Application of total-lightning data assimilation in a mesoscale convective system based on the WRF model

2014 ◽  
Vol 145-146 ◽  
pp. 255-266 ◽  
Author(s):  
Xiushu Qie ◽  
Runpeng Zhu ◽  
Tie Yuan ◽  
Xueke Wu ◽  
Wanli Li ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Wrf Model ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Mesoscale Convective ◽  
Total Lightning

scholarly journals Evaluation of Different Storm Parameters as the Proxies for Gridded Total Lightning Flash Rates: A Convection-Allowing Model Study

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 95
Author(s):  
Xinyao Qian ◽  
Haoliang Wang
Keyword(s):  
Data Assimilation ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Skill Score ◽  
Convective System ◽  
Test Case ◽  
Lightning Flash ◽  
Simulation Accuracy ◽  
Mesoscale Convective ◽  
Total Lightning

Lightning simulation is important for a variety of applications, including lightning forecast, atmospheric chemical simulation, and lightning data assimilation. In this study, the potential of five storm parameters (graupel volume, precipitation ice mass, radar echo volume, maximum updraft, and updraft volume) to be used as the proxy for the diagnosis of gridded total lightning flash rates has been investigated in a convection-allowing model. A mesoscale convective system occurred in the Guangdong province of China was selected as the test case. Radar data assimilation was used to improve the simulation accuracy of the convective clouds, hence providing strong instantaneous correlations between observed and simulated storm signatures. The areal coverage and magnitude of the simulated lightning flash rates were evaluated by comparing to those of the total lightning observations. Subjective and the Fractions Skill Score (FSS) evaluations suggest that all the five proxies tested in this study are useful to indicate general tendencies for the occurrence, region, and time of lightning at convection-allowing scale (FSS statistics for the threshold of 1 flash per 9 km2 per hour were around 0.7 for each scheme). The FSS values were decreasing as the lightning flash rate thresholds used for FSS computation increased for all the lightning diagnostic schemes with different proxies. For thresholds from 1 to 3 and 16 to 20 flashes per 9 km2 per hour, the graupel contents related schemes achieved higher FSS values compared to the other three schemes. For thresholds from 5 to 15 flashes per 9 km2 per hour, the updraft volume related scheme yielded the largest FSS. When the thresholds of lightning flash rates were greater than 13 flashes per 9 km2 per hour, the FSS values were below 0.5 for all the lightning diagnostic schemes with different proxies.

scholarly journals Diagnosing Convective Dependencies on Near-Storm Environments Using Ensemble Sensitivity Analyses

2019 ◽  
Vol 147 (2) ◽  
pp. 495-517 ◽  
Author(s):  
Christopher A. Kerr ◽  
David J. Stensrud ◽  
Xuguang Wang
Keyword(s):  
Wind Shear ◽  
Initial Conditions ◽  
Wrf Model ◽  
Vertical Wind Shear ◽  
Mesoscale Convective System ◽  
Vertical Wind ◽  
Sensitivity Analyses ◽  
Convective System ◽  
Mesoscale Convective ◽  
Storm Evolution

AbstractConvection intensity and longevity is highly dependent on the surrounding environment. Ensemble sensitivity analysis (ESA), which quantitatively and qualitatively interprets impacts of initial conditions on forecasts, is applied to very short-term (1–2 h) convective-scale forecasts for three cases during the Mesoscale Predictability Experiment (MPEX) in 2013. The ESA technique reveals several dependencies of individual convective storm evolution on their nearby environments. The three MPEX cases are simulated using a previously verified 36-member convection-allowing model (Δx = 3 km) ensemble created via the Weather Research and Forecasting (WRF) Model. Radar and other conventional observations are assimilated using an ensemble adjustment Kalman filter. The three cases include a mesoscale convective system (MCS) and both nontornadic and tornadic supercells. Of the many ESAs applied in this study, one of the most notable is the positive sensitivity of supercell updraft helicity to increases in both storm inflow region deep and shallow vertical wind shear. This result suggests that larger values of vertical wind shear within the storm inflow yield higher values of storm updraft helicity. Results further show that the supercell storms quickly enhance the environmental vertical wind shear within the storm inflow region. Application of ESA shows that these storm-induced perturbations then affect further storm evolution, suggesting the presence of storm–environment feedback cycles where perturbations affect future mesocyclone strength. Overall, ESA can provide insight into convection dependencies on the near-storm environment.

scholarly journals Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI EnKF for the Analysis and Short-Term Forecast of a Mesoscale Convective System

2020 ◽  
Vol 148 (5) ◽  
pp. 2111-2133 ◽  
Author(s):  
Rong Kong ◽  
Ming Xue ◽  
Alexandre O. Fierro ◽  
Youngsun Jung ◽  
Chengsi Liu ◽  
...  
Keyword(s):  
Mesoscale Convective System ◽  
Convective System ◽  
Lightning Flash ◽  
Moist Convection ◽  
State Variables ◽  
Short Term ◽  
Pixel Resolution ◽  
Cross Covariance ◽  
Mesoscale Convective ◽  
Total Lightning

Abstract The recently launched Geostationary Operational Environmental Satellite “R-series” (GOES-R) satellites carry the Geostationary Lightning Mapper (GLM) that measures from space the total lightning rate in convective storms at high spatial and temporal frequencies. This study assimilates, for the first time, real GLM total lightning data in an ensemble Kalman filter (EnKF) framework. The lightning flash extent density (FED) products at 10-km pixel resolution are assimilated. The capabilities to assimilate GLM FED data are first implemented into the GSI-based EnKF data assimilation (DA) system and tested with a mesoscale convective system (MCS). FED observation operators based on graupel mass or graupel volume are used. The operators are first tuned through sensitivity experiments to determine an optimal multiplying factor to the operator, before being used in FED DA experiments FEDM and FEDV that use the graupel-mass or graupel-volume-based operator, respectively. Their results are compared to a control experiment (CTRL) that does not assimilate any FED data. Overall, both DA experiments outperform CTRL in terms of the analyses and short-term forecasts of FED and composite/3D reflectivity. The assimilation of FED is primarily effective in regions of deep moist convection, which helps improve short-term forecasts of convective threats, including heavy precipitation and lightning. Direct adjustments to graupel mass via observation operator as well as adjustments to other model state variables through flow-dependent ensemble cross covariance within EnKF are shown to work together to generate model-consistent analyses and overall improved forecasts.

scholarly journals Evaluation of a Cloud-Scale Lightning Data Assimilation Technique and a 3DVAR Method for the Analysis and Short-Term Forecast of the 29 June 2012 Derecho Event

2014 ◽  
Vol 142 (1) ◽  
pp. 183-202 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Jidong Gao ◽  
Conrad L. Ziegler ◽  
Edward R. Mansell ◽  
Donald R. MacGorman ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Computational Cost ◽  
Mesoscale Convective System ◽  
Radar Reflectivity ◽  
Convective System ◽  
Variational Technique ◽  
Short Term ◽  
Short Term Forecast ◽  
Term Forecast ◽  
Mesoscale Convective

Abstract This work evaluates the short-term forecast (≤6 h) of the 29–30 June 2012 derecho event from the Advanced Research core of the Weather Research and Forecasting Model (WRF-ARW) when using two distinct data assimilation techniques at cloud-resolving scales (3-km horizontal grid). The first technique assimilates total lightning data using a smooth nudging function. The second method is a three-dimensional variational technique (3DVAR) that assimilates radar reflectivity and radial velocity data. A suite of sensitivity experiments revealed that the lightning assimilation was better able to capture the placement and intensity of the derecho up to 6 h of the forecast. All the simulations employing 3DVAR, however, best represented the storm’s radar reflectivity structure at the analysis time. Detailed analysis revealed that a small feature in the velocity field from one of the six selected radars in the original 3DVAR experiment led to the development of spurious convection ahead of the parent mesoscale convective system, which significantly degraded the forecast. Thus, the relatively simple nudging scheme using lightning data complements the more complex variational technique. The much lower computational cost of the lightning scheme may permit its use alongside variational techniques in improving severe weather forecasts on days favorable for the development of outflow-dominated mesoscale convective systems.

scholarly journals Nocturnal Convection Initiation during PECAN 2015

2019 ◽  
Vol 100 (11) ◽  
pp. 2223-2239 ◽  
Author(s):  
Tammy M. Weckwerth ◽  
John Hanesiak ◽  
James W. Wilson ◽  
Stanley B. Trier ◽  
Samuel K. Degelia ◽  
...  
Keyword(s):  
Great Plains ◽  
Current Knowledge ◽  
Wrf Model ◽  
Mesoscale Convective System ◽  
Convective System ◽  
University Of Oklahoma ◽  
Different Types ◽  
Mesoscale Convective ◽  
Convection Initiation ◽  
The University

AbstractNocturnal convection initiation (NCI) is more difficult to anticipate and forecast than daytime convection initiation (CI). A major component of the Plains Elevated Convection at Night (PECAN) field campaign in the U.S. Great Plains was to intensively sample NCI and its near environment. In this article, we summarize NCI types observed during PECAN: 1 June–16 July 2015. These NCI types, classified using PECAN radar composites, are associated with 1) frontal overrunning, 2) the low-level jet (LLJ), 3) a preexisting mesoscale convective system (MCS), 4) a bore or density current, and 5) a nocturnal atmosphere lacking a clearly observed forcing mechanism (pristine). An example and description of each of these different types of PECAN NCI events are presented. The University of Oklahoma real-time 4-km Weather Research and Forecasting (WRF) Model ensemble forecast runs illustrate that the above categories having larger-scale organization (e.g., NCI associated with frontal overrunning and NCI near a preexisting MCS) were better forecasted than pristine. Based on current knowledge and data from PECAN, conceptual models summarizing key environmental features are presented and physical processes underlying the development of each of these different types of NCI events are discussed.

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