Thunderstorm Observations Research Articles

Observation‐Driven Characterization of Soil Moisture‐Precipitation Interactions in the Central United States

AbstractSoil moisture feedbacks that initiate, enhance, or suppress convection initiation and precipitation are important components of regional hydroclimatology. However, soil moisture feedbacks and the processes through which they operate are notoriously challenging to observe and study outside of model environments. In this study, we combine a climatological assessment of event frequency‐based measurements of soil moisture‐precipitation coupling in the central United States with a process‐based analysis of the mechanisms by which wet‐ and dry‐soil feedbacks may operate in the region. We use the Thunderstorm Observation by Radar algorithm to identify the location of convection initiation, circumventing the issue of using precipitation accumulation as a proxy for convection initiation. Results show substantial spatial variability in the climatological sign and strength of soil moisture‐precipitation coupling in the central United States, including regions that exhibit signs of both wet‐ and dry‐soil feedbacks. Within the regions with the strongest feedback signals, we find consistently strong coupling between soil moisture and the partitioning of surface heat flux, and strong coupling between surface heat flux—particularly sensible heat flux—and diurnal change in planetary boundary layer height. In all three regions assessed, the process‐based metrics confirmed the potential of wet‐ and/or dry‐soil feedbacks leading to convection initiation.

Assessment of the Impacts of Thunderstorm on Flight Operations at Murtala Mohammed International Airport, Ikeja, Lagos State, Nigeria

The inefficiency of the aviation industry and the persistent rise in aviation hazards have been linked to weather phenomena. As a result, researchers are looking for better solutions to the problem. The study examined the impact of thunderstorms on flight operations at Murtala Mohammed International Airport, Lagos. The data on thunderstorms and flight operations were sourced from Nigerian Meteorological Agency (NiMet) and Nigerian Airspace Management Agency (NAMA) respectively. In order to meet the research target, descriptive statistics (mean, standard deviation, and charts) and inferential statistics (Pearson’s Product Moment Correlation (PPMC) and Regression) were used. The significance level for all inferential analyses was set at 5% (0.05). The study revealed that 77.4% of thunderstorms occurred during the rainy season (April-October) while 22.6% occurred during the dry season (November-March). It also revealed some fluctuating movements of a thunderstorm in the study area. According to the findings, thunderstorms occur most frequently at the airport in June and less frequently in January and December. The study also discovered that thunderstorms at the airport are positively and significantly related to flight delays and cancellations, while the association between flight diversions and thunderstorm occurrence is positive but statistically insignificant. Furthermore, flight delays, flight diversions, and flight cancellations interact positively among themselves. The regression result of the study revealed that a 1% increase in thunderstorm occurrence leads to a 19.4% increase in flight delay, a 7.1% increase in flight cancellation, and a 4.3% increase in flight diversion. As a result, the study presented various regression models that may be utilized to make predictions. The study proposes consistent thunderstorm observation at the airport and steady forecasts using the regression models, based on the findings. However, it further recommends that pilots, air traffic controllers, and meteorologists be trained and retrained so that they can provide better and more efficient services.

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2

The Influence of WSR-88D Intra-Volume Scanning Strategies on Thunderstorm Observations and Warnings in the Dual-Polarization Radar Era: 2011–20

Abstract The Weather Surveillance Radar-1988 Doppler (WSR-88D) network has undergone several improvements in the last decade with the upgrade to dual-polarization capabilities and the ability for forecasters to rescan the lowest levels of the atmosphere more frequently through the use of Supplemental Adaptive Intra-volume Scanning (SAILS). SAILS reduces the revisit period for scanning the lowest 1 km of the atmosphere but comes at the cost of a longer delay between scans at higher altitudes. This study quantifies how often radar volume coverage patterns (VCPs) and all available SAILS options are used during the issuance of 148 882 severe thunderstorm and 18 263 tornado warnings, and near 10 474 tornado, 58 934 hail, and 127 575 wind reports in the dual-polarization radar era. A large majority of warnings and storm reports were measured with a VCP providing denser low-level sampling coverage. More frequent low-level updates were employed near tornado warnings and reports compared to severe thunderstorm warnings and hail or wind hazards. Warnings issued near a radar providing three extra low-level scans (SAILSx3) were more likely to be verified by a hazard with a positive lead time than warnings with fewer low-level scans. However, extra low-level scans were more frequently used in environments supporting organized convection as shown using watches issued by the Storm Prediction Center. In recent years, the number of midlevel radar elevation scans is declining per hour, which can adversely affect the tracking of convective polarimetric signatures, like ZDR columns, which were found above the lowest elevation angle in over 99% of cases examined.

Moist convection drives an upscale energy transfer at Jovian high latitudes

Jupiter’s atmosphere is one of the most turbulent places in the solar system. Whereas observations of lightning and thunderstorms point to moist convection as a small-scale energy source for Jupiter’s large-scale vortices and zonal jets, this has never been demonstrated due to the coarse resolution of pre-Juno measurements. The Juno spacecraft discovered that Jovian high latitudes host a cluster of large cyclones with diameter of around 5,000 km, each associated with intermediate- (roughly between 500 and 1,600 km) and smaller-scale vortices and filaments of around 100 km. Here, we analyse infrared images from Juno with a high resolution of 10 km. We unveil a dynamical regime associated with a significant energy source of convective origin that peaks at 100 km scales and in which energy gets subsequently transferred upscale to the large circumpolar and polar cyclones. Although this energy route has never been observed on another planet, it is surprisingly consistent with idealized studies of rapidly rotating Rayleigh–Bénard convection, lending theoretical support to our analyses. This energy route is expected to enhance the heat transfer from Jupiter’s hot interior to its troposphere and may also be relevant to the Earth’s atmosphere, helping us better understand the dynamics of our own planet.

Experimental analysis of carbon monoxide to establish the origin of dissolved gasses in water, and their role in weather anomalies

This study investigates carbon monoxide (CO) gas, to identify the impact it has on atmospheric anomalies (ATMAs). A variety of experimental tests were carried out with the heat, and pressure. Data obtained was analysed with the purpose of establishing clues to verify the fundamental characteristics of CO, highlighting it as being the most environmentally unfriendly gas in the atmosphere (ATM). This paper explores weather cycles, to connect the influence of CO, to extreme ATMAs, such as hurricanes, excessive rainfall, and high volumes of humidity on hot cloudless days. Observations of thunderstorms were explored to determine the effect of the sound given off by thunder, and its influence on the water vapour it comes into contact with. Our comprehension of climate change, leaves us, concluding that the volume of carbon dioxide (CO2) is way above natures required amount in the ATM, resulting in the warming of our planet. The purpose of this study is to highlight the characteristics of CO, and discuss how we should be addressing these issues, establishing a plan of action for combating global warming.

Cb‑Fusion – forecasting thunderstorm cells up to 6 hours

As a severe weather phenomenon, thunderstorms can cause casualties and economic loss to the human society. A reliable forecast of these weather events would help to avoid or at least mitigate this damage. To date, the forecasting of thunderstorms however is still a challenge, especially for lead times of one hour and beyond. In this study we present a methodology to forecast deep-convection for several hours lead time: Cb-Fusion estimates the likelihood of thunderstorm occurrence for up to 6 hours in advance over a part of Central Europe, using a data fusion technique that blends data of multiple sources from observations, nowcasts, and numerical weather predictions with a high update rate. The Cb-Fusion is set up to operate in near real time. The skill of Cb-Fusion is evaluated based on 1743 hours of thunderstorm observations collected during the months April to October, 2019. Three categories of thunderstorm size have been distinguished: ‘large’ for a coverage area larger than 5000 km2, ‘medium’ for a coverage area between 5000 km2 and 500 km2, and ‘small’ for a coverage area smaller than 500 km2. Compared to thunderstorm forecasts from numerical models alone, the combination of data from various sources by Cb-Fusion results in a significantly better forecast skill. The study reveals that the forecast is reliable for up to 3 hours lead time for ‘medium’ and ‘large’ scale thunderstorms (median POD of 0.6 – 0.9) but little skill is found for ‘small’ scale thunderstorms and lead times between 3 and 6 hours (median POD of 0.05). It is argued that Cb-Fusion provides meaningful improvements in forecasting thunderstorms for various users.

Understanding the dynamical-microphysical-electrical processes associated with severe thunderstorms over the Beijing metropolitan region

The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards (STORM973) project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region (BMR) during the warm season from 2014 to 2018. The aim of the project was to understand how dynamical, microphysical and electrical processes interact in severe thunderstorms in the BMR, and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts. The platforms used in the field campaign included the Beijing Lightning Network (BLNET, consisting of 16 stations), 2 X-band dual linear polarimetric Doppler radars, and 4 laser raindrop spectrometers. The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region. Although diverse thunderstorm types were documented, it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area, influenced by the terrain and environmental conditions. The flash density maximums were found in eastern Changping District, central and eastern Shunyi District, and the central urban area of Beijing, suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing. In addition, the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions. The super (5% of the total), strong (35%), and weak (60%) thunderstorms contributed about 37%, 56%, and 7% to the total flashes in the BMR, respectively. Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms, the lightning flash rate can be used as an indicator of severe weather events, such as hail and short-duration heavy rainfall. Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale, through adjusting or correcting the thermodynamic and microphysical parameters of the model.

Determining future thunderstorm-prone environments in Southern Ontario by using statistical downscaling to project changes in convective available potential energy (CAPE)

Considering the potential risks associated with thunderstorms, to date, there has been limited analysis on the projection of thunderstorm occurrence trends in Canada. The small spatial and temporal scales of thunderstorms are not resolved in global climate models (GCMs). In this study, the relationship is established between thunderstorm observations from nine weather stations across Southern Ontario, Canada, and daily maximum convective available potential energy (CAPE). The results from the correlation analysis between CAPE and thunderstorm days suggested that the probability of observing a thunderstorm increases as maximum daily CAPE increases. We then utilize the novel approach of applying statistical downscaling (SDSM) to CAPE. After regenerating CAPE over a 30-year reference period (1981–2010) at each weather station, it was determined that the SDSM-modeled CAPE values well compared to observed CAPE values. Future CAPE values up to the end of the current century are then projected using the SDSM models for each station in combination with three GCMs for future climate. The forecast from the downscaling suggested large increases, as much as tripling, in annual mean CAPE, summer mean CAPE, and number of days exceeding a 50% probability and 80% probability of observing a thunderstorm at all weather stations under SRES business-as-usual and RCP 8.5 scenarios for the study period of 2011–2100. All else being equal, this suggests an increase in the number of days with conditions favorable for thunderstorms under a warmer climate.

HO Generation Above Sprite‐Producing Thunderstorms Derived from Low‐Noise SMILES Observation Spectra

AbstractNo direct observational evidence of sprite‐produced active radicals has been presented owing to the difficulty of observing a small event area in the nighttime mesosphere, whereas sprite chemical models have indicated that sprite discharge locally affects the atmospheric composition. We present the first observational evidence of a HO production above sprite‐producing thunderstorms from the coincidence of temporal‐spatial observations of HO spectra, sprite events, and thunderstorms by two space instruments, a submillimeter‐wave limb spectrometer and ultraviolet/visible Imager and a ground‐based very low frequency radiation lightning detection network. A total of three areas was identified with enhanced HO levels of approximately 10 molecules. A chemical sprite model indicates an increase in HO in the considered altitude region; however, the predicted production due to a single sprite event is smaller than the observed enhancement. Our observational results suggest that sprites potentially contribute 1% of nighttime background HO generation at altitudes of 75–80 km globally.

A sensitivity study on the response of convection initiation to in situ soil moisture in the central United States

Soil moisture can affect precipitation, however there is significant debate about the sign and strength of land–atmosphere coupling. This may be due to the differences regarding the selection of data sources, the presence of atmospheric persistence, and the spatial and temporal scales of the analysis. This study is a sensitivity analysis that quantifies how each of these factors influences land–atmosphere coupling in the central United States from 2005 to 2007. Four different sources of soil moisture are used to represent soil moisture: in situ measurements and three satellite products. The Thunderstorm Observation by Radar (ThOR) algorithm is used to identify convective events. The results show that warm-season afternoon convection initiates preferentially over dry soil, if in situ measurements are used. However, when satellite data are used the sign and strength of the soil moisture-precipitation coupling varies depending on which satellite dataset is used. This demonstrates that evaluations of land–atmosphere coupling strength are sensitive to the source of soil moisture. Our results also show that accounting for atmospheric persistence tends to weaken apparent land–atmosphere coupling. Changing the spatial scale of the analysis can also influence the sign and coupling strength. Analyses that are performed at a coarser spatial resolution tend to indicate a wet preference because they do not capture the local negative feedbacks. This study demonstrates that contradictions in the literature regarding the sign and strength of soil moisture-precipitation feedbacks can be partly attributed to differences in datasets, methods and scale of the analysis.

Thunderstorm observations in Finland – historical observations since 1887

Thunderstorm observations in Finland – historical observations since 1887

Latitudinal and Longitudinal Variations of Earth’s Magnetic Force on Electrified Hydrometeors

In this study, a hypothesis is proposed about the possible effect of Geomagnetic field (GMF) on the charge structure of a thundercloud based on Lorentz force equation and Fleming’s right-hand rule. To prove this hypothesis, a simulation using the12th International Geomagnetic Reference Field (IGRF) model has been made. In this simulation, latitudinal and longitudinal variations of Earth’s magnetic force on electrified hydrometeor are considered. With regard to the simulation results, the electrified hydrometeor’ velocity vector is noteworthy to consider GMF effect on charge structure of thundercloud. Furthermore, the influence of GMF on charge separation could clarify the reason of some real thunderstorm observations. Finally, the effect of GMF on charge structure of thunderclouds might be a mechanism for electric field development and lightning initiation.

Application of the Warn‐on‐Forecast system for flash‐flood‐producing heavy convective rainfall events

AbstractThe vision of the National Oceanic and Atmospheric Administration's (NOAA) Warn‐on‐Forecast (WoF) research and development project is to provide very short‐term probabilistic model guidance products that will aid the ability of National Weather Service forecasters to issue probabilistic warnings of severe convective hazards with higher accuracy and longer lead times. The experimental Warn‐on‐Forecast System (WoFS), which is under development, is a frequently cycled, regional, convective‐scale, on‐demand, ensemble data assimilation and prediction system. The system assimilates thunderstorm observations to forecast the life cycle and associated hazards of individual convective storms. Most of the initial research effort, since the beginning of the WoF project in 2009, has been focused on tornadic events, which constitute one of the most violent and difficult to predict weather threats. However, the system emerging from this project has significant potential to help with prediction of other hazards as well: in particular, flash‐flood‐producing, convectively driven intense rainfall events. This study focuses on the application of WoFS in 0–6‐hr probabilistic rainfall forecasts of several flash‐flood‐producing heavy rainfall events during the spring and summer of 2015 and 2016. Results indicate that WoFS successfully initializes the convective storms in the ensemble. Visual inspections and probabilistic verification metrics show that WoFS predicts the intense rainfall that often leads to flash flooding at the correct location with higher accuracy in areal coverage and amount during the 0–3 hr forecast period than during the later 3–6 hr period. Overall results indicate that the frequently updated 0–6‐hr ensemble forecast from the WoFS has the potential to highlight areas where intense rainfall can result in flash flooding and increase near‐term situational awareness of flash flood threats.

Evaluating Soil Moisture–Precipitation Interactions Using Remote Sensing: A Sensitivity Analysis

Abstract The complex interactions between soil moisture and precipitation are difficult to observe, and consequently there is a lack of consensus as to the sign, strength, and location of these interactions. Inconsistency between soil moisture–precipitation interaction studies can be attributed to a multitude of factors, including the difficulty of demonstrating causal relationships, dataset differences, and precipitation autocorrelation. The purpose of this study is to explore these potential confounding factors and determine which are most important for consideration when assessing statistical coupling between soil moisture and precipitation. Soil moisture is assessed via three remote sensing datasets: the Advanced Microwave Scanning Radiometer for Earth Observing System, the Tropical Rainfall Measuring Mission Microwave Imager, and the Essential Climate Variable Soil Moisture. Estimates of soil moisture are coupled with afternoon thunderstorm events identified by the Thunderstorm Observation by Radar (ThOR) algorithm, and dry soil or wet soil preferences for convection initiation are determined for over 16 000 thunderstorm events between 2005 and 2007. Differences in soil moisture datasets were found to have the largest impact with regard to determining wet or dry soil preferences. Precipitation autocorrelation is prevalent in the data; however, precipitation autocorrelation did not influence the results with regard to dry or wet soil preferences. Consideration of the convective environment (i.e., weakly or synoptically forced) did result in significant differences in wet/dry soil preference, but only for certain soil moisture datasets. The results suggest that observation-driven soil moisture–precipitation interaction studies should both consider the convective environment and implement multiple soil moisture datasets to assure robust results.

Ensemble Sensitivity Analysis for Targeted Observations of Supercell Thunderstorms

Ensemble sensitivity analysis (ESA) has been demonstrated for observation targeting of synoptic-scale and mesoscale phenomena, but could have similar applications for storm-scale observations with mobile platforms. This paper demonstrates storm-scale ESA using an idealized supercell simulated with a 101-member CM1 ensemble. Correlation coefficients are used as a measure of sensitivity and are derived from single-variable and multivariable linear regressions of pressure, temperature, humidity, and wind with forecast response variables intended as proxies for the strength of supercells. This approach is suitable for targeting observing platforms that simultaneously measure multiple base-state variables. Although the individual correlations are found to be noisy and difficult to interpret, averaging across small areas of the domain and over the duration of the simulation is found to simplify the analysis. However, it is difficult to identify physically meaningful results from the sensitivity calculations, and evaluation of the results suggests that the overall skill would be low in targeting observations at the storm scale solely based on these sensitivity calculations. The difficulty in applying ESA at the scale of an individual supercell is likely due to applying the linear model to an environment with highly nonlinear dynamics, rapidly changing forecast metrics, and autocorrelation.

Aerogeodesis monitoring of potential areas of spontaneous combustion of the forest

The subject matter of the article is method for detecting potential zones of forest tracts spontaneous combustion using remote sensing data of the Earth. Aim of the article is to show how to increase the speed of decision-making to prevent negative consequences caused by spontaneous combustion of forest areas without a source of fire brought in from outside. The object of the research is a comprehensive analysis of the aerogeodesic monitoring data and contact measurements to identify and localize on the satellite images areas with high fire potential in the presence of a fire source directly in the territory of a possible fire. The methods used are the positions of general physics and higher geodesy, the basics of digital image processing and thematic interpretation. Results of research. The main factors affecting the process of autoignition of forest tracts are analyzed. A method of aerogeodetic monitoring, which is based on a map of thunderstorm activity, is presented. Method is based on remote observations of thunderstorms. At the same time, the map reflects the position of active thunderstorm cells in space and the projection of their coordinates on the geodetic map of the forest and is also a route for the purposeful search and elimination of local sources of fire. In order to be able to make quick decisions related to the prevention of negative consequences, an approach is used in which thunder cells are diagnosed for the purpose of assessing fire hazard by their ability to activate the process of origin of local sources of fire. In this case, we consider such controlled parameters as - the intensity of the electric field of the thunderstorm cell and the coordinates of its spatial position with respect to the forest area. Conclusion: to identify the origination of local sources of fire in the localization of possible autoignition zones, a relationship of thunderstorm clouds with the formation of the CCD was established. Aerogeodesic monitoring of the CCD is the basis for the operative estimates obtaining of the current object state of observation and prediction of the fire hazard level. The negative impact of forest fires on climate change, both local and global, is quite significant. Insufficient knowledge of this aspect requires further collection of material and its analysis, together with little-known "indirect" factors that cause spontaneous combustion of forest tracts and their individual sites.

A Review of Thunderstorm Trends across Southern Ontario, Canada

Despite their potential impact, trends in thunderstorm occurrence in Canada have not received scientific scrutiny, one of the reasons for this likely being lack of data availability. A previous study showed thunderstorm observations at eight staffed weather stations in southern Ontario, Canada, to be accurate for distances within 10 km. We used hourly thunderstorm data from these stations and one additional station to determine whether a trend exists in the thunderstorm record in this region. A Mann-Kendall test and Theil-Sen approach determined that although some stations do have trends in number of thunderstorm hours per year over this time, a consistent increase in the number of thunderstorms that might be expected in a warming climate is not seen. Daily precipitation totals and maximum wind gust speeds were also used as proxies for thunderstorm intensity, neither of which confirmed an increase in the intensity of thunderstorms at these sites over the time period.

Lightning Mapping Array flash detection performance with variable receiver thresholds.

This study characterizes Lightning Mapping Array performance for networks that participated in the Deep Convective Clouds and Chemistry field program using new Monte Carlo and curvature matrix model simulations. These open‐source simulation tools are readily adapted to real‐time operations or detailed studies of performance. Each simulation accounted for receiver threshold and location, as well as a reference distribution of source powers and flash sizes based on thunderstorm observations and the mechanics of station triggering. Source and flash detection efficiency were combined with solution bias and variability to predict flash area distortion at long ranges. Location errors and detection efficiency were highly dependent on the station configuration and thresholds, especially at longer ranges, such that performance varied more than expected across different networks and with azimuth within networks. Error characteristics matched prior studies, which led to an increase in flash distortion with range. Predicted flash detection efficiency exceeded 95% within 100 km of all networks.

Use of RegCM gridded dataset for thunderstorm favorable conditions analysis over Poland\u2014climatological approach

The paper analyzes equivalent data for a low density meteorological station network (spatially discontinuous data) and poor temporal homogeneity of thunderstorm observational data. Due to that, a Regional Climate Model (RegCM) dataset was tested. The Most Unstable Convective Available Potential Energy index value (MUCAPE) above the 200 J kg−1 threshold was selected as a predictor describing favorable conditions for the occurrence of thunderstorms. The quality of the dataset was examined through a comparison between model results and soundings from several aerological stations in Central Europe. Good, statistically significant (0.05 significance level) results were obtained through correlation analysis; the value of Pearson’s correlation coefficient was above 0.8 in every single case. Then, using methods associated with gridded climatology, data series for 44 weather stations were derived and an analysis of correlation between RegCM modeled data and in situ thunderstorm observations was conducted with coefficients in the range of 0.75–0.90. The possibility of employing the dataset in thunderstorm climatology analysis was checked via a few examples by mapping monthly, seasonal, and annual means. Moreover, long-term variability and trend analysis along with modeled MUCAPE data were tested. As a result, the RegCM modeled MUCAPE gridded dataset was proposed as an easily available, suitable, and valuable predictor for thunderstorm climatology analysis and mapping. Finally, some limitations are discussed and recommendations for further improvements are given.