Simulated Storm Research Articles

Simulation and Assessment of Episodic Dust Storms in Eastern Saudi Arabia Using HYSPLIT Trajectory Model and Satellite Observations

The “dust belt” region extending from the western Sahara to the Gobi Desert frequently generates severe dust storms that cause hazardous air quality and disrupt daily activities. Dust storm management systems with proactive mitigation strategies can minimize the detrimental impacts of dust storms. This study applies the HYSPLIT model to simulate dust storms in Saudi Arabia, specifically targeting the eastern region. The study’s main objective is to calibrate and validate the model’s dust storm prediction module for the eastern region of Saudi Arabia. The validated HYSPLIT model, with optimized parameters such as threshold friction velocity, particle release rate, and dry deposition velocity from model calibration studies, showed a strong linear correlation between measured and predicted values. It achieved an R2 of 0.9965, indicating excellent model accuracy. The main findings of the source apportionment approach, employing air particle backward trajectories and frequency analyses, indicated that the northern regions, specifically Iraq and Syria, were the primary sources of the severe dust storms observed in the receptor area. The outcomes of this study will be a reference for future research aimed at improving dust storm management systems and selecting sites for tree-planting campaigns under the “Saudi & Middle East Green Initiatives”.

Detection and simulation of Kermanshah dust storm using HYSPLIT and WRF-chem models

Detection and simulation of Kermanshah dust storm using HYSPLIT and WRF-chem models

Using surrogate modeling to predict storm surge on evolving landscapes under climate change

Planners managing coastal flood risk under a constrained computational budget face a tradeoff. Simulating many time periods or scenarios limits how many storm simulations can be run on each landscape. In this analysis, we present a deep learning model to predict storm surge as a function of storm parameters but also landscape features and boundary conditions (e.g., sea level). It is trained on peak surge elevations from Advanced Circulation (ADCIRC) hydrodynamic simulations of coastal Louisiana in a 2020 baseline and decadal periods from 2030 to 2070 under two morphological and climate scenarios. Leave-one-landscape-out cross-validation yielded a 0.086-m RMSE and 0.050-m MAE over 90 storms per landscape and 94,013 geospatial locations. A two-sided Kolmogorov-Smirnov test comparing annual exceedance probability (AEP) estimates from the model predictions to ADCIRC simulations rejected the null hypothesis that the predicted and ADCIRC AEP values were drawn from the same distribution only 1.1% of the time.

Investigation of morphodynamic response to the storm-induced currents and waves in the Bay of Bengal

Storm surges, driven by Tropical Cyclones (TCs), pose a threat to the coastal areas of the Bay of Bengal (BoB), causing sediment transport and beach erosion. This study introduces a coupled hydrodynamic (TELEMAC-2D) -wave (TOMAWAC) -morphodynamic (GAIA) model to investigate morphodynamic changes during storm surges. The cyclonic wind is crucial for precisely predicting storm surges, wind waves, and morphodynamic bed evolution. Thus, this study introduced a modified parametric wind model to enhance wind field representation near and far from the cyclone center. The simulated storm surges and wind waves were validated against in-situ observations for TC Hudhud (2014) and TC Varadah (2016), and the simulated morphodynamic bed evolution was validated with field-measured data collected for TC Nivar (2020). Further, this study evaluates the performance of different bed load transport formulations for predicting morphodynamic bed evolution during TC Nivar (2020) under storm-induced currents and waves. Results indicate that the Engelund-Hansen model is most effective for currents alone, while the Bijker model excels for combined currents and waves along the open coast of BoB. The results also indicate that the incorporation of the effect of waves along with currents has enhanced the predictive capability of the coupled model framework.

Evaluating and comparison of WRF-chem model configurations for wind field impact on the April 2022 dust episode in western Iran

Accurate estimation of wind direction and speed is essential for enhancing the simulation and prediction of dust storms. Being highly susceptible to dust storms, Western Iran necessitates a detailed evaluation of dust concentration and wind fields. This study employs the WRF-Chem model to simulate these parameters over the period from April 7 to 26, 2022. Four different model configurations were tested, involving the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) boundary layer schemes, as well as the Lin and WRF Single-Moment 6-Class (WSM6) microphysics schemes. The results indicate that during the selected period, different synoptic systems led to the release of dust from Iraq and Saudi Arabia and its transport to western Iran. The mid-level southerly and southwesterly wind directions have a significant impact on dust transport to the northwestern regions of Iran by high and complex mountainous terrain. The horizontal and vertical distribution of simulated dust demonstrates good agreement with TERRA satellite imagery, MERRA-2 dust surface concentration, and CALIPSO, respectively. The daily dust concentration of the WRF-Chem model has a correlation of −0.32 to −0.96 with visibility and 0.68 to 0.86 with MERRA-2 data in Western Iran. The simulated dust concentration relation with visibility and AERONET AOD (Aerosol Optical Depth at 500 nm) was calculated at −0.78 and 0.29, respectively in Zanjan station. The horizontal and vertical distribution, temporal series, and statistical indices of the wind field show that the WRF-Chem model performs well in the Iran West boundary, especially in the west and northwest, where the 10-m wind speed increased to 14 m s−1. The boundary layer scheme in the WRF-Chem model has a more significant impact than the microphysics scheme in simulated 10-m wind speed and dust concentration. The final result shows that the combination of the YSU boundary layer and WSM6 microphysics schemes performs very well in simulating wind fields and dust in western Iran under various weather conditions.

Spatial inhomogeneity analyses of extreme sea levels along Lianyungang coast based on numerical simulation and Monte Carlo model

The prediction of extreme sea levels in coastal areas has been a prominent requirement of coastal engineering design and planning. The research was based on the frequent disasters caused by typhoon storm surges in China and the demand for reasonable improvement of port structures in coastal areas. Delft3D hydrodynamic model and the Monte Carlo model were integrated to predict the spatial distribution of extreme sea levels along the coast of Lianyungang city in Jiangsu province. The Monte Carlo model was adopted to generate stochastic typhoon characteristic sequences as meteorological driving forces. In the hydrodynamic model, meteorological factors were coupled with the astronomical tide to simulate storm surge scenarios. Extreme sea levels were estimated by ranking maximum levels of simulated storm surge events. This programming was feasible compared to the prediction results of frequency analysis methods. The research showed that the predicted 1 in 100-year extreme sea level of Lianyungang station was 3.75 m, while the predicted 1 in 200-year value was 3.85 m. The programming was adopted to predict extreme sea levels of several stations and analyze the spatial distribution characteristics of extreme sea levels in four port areas of Lianyungang Port. Results revealed that extreme sea levels in modeling areas had significant spatial inhomogeneity, which might be related to the concavity of coastlines, islands, and terrains. Estimating spatial extreme sea levels could better cognize the influence of inundation disasters in coastal areas and be conducive to the design of port structures and the safety of port operations.

Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing

The spatio-temporal resolution of atmospheric forcing plays a key role in the accuracy of simulated storm surges with hydrodynamic numerical models. Here, we generate five hydrodynamic hindcasts of coastal storm surges along the European Atlantic and the Mediterranean Sea coasts, forced with atmospheric fields of varying temporal (hourly and daily) and spatial (0.25° to 2°) resolution since 1940. Our results, that are validated with insitu tide gauge observations, show that storm surges obtained with daily forcing underestimate the magnitude of coastal extreme sea level events by up to 50% compared to hourly simulations and observations. Nevertheless, low-resolution simulations capture the temporal variability of storm surges, including strong episodes. Furthermore, taking advantage of the consistent set of coastal storm surge hindcasts, we demonstrate that storm surges forced with daily mean atmospheric fields, when bias corrected via quantile mapping, provide accurate values of daily maxima as calculated by a high-resolution hindcast. This transformation paves the way to obtain daily maxima storm surge estimates from low-resolution atmospheric fields, as those typically provided by large-scale and global climate models, at a lower computational cost.

Comparison of Two-Moment and Three-Moment Bulk Microphysics Schemes in Thunderstorm Simulations over Indian Subcontinent

We simulated three different thunderstorm events over India using a regional model with two different multi-moments cloud microphysical schemes: (i) Morrison double moment (Morrison-2 M) and (ii) National Taiwan University (NTU) triple moment (NTU-3 M). The results show that the choice of microphysical scheme significantly impacts storm structures, cloud formations, lightning intensity, and rainfall patterns. The lightning flash counts from the in-situ lightning detection network (LDN) are also used to compare the simulated storms. The Lightning Potential Index (LPI) was computed for both Morrison-2 M and NTU-3 M microphysics schemes and compared it with the LDN observation. Differences in simulations are attributed to the simulation of ice crystals, snow, and graupel by the microphysical schemes. The effects on the size distributions of cloud hydrometeors between the two microphysical schemes are also found to be important. The inclusions of ice crystal shapes likely accounted for the key differences between the two microphysics schemes. The results demonstrate that the simulation of lightning event characteristics is sensitive to the choice of microphysical parameterization schemes in numerical weather prediction models. In comparison to both the microphysical schemes, some aspects are better in the 2 M microphysics scheme, and some are better in the 3 M microphysics scheme. Morrison-2 M simulates more mixing ratio for the majority of cloud hydrometeors across all cases than the NTU-3 M whereas the Morrison-2 M has less rainfall bias over the ocean for the majority of the cases. Overall, the present study suggests that the choice of microphysical scheme can greatly influence the accuracy of thunderstorm and lightning event predictions in operational weather forecasting models.

Sensitivity of Coastal Squall-Line Evolution to Numerical Sea-Breeze Initialization Method

Abstract This study employs 3D idealized numerical experiments to investigate the physical processes associated with coastal convection initiation (CI) as an offshore-moving squall line traverses a mountainous coastal region. A squall line can propagate discretely as convection initiates over the lee slope downstream of the primary storm as the cold pool collides with a sea breeze. Intensity of the initiating convection, thus the downstream squall line, is sensitive to the sea-breeze numerical initialization method, since it influences sea-breeze and cold pool characteristics, instability and vertical wind shear in the sea-breeze environment, and ultimately the vertical acceleration of air parcels during CI. Here, sea breezes are generated through four commonly used numerical methods: a cold-block marine atmospheric boundary layer (MABL), a prescribed surface sensible heat flux function, a prescribed surface sensible plus latent heat flux functions, and radiation plus surface-layer parameterization schemes. For MABL-initialized sea breezes, shallow weak sea-breeze flow in a relatively low instability environment results in weak CI. For the remainder, deeper stronger sea-breeze flow in an environment of enhanced instability supports more robust CI. In a subset of experiments, however, the vertical trajectory of air parcels is suppressed leading to weaker convection. Downward acceleration forms due to the horizontal rotation of the sea-breeze flow. Accurate simulations of coastal convective storms rely on an accurate representation of sea breezes. For idealized experiments such as the present simulations, a combination of initialization methods likely produces a more realistic representation of sea breeze and the associated physical processes.

Influence of Grid Resolution and Assimilation Window Size on Simulating Storm Surge Levels

Grid resolution and assimilation window size play significant roles in storm surge models. In the Bohai Sea, Yellow Sea, and East China Sea, the influence of grid resolution and assimilation window size on simulating storm surge levels was investigated during Typhoon 7203. In order to employ a more realistic wind stress drag coefficient that varies with time and space, we corrected the storm surge model using the spatial distribution of the wind stress drag coefficient, which was inverted using the data assimilation method based on the linear expression Cd = (a + b × U10) × 10−3. Initially, two grid resolutions of 5′ × 5′ and 10′ × 10′ were applied to the numerical storm surge model and adjoint assimilation model. It was found that the influence of different grid resolutions on the numerical model is almost negligible. But in the adjoint assimilation model, the root mean square (RMS) errors between the simulated and observed storm surge levels under 5′ × 5′ and 10′ × 10′ grid resolutions were 11.6 cm and 15.6 cm, and the average PCC and WSS values for 10 tidal stations changed from 89% and 92% in E3 to 93% and 96% in E4, respectively. The results indicate that the finer grid resolution can yield a closer consistency between the simulation and observations. Subsequently, the effects of assimilation window sizes of 6 h, 3 h, 2 h, and 1 h on simulated storm surge levels were evaluated in an adjoint assimilation model with a 5′ × 5′ grid resolution. The results show that the average RMS errors were 11.6 cm, 10.6 cm, 9.6 cm, and 9.3 cm under four assimilation window sizes. In particular, the RMS errors for the assimilation window sizes of 1 h and 6 h at RuShan station were 3.9 cm and 10.2 cm, a reduction of 61.76%. The PCC and WSS values from RuShan station in E4 and E7 separately showed significant increases, from 85% to 98% and from 92% to 99%. These results demonstrate that when the assimilation window size is smaller, the simulated storm surge level is closer to the observation. Further, the results show that the simulated storm surge levels are closer to the observation when using the wind stress drag coefficient with a finer grid resolution and smaller temporal resolution.

Effects of Storm Waves Caused by Typhoon Bolaven (1215) on Korean Coast: A Comparative Analysis with Deepwater Design Waves

This paper employs the third-generation simulating waves nearshore (SWAN) ocean wave model to estimate and analyze storm waves induced by Typhoon Bolaven, focusing on its impact along the west coast and Jeju Island of Korea. Utilizing reanalyzed meteorological data from the Japan Meteorological Agency meso scale model (JMA-MSM), the study simulated storm waves from Typhoon Bolaven, which maintained its intensity up to high latitudes as it approached the Korean Peninsula in 2012. Validation of the SWAN model against observed wave data demonstrated a strong correlation, particularly in regions where wind speeds exceeded 20 m/s and wave heights surpassed 5 m. Results indicate significant storm wave heights across Jeju Island and Korea's west and southwest seas, with coastal grid points near islands recording storm wave heights exceeding 90% of the 50-year return period design wave heights. Notably, specific grid points near islands in the northern West Sea and southwest Jeju Island estimated storm wave heights at 90.22% and 91.48% of the design values, respectively. The paper highlights the increased uncertainty and vulnerability in coastal disaster predictions due to event-driven typhoons and emphasizes the need for enhanced accuracy and speed in typhoon wave predictions amid the escalating climate crisis.

Dust model sensitivity to dust source mask, sandblasting efficiency, air density, and land use: Implications for model improvement

This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared with a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 12 times more dust than does a physics-based expression. Simulations using model-predicted versus constant air density differ by only 8%. However, this difference (often overlooked) could range between 12% and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The difference between simulations within each of the four pairs is generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.

Mitigation measures of storm surge inundation at an onshore aquaculture farm

Onshore pond-based aquaculture occupies a large proportion of coastal fisheries and is vulnerable to marine flooding. One common adaptation strategy is constructing sluices along inlets to prevent flooding. The efficacies of sluices typically depend on gate operation, associated risks, and flooding processes. However, few studies were focused on inundation characteristics and mitigation measures for valuable aquaculture farms. To assess the effectiveness of sluices in flood mitigation, we simulated storm surge inundation processes in a coastal aquaculture farm in the Pearl River Delta, where storm surges frequently occurred. The newly constructed sluice can substantially reduce the extent and severity of flood inundation. The antecedent water levels in fish ponds significantly affected the inundation processes, and a water level of −0.5 ∼ 0 m below mean sea level was a recommended value for reducing inundation risk. Our modeling results regarding the effect of the sluice and antecedent water levels on mitigating flood inundation will provide a reference for flood control of onshore aquaculture farms.

Improved local time-stepping schemes for storm surge modeling on unstructured grids

This paper presents improved explicit local time-stepping (LTS) schemes of both first and second order accuracy for storm surge modeling. The two-dimensional shallow water equations are numerically solved on unstructured triangular meshes using finite volume method with Roe’s approximate Riemann solver. The LTS algorithms are designed based on explicit Euler and strong stability preserving Runge–Kutta time integration methods. A single-layer interface prediction–correction scheme is adopted to combine coarse and fine time discretization, further enhancing the stability of the LTS schemes, particularly at higher LTS levels and during long time simulations. An ideal numerical test validates the efficiency of the improved LTS models, revealing their capability to improve computational speed while preserving conservation properties and reducing accuracy loss as LTS levels increase. We further apply the LTS models to cross-scale simulations of storm surges in the Northwest Pacific. Results show that compared to the global time-stepping (GTS) models, the LTS models significantly boost computational speed by up to 37%, all while delivering equally reliable computational outcomes. With expanding high-resolution coastal data and the need for high-resolution modeling, the improved LTS models show great potential for cross-scale storm surge modeling.

Comparative evaluation of meteorological inputs for improved storm surge modeling: A case study of tropical Cyclone Vayu

The selection of meteorological inputs in storm surge is crucial, with wind and pressure fields playing a significant role in energy transfer and the study area's bathymetry. While using observed track information for wind and pressure drop has been the standard approach for the past decade, recent studies have highlighted the need for atmospheric inputs from models like the Weather Research and Forecast model (WRF) for storm surge forecast. This study aims to compare the performance of a DELFT-3D FM storm surge model forced with inputs from IMD (India Meteorological Department) observed the best track and pressure drop (EXP-1) and wind and pressure fields from WRF (EXP-2) for Tropical Cyclone Vayu, which occurred in the southern Arabian Sea basin in June 2019. The study compares the simulated storm water levels and highlights the benefits of using time and space-varying wind and pressure input for improved surge representation. Results show that the WRF-DELFT setup outperforms the IMD-DELFT setup, particularly for tide gauge locations close to the storm eye. The simulated storm surge captures the intensified stage of Vayu and provides a more realistic representation than the model forced with IMD track data. However, biases and limitations, such as inadequate representation of land surface parameterization, are identified. The study suggests further exploring wave-induced effects on total water level and multiple cyclone scenarios to enhance wind speed and track displacement prediction accuracy and improved land-sea parameterization can help address these limitations.

Simulation and synoptic investigation of a severe dust storm originated from the Urmia Lake in the Middle East

Dried lake beds are one of the largest sources of dust in the world, causing environmental problems in the surrounding areas. In this study, the desiccated Urmia Lake was the primary source of dust for all nearby synoptic stations during the April 24-25, 2017 dust episode. Synoptic analysis revealed that the heavy dust storm was triggered by a strong Black Sea cyclone and a low-pressure system over central Iraq in conjunction with a vast high-pressure system. HYSPLIT-based trajectory analysis showed that high PM10 recorded over the Urmia Lake region on April 23-26, 2017, influenced western Azerbaijan, the south of the Caspian Sea, southwestern Kazakhstan, northwestern Uzbekistan, and western Turkmenistan. The dustiest air masses (PM10 > 400 µg m–3) affected the south of the Caspian Sea and western Azerbaijan. Furthermore, the WRF-Chem model was run to evaluate the spatial distribution of dust particles in the study region. The vertical profile revealed that the simulated dust concentration ascended to 5 km from the lake. The WRF-Chem dust schemes accurately simulated dust propagation and the vertical dust profile over Urmia Lake; however, the AFWA and GOCART dust schemes showed that PM10 fluctuating changes were earlier than the measured surface PM10 at five stations around Urmia Lake on April 23-26, 2017. Furthermore, the maximum amount anticipated by the model simulation was 12 h earlier than the maximum surface mass concentration of measured PM10 at the stations throughout the period.

Photogrammetric Investigation of Storm-Induced Erosion Process on Sandy Beach Profile in Medium-Scale Flume

In this study, laboratory experiments were conducted to investigate the influence of changes in storm wave height and water level on beach response in a medium-scale wave flume. A schematic storm was simulated (rising, apex, and waning phases). A non-intrusive photogrammetric method was used to collect high-resolution and synchronous data regarding the free surface water elevation and bed level, from which shoreline location, sandbar position, cross-shore sediment transport rates, and nonlinear wave parameters were derived. The cross-shore sediment transport was in agreement with previous laboratory measurements, including the monotonous exchange from foreshore erosion to shoaling zone accretion in most stages of the storm simulation. The surf zone was the main region supplying sediment for beach morphology modification and sandbar generation. The degree of storm erosion was not completely determined by the largest wave height and water level or the cumulative wave power of the apex phase. The largest gradients of the wave parameter sequence change occurred in the rising phase, and this was the main factor generating efficient beachface erosion. It induced an increase in sandbar size, accompanied by the cross-shore motion of maximum velocity amplitude, more violent disturbances of wave nonlinearity, and increased surf zone erosion, with these factors increasing beach instability and leading to more severe storm erosion. The large wave height and water level resulted in shoreline retreat, with a more significant swash zone erosion under a higher runup. The offshore sediment transport turned toward the onshore direction as the original large sandbar deteriorated under the decreasing wave parameter sequence in the waning phase.

Effects of Dust Storm and Wildfire Events on Phytoplankton Growth and Carbon Sequestration in the Tasman Sea, Southeast Australia

Dust storms and wildfires occur frequently in south-eastern Australia. Their effects on the ecology, environment and population exposure have been the focus of many studies recently. Dust storms do not emit ground-sequestered carbon, but wildfires emit significant quantities of carbon into the atmosphere. However, both natural events promote phytoplankton growth in water bodies because carbon, and other trace elements such as iron, deposit on the surface water of oceans. Carbon dioxide is reabsorbed by phytoplankton via photosynthesis. The carbon balance cycle due to dust storms and wildfires is not well known. Recent studies on the carbon emission of the 2019–2020 summer wildfires in eastern Australia indicated that this megafire event emitted approximately 715 million tonnes of CO2 (195 Tg C) into the atmosphere from burned forest areas. This study focusses on the association of dust storms and wildfires in southeastern Australia with phytoplankton growth in the Tasman Sea due to the February 2019 dust storm event and the 2019–2020 Black Summer wildfires. Central Australia and western New South Wales were the sources of the dust storm emission (11 to 16 February 2019), and the Black Summer wildfires occurred along the coast of New South Wales and Victoria (from early November 2019 to early January 2020). The WRF-Chem model is used for dust storm simulation with the AFWA (Air Force Weather Agency of the US) dust emission version of the GOCART model, and the WRF-Chem model is used for wildfire simulation with FINN (Fire Emission Inventory from NCAR) emission data. The results show the similarities and differences in the deposition of particulate matter, phytoplankton growth and carbon reabsorption patterns in the Tasman Sea from these events. A higher rate of deposition of PM2.5 on the ocean surface corresponds to a higher rate of phytoplankton growth. Using the WRF-Chem model, during the 5-day dust storm event in February 2019, approximately ~1230 tons of total dust was predicted to have been deposited in the Tasman Sea, while ~132,000 tons of PM10 was deposited in the early stage of the wildfires from 1 to 8 November 2019.

A New Pathway for Tornadogenesis Exposed by Numerical Simulations of Supercells in Turbulent Environments

Abstract A simulation of a supercell storm produced for a prior study on tornado predictability is reanalyzed for the purpose of examining the fine-scale details of tornadogenesis. It is found that the formation of a tornado-like vortex in the simulation differs from how such vortices have been understood to form in previous numerical simulations. The main difference between the present simulation and past ones is the inclusion of a turbulent boundary layer in the storm’s environment in the present case, whereas prior simulations have used a laminar boundary layer. The turbulent environment contains significant near-surface vertical vorticity (ζ > 0.03 s−1 at z = 7.5 m), organized in the form of longitudinal streaks aligned with the southerly ground-relative winds. The ζ streaks are associated with corrugations in the vertical plane in the predominantly horizontal, westward-pointing environmental vortex lines; the vortex-line corrugations are produced by the vertical drafts associated with coherent turbulent structures aligned with the aforementioned southerly ground-relative winds (longitudinal coherent structures in the surface layer such as these are well known to the boundary layer and turbulence communities). The ζ streaks serve as focal points for tornadogenesis, and may actually facilitate tornadogenesis, given how near-surface ζ in the environment can rapidly amplify when subjected to the strong, persistent convergence beneath a supercell updraft. Significance Statement In high-resolution computer simulations of supercell storms that include a more realistic, turbulent environment, the means by which tornado-like vortices form differs from the mechanism identified in prior simulations using a less realistic, laminar environment. One possibility is that prior simulations develop intense vortices for the wrong reasons. Another possibility could be that tornadoes form in a wide range of ways in the real atmosphere, even within supercell storms that appear to be similar, and increasingly realistic computer simulations are finally now capturing that diversity.

Integrating Geographic Information Systems and Hydrometric Analysis for Assessing and Mitigating Building Vulnerability to Flash Flood Risks

Climate change represents an overwhelming challenge that demands urgent intervention for effective resolution. Among the devastating consequences of climate change, flash floods stand out as one of the most catastrophic repercussions. This research focuses on two primary objectives. Firstly, it aims to evaluate the existing state of flash flood intensity (FFI) in a specific area of Hamamatsu city, Japan, which frequently experiences flash flood incidents. Secondly, it seeks to develop a mitigation plan to alleviate the adverse impacts of flooding on buildings within the area. To accomplish these objectives, four parameters related to FFI (namely, runoff depth, runoff velocity, runoff duration, and affected portion) were selected and estimated through the implementation of hydrological and hydrodynamic models. Additionally, a hydrological model was employed, utilizing a storm event with a return period of 100 years as input. During this simulated storm event, FFI values were calculated and categorized into four distinct levels. The results revealed that more than one-tenth of the examined buildings encountered the highest scale of FFI (category 4), while categories 3 and 4 combined accounted for nearly three-quarters of all buildings in the study area. Moreover, two mitigation strategies were adopted to prevent flooding within the buildings’ vicinity. Finally, this study provides a valuable framework and guidance for decision-makers and insurance companies, enabling them to assess the flood hazard status of buildings and make informed decisions accordingly.