A warm season climatology of mesoscale convective systems in the Mediterranean basin using satellite data

2009 ◽  
Vol 102 (1-2) ◽  
pp. 29-42 ◽  
Author(s):  
Stavros Kolios ◽  
Haralambos Feidas
Keyword(s):  
Satellite Data ◽  
Mediterranean Basin ◽  
Warm Season ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
The Mediterranean ◽  
The Mediterranean Basin

scholarly journals Elucidating the Life Cycle of Warm-Season Mesoscale Convective Systems in Eastern China from the Himawari-8 Geostationary Satellite

2020 ◽  
Vol 12 (14) ◽  
pp. 2307
Author(s):  
Dandan Chen ◽  
Jianping Guo ◽  
Dan Yao ◽  
Zhe Feng ◽  
Yanluan Lin
Keyword(s):  
Life Cycle ◽  
Large Scale ◽  
Eastern China ◽  
Warm Season ◽  
Northern China ◽  
Early Morning ◽  
Geostationary Satellite ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Mesoscale Convective

The life cycle of mesoscale convective systems (MCSs) in eastern China is yet to be fully understood, mainly due to the lack of observations of high spatio-temporal resolution and objective methods. Here, we quantitatively analyze the properties of warm-season (from April to September of 2016) MCSs during their lifetimes using the Himawari-8 geostationary satellite, combined with ground-based radars and gauge measurements. Generally, the occurrence of satellite derived MCSs has a noon peak over the land and an early morning peak over the ocean, which is several hours earlier than the precipitation peak. The developing and dissipative stages are significantly longer as total durations of MCSs increase. Aided by three-dimensional radar mosaics, we find the fraction of convective cores over northern China is much lower when compared with those in central United States, indicating that the precipitation produced by broad stratiform clouds may be more important for northern China. When there exists a large amount of stratiform precipitation, it releases a large amount of latent heat and promotes the large-scale circulations, which favors the maintenance of MCSs. These findings provide quantitative results about the life cycle of warm-season MCSs in eastern China based on multiple data sources and large numbers of samples.

scholarly journals Characteristics of Mesoscale Convective Systems over China and Its Vicinity Using Geostationary Satellite FY2

2015 ◽  
Vol 28 (12) ◽  
pp. 4890-4907 ◽  
Author(s):  
Xiangrong Yang ◽  
Jianfang Fei ◽  
Xiaogang Huang ◽  
Xiaoping Cheng ◽  
Leila M. V. Carvalho ◽  
...  
Keyword(s):  
Warm Season ◽  
The United States ◽  
Geostationary Satellite ◽  
Mesoscale Convective Systems ◽  
Convective System ◽  
Convective Systems ◽  
Diurnal Cycles ◽  
Mesoscale Convective ◽  
Positive Correlations ◽  
Monthly Variations

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.

scholarly journals Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

2021 ◽  
Vol 118 (43) ◽  
pp. e2105260118
Author(s):  
Huancui Hu ◽  
L. Ruby Leung ◽  
Zhe Feng
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Land Surface ◽  
Warm Season ◽  
Summer Rainfall ◽  
Mesoscale Convective Systems ◽  
Rainfall Events ◽  
Convective Systems ◽  
Central United States ◽  
Mesoscale Convective

Land–atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture–precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture–precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. We find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture–precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

scholarly journals SAETTA: high-resolution 3-D mapping of the total lightning activity in the Mediterranean Basin over Corsica, with a focus on a mesoscale convective system event

2019 ◽  
Vol 12 (11) ◽  
pp. 5765-5790 ◽  
Author(s):  
Sylvain Coquillat ◽  
Eric Defer ◽  
Pierre de Guibert ◽  
Dominique Lambert ◽  
Jean-Pierre Pinty ◽  
...  
Keyword(s):  
High Altitude ◽  
Mediterranean Basin ◽  
Hot Spot ◽  
Mesoscale Convective System ◽  
Lightning Activity ◽  
Convective System ◽  
Stratiform Region ◽  
Mesoscale Convective ◽  
The Mediterranean ◽  
The Mediterranean Basin

Abstract. Deployed on the mountainous island of Corsica for thunderstorm monitoring purposes in the Mediterranean Basin, SAETTA is a network of 12 LMA (Lightning Mapping Array, designed by New Mexico Tech, USA) stations that allows the 3-D mapping of very high-frequency (VHF) radiation emitted by cloud discharges in the 60–66 MHz band. It works at high temporal (∼40 ns in each 80 µs time window) and spatial (tens of meters at best) resolution within a range of about 350 km. Originally deployed in May 2014, SAETTA was commissioned during the summer and autumn seasons and has now been permanently operational since April 2016 until at least the end of 2020. We first evaluate the performances of SAETTA through the radial, azimuthal, and altitude errors of VHF source localization with the theoretical model of Thomas et al. (2004). We also compute on a 240 km × 240 km domain the minimum altitude at which a VHF source can be detected by at least six stations by taking into account the masking effect of the relief. We then report the 3-year observations on the same domain in terms of number of lightning days per square kilometer (i.e., total number of days during which lightning has been detected in a given 1 km square pixel) and in terms of lightning days integrated across the domain. The lightning activity is first maximum in June because of daytime convection driven by solar energy input, but concentrates on a specific hot spot in July just above the intersection of the three main valleys. This hot spot is probably due to the low-level convergence of moist air fluxes from sea breezes channeled by the three valleys. Lightning activity increases again in September due to numerous small thunderstorms above the sea and to some high-precipitation events. Finally we report lightning observations of unusual high-altitude discharges associated with the mesoscale convective system of 8 June 2015. Most of them are small discharges on top of an intense convective core during convective surges. They are considered in the flash classification of Thomas et al. (2003) to be small–isolated and short–isolated flashes. The other high-altitude discharges, much less numerous, are long-range flashes that develop through the stratiform region and suddenly undergo upward propagations towards an uppermost thin layer of charge. This latter observation is apparently consistent with the recent conceptual model of Dye and Bansemer (2019) that explains such an upper-level layer of charge in the stratiform region by the development of a non-riming ice collisional charging in a mesoscale updraft.

Forecasting the Maintenance of Quasi-Linear Mesoscale Convective Systems

2007 ◽  
Vol 22 (3) ◽  
pp. 556-570 ◽  
Author(s):  
Michael C. Coniglio ◽  
Harold E. Brooks ◽  
Steven J. Weiss ◽  
Stephen F. Corfidi
Keyword(s):  
Convective Available Potential Energy ◽  
Warm Season ◽  
Value Added ◽  
Convective Cloud ◽  
Mesoscale Convective Systems ◽  
Linear Discriminant ◽  
Convective Systems ◽  
Shear Component ◽  
Mesoscale Convective ◽  
Deep Layers

Abstract The problem of forecasting the maintenance of mesoscale convective systems (MCSs) is investigated through an examination of observed proximity soundings. Furthermore, environmental variables that are statistically different between mature and weakening MCSs are input into a logistic regression procedure to develop probabilistic guidance on MCS maintenance, focusing on warm-season quasi-linear systems that persist for several hours. Between the mature and weakening MCSs, shear vector magnitudes over very deep layers are the best discriminators among hundreds of kinematic and thermodynamic variables. An analysis of the shear profiles reveals that the shear component perpendicular to MCS motion (usually parallel to the leading line) accounts for much of this difference in low levels and the shear component parallel to MCS motion accounts for much of this difference in mid- to upper levels. The lapse rates over a significant portion of the convective cloud layer, the convective available potential energy, and the deep-layer mean wind speed are also very good discriminators and collectively provide a high level of discrimination between the mature and dissipation soundings as revealed by linear discriminant analysis. Probabilistic equations developed from these variables used with short-term numerical model output show utility in forecasting the transition of an MCS with a solid line of 50+ dBZ echoes to a more disorganized system with unsteady changes in structure and propagation. This study shows that empirical forecast tools based on environmental relationships still have the potential to provide forecasters with improved information on the qualitative characteristics of MCS structure and longevity. This is especially important since the current and near-term value added by explicit numerical forecasts of convection is still uncertain.

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