1175/waf-d-15-0160.1 ◽

2016 ◽

Vol 31 (3) ◽

pp. 957-983 ◽

Cited By ~ 24

Author(s):

Nusrat Yussouf ◽

John S. Kain ◽

Adam J. Clark

Keyword(s):

Flash Flood ◽

Stage Iv ◽

Radar Data ◽

Precipitation Forecast ◽

Convective Precipitation ◽

Flood Event ◽

Forecast Period ◽

Low Level ◽

Probabilistic Forecasts ◽

The Impact

Abstract A continuous-update-cycle storm-scale ensemble data assimilation (DA) and prediction system using the ARW model and DART software is used to generate retrospective 0–6-h ensemble forecasts of the 31 May 2013 tornado and flash flood event over central Oklahoma, with a focus on the prediction of heavy rainfall. Results indicate that the model-predicted probabilities of strong low-level mesocyclones correspond well with the locations of observed mesocyclones and with the observed damage track. The ensemble-mean quantitative precipitation forecast (QPF) from the radar DA experiments match NCEP’s stage IV analyses reasonably well in terms of location and amount of rainfall, particularly during the 0–3-h forecast period. In contrast, significant displacement errors and lower rainfall totals are evident in a control experiment that withholds radar data during the DA. The ensemble-derived probabilistic QPF (PQPF) from the radar DA experiment is more skillful than the PQPF from the no_radar experiment, based on visual inspection and probabilistic verification metrics. A novel object-based storm-tracking algorithm provides additional insight, suggesting that explicit assimilation and 1–2-h prediction of the dominant supercell is remarkably skillful in the radar experiment. The skill in both experiments is substantially higher during the 0–3-h forecast period than in the 3–6-h period. Furthermore, the difference in skill between the two forecasts decreases sharply during the latter period, indicating that the impact of radar DA is greatest during early forecast hours. Overall, the results demonstrate the potential for a frequently updated, high-resolution ensemble system to extend probabilistic low-level mesocyclone and flash flood forecast lead times and improve accuracy of convective precipitation nowcasting.

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Near-Ground Wind Profiles of Tornadic and Nontornadic Environments in the United States and Europe from ERA5 Reanalyses

Weather and Forecasting ◽

10.1175/waf-d-20-0153.1 ◽

2020 ◽

Vol 35 (6) ◽

pp. 2621-2638

Author(s):

Brice E. Coffer ◽

Mateusz Taszarek ◽

Matthew D. Parker

Keyword(s):

United States ◽

Wind Profile ◽

Lower Troposphere ◽

The United States ◽

Objective Analysis ◽

Vertical Resolution ◽

Low Level ◽

Significant Control ◽

Severe Thunderstorms ◽

Wind Profiles

AbstractThe near-ground wind profile exhibits significant control over the organization, intensity, and steadiness of low-level updrafts and mesocyclones in severe thunderstorms, and thus their probability of being associated with tornadogenesis. The present work builds upon recent improvements in supercell tornado forecasting by examining the possibility that storm-relative helicity (SRH) integrated over progressively shallower layers has increased skill in differentiating between significantly tornadic and nontornadic severe thunderstorms. For a population of severe thunderstorms in the United States and Europe, sounding-derived parameters are computed from the ERA5 reanalysis, which has significantly enhanced vertical resolution compared to prior analyses. The ERA5 is shown to represent U.S. convective environments similarly to the Storm Prediction Center’s mesoscale surface objective analysis, but its greater number of vertical levels in the lower troposphere permits calculations to be performed over shallower layers. In the ERA5, progressively shallower layers of SRH provide greater discrimination between nontornadic and significantly tornadic thunderstorms in both the United States and Europe. In the United States, the 0–100 m AGL layer has the highest forecast skill of any SRH layer tested, although gains are comparatively modest for layers shallower than 0–500 m AGL. In Europe, the benefit from using shallower layers of SRH is even greater; the lower-tropospheric SRH is by far the most skillful ingredient there, far exceeding related composite parameters like the significant tornado parameter (which has negligible skill in Europe).

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Ensemble Probabilistic Prediction of a Mesoscale Convective System and Associated Polarimetric Radar Variables Using Single-Moment and Double-Moment Microphysics Schemes and EnKF Radar Data Assimilation

Monthly Weather Review ◽

10.1175/mwr-d-16-0162.1 ◽

2017 ◽

Vol 145 (6) ◽

pp. 2257-2279 ◽

Cited By ~ 12

Author(s):

Bryan J. Putnam ◽

Ming Xue ◽

Youngsun Jung ◽

Nathan A. Snook ◽

Guifu Zhang

Keyword(s):

Mesoscale Convective System ◽

Radar Data ◽

Convective Precipitation ◽

Convective System ◽

Ensemble Forecasts ◽

Verification Methods ◽

Probabilistic Forecasts ◽

Mesoscale Convective ◽

Single Moment ◽

Double Moment

Abstract Ensemble-based probabilistic forecasts are performed for a mesoscale convective system (MCS) that occurred over Oklahoma on 8–9 May 2007, initialized from ensemble Kalman filter analyses using multinetwork radar data and different microphysics schemes. Two experiments are conducted, using either a single-moment or double-moment microphysics scheme during the 1-h-long assimilation period and in subsequent 3-h ensemble forecasts. Qualitative and quantitative verifications are performed on the ensemble forecasts, including probabilistic skill scores. The predicted dual-polarization (dual-pol) radar variables and their probabilistic forecasts are also evaluated against available dual-pol radar observations, and discussed in relation to predicted microphysical states and structures. Evaluation of predicted reflectivity (Z) fields shows that the double-moment ensemble predicts the precipitation coverage of the leading convective line and stratiform precipitation regions of the MCS with higher probabilities throughout the forecast period compared to the single-moment ensemble. In terms of the simulated differential reflectivity (ZDR) and specific differential phase (KDP) fields, the double-moment ensemble compares more realistically to the observations and better distinguishes the stratiform and convective precipitation regions. The ZDR from individual ensemble members indicates better raindrop size sorting along the leading convective line in the double-moment ensemble. Various commonly used ensemble forecast verification methods are examined for the prediction of dual-pol variables. The results demonstrate the challenges associated with verifying predicted dual-pol fields that can vary significantly in value over small distances. Several microphysics biases are noted with the help of simulated dual-pol variables, such as substantial overprediction of KDP values in the single-moment ensemble.

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Investigating triggering mechanisms for the large hailstorm event of July 10th, 2019 on the Adriatic Sea

10.5194/egusphere-egu21-3662 ◽

2021 ◽

Author(s):

Antonio Ricchi ◽

Vincenzo Mazzarella ◽

Lorenzo Sangelantoni ◽

Gianluca Redaelli ◽

Rossella Ferretti

Keyword(s):

Adriatic Sea ◽

Initial Conditions ◽

Central Italy ◽

Radar Data ◽

Sensitivity Study ◽

Convective Cell ◽

Sea Surface ◽

Microphysics Scheme ◽

The Balkans ◽

The Impact

<div> A severe weather events hit Italy on July 9-10, 2019 causing heavy damages by the falling of large-size hail. A trough from Northern Europe affected Italy and the Balkans advecting cold air on the Adriatic Sea. The intrusion of relatively cold and dry air on the Adriatic Sea, in a first stage through the "Bora jets" generated by the Dinaric Alps gave rise to a frontal structure on the ground, which rapidly moved from North to South Adriatic. The large thermal gradient (also with the sea surface), the interaction with the complex orography and the coastal zone, generated several storm structures along the eastern Italian coast. In particular, on 10 July 2019 between 8UTC and 12UTC a deep convective cell (probably a supercell) developed along the coast North of the city of Pescara, producing intense rainfall (accumulated rainfall reaching 130 mm/3h) and a violent hailstorm with hailstones larger than 10 cm in diameter. The storm quickly moved southward, evolving into a complex multicellular structure clearly visible by observing radar data. In this work the frontal dynamics and the genesis of the storm cell are investigated using the numerical model WRF (Weather Research and Forecasting system). Numerical experiments are carried out using a 1 km grid on Central Italy, initialized using the ECMWF dataset and the Sea Surface Temperature (SST) taken by MFS-CMEMS Copernicus dataset. The sensitivity study investigated both the impact of the initial conditions, the quality and the anomaly of the SST on the Adriatic basin in those days. Furthermore, in order to quantify the importance of the use of different microphysics, Planetary boundary Layer (PBL) and radiative schemes, several experiments are performed. The role of orography in the development and location of the convective cell is also investigated. Preliminary results show that initialization and SST played a fundamental role. In particular, the initialization several hours before the event, coupled with a detailed SST allows to correctly reproduce the atmospheric fields. The microphysics scheme turned out to play a key role for this event by showing a significant greater impact than the PBL, in terms of frontal genesis on both the synoptic and local scale. </div>

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The Impact of Mixed-Phase Microphysical Processes on the Turbulence in Low-level Clouds in the Arctic

10.5194/egusphere-egu21-13693 ◽

2021 ◽

Author(s):

Jan Chylik ◽

Roel Neggers

Keyword(s):

Boundary Layer ◽

Climate Models ◽

Weather Forecast ◽

Mixed Phase ◽

The Arctic ◽

Contributing Factors ◽

Microphysics Scheme ◽

Low Level ◽

Microphysical Processes ◽

The Impact

The proper representation of Arctic mixed-phased clouds remains a challenge in both weather forecast and climate models. Amongst the contributing factors is the complexity of turbulent properties of clouds. While the effect of evaporating hydrometeors on turbulent properties of the boundary layer has been identified in other latitudes, the extent of similar studies in the Arctic has been so far limited.Our study focus on the impact of heat release from mixed-phase microphysical processes on the turbulent properties of the convective low-level clouds in the Arctic. We &#160;employ high-resolution simulations, properly constrained by relevant measurements. Semi-idealised model cases are based on convective clouds observed during the recent campaign in the Arctic: ACLOUD, which took place May--June 2017 over Fram Strait. The simulations are performed in Dutch Atmospheric Large Eddy Simulation (DALES) with double-moment mixed-phase microphysics scheme of Seifert & Beheng.The results indicate an enhancement of boundary layer turbulence is some convective regimes. Furthermore, results are sensitive to aerosols concentrations. Additional implications for the role of mixed-phase clouds in the Arctic Amplification will be discussed.

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Storm-Scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama

Monthly Weather Review ◽

10.1175/mwr-d-14-00268.1 ◽

2015 ◽

Vol 143 (8) ◽

pp. 3044-3066 ◽

Cited By ~ 46

Author(s):

Nusrat Yussouf ◽

David C. Dowell ◽

Louis J. Wicker ◽

Kent H. Knopfmeier ◽

Dustan M. Wheatley

Keyword(s):

Short Range ◽

Type System ◽

Severe Weather ◽

Forecast Errors ◽

Model Errors ◽

Ensemble Forecasts ◽

Low Level ◽

Design Storm ◽

Probabilistic Forecasts ◽

Arw Model

Abstract 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.

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Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress

Weather and Forecasting ◽

10.1175/waf-d-17-0145.1 ◽

2018 ◽

Vol 33 (2) ◽

pp. 599-607 ◽

Cited By ~ 20

Author(s):

John R. Lawson ◽

John S. Kain ◽

Nusrat Yussouf ◽

David C. Dowell ◽

Dustan M. Wheatley ◽

...

Keyword(s):

Data Assimilation ◽

Real Time ◽

Initial Conditions ◽

Spatial Scales ◽

Weather Prediction ◽

Radar Data ◽

Model Systems ◽

Deterministic Systems ◽

Forecast Lead Time ◽

The Impact

Abstract 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.

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Impact of Stochastically Perturbed Terminal Velocities on Convective-Scale Ensemble Forecasts of Precipitation

Advances in Meteorology ◽

10.1155/2020/4234361 ◽

2020 ◽

Vol 2020 ◽

pp. 1-18

Author(s):

Shizhang Wang ◽

Xiaoshi Qiao ◽

Jinzhong Min

Keyword(s):

Real Data ◽

Terminal Velocity ◽

Precipitation Forecast ◽

Ensemble Forecasts ◽

Microphysics Scheme ◽

Light Rain ◽

Hourly Precipitation ◽

Error Characteristics ◽

Convective Scale ◽

The Impact

The impact of stochastically perturbing the terminal velocities of hydrometeors on convective-scale ensemble forecasts of precipitation was examined. An idealized supercell storm case was first used to determine the terminal velocity error characteristics for a one-moment microphysics scheme in terms of the terminal velocities from a two-moment scheme. Two real cases were employed to evaluate the forecast skills resulting from perturbing the terminal velocities with real data. The results indicated that the one-moment scheme produced terminal velocities that were approximately three times higher than those of the two-moment scheme for snow and hail, which often resulted in overpredictions of hourly precipitation and areal accumulated precipitation. Therefore, stochastically perturbing the terminal velocities according to their error characteristics matched the observed hourly precipitation and areal accumulated precipitation better than the symmetrical perturbations. For the two-moment scheme, the symmetrical perturbations of the terminal velocities tended to produce lower falling speeds of precipitation hydrometeors; therefore, more light rain was produced. Compared to the unperturbed two-moment scheme, symmetrically perturbing the terminal velocities resulted in smaller precipitation errors when precipitation was overestimated but comparable or slightly larger precipitation errors when precipitation was underestimated. This work demonstrates the sensitivity of precipitation ensemble forecasts to terminal velocity perturbations and the potential benefits of adopting these perturbations; however, whether the perturbations actually result in significant improvements in precipitation forecast skill needs further study.

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Investigating triggering mechanisms for the large hailstorm event of July 10th, 2019 on the Adriatic Sea

10.5194/egusphere-egu2020-17847 ◽

2020 ◽

Author(s):

Antonio Ricchi ◽

Vincenzo mazzarella ◽

Lorenzo Sangelantoni ◽

Gianluca Redaelli ◽

Rossella Ferretti

Keyword(s):

Adriatic Sea ◽

Initial Conditions ◽

Central Italy ◽

Radar Data ◽

Sensitivity Study ◽

Convective Cell ◽

Sea Surface ◽

Microphysics Scheme ◽

The Balkans ◽

The Impact

A severe weather events hit Italy on July 9-10, 2019 causing heavy damages by the falling of large-size hail. A trough from Northern Europe affected Italy and the Balkans advecting cold air on the Adriatic Sea. The intrusion of relatively cold and dry air on the Adriatic Sea, in a first stage through the "Bora jets" generated by the Dinaric Alps gave rise to a frontal structure on the ground, which rapidly moved from North to South Adriatic. The large thermal gradient (also with the sea surface), the interaction with the complex orography and the coastal zone, generated several storm structures along the eastern Italian coast. &#160;In particular, on 10 July 2019 between 8UTC and 12UTC a deep convective cell (probably a supercell) developed along the coast North of the city of Pescara, producing intense rainfall (accumulated rainfall reaching 130 mm/3h) and a violent hailstorm with hailstones larger than 10 cm in diameter. The storm quickly moved southward, evolving into a complex multicellular structure clearly visible by observing radar data. &#160;In this work the frontal dynamics and the genesis of the storm cell are investigated using the numerical model WRF (Weather Research and Forecasting system). Numerical experiments are carried out using a 1 km grid on Central Italy, initialized using the ECMWF dataset and the Sea Surface Temperature (SST) taken by MFS-CMEMS Copernicus dataset. The sensitivity study investigated both the impact of the initial conditions, the quality and the anomaly of the SST on the Adriatic basin in those days. Furthermore, in order to quantify the importance of the use of different microphysics, Planetary boundary Layer (PBL) and radiative schemes, several experiments are performed. The role of orography in the development and location of the convective cell is also investigated. Preliminary results show that initialization and SST played a fundamental role. In particular, the initialization several hours before the event, coupled with a detailed SST allows to correctly reproduce the atmospheric fields. The microphysics scheme turned out to play a key role for this event by showing a significant greater impact than the PBL, in terms of frontal genesis on both the synoptic and local scale.

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