The Convective Systems of the Euler Systems

2001 ◽  
pp. 227-233
Author(s):  
Yuxi Zheng
Keyword(s):  
Euler Systems ◽  
Convective Systems

A five-year climatological lightning characteristics of linear mesoscale convective systems over North China

2021 ◽  
Vol 256 ◽  
pp. 105580
Author(s):  
Dongxia Liu ◽  
Mengyu Sun ◽  
Debin Su ◽  
Wenjing Xu ◽  
Han Yu ◽  
...  
Keyword(s):  
North China ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Mesoscale Convective

scholarly journals An Observational Study of Mesoscale Convective Systems with Heavy Rainfall over the Korean Peninsula

2006 ◽  
Vol 21 (2) ◽  
pp. 125-148 ◽  
Author(s):  
Hyung Woo Kim ◽  
Dong Kyou Lee
Keyword(s):  
Observational Study ◽  
Korean Peninsula ◽  
Wind Shear ◽  
Heavy Rainfall ◽  
Vertical Wind Shear ◽  
Vertical Wind ◽  
Mesoscale Convective Systems ◽  
Low Level ◽  
Convective Systems ◽  
Mesoscale Convective

Abstract A heavy rainfall event induced by mesoscale convective systems (MCSs) occurred over the middle Korean Peninsula from 25 to 27 July 1996. This heavy rainfall caused a large loss of life and property damage as a result of flash floods and landslides. An observational study was conducted using Weather Surveillance Radar-1988 Doppler (WSR-88D) data from 0930 UTC 26 July to 0303 UTC 27 July 1996. Dominant synoptic features in this case had many similarities to those in previous studies, such as the presence of a quasi-stationary frontal system, a weak upper-level trough, sufficient moisture transportation by a low-level jet from a tropical storm landfall, strong potential and convective instability, and strong vertical wind shear. The thermodynamic characteristics and wind shear presented favorable conditions for a heavy rainfall occurrence. The early convective cells in the MCSs initiated over the coastal area, facilitated by the mesoscale boundaries of the land–sea contrast, rain–no rain regions, saturated–unsaturated soils, and steep horizontal pressure and thermal gradients. Two MCSs passed through the heavy rainfall regions during the investigation period. The first MCS initiated at 1000 UTC 26 July and had the characteristics of a supercell storm with small amounts of precipitation, the appearance of a mesocyclone with tilting storm, a rear-inflow jet at the midlevel of the storm, and fast forward propagation. The second MCS initiated over the upstream area of the first MCS at 1800 UTC 26 July and had the characteristics of a multicell storm, such as a broken areal-type squall line, slow or quasi-stationary backward propagation, heavy rainfall in a concentrated area due to the merging of the convective storms, and a stagnated cluster system. These systems merged and stagnated because their movement was blocked by the Taebaek Mountain Range, and they continued to develop because of the vertical wind shear resulting from a low-level easterly inflow.

scholarly journals Life cycle of midlatitude deep convective systems in a Lagrangian framework

2012 ◽  
Vol 117 (D23) ◽  
pp. n/a-n/a ◽  
Author(s):  
Zhe Feng ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Sally A. McFarlane ◽  
Aaron Kennedy ◽  
...  
Keyword(s):  
Life Cycle ◽  
Convective Systems ◽  
Lagrangian Framework ◽  
Deep Convective Systems

scholarly journals Thermal structure of intense convective clouds derived from GPS radio occultations

2012 ◽  
Vol 12 (12) ◽  
pp. 5309-5318 ◽  
Author(s):  
R. Biondi ◽  
W. J. Randel ◽  
S.-P. Ho ◽  
T. Neubert ◽  
S. Syndergaard
Keyword(s):  
Thermal Structure ◽  
Deep Convection ◽  
Lapse Rate ◽  
Orthogonal Polarization ◽  
Cold Temperatures ◽  
Temperature Lapse Rate ◽  
Convective Systems ◽  
Convective Clouds ◽  
Strong Inversion ◽  
Cloud Tops

Abstract. Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS occultations with CALIPSO profiles over deep convection. Results show a sharp spike in GPS bending angle highly correlated to the top of the clouds, corresponding to anomalously cold temperatures within the clouds. Above the clouds the temperatures return to background conditions, and there is a strong inversion at cloud top. For cloud tops below 14 km, the temperature lapse rate within the cloud often approaches a moist adiabat, consistent with rapid undiluted ascent within the convective systems.

NAM Model Forecasts of Warm-Season Quasi-Stationary Frontal Environments in the Central United States

2010 ◽  
Vol 25 (4) ◽  
pp. 1281-1292 ◽  
Author(s):  
Shih-Yu Wang ◽  
Adam J. Clark
Keyword(s):  
United States ◽  
Mesoscale Model ◽  
Convective Available Potential Energy ◽  
Warm Season ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Wind Fields ◽  
Vapor Flux ◽  
Convective Systems ◽  
Central United States

Abstract Using a composite procedure, North American Mesoscale Model (NAM) forecast and observed environments associated with zonally oriented, quasi-stationary surface fronts for 64 cases during July–August 2006–08 were examined for a large region encompassing the central United States. NAM adequately simulated the general synoptic features associated with the frontal environments (e.g., patterns in the low-level wind fields) as well as the positions of the fronts. However, kinematic fields important to frontogenesis such as horizontal deformation and convergence were overpredicted. Surface-based convective available potential energy (CAPE) and precipitable water were also overpredicted, which was likely related to the overprediction of the kinematic fields through convergence of water vapor flux. In addition, a spurious coherence between forecast deformation and precipitation was found using spatial correlation coefficients. Composite precipitation forecasts featured a broad area of rainfall stretched parallel to the composite front, whereas the composite observed precipitation covered a smaller area and had a WNW–ESE orientation relative to the front, consistent with mesoscale convective systems (MCSs) propagating at a slight right angle relative to the thermal gradient. Thus, deficiencies in the NAM precipitation forecasts may at least partially result from the inability to depict MCSs properly. It was observed that errors in the precipitation forecasts appeared to lag those of the kinematic fields, and so it seems likely that deficiencies in the precipitation forecasts are related to the overprediction of the kinematic fields such as deformation. However, no attempts were made to establish whether the overpredicted kinematic fields actually contributed to the errors in the precipitation forecasts or whether the overpredicted kinematic fields were simply an artifact of the precipitation errors. Regardless of the relationship between such errors, recognition of typical warm-season environments associated with these errors should be useful to operational forecasters.

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

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