scholarly journals Dynamic Ensemble Analysis of Frontal Placement Impacts in the Presence of Elevated Thunderstorms during PRECIP Events

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 339 ◽  
Author(s):  
Joshua Kastman ◽  
Patrick Market ◽  
Neil Fox
Keyword(s):  
Potential Energy ◽  
Convective Available Potential Energy ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Model Ensemble ◽  
Field Campaign ◽  
Cold Pools ◽  
Frontal Zones ◽  
Convective Inhibition ◽  
Ensemble Analysis

The Program for Research on Elevated Convection with Intense Precipitation (PRECIP) field campaign sampled 10 cases of elevated convection during 2014 and 2015. These intense observing periods (IOP) mostly featured well-defined stationary or warm frontal zones, over whose inversion elevated convection would form. However, not all frontal zones translated as expected, with some poleward motions being arrested and even returning equatorward. Prior analyses of the observed data highlighted the downdrafts in these events, especially diagnostics for their behavior: the downdraft convective available potential energy (DCAPE) and the downdraft convective inhibition (DCIN). With the current study, the DCAPE and DCIN are examined for four cases: two where frontal motion proceeded poleward, as expected, and two where the frontal motions were slowed significantly or stalled altogether. Using the Weather Research and Forecasting (WRF) model, a multi-model ensemble was created for each of the four cases, and the best performing members were selected for additional deterministic examination. Analyses of frontal motions and surface cold pools are explored in the context of DCAPE and DCIN. These analyses further establish the DCAPE and DCIN, not only as a means to classify elevated convection, but also to aid in explaining frontal motions in the presence of elevated convection.

scholarly journals Assessing the Effects of Microphysical Scheme on Convective and Stratiform Characteristics in a Mei-Yu Rainfall Combining WRF Simulation and Field Campaign Observations

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Lin Liu ◽  
Chunze Lin ◽  
Yongqing Bai ◽  
Dengxin He
Keyword(s):  
Wrf Model ◽  
Cloud Microphysics ◽  
Middle Level ◽  
Weather Research And Forecasting ◽  
Field Campaign ◽  
Microphysical Properties ◽  
Double Moment ◽  
Storm Dynamics ◽  
Precipitation Structure ◽  
Upper Level

Microphysics parameterization becomes increasingly important as the model grid spacing increases toward convection-resolving scales. Using observations from a field campaign for Mei-Yu rainfall in China, four bulk cloud microphysics schemes in the Weather Research and Forecasting (WRF) model were evaluated with respect to their ability to simulate precipitation, structure, and cloud microphysical properties over convective and stratiform regimes. These are the Thompson (THOM), Morrison graupel/hail (MOR_G/H), Stony Brook University (SBU_YLIN), and WRF double-moment six-class microphysics graupel/hail (WDM6_G/H). All schemes were able to predict the rain band but underestimated the total precipitation by 23%–35%. This is mainly attributed to the underestimation of stratiform precipitation and overestimation of convective rain. For the vertical distribution of radar reflectivity, many problems remain, such as lower reflectivity values aloft in both convective and stratiform regions and higher reflectivity values at middle level. Each bulk scheme has its advantages and shortcomings for different cloud regimes. Overall, the discrepancies between model output and observations mostly exist in the midlevel to upper level, which results from the inability of the model to accurately represent the particle size distribution, ice processes, and storm dynamics. Further observations from major field campaigns and more detailed evaluation are still necessary.

scholarly journals Should Reversible Convective Inhibition be Used when Determining the Inflow Layer of a Convective Storm?

2021 ◽  
Vol 78 (10) ◽  
pp. 3047-3067
Author(s):  
Shawn S. Murdzek ◽  
Paul M. Markowski ◽  
Yvette P. Richardson ◽  
Matthew R. Kumjian
Keyword(s):  
Potential Energy ◽  
Convective Available Potential Energy ◽  
Adiabatic Process ◽  
Convective Storm ◽  
Available Potential Energy ◽  
Convective Inhibition

AbstractConvective inhibition (CIN) is one of the parameters used by forecasters to determine the inflow layer of a convective storm, but little work has examined the best way to compute CIN. One decision that must be made is whether to lift parcels following a pseudoadiabat (removing hydrometeors as the parcel ascends) or reversible moist adiabat (retaining hydrometeors). To determine which option is best, idealized simulations of ordinary convection are examined using a variety of base states with different reversible CIN values for parcels originating in the lowest 500 m. Parcel trajectories suggest that ascent over the lowest few kilometers, where CIN is typically accumulated, is best conceptualized as a reversible moist adiabatic process instead of a pseudoadiabatic process. Most inflow layers do not contain parcels with substantial reversible CIN, despite these parcels possessing ample convective available potential energy and minimal pseudoadiabatic CIN. If a stronger initiation method is used, or hydrometeor loading is ignored, simulations can ingest more parcels with large amounts of reversible CIN. These results suggest that reversible CIN, not pseudoadiabatic CIN, is the physically relevant way to compute CIN and that forecasters may benefit from examining reversible CIN instead of pseudoadiabatic CIN when determining the inflow layer.

scholarly journals Modeling the Evolution and Life Cycle of Stable Cold Pools

2016 ◽  
Vol 31 (6) ◽  
pp. 1753-1769 ◽  
Author(s):  
Travis H. Wilson ◽  
Robert G. Fovell
Keyword(s):  
Relative Humidity ◽  
Wrf Model ◽  
Central Valley ◽  
Surface Fluxes ◽  
Weather Research And Forecasting ◽  
Near Surface ◽  
Cold Pools ◽  
Drainage Flows ◽  
Forested Region ◽  
Dry Bias

Abstract Stable cold pools in California’s Central Valley (CV) are conducive to freezing temperatures, high relative humidity, and, in some cases, fog. In this study it will be shown that the Weather Research and Forecasting (WRF) Model as commonly configured cannot reproduce such conditions because of a persistent warm and dry bias near the surface. It was found that removing horizontal diffusion, which by default operates on model levels and thus up and down the valley’s sides, can reduce but not entirely fix the problem. Other improvements include enhancing the near-surface vertical resolution and the surface–air coupling, as both directly control the surface fluxes, especially evaporation. However, these alterations actually have the largest impact in the forested region surrounding the Central Valley, and influence the nighttime relative humidity in the CV only indirectly via nocturnal drainage flows. While it is not clear how realistic are the increased evaporation in the forest or the drainage flows, how and why these alterations result in significantly improved relative humidity reconstructions within the Central Valley are shown.

scholarly journals Study of Pre-Monsoon Thunderstorms and Associated Thermodynamic Features Over Bangladesh Using WRF-ARW Model

2019 ◽  
Vol 67 (2) ◽  
pp. 151-156
Author(s):  
Pappu Paul ◽  
Ashik Imran ◽  
Md Jafrul Islam ◽  
Alamgir Kabir ◽  
Sahadat Jaman ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Potential Energy ◽  
Convective Available Potential Energy ◽  
Severe Thunderstorm ◽  
Available Potential Energy ◽  
K Index ◽  
Mesoscale System ◽  
Arw Model ◽  
Convective Inhibition ◽  
Wind Distribution

Thunderstorm is a mesoscale system (from a km to below thousands of km and sustaining less than one hour). Two pre-monsoon thunderstorms events are analyzed in this study which are named as event-1 (0030-0150 UTC of 19 April 2018 over Chattogram) and event-2 (0600-1000 UTC of 4 May 2018 over Dhaka). To predict these events Mean Convective Available Potential Energy (mCAPE), Mean Convective Inhibition Energy (mCINE), K Index (KI), Total totals Index (TTI), wind distribution, and relative humidity (RH) are investigated.The model simulated mCAPE and mCINE values, 18 hours before the events, are found greater than 1700 J/Kg and less than 100 J/Kg respectively which satisfies the conditions for thunderstorms to occur.The KI values are close to 400C and TTI values are greater or equal to 450C for both events. The wind patterns and the high value of mid –tropospheric RH also favors the formation of severe thunderstorm. Dhaka Univ. J. Sci. 67(2): 151-156, 2019 (July)

scholarly journals Role of Hamiltonian energy in thunderstorms

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 519-528
Author(s):  
G. K. SAWAISARJE ◽  
SOMENATH DUTTA ◽  
S. JAGTAP
Keyword(s):  
Free Convection ◽  
Potential Energy ◽  
Convective Available Potential Energy ◽  
Lower Troposphere ◽  
Air Mass ◽  
Available Potential Energy ◽  
Special Cases ◽  
Meteorological Observatory ◽  
Synoptic Conditions ◽  
Convective Inhibition

In the present study, we propose a hypothesis that “Hamiltonian energy of thunder storm is contributing towards the energy that overcomes convective inhibition energy to lift the parcel to the level of free convection and releases convective available potential energy in the environment”. We attempt to substantiate the hypothesis. We have applied Hamiltonian structure to a thundercloud which has occurred vertically above the meteorological observatory station. Further, a total of 62 cases of thunderstorms are selected for both stations Palam and Dumdum. Hamiltonian energy is computed and investigated the cases having significant large convective inhibition energy as compared to that of convective available potential energy. We attempt to show that Hamiltonian is the energy that overcomes convective inhibition energy to lift the parcel to the level of free convection and plays a major role in thunderstorms for giving rain.     Results reveal that Hamiltonian energy is seen to be maximum at the surface and contributes to both convective inhibition energy and convective available potential energy. At the lower troposphere, it overcomes the convective inhibition energy and provides necessary trigger for air mass to move from surface to the level of free convection. While in the upper troposphere, it is contributing to the convective available potential energy such that the part of potential energy converted into kinetic energy & warm and moist air mass (unstable) acceleration is enhanced by pressure energy.                          Further, in all the six special cases stability indices had indicated possibility of thunderstorm. In addition, synoptic conditions were also favorable for the same.   

scholarly journals The Unusual Early Morning Tornado in Ciudad Acuña, Coahuila, Mexico, on 25 May 2015

2017 ◽  
Vol 145 (6) ◽  
pp. 2049-2069 ◽  
Author(s):  
Bradford S. Barrett ◽  
Luis M. Farfán ◽  
Graciela B. Raga ◽  
Daribel H. Hernández
Keyword(s):  
Convective Available Potential Energy ◽  
Early Morning ◽  
Surface Flow ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Convective Activity ◽  
Supercell Thunderstorm ◽  
Convective Inhibition ◽  
Convection Initiation ◽  
The U.S

Abstract This study analyzes the synoptic- and mesoscale conditions present during initiation and intensification of the supercell thunderstorm that produced a tornado in Ciudad Acuña, a community located in the state of Coahuila, Mexico, 10 km southwest of the U.S. border. Early morning convective activity, first detected by radar at 0628 UTC 25 May 2015, developed into an intense and well-defined supercell thunderstorm that produced a tornado between approximately 1045 and 1130 UTC. Hourly analyses from the Rapid Refresh model indicated an upslope component to surface flow in the region of convection initiation over the Serranías del Burro (SdB). Along the storm’s trajectory, dewpoint temperatures increased from 15° to 22°C, convective available potential energy increased from 1500 to near 4000 J kg−1, and convective inhibition changed from −150 J kg−1 at the time of convection initiation to near zero in Ciudad Acuña. Simulations from the Weather Research and Forecasting Model confirmed the sensitivity of both convection initiation and storm intensification to the topography of the SdB. In the control simulation and two simulations in which topography was reduced in elevation, a cluster of storms formed and intensified over the central mountains. However, when topography was further reduced and the SdB region became a large flat plain, little convective activity was seen, forming only along the dryline without intensifying or propagating to the east as was observed.

scholarly journals Identifying the Sources of Convective Memory in Cloud-Resolving Simulations

2019 ◽  
Vol 76 (3) ◽  
pp. 947-962 ◽  
Author(s):  
Maxime Colin ◽  
Steven Sherwood ◽  
Olivier Geoffroy ◽  
Sandrine Bony ◽  
David Fuchs
Keyword(s):  
Time Scale ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Small Scale ◽  
Low Level ◽  
Cold Pools ◽  
Past Behavior ◽  
Convective Scale ◽  
Mean Fields ◽  
New Framework

AbstractConvection is often assumed to be controlled by the simultaneous environmental fields. But to what extent does it also remember its past behavior? This study proposes a new framework in which the memory of previous convective-scale behavior, “microstate memory,” is distinguished from macrostate memory, and conducts numerical experiments to reveal these memory types. A suite of idealized, cloud-resolving radiative–convective equilibrium simulations in a 200-km square domain is performed with the Weather Research and Forecasting (WRF) Model. Three deep convective cases are analyzed: unorganized, organized by low-level wind shear, and self-aggregated. The systematic responses to sudden horizontal homogenization of various fields, in various atmospheric layers, designed to eliminate their specific microstructure, are compared in terms of precipitation change and time of recovery to equilibrium. Results imply a substantial role for microstate memory. Across organization types, microstructure in water vapor and temperature has a larger and longer-lasting effect on convection than in winds or hydrometeors. Microstructure in the subcloud layer or the shallow cloud layer has more impact than in the free troposphere. The recovery time scale dramatically increases from unorganized (2–3 h) to organized cases (24 h or more). Longer-time-scale adjustments also occur and appear to involve both small-scale structures and domain-mean fields. These results indicate that most convective microstate memory is stored in low-level thermodynamic structures, potentially involving cold pools and hot thermals. This memory appears strongly enhanced by convective organization. Implications of these results for parameterizing convection are discussed.

scholarly journals The Mississippi Valley Convection Minimum on Summer Afternoons: Observations and Numerical Simulations

2015 ◽  
Vol 144 (1) ◽  
pp. 263-272 ◽  
Author(s):  
Daniel J. Kirshbaum ◽  
Frédéric Fabry ◽  
Quitterie Cazenave
Keyword(s):  
Numerical Simulations ◽  
Deep Convection ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Mississippi Valley ◽  
Convection Pattern ◽  
Lower Mississippi Valley ◽  
Radar Images ◽  
Convective Inhibition ◽  
Surrounding Areas

Abstract Analysis of 15 years of composite radar images over the continental United States reveals a distinct minimum of deep-convection occurrence over the interior lower Mississippi Valley on summer afternoons, relative to surrounding areas. To understand the mechanisms behind this convection signature, quasi-idealized numerical simulations with the Weather Research and Forecasting (WRF) Model are performed. The simulations, which broadly reproduce the valley convection minimum, suggest that convective inhibition is maximized, and low-level ascent minimized, over the flat valley terrain. By contrast, weaker inhibition and stronger mechanically forced ascent over the hills flanking the valley combine to initiate convection more readily. Although the orography of the region is unremarkable, it has a stronger influence on the regional convection pattern than do variations in land use.

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