scholarly journals Mesoscale convective systems in a superparameterized E3SM simulation at high resolution

2021 ◽  
Author(s):  
G. Lin ◽  
C. R. Jones ◽  
L.R. Leung ◽  
Z. Feng ◽  
M. Ovchinnikov
Keyword(s):  
High Resolution ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Mesoscale Convective

scholarly journals A high-resolution unified observational data product of mesoscale convective systems and isolated deep convection in the United States for 2004–2017

2021 ◽  
Vol 13 (2) ◽  
pp. 827-856
Author(s):  
Jianfeng Li ◽  
Zhe Feng ◽  
Yun Qian ◽  
L. Ruby Leung
Keyword(s):  
United States ◽  
High Resolution ◽  
Atmospheric Chemistry ◽  
Rocky Mountains ◽  
Deep Convection ◽  
The United States ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Data Product ◽  
Mesoscale Convective

Abstract. Deep convection possesses markedly distinct properties at different spatiotemporal scales. We present an original high-resolution (4 km, hourly) unified data product of mesoscale convective systems (MCSs) and isolated deep convection (IDC) in the United States east of the Rocky Mountains and examine their climatological characteristics from 2004 to 2017. The data product is produced by applying an updated Flexible Object Tracker algorithm to hourly satellite brightness temperature, radar reflectivity, and precipitation datasets. Analysis of the data product shows that MCSs are much larger and longer-lasting than IDC, but IDC occurs about 100 times more frequently than MCSs, with a mean convective intensity comparable to that of MCSs. Hence both MCS and IDC are essential contributors to precipitation east of the Rocky Mountains, although their precipitation shows significantly different spatiotemporal characteristics. IDC precipitation concentrates in summer in the Southeast with a peak in the late afternoon, while MCS precipitation is significant in all seasons, especially for spring and summer in the Great Plains. The spatial distribution of MCS precipitation amounts varies by season, while diurnally, MCS precipitation generally peaks during nighttime except in the Southeast. Potential uncertainties and limitations of the data product are also discussed. The data product is useful for investigating the atmospheric environments and physical processes associated with different types of convective systems; quantifying the impacts of convection on hydrology, atmospheric chemistry, and severe weather events; and evaluating and improving the representation of convective processes in weather and climate models. The data product is available at https://doi.org/10.25584/1632005 (Li et al., 2020).

scholarly journals A high-resolution unified observational data product of mesoscale convective systems and isolated deep convection in the United States for 2004–2017

2020 ◽  
Author(s):  
Jianfeng Li ◽  
Zhe Feng ◽  
Yun Qian ◽  
L. Ruby Leung
Keyword(s):  
United States ◽  
High Resolution ◽  
Atmospheric Chemistry ◽  
Rocky Mountains ◽  
Deep Convection ◽  
The United States ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Data Product ◽  
Mesoscale Convective

Abstract. Deep convection possesses markedly distinct properties at different spatiotemporal scales. We present an original high-resolution (4 km, hourly) unified data product of mesoscale convective systems (MCSs) and isolated deep convection (IDC) in the United States east of the Rocky Mountains and examine their climatological characteristics from 2004 to 2017. The data product is produced by applying an updated FLEXTRKR (Flexible Object Tracker) algorithm to hourly satellite brightness temperature, radar reflectivity, and precipitation datasets. Analysis of the data product shows that MCSs are much larger and longer-lasting than IDC, but IDC occurs about 100 times more frequently than MCSs, with a mean convective intensity comparable to that of MCSs. Hence both MCS and IDC are essential contributors to precipitation east of the Rocky Mountains, although their precipitation shows significantly different spatiotemporal characteristics. IDC precipitation concentrates in summer in the Southeast with a peak in the late afternoon, while MCS precipitation is significant in all seasons, especially for spring and summer in the Great Plains. The spatial distribution of MCS precipitation amounts varies by seasons, while diurnally, MCS precipitation generally peaks during nighttime except in the Southeast. Potential uncertainties and limitations of the data product are also discussed. The data product is useful for investigating the atmospheric environments and physical processes associated with different types of convective systems, quantifying the impacts of convection on hydrology, atmospheric chemistry, and severe weather events, and evaluating and improving the representation of convective processes in weather and climate models. The data product is available at https://doi.org/10.25584/1632005 (Li et al., 2020).

scholarly journals Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

2020 ◽  
Vol 21 (2) ◽  
pp. 317-334
Author(s):  
Jingjing Tian ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng
Keyword(s):  
High Resolution ◽  
Spatial Variability ◽  
Great Plains ◽  
Mesoscale Convective Systems ◽  
Spatiotemporal Variability ◽  
Convective Systems ◽  
Ice Cloud ◽  
Convective Core ◽  
Mesoscale Convective ◽  
Ice Water

AbstractIn this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

scholarly journals Assessment of the High-Resolution Rapid Refresh Model’s Ability to Predict Mesoscale Convective Systems Using Object-Based Evaluation

2015 ◽  
Vol 30 (4) ◽  
pp. 892-913 ◽  
Author(s):  
James O. Pinto ◽  
Joseph A. Grim ◽  
Matthias Steiner
Keyword(s):  
United States ◽  
High Resolution ◽  
Size Distribution ◽  
Great Plains ◽  
Southeastern United States ◽  
Mesoscale Convective Systems ◽  
Eastern United States ◽  
Convective Systems ◽  
Object Based ◽  
Mesoscale Convective

Abstract An object-based verification technique that keys off the radar-retrieved vertically integrated liquid (VIL) is used to evaluate how well the High-Resolution Rapid Refresh (HRRR) predicted mesoscale convective systems (MCSs) in 2012 and 2013. It is found that the modeled radar VIL values are roughly 50% lower than observed. This mean bias is accounted for by reducing the radar VIL threshold used to identify MCSs in the HRRR. This allows for a more fair evaluation of the model’s skill at predicting MCSs. Using an optimized VIL threshold for each summer, it is found that the HRRR reproduces the first (i.e., counts) and second moments (i.e., size distribution) of the observed MCS size distribution averaged over the eastern United States, as well as their aspect ratio, orientation, and diurnal variations. Despite threshold optimization, the HRRR tended to predict too many (few) MCSs at lead times less (greater) than 4 h because of lead time–dependent biases in the modeled radar VIL. The HRRR predicted too many MCSs over the Great Plains and too few MCSs over the southeastern United States during the day. These biases are related to the model’s tendency to initiate too many MCSs over the Great Plains and too few MCSs over the southeastern United States. Additional low biases found over the Mississippi River valley region at night revealed a tendency for the HRRR to dissipate MCSs too quickly. The skill of the HRRR at predicting specific MCS events increased between 2012 and 2013, coinciding with changes in both the model physics and in the methods used to assimilate the three-dimensional radar reflectivity.

scholarly journals Correction of Radar QPE Errors for Nonuniform VPRs in Mesoscale Convective Systems Using TRMM Observations

2013 ◽  
Vol 14 (5) ◽  
pp. 1672-1682 ◽  
Author(s):  
Youcun Qi ◽  
Jian Zhang ◽  
Qing Cao ◽  
Yang Hong ◽  
Xiao-Ming Hu
Keyword(s):  
High Resolution ◽  
Vertical Direction ◽  
Tropical Rainfall Measuring Mission ◽  
The United States ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Quantitative Precipitation Estimation ◽  
Stratiform Region ◽  
Precipitation Estimation ◽  
Mesoscale Convective

Abstract Mesoscale convective systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) is often found in the stratiform region. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE). A vertical profile of reflectivity (VPR) correction is necessary to reduce such biases. However, existing VPR correction methods for ground-based radars often perform poorly for MCSs owing to their coarse resolution and poor coverage in the vertical direction, especially at far ranges. Spaceborne radars such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), on the other hand, can provide high resolution VPRs. The current study explores a new approach of incorporating the TRMM VPRs into the VPR correction for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar QPE. High-resolution VPRs derived from the Ku-band TRMM PR data are converted into equivalent S-band VPRs using an empirical technique. The equivalent S-band TRMM VPRs are resampled according to the WSR-88D beam resolution, and the resampled (apparent) VPRs are then used to correct for BB effects in the WSR-88D QPE when the ground radar VPR cannot accurately capture the BB bottom. The new scheme was tested on six MCSs from different regions in the United States and it was shown to provide effective mitigation of the radar QPE errors due to BB contamination.

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.

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