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- Author or Editor: Jeffrey Beck x
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Abstract
The existing French Application Radar à la Météorologie Infrasynoptique (ARAMIS) operational radar network covers a vast majority of the country of France, yet like many national networks, gaps in coverage are present in regions of mountainous and high terrain. Many of these areas are prone to extreme, orography-induced precipitation events, and therefore expansion of national radar networks into these regions is very important. The addition of small X-band radars, strategically placed to supplement the ARAMIS network, is discussed with emphasis on the ability to expand three-dimensional wind and reflectivity field retrieval. This expanded coverage is particularly important for terrain-related precipitation in the southern Alps. Successful dual- and multiple-Doppler syntheses were conducted using the existing ARAMIS network and two new radars located in mountainous terrain, installed within the context of the Risques Hydrométéorologiques en Territoires de Montagnes et Mediterranéens (RHYTMME) program. To illustrate the coverage and advantage that gap-filling radars can add to an existing national radar network, two case studies are presented, with multiple-Doppler syntheses revealing that terrain relief and low-level atmospheric stability influence the resulting wind field. In addition to the added coverage, the RHYTMME gap-filling radars improve wind-flow retrieval and the accuracy of reflectivity measurements over extreme southeast France and into the Mediterranean Sea.
Abstract
The existing French Application Radar à la Météorologie Infrasynoptique (ARAMIS) operational radar network covers a vast majority of the country of France, yet like many national networks, gaps in coverage are present in regions of mountainous and high terrain. Many of these areas are prone to extreme, orography-induced precipitation events, and therefore expansion of national radar networks into these regions is very important. The addition of small X-band radars, strategically placed to supplement the ARAMIS network, is discussed with emphasis on the ability to expand three-dimensional wind and reflectivity field retrieval. This expanded coverage is particularly important for terrain-related precipitation in the southern Alps. Successful dual- and multiple-Doppler syntheses were conducted using the existing ARAMIS network and two new radars located in mountainous terrain, installed within the context of the Risques Hydrométéorologiques en Territoires de Montagnes et Mediterranéens (RHYTMME) program. To illustrate the coverage and advantage that gap-filling radars can add to an existing national radar network, two case studies are presented, with multiple-Doppler syntheses revealing that terrain relief and low-level atmospheric stability influence the resulting wind field. In addition to the added coverage, the RHYTMME gap-filling radars improve wind-flow retrieval and the accuracy of reflectivity measurements over extreme southeast France and into the Mediterranean Sea.
Abstract
Idealized supercell modeling has provided a wealth of information regarding the evolution and dynamics within supercell thunderstorms. However, discrepancies in conceptual models exist, including uncertainty regarding the existence, placement, and forcing of low-level boundaries in these storms, as well as their importance in low-level vorticity development. This study offers analysis of the origins of low-level boundaries and vertical vorticity within the low-level mesocyclone of a simulated supercell. Low-level boundary location shares similarities with previous modeling studies; however, the development and evolution of these boundaries differ from previous conceptual models. The rear-flank gust front develops first, whereas the formation of a boundary extending north of the mesocyclone undergoes numerous iterations caused by competing outflow and inflow before a steady-state boundary is produced. A third boundary extending northeast of the mesocyclone is produced through evaporative cooling of inflow air and develops last. Conceptual models for the simulation were created to demonstrate the evolution and structure of the low-level boundaries. Only the rear-flank gust front may be classified as a “gust front,” defined as having a strong wind shift, delineation between inflow and outflow air, and a strong pressure gradient across the boundary. Trajectory analyses show that parcels traversing the boundary north of the mesocyclone and the rear-flank gust front play a strong role in the development of vertical vorticity existing within the low-level mesocyclone. In addition, baroclinity near the rear-flank downdraft proves to be key in producing horizontal vorticity that is eventually tilted, providing a majority of the positive vertical vorticity within the low-level mesocyclone.
Abstract
Idealized supercell modeling has provided a wealth of information regarding the evolution and dynamics within supercell thunderstorms. However, discrepancies in conceptual models exist, including uncertainty regarding the existence, placement, and forcing of low-level boundaries in these storms, as well as their importance in low-level vorticity development. This study offers analysis of the origins of low-level boundaries and vertical vorticity within the low-level mesocyclone of a simulated supercell. Low-level boundary location shares similarities with previous modeling studies; however, the development and evolution of these boundaries differ from previous conceptual models. The rear-flank gust front develops first, whereas the formation of a boundary extending north of the mesocyclone undergoes numerous iterations caused by competing outflow and inflow before a steady-state boundary is produced. A third boundary extending northeast of the mesocyclone is produced through evaporative cooling of inflow air and develops last. Conceptual models for the simulation were created to demonstrate the evolution and structure of the low-level boundaries. Only the rear-flank gust front may be classified as a “gust front,” defined as having a strong wind shift, delineation between inflow and outflow air, and a strong pressure gradient across the boundary. Trajectory analyses show that parcels traversing the boundary north of the mesocyclone and the rear-flank gust front play a strong role in the development of vertical vorticity existing within the low-level mesocyclone. In addition, baroclinity near the rear-flank downdraft proves to be key in producing horizontal vorticity that is eventually tilted, providing a majority of the positive vertical vorticity within the low-level mesocyclone.
Abstract
Model verification has traditionally relied upon in situ observations, which typically exist on a sparse network, making nonsurface model forecast verification difficult. Given increasing model resolution, supplemental observational datasets are needed. Multiple-Doppler wind retrievals using a national network of radars provide an opportunity to assess the accuracy of wind forecasts at multiple levels, as well as verification within a three-dimensional domain. Wind speed and direction verification results are presented for a 9-day period of forecasts from the French Application of Research to Operations at Mesoscale-Western Mediterranean (AROME-WMED) model using multiple-Doppler retrievals from the French Application Radar à la Météorologie Infrasynoptique (ARAMIS) network. For the analyzed period, relationships were found that suggest that errors are not only linked to forecasted evolution of meteorological phenomena, but are sensitive to terrain height below the analyzed level as well as mesoscale processes. The spatial distribution of errors at initialization and forecast times shows that biases are generally independent of location and terrain height at initialization, but that the impact of terrain below the analysis level affects the forecasted wind magnitude and direction over time. These comparisons illustrate that multiple-Doppler wind retrieval measurements accurately identify model error and can serve as an invaluable dataset for model verification.
Abstract
Model verification has traditionally relied upon in situ observations, which typically exist on a sparse network, making nonsurface model forecast verification difficult. Given increasing model resolution, supplemental observational datasets are needed. Multiple-Doppler wind retrievals using a national network of radars provide an opportunity to assess the accuracy of wind forecasts at multiple levels, as well as verification within a three-dimensional domain. Wind speed and direction verification results are presented for a 9-day period of forecasts from the French Application of Research to Operations at Mesoscale-Western Mediterranean (AROME-WMED) model using multiple-Doppler retrievals from the French Application Radar à la Météorologie Infrasynoptique (ARAMIS) network. For the analyzed period, relationships were found that suggest that errors are not only linked to forecasted evolution of meteorological phenomena, but are sensitive to terrain height below the analyzed level as well as mesoscale processes. The spatial distribution of errors at initialization and forecast times shows that biases are generally independent of location and terrain height at initialization, but that the impact of terrain below the analysis level affects the forecasted wind magnitude and direction over time. These comparisons illustrate that multiple-Doppler wind retrieval measurements accurately identify model error and can serve as an invaluable dataset for model verification.
Abstract
On 29 May 2001, Doppler on Wheels radars collected data on a supercell near Kress, Texas. The supercellular storm, cyclic in nature, produced multiple mesocyclones throughout its lifetime. Dual-Doppler syntheses were conducted using a grid spacing of 100 m, resulting in the highest-resolution observational analysis of a cyclic supercell to date. In addition, collection of data from ground-based radar allowed for the analysis of near-ground features irresolvable with airborne radar, providing another advantage over previous studies. The syntheses revealed a number of evolving low-level mesocyclones over the observation period of 900 s. While nontornadic during the synthesis period, the supercell exhibited evidence of strong (vertical vorticity greater than 10−2 s−1) low-level circulation with classic cyclic structure and multiple tornadoes beginning 3600 s later. A comparison between the current results, conceptual models, and previous lower-resolution analyses is presented. A striking similarity exists between the cyclic evolution of the Kress storm during the synthesis time period and other previous cyclic conceptual models. However, differences did exist between the Kress storm and previously studied tornadic storms. Analysis showed that the rear-flank downdraft provided the only surface boundary associated with low-level mesocyclogenesis. Other characteristics, including forward-flank gust front structure and the orientation of low-level horizontal vorticity, also differed. In addition, there was a general lack of surface convergence associated with the forward-flank reflectivity gradient, yet convergence associated with the forward-flank gust front increased with height. Finally, a large component of crosswise horizontal vorticity was found to exist throughout the supercell environment, within both the inflow and outflow. Incorporating these differences, an attempt was made to identify possible mechanisms responsible for the lack of tornadogenesis during the synthesis time period.
Abstract
On 29 May 2001, Doppler on Wheels radars collected data on a supercell near Kress, Texas. The supercellular storm, cyclic in nature, produced multiple mesocyclones throughout its lifetime. Dual-Doppler syntheses were conducted using a grid spacing of 100 m, resulting in the highest-resolution observational analysis of a cyclic supercell to date. In addition, collection of data from ground-based radar allowed for the analysis of near-ground features irresolvable with airborne radar, providing another advantage over previous studies. The syntheses revealed a number of evolving low-level mesocyclones over the observation period of 900 s. While nontornadic during the synthesis period, the supercell exhibited evidence of strong (vertical vorticity greater than 10−2 s−1) low-level circulation with classic cyclic structure and multiple tornadoes beginning 3600 s later. A comparison between the current results, conceptual models, and previous lower-resolution analyses is presented. A striking similarity exists between the cyclic evolution of the Kress storm during the synthesis time period and other previous cyclic conceptual models. However, differences did exist between the Kress storm and previously studied tornadic storms. Analysis showed that the rear-flank downdraft provided the only surface boundary associated with low-level mesocyclogenesis. Other characteristics, including forward-flank gust front structure and the orientation of low-level horizontal vorticity, also differed. In addition, there was a general lack of surface convergence associated with the forward-flank reflectivity gradient, yet convergence associated with the forward-flank gust front increased with height. Finally, a large component of crosswise horizontal vorticity was found to exist throughout the supercell environment, within both the inflow and outflow. Incorporating these differences, an attempt was made to identify possible mechanisms responsible for the lack of tornadogenesis during the synthesis time period.
Abstract
The effect of wet radome attenuation is estimated on a French operational X-band weather radar deployed in the Maritime Alps of southeastern France. As the radar is deployed in a remote location, the reflectivity factor in the immediate vicinity of the radar is used as a proxy for rain rate at the radar and by extension, to the radome wetting. By means of intercomparison with a neighboring radar that lacks a radome, a wet radome correction is deduced. The correction is reasonably consistent with theoretical expectations and with other evaluations done, for example, via disdrometer. The improvement is evaluated by comparison to a Micro Rain Radar located under the point of comparison, and the impact on quantitative precipitation estimation (QPE) retrievals is positive. The intercomparison of such observations permits a routine means of monitoring radome attenuation.
Abstract
The effect of wet radome attenuation is estimated on a French operational X-band weather radar deployed in the Maritime Alps of southeastern France. As the radar is deployed in a remote location, the reflectivity factor in the immediate vicinity of the radar is used as a proxy for rain rate at the radar and by extension, to the radome wetting. By means of intercomparison with a neighboring radar that lacks a radome, a wet radome correction is deduced. The correction is reasonably consistent with theoretical expectations and with other evaluations done, for example, via disdrometer. The improvement is evaluated by comparison to a Micro Rain Radar located under the point of comparison, and the impact on quantitative precipitation estimation (QPE) retrievals is positive. The intercomparison of such observations permits a routine means of monitoring radome attenuation.
Abstract
A stochastically perturbed parameterization (SPP) approach that spatially and temporally perturbs parameters and variables in the Mellor–Yamada–Nakanishi–Niino planetary boundary layer scheme (PBL) and introduces initialization perturbations to soil moisture in the Rapid Update Cycle land surface model was developed within the High-Resolution Rapid Refresh convection-allowing ensemble. This work is a follow-up study to a work performed using the Rapid Refresh (RAP)-based ensemble. In the present study, the SPP approach was used to target the performance of precipitation and low-level variables (e.g., 2-m temperature and dewpoint, and 10-m wind). The stochastic kinetic energy backscatter scheme and the stochastic perturbation of physics tendencies scheme were combined with the SPP approach and applied to the PBL to target upper-level variable performance (e.g., improved skill and reliability). The three stochastic experiments (SPP applied to PBL only, SPP applied to PBL combined with SKEB and SPPT, and stochastically perturbed soil moisture initial conditions) were compared to a mixed-physics ensemble. The results showed a positive impact from initial condition soil moisture perturbations on precipitation forecasts; however, it resulted in an increase in 2-m dewpoint RMSE. The experiment with perturbed parameters within the PBL showed an improvement in low-level wind forecasts for some verification metrics. The experiment that combined the three stochastic approaches together exhibited improved RMSE and spread for upper-level variables. Our study demonstrated that, by using the SPP approach, forecasts of specific variables can be improved. Also, the results showed that using a single-physics suite ensemble with stochastic methods is potentially an attractive alternative to using multiphysics for convection allowing ensembles.
Abstract
A stochastically perturbed parameterization (SPP) approach that spatially and temporally perturbs parameters and variables in the Mellor–Yamada–Nakanishi–Niino planetary boundary layer scheme (PBL) and introduces initialization perturbations to soil moisture in the Rapid Update Cycle land surface model was developed within the High-Resolution Rapid Refresh convection-allowing ensemble. This work is a follow-up study to a work performed using the Rapid Refresh (RAP)-based ensemble. In the present study, the SPP approach was used to target the performance of precipitation and low-level variables (e.g., 2-m temperature and dewpoint, and 10-m wind). The stochastic kinetic energy backscatter scheme and the stochastic perturbation of physics tendencies scheme were combined with the SPP approach and applied to the PBL to target upper-level variable performance (e.g., improved skill and reliability). The three stochastic experiments (SPP applied to PBL only, SPP applied to PBL combined with SKEB and SPPT, and stochastically perturbed soil moisture initial conditions) were compared to a mixed-physics ensemble. The results showed a positive impact from initial condition soil moisture perturbations on precipitation forecasts; however, it resulted in an increase in 2-m dewpoint RMSE. The experiment with perturbed parameters within the PBL showed an improvement in low-level wind forecasts for some verification metrics. The experiment that combined the three stochastic approaches together exhibited improved RMSE and spread for upper-level variables. Our study demonstrated that, by using the SPP approach, forecasts of specific variables can be improved. Also, the results showed that using a single-physics suite ensemble with stochastic methods is potentially an attractive alternative to using multiphysics for convection allowing ensembles.
Abstract
A stochastic parameter perturbation (SPP) scheme consisting of spatially and temporally varying perturbations of uncertain parameters in the Grell–Freitas convective scheme and the Mellor–Yamada–Nakanishi–Niino planetary boundary scheme was developed within the Rapid Refresh ensemble system based on the Weather Research and Forecasting Model. Alone the stochastic parameter perturbations generate insufficient spread to be an alternative to the operational configuration that utilizes combinations of multiple parameterization schemes. However, when combined with other stochastic parameterization schemes, such as the stochastic kinetic energy backscatter (SKEB) scheme or the stochastic perturbation of physics tendencies (SPPT) scheme, the stochastic ensemble system has comparable forecast performance. An additional analysis quantifies the added value of combining SPP and SPPT over an ensemble that uses SPPT only, which is generally beneficial, especially for surface variables. The ensemble combining all three stochastic methods consistently produces the best spread–skill ratio and generally outperforms the multiphysics ensemble. The results of this study indicate that using a single-physics suite ensemble together with stochastic methods is an attractive alternative to multiphysics ensembles and should be considered in the design of future high-resolution regional and global ensembles.
Abstract
A stochastic parameter perturbation (SPP) scheme consisting of spatially and temporally varying perturbations of uncertain parameters in the Grell–Freitas convective scheme and the Mellor–Yamada–Nakanishi–Niino planetary boundary scheme was developed within the Rapid Refresh ensemble system based on the Weather Research and Forecasting Model. Alone the stochastic parameter perturbations generate insufficient spread to be an alternative to the operational configuration that utilizes combinations of multiple parameterization schemes. However, when combined with other stochastic parameterization schemes, such as the stochastic kinetic energy backscatter (SKEB) scheme or the stochastic perturbation of physics tendencies (SPPT) scheme, the stochastic ensemble system has comparable forecast performance. An additional analysis quantifies the added value of combining SPP and SPPT over an ensemble that uses SPPT only, which is generally beneficial, especially for surface variables. The ensemble combining all three stochastic methods consistently produces the best spread–skill ratio and generally outperforms the multiphysics ensemble. The results of this study indicate that using a single-physics suite ensemble together with stochastic methods is an attractive alternative to multiphysics ensembles and should be considered in the design of future high-resolution regional and global ensembles.
Abstract
The High-Resolution Rapid Refresh Ensemble (HRRRE) is a 36-member ensemble analysis system with 9 forecast members that utilizes the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) dynamic core and the physics suite from the operational Rapid Refresh/High-Resolution Rapid Refresh deterministic modeling system. A goal of HRRRE development is a system with sufficient spread among members, comparable in magnitude to the random error in the ensemble mean, to represent the range of possible future atmospheric states. HRRRE member diversity has traditionally been obtained by perturbing the initial and lateral boundary conditions of each member, but recent development has focused on implementing stochastic approaches in HRRRE to generate additional spread. These techniques were tested in retrospective experiments and in the May 2019 Hazardous Weather Testbed Spring Experiment (HWT-SE). Results show a 6%–25% increase in the ensemble spread in 2-m temperature, 2-m mixing ratio, and 10-m wind speed when stochastic parameter perturbations are used in HRRRE (HRRRE-SPP). Case studies from HWT-SE demonstrate that HRRRE-SPP performed similar to or better than the operational High-Resolution Ensemble Forecast system, version 2 (HREFv2), and the nonstochastic HRRRE. However, subjective evaluations provided by HWT-SE forecasters indicated that overall, HRRRE-SPP predicted lower probabilities of severe weather (using updraft helicity as a proxy) compared to HREFv2. A statistical analysis of the performance of HRRRE-SPP and HREFv2 from the 2019 summer convective season supports this claim, but also demonstrates that the two systems have similar reliability for prediction of severe weather using updraft helicity.
Abstract
The High-Resolution Rapid Refresh Ensemble (HRRRE) is a 36-member ensemble analysis system with 9 forecast members that utilizes the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) dynamic core and the physics suite from the operational Rapid Refresh/High-Resolution Rapid Refresh deterministic modeling system. A goal of HRRRE development is a system with sufficient spread among members, comparable in magnitude to the random error in the ensemble mean, to represent the range of possible future atmospheric states. HRRRE member diversity has traditionally been obtained by perturbing the initial and lateral boundary conditions of each member, but recent development has focused on implementing stochastic approaches in HRRRE to generate additional spread. These techniques were tested in retrospective experiments and in the May 2019 Hazardous Weather Testbed Spring Experiment (HWT-SE). Results show a 6%–25% increase in the ensemble spread in 2-m temperature, 2-m mixing ratio, and 10-m wind speed when stochastic parameter perturbations are used in HRRRE (HRRRE-SPP). Case studies from HWT-SE demonstrate that HRRRE-SPP performed similar to or better than the operational High-Resolution Ensemble Forecast system, version 2 (HREFv2), and the nonstochastic HRRRE. However, subjective evaluations provided by HWT-SE forecasters indicated that overall, HRRRE-SPP predicted lower probabilities of severe weather (using updraft helicity as a proxy) compared to HREFv2. A statistical analysis of the performance of HRRRE-SPP and HREFv2 from the 2019 summer convective season supports this claim, but also demonstrates that the two systems have similar reliability for prediction of severe weather using updraft helicity.
Abstract
A new hybrid, sigma-pressure vertical coordinate was recently added to the Weather Research and Forecasting (WRF) Model in an effort to reduce numerical noise in the model equations near complex terrain. Testing of this hybrid, terrain-following coordinate was undertaken in the WRF-based Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) models to assess impacts on retrospective and real-time simulations. Initial cold-start simulations indicated that the majority of differences between the hybrid and traditional sigma coordinate were confined to regions downstream of mountainous terrain and focused in the upper levels. Week-long retrospective simulations generally resulted in small improvements for the RAP, and a neutral impact in the HRRR when the hybrid coordinate was used. However, one possibility is that the inclusion of data assimilation in the experiments may have minimized differences between the vertical coordinates. Finally, analysis of turbulence forecasts with the new hybrid coordinate indicate a significant reduction in spurious vertical motion over the full length of the Rocky Mountains. Overall, the results indicate a potential to improve forecast metrics through implementation of the hybrid coordinate, particularly at upper levels, and downstream of complex terrain.
Abstract
A new hybrid, sigma-pressure vertical coordinate was recently added to the Weather Research and Forecasting (WRF) Model in an effort to reduce numerical noise in the model equations near complex terrain. Testing of this hybrid, terrain-following coordinate was undertaken in the WRF-based Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) models to assess impacts on retrospective and real-time simulations. Initial cold-start simulations indicated that the majority of differences between the hybrid and traditional sigma coordinate were confined to regions downstream of mountainous terrain and focused in the upper levels. Week-long retrospective simulations generally resulted in small improvements for the RAP, and a neutral impact in the HRRR when the hybrid coordinate was used. However, one possibility is that the inclusion of data assimilation in the experiments may have minimized differences between the vertical coordinates. Finally, analysis of turbulence forecasts with the new hybrid coordinate indicate a significant reduction in spurious vertical motion over the full length of the Rocky Mountains. Overall, the results indicate a potential to improve forecast metrics through implementation of the hybrid coordinate, particularly at upper levels, and downstream of complex terrain.
