Surge Probability Research Articles

Storm Surge Projection and Objective-Based Risk Management for Climate Change Adaptation along the US Atlantic Coast.

Climate change brings intense hurricanes and storm surges to the US Atlantic coast. These disruptive meteorological events, combined with sea level rise (SLR), inundate coastal areas and adversely impact infrastructure and environmental assets. Thus, storm surge projection and associated risk quantification are needed in coastal adaptation planning and emergency management. However, the projections can have large uncertainties depending on the planning time horizon. Excessive uncertainties arise from inadequately quantified ocean-climatic processes that control hurricane formation, storm track, and SLR in time of climate change. For this challenge, we propose an objective-based analytical-statistical approach using the National Oceanic and Atmospheric Administration's (NOAA)'s Sea, Lake, and Overland Surge from Hurricanes (SLOSH) model in scenario analysis of the storm surge impacts. In this approach, synthetic hurricanes (wind profile and track direction) are simulated to yield the likely range of the maximum envelope of water (MEOW), the maximum of the maximum (MOM), local wind speed, and directions. The surge height and time progression at a location are analyzed using a validated SLOSH model for a given adaptation or planning objective with a set of uncertainty tolerance. We further illustrate the approach in three case studies at Mattapoisett (MA), Bridgeport (CT), and Lower Chesapeake Bay along the US Atlantic coast. Simulated MOMs as the worst-case surge scenarios defined the long-term climate risk to the shoreside wastewater plants in Bridgeport and environmental assets in the Lower Chesapeake Bay. The wind-surge probability envelopes in simulated MEOWs provide location-specific estimates of the storm surge probability for local adaptation analysis at four locations in Lower Chesapeake Bay and at Mattapoisett of the southeastern Massachusetts coast. Using the constraints of local bathymetry and topography, the wind-surge probability curves and time progression also provide quantitative probability estimates for emergency response planning, as illustrated in the Mattapoisett case study.

Fourth-party logistics network design with demand surge: A greedy scenario-reduction and scenario-price based decomposition algorithm

The sharing economy has offered new viable approaches for firms to tackle demand surges. In this paper, we study a novel network design problem for the fourth-party logistics network (4PLN) to cope with unpredictable demand surges, in which temporary renting of logistics resources from a sharing market is available to supplement network capacity. A chance-constrained stochastic programming model is established to minimize the overall cost for 4PLN under service level targets. To deal with the difficulties brought by the evaluation of service level, we reformulate a mixed-integer linear programming (MILP) model, that can be solved straightly, based on the sample average approximation method. Then, to address the enormous challenge posed by the coupling of the basic NP-hard network design problem and the large number of demand scenarios in the MILP version, the Scenario-Price based Decomposition Algorithm (P-DA) is designed based on the key idea of decomposing the above-coupled factors. Further, to mitigate the performance deterioration brought on by large system scale and/or sample size, we expand our base algorithm to the Greedy Scenario-Reduction and Scenario-Price based Decomposition Algorithm (GR&P-DA) through the fast processing of chance constraints by introducing a greedy method. Through computational experiments, we demonstrate the effectiveness of our proposed model and algorithms, and we analyze the impact of various model parameters, including demand level, surge magnitude, surge probability, and rental price of third-party logistics resources, on 4PLN design. Furthermore, our comparative analysis reveals that renting logistics resources to address demand surges can significantly reduce costs and discovers that deploying resources in advance does not always provide an advantage, a temporary “case-by-case” planning approach for renting will give a more cost-saving scheme when surge probability is at a low level as it avoids idle resources by not being stuck with a conservative strategy.

Characteristics of astronomical tides and their modulation on sea level extremes along the Indian coast

In this study, long-term hourly sea-level records from 18 tide gauge stations during 1972–2007 were analyzed to study the characteristics of astronomical tides, sea-level trends, and extremes around India's mainland. The de-tided signals were used to estimate these parameters and study tide and surge interaction. The observed sea level depicts significant variability in daily, seasonal, and inter-annual time scales. Semidiurnal tides are the most dominant among the high-frequency tides, with an amplitude of up to 2.5 m for M2 and 0.75 m for S2 tides in the northwestern and northeastern continental shelf and reduced to 0.25 m in the south. The amplitude of diurnal tides (O1 and K1)is relatively weak (<0.25m) at all the stations. The annual harmonics dominate the seasonal cycle, with an amplitude of 0.7 m at Garden Reach in the northeastern continental shelf, decreases to 0.15 m at Tuticorin in the south, and remains small (<0.1 m) along the west coast of India. The amplitude of lunar nodal and perigee tides are significantly high (up to 25 mm) at several stations compared to the long-term global mean sea level trend (∼3.3 mm/y). The sea level trend is significantly positive (up to 4 mm/y) for Sagar Island, Diamond Harbor, Haldia, and Mangalore; negative (up to −3 mm/y) for Garden Reach and Okha, and in-significant (0.5 mm/y) for Mumbai, Vishakhapatnam, and Paradip. Interaction between the semidiurnal tides and surges was intense at most stations, with a high probability of surge peaks during the fall-tide conditions in the northern continental shelf, at rising-tidal conditions for the south-eastern and western peninsula, and co-occurring at high tide for southern stations. The degree of tide-surge interaction increases from south to north with an increase in tidal range and significant nodal and perigee tidal modulation.

Episodes of extreme international capital inflows in emerging and developing economies: The role of global economic policy uncertainty.

Based on annual data for 31 emerging and developing economies in the period 2000–2020, this paper explores the impact of global economic policy uncertainty on episodes of extreme international capital inflows. Following previous researches, we identify episodes of surges and stops. The results show that the global economic policy uncertainty can significantly increase the probability of surges and decrease the probability of stops in emerging and developing economies. The heterogeneity tests show that these effects vary with economic growth, financial development, the degree of economic globalization and global liquidity. Above effects are significant in the groups with higher economic growth, higher financial development, higher economic globalization and higher global liquidity. Further analyses show that as global economic policy uncertainty rises, its impact on surges and stops gradually declines. In addition, global economic policy uncertainty has a significant negative effect on the surge in advanced economies, which could confirm the above conclusion to a certain extent.

A Machine Learning Framework to Automate the Classification of Surge‐Type Glaciers in Svalbard

AbstractSurge‐type glaciers are present in many cold environments in the world. These glaciers experience a dramatic increase in velocity over short time periods, the surge, followed by an extended period of slow movement, the quiescence. This study aims at understanding why only few glaciers exhibit a transient behavior. We develop a machine learning framework to classify surge‐type glaciers, based on their location, exposure, geometry, climatic mass balance and runoff. We apply this approach to the Svalbard archipelago, a region with a relatively homogeneous climate. We compare the performance of logistic regression, random forest, and extreme gradient boosting (XGBoost) machine learning models that we apply to a newly combined database of glaciers in Svalbard. Based on the most accurate model, XGBoost, we compute surge probabilities along glacier centerlines and quantify the relative importance of several controlling features. Results show that the surface and bed slopes, ice thickness, glacier width, climatic mass balance, and runoff along glacier centerlines are the most significant features explaining surge probability for glaciers in Svalbard. A thicker and wider glacier with a low surface slope has a higher probability to be classified as surge‐type, which is in good agreement with the existing theories of surging. Finally, we build a probability map of surge‐type glaciers in Svalbard. The framework shows robustness on classifying surge‐type glaciers that were not previously classified as such in existing inventories but have been observed surging. Our methodology could be extended to classify surge‐type glaciers in other areas of the world.

Tropical cyclone storm surge probabilities for the east coast of the United States: a cyclone-based perspective

Abstract. To improve our understanding of the influence of tropical cyclones (TCs) on coastal flooding, the relationships between storm surge and TC characteristics are analyzed for 12 sites along the east coast of the United States. This analysis offers a unique perspective by first examining the relationship between the characteristics of TCs and their resulting storm surge and then determining the probabilities of storm surge associated with TCs based on exceeding certain TC characteristic thresholds. Using observational data, the statistical dependencies of storm surge on TCs are examined for these characteristics: TC proximity, intensity, path angle, and propagation speed, by applying both exponential and linear fits to the data. At each tide gauge along the east coast of the United States, storm surge is influenced differently by these TC characteristics, with some locations more strongly influenced by TC intensity and others by TC proximity. The correlation for individual and combined TC characteristics increases when conditional sorting is applied to isolate strong TCs close to a location. The probabilities of TCs generating surge exceeding specific return levels (RLs) are then analyzed for TCs passing within 500 km of a tide gauge, where between 6 % and 28 % of TCs were found to cause surge exceeding the 1-year RL. If only the closest and strongest TCs are considered, the percentage of TCs that generate surge exceeding the 1-year RL is between 30 % and 70 % at sites north of Sewell's Point, VA, and over 65 % at almost all sites south of Charleston, SC. When examining storm surge produced by TCs, single-variable regression provides a good fit, while multi-variable regression improves the fit, particularly when focusing on TC proximity and intensity, which are, probabilistically, the two most influential TC characteristics on storm surge.

CENTRIFUGAL COMPRESSOR PERFORMANCE MAPS TREATMENT FOR INTERNAL COMBUSTION ENGINES OPERATING CYCLE SIMULATION

Simulation of the supercharged internal combustion engines operation cycle is impossible without correct estimation of the supercharger operating parameters. Standard approach is to use specially prepared performance maps of compressor and turbine of the turbocharger, which are based on the experimental (or manufacturer’s) raw data. Centrifugal compressor performance maps interpolation, extrapolation and treatment provides challenging requirements as it is important to get correct simulation under such special conditions as compressor choke, rotating stall and pumping surge. At the same time it’s important to obtain the fast and stable calculations of the engine’s operating cycle. Blitz-PRO – online internal combustion engines operating cycle simulation service – offers supercharger performance maps preprocessing and implementation. It provides three different modes of compressor surge consideration during calculations: 1) full-scale surge mode using Moore-Greitzer approach; 2) mild surge mode with flexible adjustment; 3) “stable” mode, when the surge is neglected and the compressor constant-speed lines are extended from the rotating stall point to the lower mass flow region with the hyperbolic equation. Using the MAN 8G70ME-E engine 12140 kW, 82 rpm operating point as an example, the calculation results are compared for three modes of compressor surge consideration. The “stable” mode provides the fastest and the most stable calculations, while the calculations under the full-scale surge mode could generate the numerical (nonphysical) instability of calculations, which are caused by the high sensitivity of the two-stroke engines to the gas exchange processes as it is shown. The mild surge mode provides fast and stable enough calculation with the surge consideration ability, which could be assumed as the best solution for the given example. The researcher should choose between provided three modes of the centrifugal compressor surge consideration according to the calculations tasks, preferring “stable” mode for initial model setup and mild surge mode for the surge probability check, while the accurate compressor surge simulation needs further development.

Predicting Major Storm Surge Levels

The National Atmospheric and Oceanic Administration (NOAA) calculates the surge probability distribution along the coast from their long-term tidal stations. This process is sufficient for predicting the surge from common storms but tends to underestimate large surges. Across 23 long-term tidal stations along the East Coast of the United States, 100-year surges were observed 49 times, although they should have occurred only 23 times. We hypothesize that these 100-year surges are not the tail outcome from common storms but are actually caused by major hurricanes. Matching these 100-year surges with major hurricanes revealed that major hurricanes caused 43 of the 49 surges. We consequently suggest a revised approach to estimating the surge probability distribution. We used tidal data to estimate the probability of common surges but analyzed major hurricane surges separately, using the return rate of major hurricanes and the observed surge from each major hurricane to predict hurricane surges. The revision reveals that expected coastal flooding damage is higher than we thought, especially in the southeast United States.

Coastal Resilience Against Storm Surge from Tropical Cyclones

It is well known that seawalls are effective at stopping common storm surges in urban areas. This paper examines whether seawalls should be built to withstand the storm surge from a major tropical cyclone. We estimate the extra cost of building the wall tall enough to stop such surges and the extra flood benefit of this additional height. We estimate the surge probability distribution from six tidal stations spread along the Atlantic seaboard of the United States. We then measure how valuable the vulnerable buildings behind a 100 m wall must be to justify such a tall wall at each site. Combining information about the probability distribution of storm surge, the average elevation of protected buildings, and the damage rate at each building, we find that the value of protected buildings behind this 100 m wall must be in the hundreds of millions to justify the wall. We also examine the additional flood benefit and cost of protecting a km2 of land in nearby cities at each site. The density of buildings in coastal cities in the United States are generally more than an order of magnitude too low to justify seawalls this high. Seawalls are effective, but not at stopping the surge damage from major tropical cyclones.

The effects of natural structure on estimated tropical cyclone surge extremes

The past 12 years have seen significant steps forward in the science and practice of coastal flood analysis. This paper aims to recount and critically assess these advances, while helping identify next steps for the field. This paper then focuses on a key problem, connecting the probabilistic characterization of flood hazards to their physical mechanisms. Our investigation into the effects of natural structure on the probabilities of storm surges shows that several different types of spatial-, temporal-, and process-related organizations affect key assumptions made in many of the methods used to estimate these probabilities. Following a brief introduction to general historical methods, we analyze the two joint probability methods used in most tropical cyclone hazard and risk studies today: the surface response function and Bayesian quadrature. A major difference between these two methods is that the response function creates continuous surfaces, which can be interpolated or extrapolated on a fine scale if necessary, and the Bayesian quadrature optimizes a set of probability masses, which cannot be directly interpolated or extrapolated. Several examples are given here showing significant impacts related to natural structure that should not be neglected in hazard and risk assessment for tropical cyclones including: (1) differences between omnidirectional sampling and directional-dependent sampling of storms in near coastal areas; (2) the impact of surge probability discontinuities on the treatment of epistemic uncertainty; (3) the ability to reduce aleatory uncertainty when sampling over larger spatial domains; and (4) the need to quantify trade-offs between aleatory and epistemic uncertainties in long-term stochastic sampling.

Applying the expanded Le Chatelier-Braun principle to carbon oxidation in converter baths. 1. Stochastic structure of the harmonic series in the fluctuation of the variable oxidation component

In converter baths, the arrhythmic behavior in the oxidation of carbon and the probability of surges may be assessed from the dispersion of the fluctuation in the variable component of carbon’s oxidation rate ΔVC during intense oxidation. In such conditions, ΔVC may be regarded as a weakly ergodic random process. That approach permits investigation of the frequency series in the fluctuation of the random component ΔVC. It is represented by a practically continuous frequency sequence corresponding to the structural components of the converter process.

Regional attributes of hurricane surge response functions for hazard assessment

Accurate quantification of hurricane surge probabilities is critically important for coastal planning and design. Recently, the joint probability method has been shown to yield statistically reliable surge probabilities and has quickly become the method of choice for extreme-value surge analysis in the United States. A main disadvantage of the joint probability method is the requirement to have accurate computational surge simulations for a large array of hurricane conditions. Recently, this shortcoming has been overcome by using a variety of interpolation schemes to reduce the number of surge simulations required to an optimal sample for joint probability analysis. One interpolation scheme uses response functions, or physically based dimensionless scaling laws, that consider the relative impact of hurricane landfall position, central pressure, and storm size on surge magnitude at the location of interest. Here, the influence of regional changes in bathymetry on the physically based response function form is investigated. It will be shown that the influence of continental shelf width on surge generation along a continuous coast is coupled with the influence of storm size and that this coupled physical effect can be treated within the response functions via dimensionless scaling. The surge response function model presented here has an algebraic form for rapid calculation. This model performs well for the entire 600-km Texas coast, yielding accurate surge estimates (root-mean-square errors less than 0.22 m and R 2 correlations better than 0.97) with virtually no bias (mean error magnitudes less than 0.03 m).

A surge response function approach to coastal hazard assessment. Part 2: Quantification of spatial attributes of response functions

In response to the 2004 and 2005 hurricane seasons, surge risk assessment approaches have been re-evaluated to develop more rapid, reliable methods for predicting the risk associated with extreme hurricanes. Here, the development of dimensionless surge response functions relating surge to hurricane meteorological parameters is presented. Such response functions present an opportunity to maximize surge data usage and to improve statistical estimates of surge probability by providing a means for defining continuous probability density functions. A numerical modeling investigation was carried out for the Texas, USA coastline to develop physical scaling laws relating storm surge response with hurricane parameters including storm size, intensity, and track. It will be shown that these scaling laws successfully estimate the surge response at any arbitrary location for any arbitrary storm track within the study region. Such a prediction methodology has the potential to decrease numerical computation requirements by 75% for hurricane risk assessment studies.

Estimation of return periods for extreme sea levels: a simplified empirical correction of the joint probabilities method with examples from the French Atlantic coast and three ports in the southwest of the UK

The joint probability method (JPM) to estimate the probability of extreme sea levels (Pugh and Vassie, Extreme sea-levels from tide and surge probability. Proc. 16th Coastal Engineering Conference, 1978, Hamburg, American Society of Civil Engineers, New York, pp 911–930, 1979) has been applied to the hourly records of 13 tide-gauge stations of the tidally dominated Atlantic coast of France (including Brest, since 1860) and to three stations in the southwest of the UK (including Newlyn, since 1916). The cumulative total length of the available records (more than 426 years) is variable from 1 to 130 years when individual stations are considered. It appears that heights estimated with the JPM are almost systematically greater than the extreme heights recorded. Statistical analysis shows that this could be due: (1) to surge–tide interaction (that may tend to damp surge values that occur at the time of the highest tide levels), and (2) to the fact that major surges often occur in seasonal periods that may not correspond to those of extreme astronomical tides. We have determined at each station empirical ad hoc correction coefficients that take into account the above two factors separately, or together, and estimated return periods for extreme water levels also at stations where only short records are available. For seven long records, for which estimations with other computing methods (e.g. generalized extreme value [GEV] distribution and Gumbel) can be attempted, average estimations of extreme values appear slightly overestimated in relation to the actual maximum records by the uncorrected JPM (+16.7 ± 7.2 cm), and by the Gumbel method alone (+10.3 ± 6.3 cm), but appear closer to the reality with the GEV distribution (−2.0 ± 5.3 cm) and with the best-fitting correction to the JPM (+2.9 ± 4.4 cm). Because the GEV analysis can hardly be extended to short records, it is proposed to apply at each station, especially for short records, the JPM and the site-dependent ad hoc technique of correction that is able to give the closest estimation to the maximum height actually recorded. Extreme levels with estimated return times of 10, 50 and 100 years, respectively, are finally proposed at all stations. Because astronomical tide and surges have been computed (or corrected) in relation to the yearly mean sea level, possible changes in the relative sea level of the past, or foreseeable in the future, can be considered separately and easily added to (or deduced from) the extremes obtained. Changes in climate, on the other hand, may modify surge and tide distribution and hence return times of extreme sea levels, and should be considered separately.

Controls on glacier surging in Svalbard

AbstractThe geographical distribution of surge-type glaciers worldwide displays a remarkably non-random pattern. Surge-type glaciers tend to be concentrated in certain glacierized areas and to be completely absent in others. This observation suggests that special conditions are required for surges to occur. However, the factors controlling the spatial occurrence of surge-type behaviour are not known. To investigate this problem we performed probability statistical analysis on a sample population of 615 glaciers in Svalbard. The probability that a glacier in the sample population is surge-type is 36.4%. Within the sampled area there is a spatial variation in the concentration of surge-type glaciers. Several geometric and environmental factors associated with glaciers in the sample population were measured and tested to determine if they are related to the probability of surging. Of the geometric factors tested (length, slope, elevation, orientation and presence or absence of tributaries), only glacier length is related to surging, with surge probability increasing with increasing length. Elevated probabilities of surging were also found for glaciers associated with sedimentary subglacial rocks and sub-polar thermal regimes. The distributions of related factors were used to predict the spatial distribution of surge-type glaciers. However, in each case the individual factors were unable to reproduce the observed pattern of surge-type glacier distribution.

Controls on glacier surging in Svalbard

Abstract The geographical distribution of surge-type glaciers worldwide displays a remarkably non-random pattern. Surge-type glaciers tend to be concentrated in certain glacierized areas and to be completely absent in others. This observation suggests that special conditions are required for surges to occur. However, the factors controlling the spatial occurrence of surge-type behaviour are not known. To investigate this problem we performed probability statistical analysis on a sample population of 615 glaciers in Svalbard. The probability that a glacier in the sample population is surge-type is 36.4%. Within the sampled area there is a spatial variation in the concentration of surge-type glaciers. Several geometric and environmental factors associated with glaciers in the sample population were measured and tested to determine if they are related to the probability of surging. Of the geometric factors tested (length, slope, elevation, orientation and presence or absence of tributaries), only glacier length is related to surging, with surge probability increasing with increasing length. Elevated probabilities of surging were also found for glaciers associated with sedimentary subglacial rocks and sub-polar thermal regimes. The distributions of related factors were used to predict the spatial distribution of surge-type glaciers. However, in each case the individual factors were unable to reproduce the observed pattern of surge-type glacier distribution.

Characteristics of surge‐type glaciers

Glaciers can be divided into two classes according to their flow behavior: normal (relatively steady annually averaged flow rate) and surge‐type (pronounced cyclic flow variations having a typical periodicity of 10–100 years). We have examined the population statistics of 2356 glaciers in the St. Elias Mountains, Yukon Territory, Canada, and estimate that 151 (6.4%) of these glaciers are surge‐type. To explore how various glacier attributes are associated with surging, we compare the probability of surging associated with various subsets of the complete population to appropriate reference values. In this way, potential influences on surge tendency can be examined. For the 55 drainage basins analyzed, there is a pronounced spatial variation in the concentration of surge‐type glaciers, but no obvious environmental control can be evinced. Within the study area the greatest concentration lies in the northern St. Elias Mountains, a region of high topographic elevation that is experiencing rapid tectonic uplift. Analysis of the influence of length on surge tendency reveals that long glaciers have a significantly greater probability of being surge‐type than short glaciers. The surge probability increases monotonically from 0.61% for very short glaciers (0–1 km) to 65.1% for long glaciers (10–75 km). This result suggests that ice sheets and ice caps, or at least portions of them, should have a high probability of surging. Tributary glaciers have a greater tendency to surge than trunk glaciers, presumably because they may themselves be surge‐type and may additionally participate in surges of the trunk glacier. The nonrandom geographical distribution of surge‐type glaciers is not simply a consequence of the variation from basin to basin of the glacier length distribution. Surge‐type glaciers tend to have a higher overall elevation than normal glaciers: the elevation of the highest point of the accumulation zone, the elevation of the snow line, and the elevation of the lowest point of the ablation zone, on average, exceed the corresponding elevations for normal glaciers. There is no significant difference between the overall slopes of surge‐type and normal glaciers, although there is a tendency for surge‐type glaciers to have greater slope in the accumulation zone and lesser slope in the ablation zone than normal glaciers. Although the prevalent flow direction for glaciers in the Yukon data set is to the north, surge‐type glaciers tend to flow to the east and southeast. This orientation influence is probably explained by the fact that many of the longest glaciers also flow to the east and southeast.

Estimating extreme currents by combining tidal and surge probabilities

The need to obtain realistic estimates of extreme currents for the design of off-shore structures requires optimum use to be made of the data available. Methods of applying joint tide-surge probability techniques to the data are considered, and illustrated by analysis of one year of current meter observations in the North Sea. Tidal and meteorologically-induced vector components of the total observed current vector are isolated and their separate two-dimensional frequency distributions are computed. These distributions are then recombined to give probabilities of extreme total currents from several directions.