scholarly journals Simulation of Polarimetric Radar Variables from 2013 CAPS Spring Experiment Storm-Scale Ensemble Forecasts and Evaluation of Microphysics Schemes

2016 ◽  
Vol 145 (1) ◽  
pp. 49-73 ◽  
Author(s):  
Bryan J. Putnam ◽  
Ming Xue ◽  
Youngsun Jung ◽  
Guifu Zhang ◽  
Fanyou Kong
Keyword(s):  
Mesoscale Convective System ◽  
Liquid Water Content ◽  
Convective System ◽  
Polarimetric Radar ◽  
Ensemble Forecasts ◽  
Direct Evaluation ◽  
Mesoscale Convective ◽  
Double Moment ◽  
Size Sorting ◽  
Radar Simulator

Abstract Polarimetric radar variables are simulated from members of the 2013 Center for Analysis and Prediction of Storms (CAPS) Storm-Scale Ensemble Forecasts (SSEF) with varying microphysics (MP) schemes and compared with observations. The polarimetric variables provide information on hydrometeor types and particle size distributions (PSDs), neither of which can be obtained through reflectivity (Z) alone. The polarimetric radar simulator pays close attention to how each MP scheme [including single- (SM) and double-moment (DM) schemes] treats hydrometeor types and PSDs. The recent dual-polarization upgrade to the entire WSR-88D network provides nationwide polarimetric observations, allowing for direct evaluation of the simulated polarimetric variables. Simulations for a mesoscale convective system (MCS) and supercell cases are examined. Five different MP schemes—Thompson, DM Milbrandt and Yau (MY), DM Morrison, WRF DM 6-category (WDM6), and WRF SM 6-category (WSM6)—are used in the ensemble forecasts. Forecasts using the partially DM Thompson and fully DM MY and Morrison schemes better replicate the MCS structure and stratiform precipitation coverage, as well as supercell structure compared to WDM6 and WSM6. Forecasts using the MY and Morrison schemes better replicate observed polarimetric signatures associated with size sorting than those using the Thompson, WDM6, and WSM6 schemes, in which such signatures are either absent or occur at abnormal locations. Several biases are suggested in these schemes, including too much wet graupel in MY, Morrison, and WDM6; a small raindrop bias in WDM6 and WSM6; and the underforecast of liquid water content in regions of pure rain for all schemes.

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

2017 ◽  
Vol 145 (6) ◽  
pp. 2257-2279 ◽  
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.

The Analysis and Prediction of Microphysical States and Polarimetric Radar Variables in a Mesoscale Convective System Using Double-Moment Microphysics, Multinetwork Radar Data, and the Ensemble Kalman Filter

2014 ◽  
Vol 142 (1) ◽  
pp. 141-162 ◽  
Author(s):  
Bryan J. Putnam ◽  
Ming Xue ◽  
Youngsun Jung ◽  
Nathan Snook ◽  
Guifu Zhang
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Cold Pool ◽  
Convective System ◽  
Polarimetric Radar ◽  
Microphysics Scheme ◽  
Mesoscale Convective ◽  
Double Moment

Abstract Doppler radar data are assimilated with an ensemble Kalman Filter (EnKF) in combination with a double-moment (DM) microphysics scheme in order to improve the analysis and forecast of microphysical states and precipitation structures within a mesoscale convective system (MCS) that passed over western Oklahoma on 8–9 May 2007. Reflectivity and radial velocity data from five operational Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars as well as four experimental Collaborative and Adaptive Sensing of the Atmosphere (CASA) X-band radars are assimilated over a 1-h period using either single-moment (SM) or DM microphysics schemes within the forecast ensemble. Three-hour deterministic forecasts are initialized from the final ensemble mean analyses using a SM or DM scheme, respectively. Polarimetric radar variables are simulated from the analyses and compared with polarimetric WSR-88D observations for verification. EnKF assimilation of radar data using a multimoment microphysics scheme for an MCS case has not previously been documented in the literature. The use of DM microphysics during data assimilation improves simulated polarimetric variables through differentiation of particle size distributions (PSDs) within the stratiform and convective regions. The DM forecast initiated from the DM analysis shows significant qualitative improvement over the assimilation and forecast using SM microphysics in terms of the location and structure of the MCS precipitation. Quantitative precipitation forecasting skills are also improved in the DM forecast. Better handling of the PSDs by the DM scheme is believed to be responsible for the improved prediction of the surface cold pool, a stronger leading convective line, and improved areal extent of stratiform precipitation.

Relationships between Lightning Location and Polarimetric Radar Signatures in a Small Mesoscale Convective System

2009 ◽  
Vol 137 (12) ◽  
pp. 4151-4170 ◽  
Author(s):  
Nicole R. Lund ◽  
Donald R. MacGorman ◽  
Terry J. Schuur ◽  
Michael I. Biggerstaff ◽  
W. David Rust
Keyword(s):  
Mesoscale Convective System ◽  
Convective System ◽  
Polarimetric Radar ◽  
Mature Phase ◽  
Mesoscale Convective ◽  
Mapping Array ◽  
Lightning Initiation ◽  
Convective Cells ◽  
Differential Reflectivity ◽  
Kinematic Properties

Abstract On 19 June 2004, the Thunderstorm Electrification and Lightning Experiment observed electrical, microphysical, and kinematic properties of a small mesoscale convective system (MCS). The primary observing systems were the Oklahoma Lightning Mapping Array, the KOUN S-band polarimetric radar, two mobile C-band Doppler radars, and balloonborne electric field meters. During its mature phase, this MCS had a normal tripolar charge structure (lightning involved a midlevel negative charge between an upper and a lower positive charge), and flash rates fluctuated between 80 and 100 flashes per minute. Most lightning was initiated within one of two altitude ranges (3–6 or 7–10 km MSL) and within the 35-dBZ contours of convective cells embedded within the convective line. The properties of two such cells were investigated in detail, with the first lasting approximately 40 min and producing only 12 flashes and the second lasting over an hour and producing 105 flashes. In both, lightning was initiated in or near regions containing graupel. The upper lightning initiation region (7–10 km MSL) was near 35–47.5-dBZ contours, with graupel inferred below and ice crystals inferred above. The lower lightning initiation region (3–6 km MSL) was in the upper part of melting or freezing layers, often near differential reflectivity columns extending above the 0°C isotherm, which is suggestive of graupel formation. Both lightning initiation regions are consistent with what is expected from the noninductive graupel–ice thunderstorm electrification mechanism, though inductive processes may also have contributed to initiations in the lower region.

scholarly journals Genesis of Hurricane Julia (2010) within an African Easterly Wave: Developing and Nondeveloping Members from WRF–LETKF Ensemble Forecasts

2014 ◽  
Vol 71 (7) ◽  
pp. 2763-2781 ◽  
Author(s):  
Stefan F. Cecelski ◽  
Da-Lin Zhang ◽  
Takemasa Miyoshi
Keyword(s):  
Surface Pressure ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Ensemble Forecasts ◽  
Upper Troposphere ◽  
African Easterly Wave ◽  
Easterly Wave ◽  
Mesoscale Convective ◽  
Rossby Radius Of Deformation ◽  
Faster Development

Abstract In this study, the predictability of and parametric differences in the genesis of Hurricane Julia (2010) are investigated using 20 mesoscale ensemble forecasts with the finest resolution of 1 km. Results show that the genesis of Julia is highly predictable, with all but two members undergoing genesis. Despite the high predictability, substantial parametric differences exist between the stronger and weaker members. Notably, the strongest-developing member exhibits large upper-tropospheric warming within a storm-scale outflow during genesis. In contrast, the nondeveloping member has weak and more localized warming due to inhibited convective development and a lack of a storm-scale outflow. A reduction in the Rossby radius of deformation in the strongest member aids in the accumulation of the warmth, while little contraction takes place in the nondeveloping member. The warming in the upper troposphere is responsible for the development of meso-α-scale surface pressure falls and a meso-β surface low in the strongest-developing member. Such features fail to form in the nondeveloping member as weak upper-tropospheric warming is unable to induce meaningful surface pressure falls. Cloud ice content is nearly doubled in the strongest member as compared to its nondeveloping counterparts, suggesting the importance of depositional heating of the upper troposphere. It is found that the stronger member undergoes genesis faster due to the lack of convective inhibition near the African easterly wave (AEW) pouch center prior to genesis. This allows for the faster development of a mesoscale convective system and storm-scale outflow, given the already favorable larger-scale conditions.

Ensemble Probabilistic Forecasts of a Tornadic Mesoscale Convective System from Ensemble Kalman Filter Analyses Using WSR-88D and CASA Radar Data

2012 ◽  
Vol 140 (7) ◽  
pp. 2126-2146 ◽  
Author(s):  
Nathan Snook ◽  
Ming Xue ◽  
Youngsun Jung
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Convective System ◽  
Ensemble Forecasts ◽  
Probabilistic Forecasts ◽  
Mesoscale Convective

Abstract This study examines the ability of a storm-scale numerical weather prediction (NWP) model to predict precipitation and mesovortices within a tornadic mesoscale convective system that occurred over Oklahoma on 8–9 May 2007, when the model is initialized from ensemble Kalman filter (EnKF) analyses including data from four Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) X-band and five Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars. Ensemble forecasts are performed and probabilistic forecast products generated, focusing on prediction of radar reflectivity (a proxy of quantitative precipitation) and mesovortices (an indication of tornado potential). Assimilating data from both the CASA and WSR-88D radars for the ensemble and using a mixed-microphysics ensemble during data assimilation produces the best probabilistic mesovortex forecast. The use of multiple microphysics schemes within the ensemble aims to address at least partially the model physics uncertainty and effectively plays a role of flow-dependent inflation (in precipitation regions) during EnKF data assimilation. The ensemble predicts with high probability (approximately 0.65) the near-surface mesovortex associated with the first of three reported tornadoes. Though a bias toward stronger precipitation is noted in the ensemble forecasts, all experiments produce skillful probabilistic forecasts of radar reflectivity on a 0–3-h time scale as evaluated by multiple probabilistic verification metrics. These results suggest that both the inclusion of CASA radar data and use of a mixed-microphysics ensemble during EnKF data assimilation positively impact the skill of 2–3-h ensemble forecasts of mesovortices, despite having little impact on the quality of precipitation forecasts (analyzed in terms of predicted radar reflectivity), and are important steps toward an operational EnKF-based ensemble analysis and probabilistic forecast system to support convective-scale warn-on-forecast operations.

The Hydrometeor Classification Algorithm for the Polarimetric WSR-88D: Description and Application to an MCS

2009 ◽  
Vol 24 (3) ◽  
pp. 730-748 ◽  
Author(s):  
Hyang Suk Park ◽  
A. V. Ryzhkov ◽  
D. S. Zrnić ◽  
Kyung-Eak Kim
Keyword(s):  
Fuzzy Logic ◽  
Classification Scheme ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Classification Algorithm ◽  
Convective System ◽  
Polarimetric Radar ◽  
The Matrix ◽  
Mesoscale Convective ◽  
Radar Measurements

Abstract This paper contains a description of the most recent version of the hydrometeor classification algorithm for polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). This version contains several modifications and refinements of the previous echo classification algorithm based on the principles of fuzzy logic. These modifications include the estimation of confidence factors that characterize the possible impacts of all error sources on radar measurements, the assignment of the matrix of weights that characterizes the classification power of each variable with respect to every class of radar echo, and the implementation of a class designation system based on the distance from the radar and the parameters of the melting layer that are determined as functions of azimuth with polarimetric radar measurements. These additions provide considerable flexibility and improve the discrimination between liquid and frozen hydrometeors. The new classification scheme utilizes all available polarimetric variables and discerns 10 different classes of radar echoes. Furthermore, a methodology for the new fuzzy logic classification scheme is discussed and the results are illustrated using polarimetric radar data collected with the Norman, Oklahoma (KOUN), WSR-88D prototype radar during a mesoscale convective system event on 13 May 2005.

scholarly journals Predictability and Dynamics of Warm-Core Mesoscale Vortex Formation with the 8 May 2009 “Super Derecho” Event

2017 ◽  
Vol 145 (3) ◽  
pp. 811-832 ◽  
Author(s):  
Caleb T. Grunzke ◽  
Clark Evans
Keyword(s):  
Vortex Formation ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Ensemble Forecasts ◽  
Low Level ◽  
Warm Core ◽  
Ensemble Adjustment Kalman Filter ◽  
Mesoscale Convective ◽  
Upper Level ◽  
Convection Initiation

The predictability and dynamics of the warm-core mesovortex associated with the northern flank of the 8 May 2009 “super derecho” event are examined by coupling the Advanced Research Weather Research and Forecasting Model with the ensemble adjustment Kalman filter implementation within the Data Assimilation Research Testbed facility. Cycled analysis started at 1200 UTC 2 May 2009, with observations assimilated every 6 h until 1200 UTC 7 May 2009, at which time a 50-member ensemble of 36-h convection-allowing ensemble forecasts were launched. The ensemble forecasts all simulated a mesoscale convective system, but only 7 out of 50 members produced a warm-core mesovortex-like feature similar in intensity to the observed mesovortex. Ensemble sensitivity and composite analyses were conducted to analyze the environmental differences between ensemble members. A more amplified upstream upper-level trough near the time of observed convection initiation is associated with a stronger simulated mesovortex. The amplification of the trough results in increases in the magnitudes of the low-level jet and thermal gradient. Consequently, more moisture is transported poleward into western Kansas, leading to earlier convection initiation in ensemble members with the strongest mesovortices. A circulation budget is performed on the ensemble members with the strongest (member 10) and weakest (member 5) time-averaged circulations. The ascending front-to-rear flow, descending rear-to-front flow, and divergent low-level flow of an MCS are more prominent in member 10, which is hypothesized to allow for the convergence of more background cyclonic absolute vorticity and, thus, facilitating the development of a stronger mesovortex.

scholarly journals Comprehensive Analysis of a Coast Thunderstorm That Produced a Sprite over the Bohai Sea

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 718
Author(s):  
Cong Pan ◽  
Jing Yang ◽  
Kun Liu ◽  
Yu Wang
Keyword(s):  
Bohai Sea ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Return Stroke ◽  
Absolute Value ◽  
Transient Luminous Events ◽  
Stratiform Region ◽  
Before And After ◽  
Mesoscale Convective ◽  
Cloud To Ground Lightning

Sprites are transient luminous events (TLEs) that occur over thunderstorm clouds that represent the direct coupling relationship between the troposphere and the upper atmosphere. We report the evolution of a mesoscale convective system (MCS) that produced only one sprite event, and the characteristics of this thunderstorm and the related lightning activity are analyzed in detail. The results show that the parent flash of the sprite was positive cloud-to-ground lightning (+CG) with a single return stroke, which was located in the trailing stratiform region of the MCS with a radar reflectivity of 25 to 35 dBZ. The absolute value of the negative CG (−CG) peak current for half an hour before and after the occurrence of the sprite was less than 50 kA, which was not enough to produce the sprite. Sprites tend to be produced early in the maturity-to-dissipation stage of the MCS, with an increasing percentage of +CG to total CG (POP), indicating that the sprite production was the attenuation of the thunderstorm and the area of the stratiform region.

Sign in / Sign up

Export Citation Format

Share Document