Inter-Zone Differences of Convective Development in a Convection Outbreak Event over Southeastern Coast of China: An Observational Analysis

Among the densely-populated coastal areas of China, the southeastern coast has received less attention in convective development despite having been suffering from significantly increasing thunderstorm activities. The convective complexity under such a region with extremely complex underlying and convective conditions deserves in-depth observational surveys. This present study examined a high-impact convection outbreak event with over 40 hail reports in the southeastern coast of China on 6 May 2020 by focusing on contrasting the convective development (from convective initiation to supercell occurrences) among three adjacent convection-active zones (north (N), middle (M), and south (S)). The areas from N to S featured overall flatter terrain, higher levels of free convection, lower relative humidity, larger convective inhibition, more convective available potential energy, and greater vertical wind shears. With these mesoscale environmental variations, distinct inter-zone differences in the convective development were observed with the region’s surveillance radar network and the Himawari-8 geostationary satellite. Convection initiated in succession from N to S and began with more warm-rain processes in N and M and more ice-phase processes in S. The subsequent convection underwent more vigorous vertical growth from N to S. The extremely deep convection in S was characterized by the considerably strong precipitation above the freezing level, echo tops of up to 18 km, and a great amount of deep (even overshooting) and thick convective clouds with significant cloud-top glaciation. Horizontal anvil expansion in convective clouds was uniquely apparent over S. From N to S, more pronounced mesocyclone and weak-echo region signatures indicated high risks of severe supercell hailstorms. These results demonstrate the strong linkage between the occurrence likelihood of severe convection and associated weather (such as supercells and hailstones) and the early-stage convective development that can be well-captured by high-resolution observations and may facilitate fine-scale convection nowcasting.

The severe thunderstorm of 5th April, 2010 at Guwahati airport : An observational study

During the afternoon of 5th April, 2010, a thunderstorm swept across Guwahati Airport (Lat. 26º26´, Long 91º35´) and neighborhood from northwest direction. Strong squally winds (reaching up to 49 knots) and high intensity rain (11mm in 15 minutes) were registered accompanying the storm. One person was killed by the falling tree due to squally winds and several others were injured by the event. The observed evolution of temperature, humidity, wind and pressure at Guwahati Airport, as well as the sequence of satellite and radar images, revealed the presence and movement of convective cells. An observational analysis of the event has been given in this paper. The aim of the study is to contribute to the characterization of these events by analyzing the observational information available. The diagnosis is aimed at helping forecasters to identify this kind of organized deep convective events and being able to issue timely warnings. The synoptic scenario shows warm and moist advection from the Bay of Bengal in low levels over Northeastern region of India and an upper-level north-south trough running from Sub-Himalayan West Bengal to north Orissa. This situation is known to be favorable for development of severe convection over Northeastern region of India during pre-monsoon season.

New Perspectives on Ensemble Sensitivity Analysis with Applications to a Climatology of Severe Convection

Ensemble sensitivity analysis (ESA) is a statistical technique applied within an ensemble to reveal the atmospheric flow features that relate to a chosen aspect of the flow. Given its ease of use (it is simply a linear regression between a chosen function of the forecast variables and the entire atmospheric state earlier or simultaneously in time), ensemble sensitivity has been the focus of several studies over roughly the last ten years. Such studies have primarily tried to understand the relevant dynamics and/or key precursors of high-impact weather events. Other applications of ESA have been more operationally oriented, including observation targeting within data assimilation systems and real-time adjustment techniques that attempt to utilize both sensitivity information and observations to improve forecasts.While ESA has gained popularity, its fundamental properties remain a substantially underutilized basis for realizing the technique’s full scientific potential. For example, the relationship between ensemble sensitivity and the pure dynamics of the system can teach us how to appropriately apply various sensitivity-based applications, and combining sensitivity with other ensemble properties such as spread can distinguish between a fluid dynamics problem and a predictability one. This work aims to present new perspectives on ensemble sensitivity, and clarify its fundamentals, with the hopes of making it a more accessible, attractive, and useful tool in the atmospheric sciences. These new perspectives are applied in part to a short climatology of severe convection forecasts to demonstrate the unique knowledge that can gained through broadened use of ESA.

Environmental Evolution of Long-Lived Supercell Thunderstorms in the Great Plains

Long-lived supercells (containing mesocyclones persisting for at least 4 hours) are relatively rare, but present significant risk for society as a result of their intensity and associated hazards over an extended time period. The persistence of a rotating updraft is tied to near-storm environmental characteristics; however, given the established prevalence of mesoscale environmental heterogeneity near severe convection, it is unknown to what extent those near-storm characteristics vary over the lifetime of a supercell, nor how quickly the storm responds to such changes. This study examines 147 long-lived, isolated supercells, focusing on the evolution of their near-storm environments using model analysis soundings generated each hour throughout the storm’s lifetime. Environmental variability is quantified via a series of common forecasting parameters, with impacts of measured changes related to production of severe weather and overall storm longevity. The diurnal and maturity-relative distributions of forecasting parameters are examined, along with comparisons among subsets of marginally vs. very long-lived supercells, as well as dissipation before vs. after sunset. The diurnal cycle is a dominant trend over the lifetime of all supercells, with attendant impacts to relevant thermodynamic and kinematic parameters, timing of storm initiation and dissipation, as well as severe weather production. Notably, changes in the near-storm environment are connected to supercell longevity and generation of severe weather reports. The long-term goal of the above analyses is to enhance short-term forecasts of supercells by better anticipating storm evolution as a result of environmental variations.

Examining Terrain Effects on an Upstate New York Tornado Event Utilizing a High-Resolution Model Simulation

The complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

XGB+FM for Severe Convection Forecast and Factor Selection

In the field of meteorology, radiosonde data and observation data are critical for analyzing regional meteorological characteristics. Because of the high false alarm rate, severe convection forecasting is still challenging. In addition, the existing methods are difficult to use to capture the interaction of meteorological factors at the same time. In this research, a cascade of extreme gradient boosting (XGBoost) for feature transformation and a factorization machine (FM) for second-order feature interaction to capture the nonlinear interaction—XGB+FM—is proposed. An attention-based bidirectional long short-term memory (Att-Bi-LSTM) network is proposed to impute the missing data of meteorological observation stations. The problem of class imbalance is resolved by the support vector machines–synthetic minority oversampling technique (SVM-SMOTE), in which two oversampling strategies based on the support vector discrimination mechanism are proposed. It is proven that the method is effective, and the threat score (TS) is 7.27~14.28% higher than other methods. Moreover, we propose the meteorological factor selection method based on XGB+FM and improve the forecast accuracy, which is one of our contributions, as well as the forecast system.