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

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).

2021 ◽  
Vol 13 (2) ◽  
pp. 827-856
Author(s):  
Jianfeng Li ◽  
Zhe Feng ◽  
Yun Qian ◽  
L. Ruby Leung

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).


2007 ◽  
Vol 22 (4) ◽  
pp. 813-838 ◽  
Author(s):  
Israel L. Jirak ◽  
William R. Cotton

Abstract Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.


2015 ◽  
Vol 30 (4) ◽  
pp. 892-913 ◽  
Author(s):  
James O. Pinto ◽  
Joseph A. Grim ◽  
Matthias Steiner

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.


2013 ◽  
Vol 14 (5) ◽  
pp. 1672-1682 ◽  
Author(s):  
Youcun Qi ◽  
Jian Zhang ◽  
Qing Cao ◽  
Yang Hong ◽  
Xiao-Ming Hu

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.


2003 ◽  
Vol 131 (8) ◽  
pp. 1939-1943
Author(s):  
David M. Brommer ◽  
Robert C. Balling ◽  
Randall S. Cerveny

Abstract In approximately half of Arizona's summer season (June–September) mesoscale convective systems evolve into mesoscale convective vortices (MCVs). Analysis of satellite imagery identified MCVs in Arizona over the period 1991–2000, and local and regional rawinsonde data discriminated conditions conducive for MCV development. These results indicate that MCVs are more likely to form from convective systems when the local and regional environments are characterized by relative stability in the 850–700-hPa layer and moderate wind shear in the 500–200-hPa layer. These characteristics are similar to results reported for MCV development in the central United States.


2015 ◽  
Vol 28 (12) ◽  
pp. 4890-4907 ◽  
Author(s):  
Xiangrong Yang ◽  
Jianfang Fei ◽  
Xiaogang Huang ◽  
Xiaoping Cheng ◽  
Leila M. V. Carvalho ◽  
...  

Abstract This study investigates mesoscale convective systems (MCSs) over China and its vicinity during the boreal warm season (May–August) from 2005 to 2012 based on data from the geostationary satellite Fengyun 2 (FY2) series. The authors classified and analyzed the quasi-circular and elongated MCSs on both large and small scales, including mesoscale convective complexes (MCCs), persistent elongated convective systems (PECSs), meso-β circular convective systems (MβCCSs), meso-β elongated convective system (MβECSs), and two additional types named small meso-β circular convective systems (SMβCCSs) and small meso-β elongated convective systems (SMβECSs). Results show that nearly 80% of the 8696 MCSs identified in this study fall into the elongated categories. Overall, MCSs occur mainly at three zonal bands with average latitudes around 20°, 30°, and 50°N. The frequency of MCSs occurrences is maximized at the zonal band around 20°N and decreases with increase in latitude. During the eight warm seasons, the period of peak systems occurrences is in July, followed decreasingly by June, August, and May. Meanwhile, from May to August three kinds of monthly variations are observed, which are clear northward migration, rapid increase, and persistent high frequency of MCS occurrences. Compared to MCSs in the United States, the four types of MCSs (MCCs, PECSs, MβCCSs, and MβECSs) are relatively smaller both in size and eccentricity but exhibit nearly equal life spans. Moreover, MCSs in both countries share similar positive correlations between their duration and maximum extent. Additionally, the diurnal cycles of MCSs in both countries are similar (local time) regarding the three stages of initiation, maturation, and termination.


Sign in / Sign up

Export Citation Format

Share Document