bluuebunny/crossref_metadata_2025 huggingface dataset:
thundeR - a rawinsonde package for processing convective parameters and visualizing atmospheric profiles
Authors: Taszarek Mateusz , Czernecki Bartosz , Szuster Piotr
Published: March 2023

ThundeR is a freeware R language package for sounding and hodograph visualization, and rapid computation of convective parameters commonly used in the research and operational prediction of severe convective storms. Core algorithm is based on C++ code seamlessly integrated into the R language within the RCPP library. This solution allows to compute a large number of thermodynamic and kinematic parameters within hundredths of a second per atmospheric profile. Such performance enables to process large numerical datasets such as reanalyses or weather prediction models for the research and operational purposes. ThundeR package has been developed since 2017 and is constantly updated with new features and parameters following requests from the community and the most up to date research findings on severe storm environments. The most recent version of the package (v1.1) allows users to calculate 201 parameters, manually specify mixing and altitude of a convective parcel, input a manual storm motion vector, and control plotting of CAPE, CIN, DCAPE and SRH polygons. An online tool available at www.rawinsonde.com allows users to use thundeR package in visualizing rawinsonde measurements and historical atmospheric profiles from ERA5 reanalysis since 1950. As of January 2023, thundeR package has been used in more than 20 peer-reviewed studies.
The Northern Tornadoes Project – Shifting the Post-Event Paradigm in Canada
Authors: Sills David , Kopp Gregory
Published: March 2023

The Northern Tornadoes Project (NTP) was founded in 2017 at Canada's Western University, supported by social impact fund ImpactWX, with the aim of better detecting tornado occurrence, improving severe and extreme weather prediction, mitigating against harm to people and property, and investigating the future implications of climate change.

The project was initially limited in scope – attempting to find at least a few undocumented tornadoes in the northern forests of Ontario and Quebec. After demonstrating that the NTP could more than double the annual tornado count in those provinces, the NTP set out to detect, assess and document every tornado that occurs across the country. We also forged other partnerships with Western Libraries, University of Manitoba, York University, Pelmorex’s The Weather Network, Instant Weather, and CatIQ. Research collaborations were undertaken with a number of academic institutions inside and outside of Canada.

As the project evolved, the NTP required new techniques and technologies to allow us to meet our ambitious scientific goals. Cutting-edge remote sensing capacity, including ultra high-resolution satellite imagery and piloted and remotely piloted aircraft systems, needed to be utilized and the latest processing techniques adopted. New means of assessing wind damage were employed. Even a new set of definitions related to tornadoes and related phenomenon had to be developed. The societal impacts of significant events are also increasingly being investigated and becoming part of the event record.

Interestingly, as our assessment tools reach ever-higher resolution, new problems emerge. A lower-resolution image showing what might have been considered a wide tornado path through the forest in the past now often shows evidence of a mix of tornado and downburst damage, and thorough tree-by-tree analysis is needed to untangle the two. Thus, methods for rating and documenting tornado and downburst damage must also evolve as resolution increases.

In addition, the NTP is building new ways of using social media reports of severe weather as crowdsourced data, including creating a community of ‘super-contributors’ that provide high-quality evidence. Sophisticated methods for ‘scraping’ social media for key reports are also under development.

As a result of these detection, assessment and documentation processes, we are generating novel research-quality data sets that are being employed by a number of different types of users. All NTP data are open source in order to foster further innovation.

The presentation will provide a number of detailed examples showing how the NTP has shifted the post-event paradigm in Canada.
A Deep Learning approach for MCS detection: application for storm tracking and nowcasting
Authors: Arnould Gabriel , Montmerle Thibaut , Moisselin Jean-Marc , Rottner Lucie
Published: March 2023

Storms deeply impact human safety and economic activities by generating severe hazards such as large hail, strong wind gusts or floods. The more critical phenomena often imply mesoscale convective systems (MCS) that originate from the aggregation of intense cells. The induced circulation reinforces the system and maintains it for a long time.

Convective-scale numerical weather prediction (NWP) models are now able to simulate realistically such storms. Nevertheless, model and displacement errors often alter the forecast accuracy and ultimately the weather alerts efficiency.

In order to study the predictability of MCS, present work attempts to automatically detect, track and characterize such system in the outputs of the operational high resolution nowcasting model used at Météo-France, Arome-NWC. Such system provides 6h forecast every hour by updating the last AROME-France forecast towards the latest conventional and radar observations, thanks to a 3D variational (3DVar) data assimilation system.

Three methods are developed and compared. The first one applies a segmentation algorithm on images of maximum simulated reflectivity (Zmax). The second one applies a watershed transformation algorithm on Zmax, using as seed the 10,8 µm brightness temperature (TB10.8) from the SEVIRI imager onboard geostationary satellite MSG, that is diagnosed by applying the RTTOV radiative transfer algorithm to simulated variables. Finally, the last one trains a convolutional neural network (CNN) from MCS that are hand-labelled from simulated Zmax and TB10.8 images. Subjective analyses and objective evaluation based on objects-oriented scores depict the third approach as the more reliable.

The operational benefits of this object-oriented approach are investigated on several convective cases using synthesis plots. Superimposing the MCS detected in the different available hourly runs of Arome-NWC, as well as comparing tracked parameters within the MCS throughout the different forecasts, help in assessing the behavior of the successive runs. That could facilitate the analysis of the forecaster in tricky situations, leading to a positive impact on the weather alert efficiency.
Supercell interactions with surface baroclinic zones in the Carpathian Basin
Authors: Komjáti Kornél , Csirmaz Kálmán , Breuer Hajnalka , Kurcsics Máté , Horváth Ákos
Published: March 2023

Several previous studies have shown that near-surface thermal or outflow boundaries might have a significant impact on supercell development – especially low-level mesocyclone intensification. Supercells that cross surface boundaries at an acute angle usually produce rapid and intense tornadoes on the cool side, even local tornado outbreaks, and in some cases, large hail and damaging wind gusts can occur as well. Similar interactions can be present in the Carpathian Basin as well, however, the investigation of these processes in this region is more difficult due to the complex terrain. This complexity can lead to processes on a much more localized scale. Based on observations, these local thermal baroclinic zones are typically associated with shallow surface lows over Hungary. The surface confluent flow and the equivalent potential temperature gradient zone created by preceding precipitation bears substantial horizontal vorticity near the ground that might be favorable for the low-level intensification of mesocyclones in supercells.

In this research, we investigate these local baroclinic zones and their influence on supercell intensification using non-hydrostatic WRF (Weather Research and Forecasting) real and idealized simulations. We inspect how the presence of the surface baroclinic zone affected the dynamics of the simulated thunderstorm. The gained results may add significant contributions to our understanding of these processes, and support the early recognition of their patterns in the operational routine.
The Belgian Lightning Location System (BELLS)
Authors: Poelman Dieter
Published: March 2023

The Royal Meteorological Institute of Belgium (RMI) has been operating a lightning detection network since 1992. Over the past years, the network has undergone upgrades at the level of soft- and hardware. The present-day Belgian Lightning Location System (BELLS) consists out of 14 LS7002 sensors, out of which five are owned by RMI and positioned within Belgium. The sensors detect low frequency (LF) electromagnetic signals generated by lightning in the 1-350 kHz range. Combined with Vaisala’s latest Total Lightning Processor (TLP), the network uses a combination of magnetic direction finding and time-of-arrival for detecting (intra)cloud (IC) lightning pulses and cloud-to-ground (CG) lightning strokes. 
Based on BELLS data of the last 10 years, i.e., 2013-2022, the temporal and spatial distribution of CG lightning will be discussed. In addition, while the CG detection efficiency can be fairly accurately determined through the use of ground-truth video data, this is not as straightforward in case of IC lightning. Hence, in order to evaluate the performance of the cloud lightning detection, the ratio of the number of cloud lightning pulses to the number of CG lightning return strokes can serve as a measure of change in the network’s cloud lightning detection efficiency. The behavior of this ratio is examined with specific attention to the influence of the length of the baseline between the sensors. Finally, estimated peak currents for negative first and subsequent CG strokes and cloud pulses are reviewed.
Hailstorm in Eastern Croatia - analysis and forecasting potential by convection-permitting numerical model
Authors: Renko Tanja , Malečić Barbara , Mikuš Jurković Petra , Kozarić Tomislav , Horvath Kristian
Published: March 2023

Warm seasons of 2021 was quite exceptional if we consider the hail occurrence in the continental part of Croatia which attracted a lot of public attention due to the announced changes in the Law on the Hail Suppression System. One of the events that sparked a great debate in the public occurred on 25 June near the town of Požega due to hail size and damage, although this event was very well forecasted, and orange warning for thunderstorm was issued one day in advance.

This work aims to explore the atmospheric conditions present during this hailstorm but also a forecasting potential of such events using the convection-permitting km-scale numerical models.

On that day ahead of an advancing trough that stretched from Scandinavia to the western Mediterranean all necessary ingredients for severe deep moist convection were recognized. Convective initiation started first in Bosnia and Herzegovina ahead of the surface cold front. For damage in the vicinity of town Požega, most important were convective cells that were advected into the area of Slavonian Posavina. They experienced "explosive" development, and then moved in the southwestern and southern flow across western Slavonia. The estimated convective available potential energy of the air parcel raised from the ground to the level of free convection (SBCAPE) in the Zagreb area, based on radiosounding at 12 UTC was about 2700 J/kg and the deep layer wind shear was estimated at 20-25 m/s, which favored the formation of a supercell thunderstorm.

Here, convection-permitting km-scale WRF model is utilized to inspect the ability of the WRF model to reproduce the atmospheric conditions leading to formation and evolution of an extremely damaging hailstorm. Additionally, the ability of HAILCAST and Lightning Potential Index (LPI) diagnostics to reproduce the main characteristics of observed hail and lightning is explored. HAILCAST is a one-dimensional hail growth model that forecasts the maximum hail diameter at the ground. Similarly, LPI highlights the areas with the potential for developing lightning activity. Moreover, the sensitivity experiments are performed to investigate the impact that convection parameterization has on the simulated timing and characteristics of convection.

The results reveal that the WRF model, when run at the km-scale resolution (1.5 km) can reproduce the synoptic and mesoscale conditions present during an extremely damaging hailstorm occurring over Croatia. Moreover, HAILCAST and LPI diagnostics reproduce hail and lightning characteristics comparable to those observed.
Severe thunderstorm in the central part of Croatia on 15th September 2022
Authors: Mikus Jurkovic Petra , Kozaric Tomislav , Kalin Lovro , Renko Tanja , Pirak Tomislav
Published: March 2023

Severe thunderstorm with gale-force and most likely hurricane-like wind gusts, heavy rain showers and locally large hail affected area of Bjelovarsko–bilogorska county in the central part of Croatia in the afternoon hours on 15th September 2022. Some locals also mentioned the possibility of a tornado. The thunderstorm caused significant damage to property, crops and forests estimated at approximately 8 million EUR. A natural disaster was declared in two cities and five county municipalities.

Due to very high impact and even the possible occurrence of a tornado, detail synoptic and mesoscale analysis of severe thunderstorm was performed. Moreover, for the first time in recent history, an official on-site meteorological inspection of affected areas was done. That resulted in abundant photo and video materials which were used for the analysis of damage patterns and determination of the phenomena that caused the damage.

On 15th September 2022, the ridge over Croatia weakened and the southwesterly flow strengthened bringing a significant amount of moisture. The dew point temperature was between 16 and 18 °C. A cold front was approaching from the northwest, and in the upper levels a colder air was advected above the very heated surface, due to which the instability of the atmosphere increased. According to radio sounding measurement in Zagreb–Maksimir at 12 UTC, the most unstable CAPE (MU CAPE) was 888 J/kg, and 0-6 km bulk shear was 24.5 m/s which are characteristic values of the environment where supercells can form. The wind shear was mainly concentrated in the lower layers of the troposphere, from 0 to 3 km (23.6 m/s), and it was also significant in the layer from 0 to 1 km (12.1 m/s), which favors the formation of tornadoes.

Radar reflectivity analysis confirmed the presence of a supercell, and a bow-shape was detected what is characteristic for storms with damaging winds. In the satellite imagery during the mature phase of the thunderstorm, the overshooting tops were observed indicating very strong convective updraft. By analyzing the forest damage areas from the ground and using the aerial drone footage, no evidence of wind spinning was found. All trees were knocked down in the approximately same straight-line direction, only slightly divergent damage pattern was observed. Such a damage pattern is usually associated with downbursts.
Citizen observations via smartphone in Belgium: data collection and applications
Authors: Reyniers Maarten , Delobbe Laurent , Watelet Sylvain
Published: March 2023

The detection and prediction of very local weather effects, like wind gusts or hail storms, remains a challenging issue in meteorology. Especially in the case of severe storms, there is often a lack of detailed ground truth data to assess the precise conditions of the event. One promising approach to supplement the information obtained with the classical instruments like radar and satellite, is the collection of citizen weather reports through smartphones. In August 2019, the Royal Meteorological Institute of Belgium (RMIB) added such a reporting feature in its smartphone app. Currently the database of citizen reports holds more than two and a half million records. Since May 2022, the app users are also able to add a photo to their observation.

In this presentation, we describe the general concept of the app feature and how the quality control of the reports and the filtering of the photos are organised. Then, we give some general statistics of the aggregated dataset. We will show that this unconventional observation system brings uncommon sources of uncertainties and biases related to the human nature of the observations. The collected data have already been exploited in several use cases at RMIB, such as the verification of the official weather warnings and the forecasts per commune as sent out by the weather office. We will further focus on the verification of the operational radar-based hail detection algorithm used at RMIB. Among all reported observations, 23 % concern precipitation (rain, snow or hail) and 0.7 % hail. We will examine the extent to which such a dataset allows evaluating the performance of the algorithm in terms of probability of correct and false detections. These applications show that the citizen observations are an extremely valuable new source of very localised information for many applications in research and operations at RMIB.
Supercell thunderstorms in complex topography - how lakes in mountain valleys can increase occurrence frequency
Authors: Feldmann Monika , Rotunno Richard , Germann Urs , Berne Alexis
Published: March 2023

While supercell thunderstorms are one of the most severe convective phenomena, their behavior in complex terrain is still poorly understood.

Observational studies in the Southern Alps have revealed local supercell "hotspots" associated with valleys with large lakes. With a newly developed radar-based, mesocyclone-detection algorithm, the occurrence and evolution of supercell thunderstorms in the Alpine region were characterized. That study highlights the influence of orography on both storm intensity and occurrence frequency. To disentangle the different influential factors, an idealized modeling framework is established using the mesoscale model CM1. In different modeling experiments the key characteristics of this region have been generalized. The modeling scenarios are based on a high-CAPE environment with unidirectional shear, where a warm bubble serves to initiate the convection.  Mimicking the environment of the southern Prealps in central Europe, scenarios with a high mountain ridge, valleys and lakes are explored. Varying both the topographic features and the initial conditions permits the investigation of the individual impact of slopes, valleys and moisture sources.

The dynamic and thermodynamic impact of mountain valleys with lakes increases the range of atmospheric conditions that supports supercellular development through horizontal vorticity production and maintenance of high equivalent potential temperature. This influence results in a systematic location dependence of the frequency, intensity and lifetime of supercells, as also found in observations.
Detection of Differential Reflectivity columns using operational c-band radar and their relation to hail probability and size in Switzerland
Authors: Aregger Martin , Martius Olivia , Hering Alessandro , Germann Urs
Published: March 2023

Differential reflectivity columns (ZDRC) have been observed during and at the onset of severe convection. From modelling studies, we know that they have the potential to characterise updrafts in convection and consequently may help in the nowcasting of hail falls. Here we investigate the occurrence and characteristics of ZDRC in the northern and southern boundary regions of the Swiss alps, two regions where convective storms are particularly frequent and storm-related damages, especially the impacts of hail, are of explicit concern.

We investigate the relation between ZDRC and the probability and size of hail on the ground by combining polarimetric data from the Swiss weather radar network with a wealth of ground-based hail information from crowd-sources hail reports and a network of automatic novel hail sensors. First, several manual case studies are performed and analysed. Then, in a second step, ZDRC are characterised for the whole convective season of 2021 with the assistance of an automated ZDRC detection algorithm.

Automated ZDRC detection in the alpine region provides challenges regarding visibility and data quality. Effects such as ground clutter and the shielding of the radar beam by topography must be considered. Further, differential reflectivity (ZDR) measurements suffer from the effects of differential attenuation and artefacts, such as three-body scattering, which have to be taken into account. The Swiss radar network consists of 5 radars, of which two are located at an altitude close to 3000 m above sea level, in an arrangement which allows for most geographical locations to be in the range of multiple radars. This configuration leads to good visibility in the Alps as well as the potential to use compositing to work around attenuation effects. We derive a 3D composite of ZDR in which we identify ZDRC with an algorithm using minimum thresholds of ZDR and ZDRC height and perform further filtering of the data using reflectivity and correlation coefficient information.
Nowcasting thunderstorm hazards with radar polarimetry using deep learning
Authors: Rombeek Nathalie , Leinonen Jussi , Hamann Ulrich
Published: March 2023

Severe convective weather events, such as hail, lightning and heavy rainfall pose a great threat to humans and cause a considerable amount of economic damage. Nowcasting convective storms can provide precise and timely warnings and, thus, mitigate the impact of these storms. Dual-polarization weather radars are a crucial source of information for nowcasting severe convective events. These radars provide important information about the microphysics of the convective systems, on top of the rainfall rate and vertical structure of the reflectivity. Nevertheless, polarimetric variables, which can provide additional information about the size, shape and orientation of particles, are often not considered in nowcasting.

This work presents the importance of polarimetric variables as an additional data source for nowcasting thunderstorm hazards using machine learning, compared to using radar reflectivity alone. We add these data to the neural network architecture of Leinonen et al. 2022 (Seamless lightning nowcasting with recurrent-convolutional deep learning), which uses convolutional and recurrent layers and analyzes inputs from multiple data sources simultaneously. This network has a common framework, which enables nowcasting of hail, lightning and heavy rainfall for lead times up to 60 min with a 5 min resolution. The study area is covered by the Swiss operational radar network, which consists of five operational polarimetric C-band radars. In addition, we analyze the contribution of quality indices as an additional information source, which takes the uncertainty of the radar observations throughout the complex mountainous terrain and scanning strategy in Switzerland into account. Results indicate that including polarimetric variables and quality indices improves the accuracy of nowcasting convective storms.
Predictions of Severe Weather with Random Forests and the Global Ensemble Forecast System
Authors: Hill Aaron , Schumacher Russ
Published: March 2023

Artificial Intelligence and Machine Learning techniques in meteorology have proliferated in recent years. Of particular interest are meteorological hazards -- tornadoes, large hail, and damaging winds -- that occur on spatial and temporal scales that are not well represented in numerical weather prediction (NWP) model output. The predictability limit for these hazards is short, so reliable probabilistic forecasts are needed rather than deterministic predictions that will inevitably have large errors. To address these challenges, over the past several years we have developed a suite of probabilistic forecast systems, referred to as Colorado State University-Machine Learning Probabilities (CSU-MLP), that use the Global Ensemble Forecast System (GEFS) Reforecast datasets, historical observations of severe weather, and machine learning algorithms to generate skillful, reliable guidance that operational forecasters can use as a "first guess" when generating outlooks. The CSU-MLP utilizes Random Forests (RFs) to generate probabilistic severe weather forecasts out to 8 days by training the RFs to learn how local environments relate to severe weather events. Nearly a decade of daily forecast initializations from the GEFS reforecast dataset are used to train the RFs and over two years of real-time forecasts are used to quantify forecast skill. This presentation will provide background on the CSU-MLP system, highlight the skill of the system in depicting severe weather events, and touch on the value added to the operational forecast process at U.S. national forecast centers, including feedback we have received from our operational forecast partners.

 

 
Characteristics and environments of flash-flood-producing storms in the UK
Authors: Clark Matthew
Published: March 2023

A set of 103 surface-water flooding events in the UK over the period 2015 – 2021 has been identified using impact reports from a variety of sources. For inclusion, flooding impacts had to meet basic severity criteria (broadly comprising internal flooding of multiple properties, or disruption to key infrastructure such as hospitals) and the flooding had to be associated with deep, moist convection (assessed by analysis of radar data in conjunction with the flood reports). The synoptic-scale, mesoscale and storm-scale environments of the identified events were explored using ERA5 reanalysis data, radar data and surface meso-analysis, the latter incorporating bias-corrected observations from a network of home automatic weather stations. One of the main findings is that surface-water flooding events in the UK often occurred in environments of relatively weak vertical wind shear (median effective bulk wind difference = 12.8 knots) and small buoyant instability (median MUCAPE = 561 J kg-1), though a few cases exhibited much larger vertical wind shear and CAPE. Mesoscale features such as convergence lines were often important in focussing repeated convection initiation over a small area. In this presentation, results of the work will be described in more detail, and some conclusions drawn about the typical characteristics of surface-water-flood-producing storms in the UK.
Modelling fire-generated thunderstorms: Pedrógão Grande case study
Authors: Couto Flavio T. , Filippi Jean-Baptiste , Baggio Roberta , Salgado Rui
Published: March 2023

The development of PyroCumulonimbus clouds during mega fire events has high impact in the evolution of the fire fronts and their development is frequently associated with strong convective processes due the heat and moisture released by the combustion. In 2017, Portugal was affected by several episodes of extreme wildfires with such a cloud system. The “Pedrógão Grande” mega fire caused more than 60 fatalities and burned a total area of almost 29,000 ha. In general, the atmospheric models do not account for fire-atmosphere interactions. Aiming to investigate the pyro-convective activity during the Pedrógão Grande mega fire, a numerical simulation was run with the Meso-NH model coupled to the ForeFire model. The Meso-NH model was configured into three nested domains. The horizontal resolution is 2000 m for the outer domain (600 km × 600 km). The inner computational grids have grid increments of respectively 400 m (120 km × 120 km) and 80 m (24 km × 24 km) for the innermost model. Initial and lateral boundary conditions for the outer domain are provided by ECMWF analysis, with updates every 6 h. The simulation with the coarsest resolution began on 17th June 2017 at 0600 UTC, with a progressive downscaling up to the finest resolution beginning at 1300 UTC. The vertical resolution is the same for all the nested domains, with 50 levels and a first level above the ground at 30 m height. The study used the reference fire propagation deduced from the official investigation (forced fire) and the emission of heat and vapour into the atmosphere was made using the ForeFire model. The results highlight the importance of the use of cloud resolving models configured with very-high spatial and temporal resolutions (80m, 10s) for representing the development of phenomena associated to pyro-convective activity, namely those occurring in the micro-scale from the cloud microphysics processes, like very-localised microbursts. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).
Enhanced climatology of large hail in the UK: Radar-derived diurnal cycle and storm mode
Authors: Wells Henry , Hillier John , Garry Freya , Dunstone Nick , Chen Huili , Kahraman Abdullah , Keat William , Clark Matthew
Published: March 2023

Large hail, with a diameter of at least 20 mm, is a hazard associated with severe convective storms (SCS) that can cause significant damage. Understanding of atmospheric environments conducive to large hail is underpinned by catalogues of past events. Because of the small footprint of hail events, these often rely on crowdsourced reports. In the UK, the relative rarity of large hail and low public awareness of SCS hazards makes obtaining a complete set of reports difficult, and in many cases the precise time of the hail is not recorded. In this study, the two major databases of UK large hail reports are merged for the first time. Composite radar reflectivity data are used to verify and enhance 260 reports since 2006. Time of the hail and the basic storm mode (isolated, clustered or linear) are visually estimated from animations. Compared to the UK’s most severe historic hailstorms (1800–2004), our quality controlled climatology of all sizes of large hail shows a diurnal cycle with a slightly broader peak. Around 55% of large hail events are associated with isolated cells, while 34% have supercellular characteristics, a much lower proportion than found in the USA. The full event set (1979–2022), comprising over 850 reports, is used to update the seasonal, spatial and size distributions of large hail in the UK. We intend that this hail event set forms part of a multi-hazard analysis of UK SCS, also including tornadoes and extreme rainfall, and its relationship to background atmospheric conditions. The effect of climate change on UK SCS will be investigated through past and future trends in these background conditions.
Development and Evaluation of Operational Lightning Forecasting System based on Lighting Detection Network
Authors: Son MyoungJae , Kim Hae-Lim , Nam Kyung-Yeub
Published: March 2023

 Recently, severe weather such as heavy rainfall, typhoon, hail, and lightning has become more frequent due to climate change. Especially heavy rains and localized precipitation systems accompanied by lightning strikes has not only human casualties but also social and economic impacts. To minimize the damage caused by lighting, research into the causes of lighting and their predictions are necessary.

 Korea Meteorological Administration(KMA) has been operating the Lightning Forecasting model to predict lightning forecast information on the Korean Peninsula. This model uses the energy density of lightning strikes detected by a total of 21 sensors of the LINET(LIghtning NETwork) systems(Nowcast, Germany). The energy density is calculated as the energy per unit area per unit time(kAkm-2hr-1) using CC(cloud-to-cloud) and CG(cloud-to-ground) lightning observation. This provides quantitative information on where strong lightning strikes are concentrated. In addition, the vector fields derived by applying the variational Echo Tracking(VET) algorithm are performed on the energy density and these are advected to the entire density field calculated by the semi-Lagrangian backward advection method. Finally, This very short-term quantitative lightning forecast data is produced every 10 minutes up to 6 hours ahead.

 The evaluation of lightning forecasting is performed from 2019 to 2021 based on each month and season which is a total of 192 cases, and regions for the Korean Peninsula. The verification methods range from simple traditional skill scores to methods for quantitative comparison between the prediction model and lightning frequency observation. Based on the results of the evaluation, the record score of the total critical success index(CSI) is 0.48 within 1 hour, autumn is the highest season(0.51), and winter season(January, CSI=0.17) is the lowest(0.17).

 

Acknowledgements:

This research was supported by the ”Development of Integrated radar analysis and customized radar technology (KMA2021-03021)” of “Development of integrated application technology for Korea weather radar” project funded by the Weather Radar Center, Korea Meteorological Administration.
Convective environment in ALADIN Reanalysis
Authors: Vokoun Martin , Zacharov Petr
Published: March 2023

In the framework of the national project PERUN (Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia) new ALADIN (Aire Limitée, Adaptation Dynamique, Development International) Reanalyses are now available for the evaluation purposes. The reanalyses use boundary conditions from European reanalysis ERA5, the first reanalysis uses an assimilation of various meteorological every six hours. The domain of the reanalyses covers Europe with 2.3 km of horizontal resolution. As the evaluation domain we use primarily the area of the Czech Republic.

The reanalysis contain, among other things, outputs describing the convective environment in a 25-year series (1990-2014). The aim of this work is evaluation of CAPE (Convective Available Potential Energy), CIN (Convective INhibition) and wind shear data, as the key values for convection formation. These data are assessed in the perspective of the common temporal and spatial characteristics. Within this study, reanalysis data were verified by sounding data at least from meteorological station Praha-Libuš. These results will be applied for comparison with the ALADIN climate model for period 2025 – 2100. This run use boundary conditions from the climate model CMIP6 with scenario SSP5-8.5 where emissions follow a worst-case pathway until 2040 from all other emission scenarios.
Simulations of Rising Thermals Using a Lagrangian Stochastic Closure for the Subgrid Turbulent Fluxes
Authors: Jewtoukoff Valerian , Abade Gustavo , Waclawczyk Marta
Published: March 2023

Turbulent clouds are challenging to model and simulate due to uncertainties in processes occurring at unresolved subgrid scales (SGS). These processes include the transport of cloud particles, supersaturation fluctuations, turbulent mixing, and the resulting stochastic droplet activation and growth by condensation. In this work, we use a stochastic Filtered Density Function (FDF) particle method to describe both temperature and the amount of water vapor distribution at unresolved scales in rising thermals. The particle method is solved in combination with an Eulerian scheme (here we use the CM1 model, Bryan and Fritsch 2002). In this hybrid implementation, the particle method plays two important roles: (a) it models the SGS variability of the environment where cloud particles would activate and grow by condensation, and (b) it provides the SGS unresolved fluxes that close the filtered equations underlying the Eulerian scheme, devoid of any approximation. The hybrid algorithm is tested in 2D and 3D simulations of dry and moist thermals against schemes that use standard subgrid models (such as Deardorff’s parametrization of the eddy viscosity). Our simulations suggest that FDF models may expand the ability of Large Eddy Simulations to represent cloud entrainment and associated microphysical details at the edge of cumulus clouds. Furthermore, the intrinsic character of this particle-based method is also useful to study generation and reorientation of vorticity around and within thunderstorm clouds.
Does big CAPE equate to big tornado potential in supercell thunderstorms?
Authors: Peters John M
Published: March 2023

Convective available potential energy (CAPE), when considered by itself, is not a skillful discriminator of tornadic supercells from their nontornadic counterparts.  However, there is a longstanding notion that large CAPE may allow strong-to-violent tornadoes to occur in environments with otherwise weak vertical wind shear.  There is also anecdotal evidence that the largest tornadoes often occur on days with moderate-to-extreme CAPE.  These notions and anecdotes prompt us to ask whether large CAPE is conditionally supportive for significant tornado formation?

We use a matrix of large-eddy simulations of supercells to address this question, wherein the vertical wind shear and the magnitude and vertical distribution of CAPE are independently varied.  Our analysis of these simulations identifies two influences of CAPE on storm evolution that potentially facilitate both tornadogenesis, and the formation of large and intense tornadoes.  Large CAPE generally fostered more negatively buoyant and expansive cold pools.  In environments with strong shear and low-level storm-relative flow, a more negatively buoyant rear-flank downdraft amid large CAPE fortified the rear-flank convergence zone beneath the updraft, leading to a more efficient projection of initially horizontal streamwise vorticity into the vertical.  This led to more intense mesocyclones and tornadoes, when compared to simulations with the same wind profile but smaller CAPE.  In environments with weak vertical wind shear and large CAPE, storms were more resistant to the negative effects of entrainment and thereby more prone to sustaining mesocyclones and producing tornadoes, when compared to environments with both weak shear and CAPE.  We argue that these processes explain past anecdotes about the role of CAPE in tornadogenesis.
Guidelines for Satellite-based Nowcasting in Africa
Authors: De Coning Estelle , Nietosvaara Vesa
Published: March 2023

Nowcasting has enormous value and potential in Africa, where populations and economic activity are highly vulnerable to rapidly changing weather conditions, including rapidly developing storms, heavy rainfall and dust storms, which are becoming more frequent and intense with climate change. Timely issuing of warnings, a few hours before an event, can enable the public and decision makers to take action, which can save lives and livelihoods, as well as support national economies. The potential applications of nowcasting across the continent are wide-ranging, and can cover various sectors and activities, including urban warning systems for flash floods, early warnings to fisherfolk at risk from drowning on lakes, protection of crops, water management systems, protection of cattle, aviation warnings as well as the transport sector.

The vulnerability of African countries to weather-related risks make the continent a priority for the development of nowcasting, and is the primary driver for recently published "Guidelines for Satellite-based Nowcasting in Africa". It provides guidelines for the implementation of a range of satellite nowcasting capabilities available for Africa with the advent of the Meteosat Third Generation (MTG) satellite system. The successful launch of the first MTG satellite on 13 December 2022 marks a major improvement over the previous geostationary satellite system. This aligns very well with the UN SG announcement to improve Early Warnings for All, led by the WMO and UNDRR.

The present guidelines are urgently needed, given that there is currently a lack of early warnings on this timescale in Africa. The guidelines aim to provide recommendations that will help facilitate near-term implementation, as well as the development of capacity and sustainability of services overtime. The various options are broken down in the document into different technical, operational, logistical and management aspects. The guidelines can be used to create templates and roadmaps for the establishment and maintenance of nowcasting functions in African countries.

The intended readership includes National Meteorological and Hydrological Services in Africa, Regional Specialized Meteorological Centres, Regional Training Centres, WMO-CGMS VLab Centres of Excellence for Training in Satellite Meteorology, and international agencies.
The higher relative concentration of K+ to Na+ in saline water improves soil hydraulic conductivity, salt leaching efficiency and structural stability
Authors: Yan Sihui , Zhang Binbin , Zhang Tonggang , Cheng Yu , Wang Chun , Luo Min , Feng Hao , Zhang Tibin , Siddique Kadambot H. M.
Published: March 2023

Abstract. Soil salinity and sodicity caused by saline water irrigation are widely observed globally. Clay dispersion and swelling are influenced by sodium (Na+) concentration and electrical conductivity (EC) of soil solution. Specifically, soil potassium (K+) also significantly affects soil structural stability, but which concern was rarely addressed in previous studies or irrigation practices. A soil column experiment was carried out to examine the effects of saline water with different relative concentrations of K+ to Na+, including K+/Na+ of 0:1 (K0Na1), 1:1 (K1Na1), 1:0 (K1Na0) at a constant EC (4 dS m-1), and deionized water as the control (CK), on soil physicochemical properties. The results indicated that at the constant EC of 4 dS m-1, the infiltration rate and water content were significantly (P < 0.05) affected by K+/Na+ values, K0Na1, K1Na1 and K1Na0 significantly (P < 0.05) reduced saturated hydraulic conductivity by 43.62 %, 29.04 % and 18.06 % respectively compared with CK. The volumetric water content was significantly (P < 0.05) higher in K0Na1 than CK at both 15 and 30 cm soil depths. K1Na1 and K1Na0 significantly (P < 0.05) reduced the desalination time and required leaching volume. K0Na1 and K1Na1 reached the desalination standard after the fifth and second infiltration, respectively, as K1Na0 did not exceed the bulk electrical conductivity required for desalination prerequisite throughout the whole infiltration cycle at 15 cm soil layer. Furthermore, due to the transformation of macropores into micropores spurred by clay dispersion, soil total porosity in K0Na1 dramatically decreased compared with CK, and K1Na0 even increased the proportion of soil macropores. The higher relative concentration of K+ to Na+ in applied water was more conducive to soil aggregate stability, alleviating the risk of macropores reduction caused by sodicity.
Simulation of marine stratocumulus using the super-droplet method: Numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.0
Authors: Yin Chongzhi , Shima Shin-ichiro , Xue Lulin , Lu Chunsong
Published: March 2023

Abstract. Marine stratocumulus clouds play an important role in the planet’s radiation budget by reflecting the incident solar radiation. Some studies have shown that the uncertainty in temperature projections in global warming simulations is mainly caused by the representation of marine low clouds in global climate models. Using the Super Droplet Method (SDM), an advanced and highly accurate particle-based numerical simulation method for cloud microphysics, the characteristics and morphology of the simulated clouds are closer to those of natural clouds. We explore separately how small a grid length is necessary for accurate simulations of stratocumulus using the SDM and a double-moment scheme called SN14 which is a traditional and simpler cloud microphysics scheme and how many Super-droplet number per grid is required for an accurate simulation using SDM. This result can be used as a reference for future related research, saving computational resources while ensuring the accuracy of the simulation. The results of both schemes are compared with the results of model intercomparison project (MIP) results showing a good agreement. The difference of results of SDM and SN14 could be explained by the numerical diffusion and different performance of aerosol particles. The former is a numerical calculation error that is present in the simulation of SN14 but not in the SDM. SDM can simulate the motion and microphysical processes of aerosol particles more accurately, so it explicitly calculates the process of aerosol removal, and this would make the cloud holes larger and longer lasting. The results of this comparison also suggest that cloud-aerosol interactions could be critical to understanding the behavior and morphology of marine stratocumulus. We hope that our findings on the mechanisms of cloud-aerosol interactions will provide new insights for future studies and help us understand stratocumulus clouds.
The flexural isostatic response of climatically driven sea-level changes on continental-scale deltas
Authors: Polanco Sara , Blum Mike , Salles Tristan , Frederick Bruce C. , Farrington Rebecca , Ding Xuesong , Mather Ben , Mallard Claire , Moresi Louis
Published: March 2023

Abstract. The interplay between climate-forced sea-level change, sediment erosion and deposition, and flexural adjustments in deep time on passive margin deltas remains poorly understood. We performed a series of conceptual simulations to investigate flexural isostatic responses to high-frequency fluctuations in water and sediment load associated with climatically driven sea-level changes. We model a large drainage basin that discharges to a continental margin to generate a deltaic depocenter, then prescribe synthetic and climatic-driven sea-level curves of different frequencies to assess flexural response. Results show that flexural isostatic adjustments are bidirectional over 100–1000 kyr timescales and are in sync with the magnitude, frequency, and direction of sea-level fluctuations, and that isostatic adjustments play an important role in driving along-strike and cross-shelf river-mouth migration and sediment accumulation. Our findings demonstrate that climate-forced sea-level changes produce a feedback mechanism that results in self-sustaining creation of accommodation into which sediment is deposited and plays a major role in delta morphology and stratigraphic architecture.