Storm Research Articles

Variability of Near-Surface Aerosol Composition in Moscow in 2020–2021: Episodes of Extreme Air Pollution of Different Genesis

During 2020–2021, a comprehensive experiment was conducted to study the composition of near-surface atmospheric aerosol in Moscow. The paper considers the experimental data together with synoptic and meteorological conditions. Attention is focused on six episodes of extremely high aerosol mass concentration values: in March and October 2020, as well in March, April, May and July 2021. In all these cases (and only in them), the average daily mass concentration of PM10 aerosol exceeded the Maximum Permissible Concentration (MPC) value (according to Russian standards, 60 μg/m3). The origin of the aerosol during these periods of extreme pollution is revealed, which is the main result of the work. It was shown that the July episode of 2021 was associated with a local intensive anthropogenic source that arose as a result of the active dismantling and demolition of multistory industrial buildings. The remaining spring and autumn episodes were caused by atmospheric transport of both smoke aerosol from various regions with strong biomass fires and dust aerosol from arid zones of the south of European territory of Russia (ETR) with dust wind storms. The cases of atmospheric pollution transport to Moscow region from the other regions are confirmed with the help of air mass transport trajectories (HYSPLIT 4 model) and MERRA-2 reanalysis data on black carbon and/or dust distribution in the atmosphere over ETR. Differences in the elemental composition of the near-surface aerosol of Moscow air during periods with extremely high aerosol concentrations are analyzed in comparison with each other and with unperturbed conditions for the season.

The modern wave-induced coastal staircase morphology along the western shores of the Dead Sea

This research provides insights into the formation of the coastal cliffs comprising the staircase morphology along the western coast of the Dead Sea as a result of its anthropogenic, regressive modern (last ~50 years) lake-level fall. The analysis of this morphology is based on observations and measurements of the impact of seasonal lake-level rises of 0–0.2 m and 0.7–2 m in normal versus exceptionally wet winters, respectively. We conducted repeated detailed topographic surveys of the shores for characterizing the evolving morphology with time, and coupled them with wind speed and wave amplitude during cliff formations. The detailed lake-level curve and the almost monotonic level decline allow associating each cliff with the exact year and season of its formation. This detailed chronology allowed, in turn, to identify and associate the pronounced and well-documented seasonality in the lake-level fall with the wind and wave data during specific seasons, years, and multi-year episodes. As a result, we can point at the controlling processes and environmental conditions for cliff formation. Under the regional Mediterranean climate with its distinct seasonality, winters are characterized by eastern Mediterranean low-pressure systems, generating the Jordan River flow in its northern headwaters and its discharge into the lake; this discharge controls the level fluctuations. At the Dead Sea area, these winter systems precipitate little. However, they generate high winds and storm waves that erode an additional coastal cliff at the base of the preexisting staircase every winter. Therefore, at the seasonal scale, a clear separation exists between (a) individual, cliff-forming, stronger wind storms operating only during winters under relatively stable water levels, and (b) the ~1-m annual lake-level fall, mostly during summers. This pronounced seasonality in both the wind and lake level (a) dictates the seasonal pace of cliff formation at vertical intervals similar to the magnitude (~1 m) of the annual lake-level fall by evaporation and artificial brine diversion, and (b) facilitates the cliff separation in the landscape. This regular pacing by winter storms, the minor lake-level rises, and the annual evaporation and diversion support the preservation of the individual cliffs that assemble into the staircase morphology in the coarse-clastic delta fronts and mudflats characterizing the recently emerging coast. Anomalous lake-level rises during exceptionally wet winters are more erosive, even with regular wind storms; they create the largest lateral erosion. Under the emerging shore topography, which results from the steep bathymetry, the outcome is cliffs often much higher than the respective amplitude of their causative lake-level rises. This depends on the duration of the rise and of individual storms and indicates that under the variance of the modern hydroclimatology, the abnormal seasonal lake-level rises operating with regular winter storms, can aggressively erode the shore.Proposed plans to stabilize or raise the falling water level of the Dead Sea would induce coastal erosion and stream incision, which would threaten the existing highway and other infrastructure built close to its shore.

Modeling the impact of sea level rise on maximum water elevation during storm surge events: a closer look at coastal embayments

Storm-surge models are commonly used to assess the impacts of hurricanes and coastal storms in coastal areas. Including the impact of the projected future sea level rise (SLR) in these models is a necessary step for a realistic flood risk assessment. Commonly, SLR is superimposed linearly on the simulated water elevation. This approach, while efficient, may lead to inaccuracies. Furthermore, developing a new model with updated data (e.g., boundary conditions, bathymetry) that include the effects of SLR (i.e., nonlinear approach) is time consuming. We compare the linear and nonlinear approaches to include the effect of SLR in predicting maximum water/flood elevations (MWE) as a result of storm surge. After a simplified theoretical analysis, a number of idealized cases based on the typical coastal bodies of water are modeled to assess the impact of SLR on MWE using the linear superposition and nonlinear approaches. Additionally, two case studies are carried out: Narragansett Bay, RI, and Long Island Sound, CT (USA). Results show that for the idealized cases with variable depth, in general, the linear superposition of SLR to MWE is conservative (i.e., predicts a larger flood elevation) relative to the nonlinear approach. However, if a constant depth is considered, results are not consistent (i.e., linear superposition can overestimate or underestimate MWE, and the results depended on the geometry). The simulated MWE from the Narragansett Bay simulation confirms the outcome of idealized cases showing that linear assumption is conservative up to 10% relative to the nonlinear approach. For this study, Hurricane Sandy and a synthetic storm from the US Army Corps of Engineers North Atlantic Comprehensive Coastal Study (NACCS) dataset are simulated. Long Island Sound model results are also consistent with the idealized case. In general, based on the results of the idealized and real case studies, a discrepancy of up to 10% between the linear and nonlinear approaches is expected in estimation of MWE which can be under- or over-estimation of flood elevation, depending on the geometry.

Predicted Sea‐Level Rise‐Driven Biogeomorphological Changes on Fire Island, New York: Implications for People and Plovers

AbstractForecasting biogeomorphological conditions for barrier islands is critical for informing sea‐level rise (SLR) planning, including management of coastal development and ecosystems. We combined five probabilistic models to predict SLR‐driven changes and their implications on Fire Island, New York, by 2050. We predicted barrier island biogeomorphological conditions, dynamic landcover response, piping plover (Charadrius melodus) habitat availability, and probability of storm overwash under three scenarios of shoreline change (SLC) and compared results to observed 2014/2015 conditions. Scenarios assumed increasing rates of mean SLC from 0 to 4.71 m erosion per year. We observed uncertainty in several morphological predictions (e.g., beach width, dune height), suggesting decreasing confidence that Fire Island will evolve in response to SLR as it has in the past. Where most likely conditions could be determined, models predicted that Fire Island would become flatter, narrower, and more overwash‐prone with increasing rates of SLC. Beach ecosystems were predicted to respond dynamically to SLR and migrate with the shoreline, while marshes lost the most area of any landcover type compared to 2014/2015 conditions. Such morphological changes may lead to increased flooding or breaching with coastal storms. However—although modest declines in piping plover habitat were observed with SLC—the dynamic response of beaches, flatter topography, and increased likelihood of overwash suggest storms could promote suitable conditions for nesting piping plovers above what our geomorphology models predict. Therefore, Fire Island may offer a conservation opportunity for coastal species that rely on early successional beach environments if natural overwash processes are encouraged.

Comparison of Extreme Coastal Flooding Events between Tropical and Midlatitude Weather Systems in the Delaware and Chesapeake Bays for 1980–2019

Abstract Coastal flooding is one of the most costly and deadly natural hazards facing the U.S. mid-Atlantic region today. Impacts in this heavily populated and economically significant region are caused by a combination of the location’s exposure and natural forcing from storms and sea level rise. Tropical cyclones (TCs) and midlatitude (ML) weather systems each have caused extreme coastal flooding in the region. Skew surge was computed over each tidal cycle for the past 40 years (1980–2019) at several tide gauges in the Delaware and Chesapeake Bays to compare the meteorological component of surge for each weather type. Although TCs cause higher mean surges, ML weather systems can produce surges just as severe and occur much more frequently, peaking in the cold season (November–March). Of the top 10 largest surge events, TCs account for 30%–45% in the Delaware and upper Chesapeake Bays and 40%–45% in the lower Chesapeake Bay. This percentage drops to 10%–15% for larger numbers of events in all regions. Mean sea level pressure and 500-hPa geopotential height (GPH) fields of the top 10 surge events from ML weather systems show a low pressure center west-southwest of “Delmarva” and a semistationary high pressure center to the northeast prior to maximum surge, producing strong easterly winds. Low pressure centers intensify under upper-level divergence as they travel eastward, and the high pressure centers are near the GPH ridges. During lower-bay events, the low pressure centers develop farther south, intensifying over warmer coastal waters, with a south-shifted GPH pattern relative to upper-bay events. Significance Statement Severe coastal flooding is a year-round threat in the U.S. mid-Atlantic region, and impacts are projected to increase in magnitude and frequency. Research into the meteorological contribution to storm surge, separate from mean sea level and tidal phase, will increase the scientific understanding and monitoring of changing atmospheric conditions. Tropical cyclones and midlatitude weather systems both significantly impact the mid-Atlantic region during different times of year. However, climate change may alter the future behavior of these systems differently. Understanding the synoptic environment and quantifying the surge response and subbay geographic variability of each weather system in this region will aid in public awareness, near-term emergency preparation, and long-term planning for coastal storms.

Analysis of underwater noise due to hurricanes in the northern Gulf of Mexico

The proposed study will use broadband deep-water ambient sound field information collected by stationary and mobile passive acoustic monitoring platforms during a hurricane passage in the northern Gulf of Mexico. EARS buoys will be used for stationary data collection and reconnaissance flights of Slocum gliders equipped with hydrophones for mobile collection. The goal is to use these data to reconstruct storm wind speed distributions and to quantify changes in the ocean environment during hurricanes and tropical storms. The majority of this research is the signal processing involved in analyzing the collected noise data. Signal processing techniques employed include Fourier transform frequency analysis, Wavelet transform signal analysis, Bayesian signal processing, and machine learning, all of which have been applied to similar acoustic data in the past. Machine learning techniques are used to compare and correlate analyses from both bottom-moored EARS and moving glider data. Comparisons of data from gliders and from stationary EARS buoys can be made with similar analyses of recorded stationary EARS buoy data from the same and nearby locations over several recent years, now with a focus on estimating wind speeds from acoustic noise analysis. [This material is based upon the work supported by the Office of the Under Secretary of Defense for Research and Engineering under Award No. FA9550-21-1-0215.]

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

Bound to the Land: Cove Fort in Kesler Family History and Memory

Bound to the Land: Cove Fort in Kesler Family History and Memory

Automatic mapping of Italian forest disturbances between 1985 and 2019 using Landsat imagery and Google Earth Engine

Forests play a key role in the carbon cycle and the fight against climate change. Long-term monitoring of forest dynamics represents a key element for understanding forests transformations due to forest harvestings and disturbances including fires, wind storms, frost or drought events, and pathogen attacks. This work aims at mapping and evaluating the forest disturbances that have occurred in Italy since 1985, using Landsat satellite imagery and apposite algorithms. We predicted about 1.8 million forest disturbances occurring during the observation period. Disturbances ranged between 27.923 ha in 2014 and 261.733 ha in 1985. Most of the forest disturbances have been identified in Sicilia and Calabria. Commission errors fluctuated between 29% in 2012 and 65% in 2001 while omission errors were between 8% in 2014 and 88% in 2003. The results that we present in this work can increase our understanding of Italian forests, and serve as basis for future research, while the methodology we applied can support the production of official statistics on forest disturbances.

MODERN CHANGES COUNTOUR OF COASTLINE SPITS OF THE SEA OF AZOV

Problem Statement and Purpose. At present the studying of the shores and their dynamics configuration and especially the most active parts – the heads of the Azov spits, is caused by both reasons dynamic and geopolitical changes as well. A large number of spits is a characteristic feature of the shores of the Azov Sea. There are spits all over the coast of the Azov Sea. However, spits oriented deep into the Azov Sea shore line there are just on the northern sea area. The reason of intense lithodynamic processes in the coastal zone of the Azov is the high velocities of currents in the bottom layer as a result of storm winds. In the coastal zone of the sea the cycle of abrasion rate from 1 to 4 m per year (sometimes up to 15m per year) was established. Fluctuations in the level of the Azov Sea are provides by many natural factors acting simultaneously and input to abrasion processes. The largest range of fluctuations is associated with wind activity phenomena. Data & Methods. In the paper takes into account the regular field studies of the position of the coastline of the distal parts – the streamer heads using of satellite radio navigation systems – GPS receivers. The radio navigation equipment recorded the exact route along the interaction zone. The sampling was carried out in a calm period on the sea surface. The data in situ (recorded routes) were compared with retrospective data of GIS systems. Cartographic materials, various specialized sources of information and satellite images were also used for the further analysis. Results. In fact, this paper is an attempt for the first time analysis of the available retrospective, modern and satellite monitoring data for the comparing of the dynamics of the Azov spits in frame of Ukraine area. As an example the dynamics of the coast line of the spits: Biryuchiy Island, Obitochnaya, Berdyanskaya and Belosaraiskaya were done. The study of the modern state of the Ukrainian coast line in the Azov Sea, the possible degradation of the coastal part of the sea and the reasons causes of it isessential for the sustainable development of the economy, the recreational potential of the region, the social level of the population and the geopolitical situation in the event of delimitation in the Azov Sea.

Morphological wave attenuation of the nature-based flood defense: A case study from Chongming Dongtan Shoal, China

The risk of coastal storm flooding is deteriorating under global warming, especially for the heavily urbanized deltaic cities, like Shanghai. The Nature-Based Flood Defense (NBFD), as an eco-friendly design alternative for hard infrastructure against coastal flooding, is gaining attention. Nevertheless, the vulnerability of saltmarsh due to the biological instability, resulting in the uncertainties on coastal protection, is considered the bottleneck challenge that hinders the broad application of the NBFD concept. We argue that except for direct wave attenuations by the above-ground vegetation during storms, the gradual sediment trapping and consolidating during the non-storm period is a more crucial function of coastal saltmarsh, which mitigates storm waves by forming a broader and higher intertidal morphology. This benefit is an important value of saltmarsh-based coastal protection but is largely neglected in many NBFD studies. Taking Chongming Dongtan Shoal (CDS) as a case study, we demonstrated that over 2/3th wave attenuation during storms is contributed by the saltmarsh morphology, and less than 1/3th is from the saltmarsh vegetation. The relative contribution of the saltmarsh morphology on wave mitigation is even enhanced under the increasing storm grades from 100 yrs. to 5000 yrs. return levels. To promote this idea for broader application, the cost-benefit analysis of three artificial NBFD solutions (e.g., submerged breakwater, timber piles, and sand nourishment) are compared. We identified an optimal measure of the submerged breakwater for CDS, which minimizes the ecological impact and maximizes the cost-benefit. Moreover, the wave-free zone behind the breakwater increases the chance of vegetation establishment, helps suspended sediment trapping, hence fostering a beneficent cycle for saltmarsh restoration. In summary, ignoring the contribution of saltmarsh morphology on wave attenuation largely underestimated the benefits of vegetation-based coastal protection, which should be greatly emphasized to provide a solid basis for developing NBFD.

Wind effect on zooplankton distribution in the estuary of the Pregolya River (the Baltic Sea basin) after technogenic transformation of its riverbed

In 2014–2018, large-scale hydrotechnical works were carried out in the estuary of the Pregolya River. The structural changes in the summer zooplankton in the river mouth in 2019 were revealed in comparison with the data obtained prior the riverbed transformation. In June 2019, zooplankton total abundance and biomass were of (136 ± 111) thousand ind.·m−3 and (860 ± 840) mg·m−3, respectively. It is comparable with mean annual data of 1996–2006: (71 ± 66) thousand ind.·m−3 and (664 ± 337) mg·m−3, respectively. In the summer of 2019, for the first time, the euryhaline species Eurytemora affinis inhabiting the Vistula Lagoon was recorded in the Novaya Pregolya branch. The presence of this species in the river branches, as well as the values of water salinity, may result from an increase in the frequency or intensity of water surges into the river from the Vistula Lagoon. In this regard, the wind conditions in 1998–2006 and 2011–2019 were analyzed. In 2011–2019, there was no increase in the frequency of winds acting along the effective surge direction (southwest and west ones) compared with those in 1996–2006. However, a rise in the frequency of storms was noted, inter alia in summer. Westerly storm winds cause upstream water inflow from the Vistula Lagoon and channel. Probably, the destruction of river macrophyte communities, concreting of embankments, and a change in the channel bottom configuration affected the intensity of water inflow from the lagoon into the river branches during surges and became the main factor affecting the distribution of euryhaline species from the lagoon in the river branches.

Impact of Coastal Disasters on Women in Urban Slums: A New Index

Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.

Isotopic variability in tropical cyclone precipitation is controlled by Rayleigh distillation and cloud microphysics

Tropical cyclones produce rainfall with extremely negative isotope values (δ18O and δ2H), but the controls on isotopic fractionation during tropical cyclones are poorly understood. Here we studied the isotopic composition of rainfall at sites across central Texas during Hurricane Harvey (2017) to better understand these processes. Rainfall δ18O trend towards more negative values as a result of Rayleigh distillation of precipitation-generating airmasses as they travel towards the center of the storm. Superimposed on these gradual changes are abrupt isotopic shifts with exceptionally low deuterium excess values. These appear to be controlled by microphysical processes associated with the passage of spiral rainbands over the sampling locations. Isotope-enabled climate modeling suggests that it may be possible to identify the signature of tropical cyclones from annually resolved isotopic proxy records, but will depend on the size of the storm and the proximity of the site to the core of the storm system.

Vulnerability and Risk Assessment to Climate Change in Sagar Island, India

Inhabitants of low-lying islands face increased threats due to climate change as a result of their higher exposure and lesser adaptive capacity. Sagar Island, the largest inhabited estuarine island of Sundarbans, is experiencing severe coastal erosion, frequent cyclones, flooding, storm surges, and breaching of embankments, resulting in land, livelihood, and property loss, and the displacement of people at a huge scale. The present study assessed climate change-induced vulnerability and risk for Sagar Island, India, using an integrated geostatistical and geoinformatics-based approach. Based on the IPCC AR5 framework, the proportion of variance of 26 exposure, hazard, sensitivity, and adaptive capacity parameters was measured and analyzed. The results showed that 19.5% of mouzas (administrative units of the island), with 15.33% of the population at the southern part of the island, i.e., Sibpur–Dhablat, Bankimnagar–Sumatinagar, and Beguakhali–Mahismari, are at high risk (0.70–0.80). It has been concluded that the island has undergone tremendous land system transformations and changes in climatic patterns. Therefore, there is a need to formulate comprehensive adaptation strategies at the policy- and decision-making levels to help the communities of this island deal with the adverse impacts of climate change. The findings of this study will help adaptation strategies based on site-specific information and sustainable management for the marginalized populations living in similar islands worldwide.

Sources, Mechanisms, and Timescales of Sediment Delivery to a New England Salt Marsh

AbstractThe availability and delivery of an external clastic sediment source is a key factor in determining salt marsh resilience to future sea level rise. However, information on sources, mechanisms, and timescales of sediment delivery are lacking, particularly for wave‐protected mesotidal estuaries. Here we show that marine sediment mobilized and delivered during coastal storms is a primary source to the North and South Rivers, a mesotidal bar‐built estuary in a small river system impacted by frequent, moderate‐intensity storms that is typical to New England (United States). On the marsh platform, deposition rates, clastic content, and dilution of fluvially‐sourced contaminated sediment by marine material all increase down‐estuary toward the inlet, consistent with a predominantly marine‐derived sediment source. Marsh clastic deposition rates are also highest in the storm season. We observe that periods of elevated turbidity in channels and over the marsh are concurrent with storm surge and high wave activity offshore, rather than with high river discharge. Flood tide turbidity also exceeds ebb tide turbidity during storm events. Timescales of storm‐driven marine sediment delivery range from 2.5 days to 2 weeks, depending on location within the estuary; therefore the phasing of storm surge and waves with the spring‐neap cycle determines how effectively post‐event suspended sediment is delivered to the marsh platform. This study reveals that sediment supply and the associated resilience of New England mesotidal salt marshes involves the interplay of coastal and estuarine processes, underscoring the importance of looking both up‐ and downstream to identify key drivers of environmental change.

Boulder Dislodgement During Coastal Storms and Tsunamis: Insights From a New Ensemble Model

AbstractBoulders are excellent candidate deposits to study coastal inundation events by storms and tsunamis due to their significant preservation potential. However, it is difficult to infer how and what forcing dislodged the boulder. We present a new model that enables ensemble and Monte‐Carlo‐type simulations to study the sensitivity of boulder, the fluid flow, and environmental parameters. Our examples show that boulder transport is complex and nonlinear, and to acknowledge the uncertainties of the boulder's preexisting transport conditions, a range of velocities and environmental parameters should be used to quantify the flow that caused boulder dislodgement.

Monitoring of Climatic Factors Affecting on Dust & Sand Storm in Tehran Province

In this study, according to the objectives and implementation method, climatic factors affecting ‎the dust phenomenon in active meteorological stations in Tehran province for a period of 30 years ‎were studied and analyzed. The results showed that in Mehrabad meteorological station, ‎temperature, humidity, rainfall, evaporation factors were directly related to DSI indices, wind ‎trend and dust storm changes, Lancaster, wind and storm diagrams, SPEI and the increase of ‎drought indices in the statistical period increased with temperature, evaporation and decrease. ‎Rainfall and humidity are proportional. DSI dust storm indexes were compared to 1 and ‎Lancaster drought index was compared to 50 and SPEI index was compared positively and ‎negatively in different years of the statistical period in the region and was classified in terms of ‎drought and wet season. The results of monthly and annual changes in wind trend and dust ‎storms showed that the region has no wind in all months and seasons with a speed of more than ‎‎20 meters per second. In terms of wind speed and frequency percentage, the highest wind speed ‎was related to late May and early June, and the lowest wind speed was related to late December ‎and early January. In addition, according to the changes in the wind trend and the documents of the ‎winds and thunderstorms, the prevailing wind direction in the region was from the west.‎

Using a Cost-Effective Approach to Increase Background Ensemble Member Size within the GSI-Based EnVar System for Improved Radar Analyses and Forecasts of Convective Systems

Abstract A valid time shifting (VTS) method is explored for the GSI-based ensemble variational (EnVar) system modified to directly assimilate radar reflectivity at convective scales. VTS is a cost-efficient method to increase ensemble size by including subensembles before and after the central analysis time. Additionally, VTS addresses common time and phase model error uncertainties within the ensemble. VTS is examined here for assimilating radar reflectivity in a continuous hourly analysis system for a case study of 1–2 May 2019. The VTS implementation is compared against a 36-member control experiment (ENS-36), to increase ensemble size (3 × 36 VTS), and as a cost-savings method (3 × 12 VTS), with time-shifting intervals τ between 15 and 120 min. The 3 × 36 VTS experiments increased the ensemble spread, with largest subjective benefits in early cycle analyses during convective development. The 3 × 12 VTS experiments captured analysis with similar accuracy as ENS-36 by the third hourly analysis. Control forecasts launched from hourly EnVar analyses show significant skill increases in 1-h precipitation over ENS-36 out to hour 12 for 3 × 36 VTS experiments, subjectively attributable to more accurate placement of the convective line. For 3 × 12 VTS, experiments with τ ≥ 60 min met and exceeded the skill of ENS-36 out to forecast hour 15, with VTS-3 × 12τ90 maximizing skill. Sensitivity results demonstrate preference to τ = 30–60 min for 3 × 36 VTS and 60–120 min for 3 × 12 VTS. The best 3 × 36 VTS experiments add a computational cost of 45%–67%, compared to the near tripling of costs when directly increasing ensemble size, while best 3 × 12 VTS experiments save about 24%–41% costs over ENS-36. Significance Statement The purpose of this work is to study a valid time shifting method to improve the prediction of severe convective storm systems over the continental United States. This method improves ensemble-based radar reflectivity analyses by including ensemble member information at times before and after the analysis time, thereby increasing the ensemble size at just a fractional added computational cost. The results show the method can boost the accuracy of high-resolution convection prediction out to at least 12 h. This case study motivates future systematic testing in a real-time setting and potential implementation to enhance the U.S. operational ensemble-based convection-allowing forecast model and data assimilation system.

Modelling the Effect of ‘Roller Dynamics’ on Storm Erosion: Sylt, North Sea

Coastal storm erosion can lead to episodic morphological changes and hinterland flooding that requires sustainable management. An accurate estimation of storm erosion can determine the success of hazard mitigation strategies. Two morphological models, Delft3D and XBeach, were applied separately to a stormy period with “Roller” and “No Roller” wave dynamics activated, to estimate erosion of the beach and dune system on the Sylt island. This is the first numerical impact assessment of roller dynamics on coastal erosion using the two models. The choice of model had more impact on the hydrodynamic and morphological predictions than the option to include or omit roller dynamics. Agreement between measured and simulated waves was higher in Delft3D (R2 > 0.90 and RMSE < 0.15 m) than XBeach. Storm erosion in both models had the highest sensitivity to the roller parameter Beta. Both models predicted a similar storm erosion pattern along the coast, albeit different magnitudes. It is found that Delft3D cannot produce comparable storm erosion to XBeach, when the roller dynamics and avalanching are considered. Delft3D is less sensitive to the roller dynamics than XBeach. Including roller dynamics in Delft3D increased storm erosion up to 31% and in XBeach decreased the erosion down to 58% in the nearshore area, while the erosion in the dune area increased up to 13% in Deflt3D and up to 97% in XBeach. Both models are skilled in simulating storm impact. For the simulation of a storm period with intermittent calm periods, it is suggested that applying a time-varying parameter setting for wave dynamics and sediment transport to capture storm erosion and post-storm beach recovery processes could improve results. Such a modelling approach may ultimately increase the accuracy of estimating storm erosion to support coastal management activities (e.g., sand nourishment volume).