scholarly journals ENSEMBLE FORECAST OF EXTREME STORM SURGE: A CASE STUDY OF 2013 TYPHOON HAIYAN

2017 ◽  
pp. 10 ◽  
Author(s):  
Ryota Nakamura ◽  
Tomoya Shibayama
Keyword(s):  
Storm Surge ◽  
Storm Surges ◽  
Ensemble Forecast ◽  
Ensemble Member ◽  
Forecast System ◽  
Extreme Storm ◽  
Ensemble Mean ◽  
Almost All ◽  
Simple Numerical Model

The object of this study is to evaluate an ensemble forecast of extreme storm surge by using a case of Typhoon Haiyan (2013) and its associated storm surge. A simple numerical model composed of ARW-WRF, FVCOM and SWAN is employed as a forecast system for storm surge. This ensemble system can successfully forecast storm surge 3-4 days before it happened. However, the typhoons in almost all ensemble members were underpredicted probably because of its difficulty in forecasting a track and central pressure of highly intense typhoon. This leads to the underestimation of a prediction of storm surges around Leyte Gulf. Compensating the underestimation of forecasted extreme storm surge, it can be important to not only examine the ensemble mean among members but also consider the phase-shifted manipulation and the worst ensemble member in the case where the extreme storm surge is forecasted. In addition, the ensemble forecast system can have a potential to determine the time at which the peak of extreme surge appears with a high precision.

scholarly journals Statistical Prediction of Extreme Storm Surges Based on a Fully Supervised Weather-Type Downscaling Model

2020 ◽  
Vol 8 (12) ◽  
pp. 1028
Author(s):  
Wagner Costa ◽  
Déborah Idier ◽  
Jérémy Rohmer ◽  
Melisa Menendez ◽  
Paula Camus
Keyword(s):  
Storm Surge ◽  
Storm Surges ◽  
Absolute Error ◽  
Weather Type ◽  
Statistical Prediction ◽  
Daily Maximum ◽  
Maximum Absolute Error ◽  
Extreme Storm ◽  
Gauge Station ◽  
Data Driven Approach

Increasing our capacity to predict extreme storm surges is one of the key issues in terms of coastal flood risk prevention and adaptation. Dynamically forecasting storm surges is computationally expensive. Here, we focus on an alternative data-driven approach and set up a weather-type statistical downscaling for daily maximum storm surge (SS) prediction, using atmospheric hindcasts (CFSR and CFSv2) and 15 years of tidal gauge station measurements. We focus on predicting the storm surge at La Rochelle–La Pallice tidal gauge station. First, based on a sensitivity analysis to the various parameters of the weather-type approach, we find that the model configuration providing the best performance in SS prediction relies on a fully supervised classification using minimum daily sea level pressure (SLP) and maximum SLP gradient, with 1° resolution in the northeast Atlantic domain as the predictor. Second, we compare the resulting optimal model with the inverse barometer approach and other statistical models (multi-linear regression; semi-supervised and unsupervised weather-types based approaches). The optimal configuration provides more accurate predictions for extreme storm surges, but also the capacity to identify unusual atmospheric storm patterns that can lead to extreme storm surges, as the Xynthia storm for instance (a decrease in the maximum absolute error of 50%).

scholarly journals Simulation of storm surge inundation under different typhoon intensity scenarios: case study of Pingyang County, China

2020 ◽  
Vol 20 (10) ◽  
pp. 2777-2790
Author(s):  
Xianwu Shi ◽  
Pubing Yu ◽  
Zhixing Guo ◽  
Zhilin Sun ◽  
Fuyuan Chen ◽  
...  
Keyword(s):  
Storm Surge ◽  
Water Depth ◽  
Storm Surges ◽  
Economic Losses ◽  
Astronomical Tide ◽  
Evacuation Plans ◽  
Typhoon Intensity ◽  
Typhoon Tracks ◽  
The Impact

Abstract. China is one of the countries that is most seriously affected by storm surges. In recent years, storm surges in coastal areas of China have caused huge economic losses and a large number of human casualties. Knowledge of the inundation range and water depth of storm surges under different typhoon intensities could assist predisaster risk assessment and making evacuation plans, as well as provide decision support for responding to storm surges. Taking Pingyang County in Zhejiang Province as a case study area, parameters including typhoon tracks, radius of maximum wind speed, astronomical tide, and upstream flood runoff were determined for different typhoon intensities. Numerical simulations were conducted using these parameters to investigate the inundation range and water depth distribution of storm surges in Pingyang County considering the impact of seawall collapse under five different intensity scenarios (corresponding to minimum central pressure values equal to 915, 925, 935, 945, and 965 hPa). The inundated area ranged from 103.51 to 233.16 km2 for the most intense typhoon. The proposed method could be easily adopted in various coastal counties and serves as an effective tool for decision-making in storm surge disaster risk reduction practices.

scholarly journals Storm-induced sediment supply to coastal dunes on sand flats

2020 ◽  
Vol 8 (2) ◽  
pp. 335-350 ◽  
Author(s):  
Filipe Galiforni-Silva ◽  
Kathelijne M. Wijnberg ◽  
Suzanne J. M. H. Hulscher
Keyword(s):  
Numerical Model ◽  
Storm Surge ◽  
Storm Surges ◽  
Coastal Dunes ◽  
Sediment Supply ◽  
Aeolian Transport ◽  
Sand Flat ◽  
Sediment Transfer ◽  
Sand Flats

Abstract. Growth of coastal dunes requires a marine supply of sediment. Processes that control the sediment transfer between the subtidal and the supratidal zone are not fully understood, especially in sand flats close to inlets. It is hypothesised that storm surge events induce sediment deposition on sand flats, providing fresh material for aeolian transport and dune growth. The objective of this study is to identify which processes cause deposition on the sand flat during storm surge conditions and discuss the relationship between the supratidal deposition and sediment supply to the dunes. We use the island of Texel (NL) as a case study, of which multiannual topographic and hydrographic datasets are available. Additionally, we use the numerical model XBeach to simulate the most frequent storm surge events for the area. Results show that supratidal shore-parallel deposition of sand occurs in both the numerical model and the topographic data. The amount of sand deposited is directly proportional to surge level and can account for more than a quarter of the volume deposited at the dunes yearly. Furthermore, storm surges are also capable of remobilising the top layer of sediment of the sand flat, making fresh sediment available for aeolian transport. Therefore, in a sand flat setting, storm surges have the potential of reworking significant amounts of sand for aeolian transport in periods after the storm and as such can also play a constructive role in coastal dune development.

scholarly journals Multivariate analysis of extreme storm surges in a semi-enclosed bay

2017 ◽  
Author(s):  
Yao Luo ◽  
Hui Shi ◽  
Dongxiao Wang
Keyword(s):  
Multivariate Analysis ◽  
Storm Surges ◽  
Multidimensional Data ◽  
Practical Case ◽  
Analysis Method ◽  
Extreme Storm ◽  
Practical Guidelines ◽  
Enclosed Bay ◽  
Joint Probabilities

Abstract. The prediction of extreme storm surges is a critical task for coastal area protection. This study examines extreme storm surges in Beibu Bay, a semi-enclosed bay in the South China Sea, and their joint probabilities. A method for the advanced prediction of the extreme storm surges is proposed using a multivariate extreme statistical method. We further present practical guidelines of the proposed multivariate analysis method, including guidelines for simulation. The simulation can be extended to multidimensional data to simplify computation, so the proposed approach can be extended to use more points' data from the semi-enclosed bay for predicting extreme storm surges probabilities. A practical case study illustrates the application of the proposed techniques for extreme storm surges prediction. A comparison of the conditional probabilities obtained from observations and simulation data show that the proposed method is effective.

scholarly journals A Comparison of Perturbations from an Ensemble Transform and an Ensemble Kalman Filter for the NCEP Global Ensemble Forecast System

2016 ◽  
Vol 31 (6) ◽  
pp. 2057-2074 ◽  
Author(s):  
Xiaqiong Zhou ◽  
Yuejian Zhu ◽  
Dingchen Hou ◽  
Daryl Kleist
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Forecast Model ◽  
Skill Score ◽  
Ensemble Forecast ◽  
Boreal Summer ◽  
Lead Times ◽  
Operational Environment ◽  
Forecast System ◽  
Ensemble Mean

Abstract Two perturbation generation schemes, the ensemble transformation with rescaling (ETR) and the ensemble Kalman filter (EnKF), are compared for the NCEP operational environment for the Global Ensemble Forecast System (GEFS). Experiments that utilize each of the two schemes are carried out and evaluated for two boreal summer seasons. It is found that these two schemes generally have comparable performance. Experiments utilizing both perturbation methods fail to generate sufficient spread at medium-range lead times beyond day 8. In general, the EnKF-based experiment outperforms the ETR in terms of the continuous ranked probability skill score (CRPSS) in the Northern Hemisphere (NH) for the first week. In the SH, the ensemble mean forecast is more skillful from the ETR perturbations. Additional experiments are performed with the stochastic total tendency perturbation (STTP) scheme, in which the total tendencies of all model variables are perturbed to represent the uncertainty in the forecast model. An improved spread–error relationship is found for the ETR-based experiments, but the STTP increases the ensemble spread for the EnKF-based experiment that is already overdispersive at early lead times, especially in the SH. With STTP employed, an increase in the EnKF-based CRPSS in the NH is reduced with a larger degradation in both the probability and ensemble-mean forecast skills in the SH. The results indicate that a rescaling of the EnKF initial perturbations and/or tuning of the STTP scheme is required when STTP is applied using the EnKF-based perturbations. This study provided guidance for the replacement of ETR with EnKF perturbations as part of the 2015 GEFS implementation.

Global Assessments of Surface Winds and Waves From an Ensemble Forecast System Using Satellite Data

2019 ◽  
Author(s):  
Ricardo Martins Campos ◽  
C. Guedes Soares
Keyword(s):  
Satellite Data ◽  
Ensemble Forecast ◽  
Altimeter Data ◽  
Forecast System ◽  
Significant Wave ◽  
Error Metrics ◽  
Control Member ◽  
Ensemble Mean ◽  
Wave Heights ◽  
Significant Wave Heights

Abstract This paper evaluates the 10-m wind intensities and significant wave heights from the NCEP Ensemble Forecast System using altimeter data. A total of 20 perturbed members plus a control member (deterministic run) compose the ensemble. The assessment is focused on the comparison between the control run and the ensemble mean, in terms of benefits presented by four error metrics. Four satellite missions are selected for the assessments, obtained from AVISO and NESDIS/NOAA databases. Results show that the scatter components of the errors strongly depends on the latitude, were extra-tropical locations at longer forecast times present large errors. A significant improvement using the ensemble forecast compared to deterministic runs was verified at these locations, where the RMSE of day 10 was reduced from 5 to 3.5 m/s for U10 and from 1.8 to 1.3 meters for Hs.

scholarly journals How Do Forecasters Utilize Output from a Convection-Permitting Ensemble Forecast System? Case Study of a High-Impact Precipitation Event

2014 ◽  
Vol 29 (2) ◽  
pp. 466-486 ◽  
Author(s):  
Clark Evans ◽  
Donald F. Van Dyke ◽  
Todd Lericos
Keyword(s):  
Heavy Precipitation ◽  
Ensemble Forecast ◽  
High Impact ◽  
Added Value ◽  
Precipitation Event ◽  
Preparation Process ◽  
Forecast System ◽  
System Output ◽  
Precipitation Thresholds

Abstract The proliferation of ensemble forecast system output in recent years motivates this investigation into how operational forecasters utilize convection-permitting ensemble forecast system guidance in the forecast preparation process. A 16-member, convection-permitting ensemble forecast of the high-impact heavy precipitation resulting from Tropical Storm Fay (2008) is conducted and evaluated. The ensemble provides a skillful, albeit underdispersive and bimodal, forecast at all precipitation thresholds considered. A forecasting exercise is conducted to evaluate how forecasters utilize the ensemble forecast system guidance. Forecasters made two storm-total accumulated precipitation forecasts: one before and one after evaluating the ensemble guidance. Concurrently, forecasters were presented with questionnaires designed to gauge their thought processes in preparing each of their forecasts. Exercise participants felt that the high-resolution ensemble guidance added value and confidence to their forecasts, although it did not meaningfully reduce forecast uncertainty. Incorporation of the ensemble guidance into the forecast preparation process resulted in a modest mean improvement in forecast skill, with each forecast found to be skillful at all accumulated precipitation thresholds. Forecasters primarily utilized the ensemble guidance to identify a “most likely” forecast outcome from disparate deterministic guidance solutions and to help quantify the uncertainty associated with the forecast. Forecasters preferred ensemble guidance that enabled them to quickly understand the range of solutions provided by the ensemble, particularly over the entirety of the domain. Forecasters were generally aware of the diversity of solutions provided by the ensemble guidance; however, only a select few actively interrogated this information when revising their forecasts and each did so in different ways.

scholarly journals INTER-COMPARISON OF COASTAL MODELS: CASE STUDY OF STORM SURGE AT NEMURO IN JAPAN

2018 ◽  
pp. 79
Author(s):  
Ryota Nakamura ◽  
Martin Mäll ◽  
Tomoya Shibayama ◽  
Shigeru Kato
Keyword(s):  
Storm Surge ◽  
Ocean Circulation ◽  
Essential Role ◽  
Gradual Increase ◽  
Storm Surges ◽  
Japan Trench ◽  
Coastal Circulation ◽  
Sea Drag ◽  
Storm Surge Event

The numerical coastal circulation models play an essential role in predicting storm surges. Several models (e.g. ADCIRC: Dietrich et al., 2004, FVCOM: Chen et al., 2003) have been previously inter-compared (Kerr et al., 2013; Chen et al., 2013). In these studies, storm surges were reproduced in locations where the bathymetry has a gradual increase from offshore to coast, within a closed gulf. On the other hand, there are few studies in regards to modelling storm surge where the near coast bathymetry is steep and connected to open ocean. Considering the storm surge dependence on local bathymetry, it can be important to conduct an inter-comparison of ocean circulation models in such a region. In this study, numerical coastal circulation models (2D-ADCIRC and 3D-FVCOM) are compared by using a 2014 Dec. storm surge event at Nemuro city in Hokkaido (Japan), which was caused by a rapidly intensified extra-tropical cyclone approaching the area. In this region, local bathymetry is steep due to Japan Trench. The cyclone caused a storm surge of nearly up to 1.8 m within the Nemuro city between 00:00 UTC 16th and 17th Dec. 2014. The aim of this study is to evaluate the performance of ocean circulation models using several air-sea drag coefficients and contribute to inter-comparison studies using ADCIRC and FVCOM.

scholarly journals Hydrodynamic and Waves Response during Storm Surges on the Southern Brazilian Coast: A Hindcast Study

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3538
Author(s):  
Andre de Souza de Lima ◽  
Arslaan Khalid ◽  
Tyler Will Miesse ◽  
Felicio Cassalho ◽  
Celso Ferreira ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Storm Surges ◽  
Coastal Communities ◽  
Brazilian Coast ◽  
Forecast System ◽  
Modeling Framework ◽  
Meteorological Forcing ◽  
The Impact

The Southern Brazilian Coast is highly susceptible to storm surges that often lead to coastal flooding and erosive processes, significantly impacting coastal communities. In addition, climate change is expected to result in expressive increases in wave heights due to more intense and frequent storms, which, in conjunction with sea-level rise (SLR), has the potential to exacerbate the impact of storm surges on coastal communities. The ability to predict and simulate such events provides a powerful tool for coastal risk reduction and adaptation. In this context, this study aims to investigate how accurately storm surge events can be simulated in the Southwest Atlantic Ocean employing the coupled ADCIRC+SWAN hydrodynamic and phase-averaged wave numerical modeling framework given the significant data scarcity constraints of the region. The model’s total water level (TWL) and significant wave height (Hs) outputs, driven by different sources of meteorological forcing, i.e., the Fifth Generation of ECMWF Atmospheric Reanalysis (ERA 5), the Climate Forecast System Version 2 (CFSv2), and the Global Forecast System (GFS), were validated for three recent storm events that affected the coast (2016, 2017, and 2019). In order to assess the potentially increasing storm surge impacts due to sea-level rise, a case study was implemented to locally evaluate the modeling approach using the most accurate model setup for two 2100 SLR projections (RCP 4.5 and 8.5). Despite a TWL underestimation in all sets of simulations, the CFSv2 model stood out as the most consistent meteorological forcing for the hindcasting of the storm surge and waves in the numerical model, with an RMSE range varying from 0.19 m to 0.37 m, and an RMSE of 0.56 m for Hs during the most significant event. ERA5 was highlighted as the second most accurate meteorological forcing, while adequately simulating the peak timings. The SLR study case demonstrated a possible increase of up to 82% in the TWL during the same event. Despite the limitations imposed by the lack of continuous and densely distributed observational data, as well as up to date topobathymetric datasets, the proposed framework was capable of expanding TWL and Hs information, previously available for a handful of gauge stations, to a spatially distributed and temporally unlimited scale. This more comprehensive understanding of such extreme events represents valuable knowledge for the potential implementation of more adequate coastal management and engineering practices for the Brazilian coastal zone, especially under changing climate conditions.

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