On the recurvature of tropical cyclones and the storm surge problem in Bangladesh

The disproportionality of the large frequency of occurrence of severe storm surges on the coast of Bangladesh is highlighted. The reasons for the recurvature of these storms towards the Bangladesh coast and the associated severe surges are discussed in this paper.Atmospheric Environment Service, Ice Center, Environment Canada, 373 Sussex Drive, Ottawa, Ontario, Canada K1A 0H3.     

Advances in surrogate modeling for storm surge prediction: storm selection and addressing characteristics related to climate change

This paper establishes various advancements for the application of surrogate modeling techniques for storm surge prediction utilizing an existing database of high-fidelity, synthetic storms (tropical cyclones). Kriging, also known as Gaussian process regression, is specifically chosen as the surrogate model in this study. Emphasis is first placed on the storm selection for developing the database of synthetic storms. An adaptive, sequential selection is examined here that iteratively identifies the storm (or multiple storms) that is expected to provide the greatest enhancement of the prediction accuracy when that storm is added into the already available database. Appropriate error statistics are discussed for assessing convergence of this iterative selection, and its performance is compared to the joint probability method with optimal sampling, utilizing the required number of synthetic storms to achieve the same level of accuracy as comparison metric. The impact on risk estimation is also examined. The discussion then moves to adjustments of the surrogate modeling framework to support two implementation issues that might become more relevant due to climate change considerations: future storm intensification and sea level rise (SLR). For storm intensification, the use of the surrogate model for prediction extrapolation is examined. Tuning of the surrogate model characteristics using cross-validation techniques and modification of the tuning to prioritize storms with specific characteristics are proposed, whereas an augmentation of the database with new/additional storms is also considered. With respect to SLR, the recently developed database for the US Army Corps of Engineers’ North Atlantic Comprehensive Coastal Study is exploited to demonstrate how surrogate modeling can support predictions that include SLR considerations.     

Mitigating the effects of storm surges generated by tropical cyclones: A proposal

One of the regions of the globe that is frequently and very significantly affected by storm surges is Bangladesh. These high amplitude water-level oscillations are generated by the meteorological forcing fields due to tropical cyclones in the Bay of Bengal. The tide also plays a significant role in determining the time history of the total water level. Due to the greenhouse warming associated with the increasing levels of carbon dioxide in the atmosphere, it is expected that the frequency and intensity of tropical cyclones in the Bay of Bengal will increase substantially within the next 50 to 100 years. This new breed of tropical cyclones, referred to as hypercanes, will generate storm surges on the coast of Bangladesh which could attain amplitudes of up to 15 m, much greater than the present-day amplitudes of up to 6 m. Various mitigation procedures are discussed and compared.     

On the accuracy of atmospheric forcing for extra-tropical storm surge prediction

The ability of the SMARA storm surge numerical prediction system to reproduce local effects in estuarine and coastal winds was recently improved by considering one-way coupling of the air–sea momentum exchange through the wave stress, and best forecasting practices for downscaling. The inclusion of long period atmospheric pressure forcing in tide and tide/surge calculations corrected a systematic error in the surge, produced by the South Atlantic Ocean quasi-stationary pressure patterns. The maximum forecast range for the storm surge at Buenos Aires provided by the real-time use of water level observations is approximately 12 h. The best available water level prediction is the 6-h forecast (nowcast) based on the closest water level observations. The 24-h forecast from the numerical models slightly improves this nowcast. Although the numerical forecast accuracy degrades after the first 48 h, the improvement to the full range observation-based prediction is maintained at the inner Río de la Plata area and extends to the first 3 days at the intermediate navigation channels.     

Simulation of extreme water levels in response to tropical cyclones along the Indian coast: a climate change perspective

Natural Hazards - Indian coasts are often influenced by life-threatening water levels caused by tropical cyclones. To have a better long-term planning for the coastal districts due to tropical...     

Tropical cyclones,global climate change and the role of Quaternary studies

The number and types of late Quaternary records of tropical cyclones (TCs) and temperate storms have been increasing globally over the past 10 years. There are now numerous such records for the Atlantic Ocean (USA) and Gulf of Mexico and Caribbean Sea, South Pacific Ocean, and a fewer number from the northwest Pacific and Indian Ocean regions. The most obvious characteristic of these records is that many reveal extended alternating periods of greater and lesser TC activity over the past 6000 years. The length of these phases of relative inactivity and greater activity depends on the chronological resolution of the record, with the coarser‐resolution ones displaying multi‐century to millennial‐scale episodes and the high‐resolution records displaying decadal to centennial‐scale oscillations. In several instances the likely causes of these alternating periods of TC behaviour have been attributed to different phases of climate when El Niños and La Niñas dominated or to longer‐term variations in sea surface temperatures and possibly solar forcing. The picture emerging from these records is that TC behaviour is not entirely stochastic over the long term and that any simulations of long‐term TC behaviour need to account for these climatic influences. Incorporation of these observations, and the many more needed, is important for understanding the future behaviour of TCs. Copyright © 2011 John Wiley & Sons, Ltd.     

Improvements in storm surge surrogate modeling for synthetic storm parameterization,node condition classification and implementation to small size databases

Surrogate models are becoming increasingly popular for storm surge predictions. Using existing databases of storm simulations, developed typically during regional flood studies, these models provide fast-to-compute, data-driven approximations quantifying the expected storm surge for any new storm (not included in the training database). This paper considers the development of such a surrogate model for Delaware Bay, using a database of 156 simulations driven by synthetic tropical cyclones and offering predictions for a grid that includes close to 300,000 computational nodes within the geographical domain of interest. Kriging (Gaussian Process regression) is adopted as the surrogate modeling technique, and various relevant advancements are established. The appropriate parameterization of the synthetic storm database is examined. For this, instead of the storm features at landfall, the features when the storm is at closest distance to some representative point of the domain of interest are investigated as an alternative parametrization, and are found to produce a better surrogate. For nodes that remained dry for some of the database storms, imputation of the surge using a weighted k nearest neighbor (kNN) interpolation is considered to fill in the missing data. The use of a secondary, classification surrogate model, combining logistic principal component analysis and Kriging, is examined to address instances for which the imputed surge leads to misclassification of the node condition. Finally, concerns related to overfitting for the surrogate model are discussed, stemming from the small size of the available database. These concerns extend to both the calibration of the surrogate model hyper-parameters, as well as to the validation approaches adopted. During this process, the benefits from the use of principal component analysis as a dimensionality reduction technique, and the appropriate transformation and scaling of the surge output are examined in detail.

     

Modelling a storm surge under future climate scenarios: case study of extratropical cyclone Gudrun (2005)

Weather Research and Forecasting atmosphere model and Finite Volume Community Ocean Model were for the first time used under the pseudo-climate simulation approach, to study the parameters of an extreme storm in the Baltic Sea area. We reconstructed the met-ocean conditions during the historical storm Gudrun (which caused a record-high +275 cm surge in Pärnu Bay on 9 January 2005) and simulated the future equivalent of Gudrun by modifying the background conditions using monthly mean value differences in sea surface temperature (SST), atmospheric air temperature and relative humidity from MIROC5 in accordance with the IPCC scenarios RCP4.5 and RCP8.5 for 2050 and 2100. The simulated storm route and storm surge parameters were in good accordance with the observed ones. Despite expecting the continuation of recently observed intensification of cyclonic activity in winter months, our numerical simulations showed that intensity of the strongest storms and storm surges in the Baltic Sea might not increase by the end of twenty-first century. Unlike tropical cyclones, which derive their energy from the increasing SST, the extratropical cyclones (ETCs) harvest their primary energy from the thermal differences on the sides of the polar front, which may decrease if the Arctic warms up. For climatological generalizations on future ETCs, however, it is necessary to re-calculate a larger number of storms, including those with different tracks and in different thermal conditions.     

Assessing storm surge impacts on coastal inundation due to climate change: case studies of Baltimore and Dorchester County in Maryland

Natural Hazards - Hurricane Isabel (2003) generated record flooding around Chesapeake Bay and caused extensive damage in rural Eastern Shore of Maryland and metropolitan cities like Baltimore....     

Predictability of landfall location and surge height of tropical cyclones over North Indian Ocean (NIO)

Natural Hazards - Forecasting, with precision, the location of landfall and the height of surge of cyclonic storms prevailing over any ocean basin is very important to cope with the associated...     

On the initialization of tropical cyclones with a three dimensional variational analysis

A method of initializing tropical cyclones in high-resolution numerical models is developed by modifying a data assimilation system, the NRL atmospheric variational data assimilation system (NAVDAS), which was designed for general mesoscale weather prediction using a three-dimensional variational (3DVAR) analysis with intermittent updates. The method includes the following three upgrades to overcome difficulties resulting from tropical cyclone initialization with the NAVDAS analysis. First, synthetic observation soundings are generated on 9 vertical levels at 49 points for strong storms (v _max?>?23.1?m?s^?1) and 41 points for weak storms around each cyclone center to supplement the observations used by the analysis. Secondly, a vortex relocation method for nested grids is developed to correct the cyclone position in the background fields of the analysis for each nested mesh. Lastly, the 3DVAR analysis is modified to gradually reduce the horizontal length scale and geostrophic coupling constraint near the center of a tropical cyclone for minimizing the problems introduced by improper covariances and coupling constraint used in the analysis. The synthetic observations significantly improve the intensity and structure of the analysis and the track forecast. The vortex relocation significantly improves the first guess background, avoiding the large analysis corrections that would be needed to correct cyclone position, and reducing the imbalance introduced by such large analysis increments. The modifications to the analysis length scale and geostrophic coupling constraint successfully improve the inner core analysis, providing a tighter circulation, and reducing the underestimate of the mass field gradient. Among the three upgrades, the vortex relocation provides the largest improvement to the tropical cyclone initialization and forecast.     

Estimation of property loss and business interruption loss caused by storm surge inundation due to climate change: a case of Typhoon Vera revisit

This paper estimates property loss and business interruption loss under scenarios of storm surge inundation to explore the economic impact of climate change on Ise Bay, Japan. Scenarios-based analyses are conducted with respect to Typhoon Vera, which caused the most severe storm surge in the recorded history of Japan in 1959. Four different hazard scenarios are chosen from a series of typhoon storm surge inundation simulations: Typhoon Vera’s landfall with respect to the condition of the past seawall; Typhoon Vera’s landfall with respect to the condition of the current seawall; intensifying Typhoon Vera, but retaining its original tracks; and intensifying Typhoon Vera, but choosing the worst tracks from various possible typhoon tracks. Our economic loss estimation takes advantage of fine geographical scale census and economic census data that enable us to understand the spatial distribution of property loss and business interruption loss as well as identify the most potentially affected areas and business sectors on a sub-city scale. By comparing the property loss and business interruption loss caused by different hazard scenarios, the effect of different seawalls is evaluated and the economic impact of future climate change is estimated. The results indicate that although the current seawall can considerably reduce the scale of losses, climate change can cause Ise Bay to experience more serious storm surge inundation. Moreover, the resulting economic losses would increase significantly owing to a combination of climate change and the worst track scenario. It is, therefore, necessary to consider more countermeasures to adapt to climate change in this area.     

Estimation of property loss and business interruption loss caused by storm surge inundation due to climate change: a case of Typhoon Vera revisit

This paper estimates property loss and business interruption loss under scenarios of storm surge inundation to explore the economic impact of climate change on Ise Bay, Japan. Scenarios-based analyses are conducted with respect to Typhoon Vera, which caused the most severe storm surge in the recorded history of Japan in 1959. Four different hazard scenarios are chosen from a series of typhoon storm surge inundation simulations: Typhoon Vera’s landfall with respect to the condition of the past seawall; Typhoon Vera’s landfall with respect to the condition of the current seawall; intensifying Typhoon Vera, but retaining its original tracks; and intensifying Typhoon Vera, but choosing the worst tracks from various possible typhoon tracks. Our economic loss estimation takes advantage of fine geographical scale census and economic census data that enable us to understand the spatial distribution of property loss and business interruption loss as well as identify the most potentially affected areas and business sectors on a sub-city scale. By comparing the property loss and business interruption loss caused by different hazard scenarios, the effect of different seawalls is evaluated and the economic impact of future climate change is estimated. The results indicate that although the current seawall can considerably reduce the scale of losses, climate change can cause Ise Bay to experience more serious storm surge inundation. Moreover, the resulting economic losses would increase significantly owing to a combination of climate change and the worst track scenario. It is, therefore, necessary to consider more countermeasures to adapt to climate change in this area.

     

气候变化背景下淮河流域场次暴雨事件时空演变分析

全球气候变化对暴雨洪涝等极端天气事件的发生产生了显著影响,识别气候变化背景下暴雨事件的时空变化特征是暴雨洪涝灾害综合应对的关键.以淮河流域为研究区,基于流域内229个气象站点1950-2012年的实测逐小时降水数据,遵循淮河流域实际情况对暴雨事件进行场次划分,并以此作为基础统计单元,借助地理信息系统平台,运用统计学方法并结合气象学理论,以场次暴雨事件开始时间、达到雨强峰值历时、场次平均暴雨历时及暴雨事件发生频次4个指标分析不同年代背景下淮河流域场次暴雨事件发生的过程变化及时空演变特征.结果表明：在气候变化的背景下,场次暴雨发生时间呈现宽幅化和极值化的变化趋势,暴雨发生时间出现了后移和双峰化的特征;暴雨历时及到达雨强峰值历时均呈现增加趋势,整个流域场次暴雨事件在1990s-2000s进入一个增加时期;全球性的气候变化使流域内暴雨事件发生的频次不断增加,历时不断增大,长历时高频次特征明显,尤其是近20 a来,淮河流域暴雨事件高发区域呈现出从流域部分地区向全流域扩张的趋势.