Return period of extreme rainfall substantially decreases under 1.5 °C and 2.0 °C warming: a case study for Uttarakhand, India

Abstract. With access to claims, insurers have a long tradition of being knowledge leaders on damages caused by windstorms. However, new opportunities have arisen to better assess the risks of winter windstorms in Europe through the availability of historic footprints provided by the Windstorm Information Service (Copernicus WISC). In this study, we compare how modelling of building damages complements claims-based risk assessment. We describe and use two windstorm risk models: an insurer's proprietary model and the open source CLIMADA platform. Both use the historic WISC dataset and a purposefully built, probabilistic hazard event set of winter windstorms across Europe to model building damages in the canton of Zurich, Switzerland. These approaches project a considerably lower estimate for the annual average damage (CHF 1.4 million), compared to claims (CHF 2.3 million), which originates mainly from a different assessment of the return period of the most damaging historic event Lothar–Martin. Additionally, the probabilistic modelling approach allows assessment of rare events, such as a 250-year-return-period windstorm causing CHF 75 million in damages, including an evaluation of the uncertainties. Our study emphasizes the importance of complementing a claims-based perspective with a probabilistic risk modelling approach to better understand windstorm risks. The presented open-source model provides a straightforward entry point for small insurance companies.

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The Use of Laser Precipitation Monitor (LPM) of Disdrometer and Weather Radar to Determine the Microphysics Characteristics of Extreme Rainfall in Jakarta. (Jakarta Flood Case Study February 25, 2020)

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/893/1/012017 ◽

2021 ◽

Vol 893 (1) ◽

pp. 012017

Author(s):

I D G A Putra ◽

A Sopaheluwakan ◽

B P Adi ◽

K A Sudama ◽

J Rizal ◽

...

Keyword(s):

Extreme Rainfall ◽

Weather Radar ◽

Heavy Rain ◽

Maximum Diameter ◽

Convective Clouds ◽

Data Volume ◽

Accumulated Rainfall ◽

The One ◽

The Relationship

Abstract Heavy rains on February 24, 2020, caused flooding in most parts of Jakarta and its surroundings. The one-day observation of accumulated rainfall from the Laser Precipitation Monitor (LPM) was recorded at 358.6 mm/day at the Kemayoran station on February 25, 2020, at 00.00 UTC (07.00 Jakarta Time). In this study, analysis of the microphysical characteristics of extreme rainfall using LPM installed at Kemayoran meteorology station and weather radar at Cengkareng meteorology station with a spatial radius of 250 km. LPM is used to measure the diameter of the raindrops, the velocity of falling raindrops, LPM reflectivity, and the amount of accumulated rainfall with time resolution per minute and stored in excel data format. While the weather radar is used to measure the reflectivity spatially and temporally in the data volume format (.vol). The method used is, first, to find the relationship between LPM reflectivity and the amount of LPM rainfall with regression analysis. Second, the radar reflectivity is converted into estimated rainfall intensity for the Jakarta area and its surroundings. The results of this study found a relationship between LPM reflectivity (X) and rainfall accumulation LPM (Y) to form a regression relationship with the formula Y = 0.013X with R2 = 0.3777. Based on the record of the LPM time series, the peak of rainfall occurred at 18.17 UTC with 1000 raindrops, the maximum fall speed was 10 m/s, and the maximum diameter is 8.5 millimeters. Based on the results of microphysical measurements of LPM, spatial plots, and vertical cross-section radar, it can be concluded that flooding in Jakarta is due to heavy rain from convective clouds.

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Weibull parameter calculation and estimation of wind speeds for the return period: A case study in the Kori and Wolsong NPP areas

Annals of Nuclear Energy ◽

10.1016/j.anucene.2017.04.040 ◽

2017 ◽

Vol 108 ◽

pp. 406-412 ◽

Cited By ~ 3

Author(s):

Jong Kuk Lee ◽

Kwan-Hee Lee ◽

Sung Il Kim ◽

Daesik Yook ◽

Sangmyeon Ahn

Keyword(s):

Return Period ◽

Weibull Parameter ◽

Parameter Calculation ◽

Wind Speeds

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Interevent Time Distribution of Renewal Point Process, Case Study: Extreme Rainfall in South Sulawesi

Journal of Physics Conference Series ◽

10.1088/1742-6596/979/1/012090 ◽

2018 ◽

Vol 979 ◽

pp. 012090

Author(s):

Nurtiti Sunusi

Keyword(s):

Point Process ◽

Time Distribution ◽

Extreme Rainfall ◽

South Sulawesi ◽

Interevent Time

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Global flood hazard map and exposed GDP comparison: a China case study

10.5194/nhess-2020-1 ◽

2020 ◽

Author(s):

Jerom P. M. Aerts ◽

Steffi Uhlemann-Elmer ◽

Dirk Eilander ◽

Philip J. Ward

Keyword(s):

Return Period ◽

Flood Hazard ◽

Regional Scale ◽

Flood Protection ◽

Economic Losses ◽

Return Periods ◽

Hazard Maps ◽

High Exposure ◽

Pluvial Flooding

Abstract. Floods are among the most frequent and damaging natural hazard events in the world. In 2016, economic losses from flooding amounted to $56 bn globally, of which $20 bn occurred in China (Munich Re, 2017). National or regional scale mapping of flood hazard is at present providing an inconsistent and incomplete picture of floods. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing of the global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse 8 global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modelled inundated area and exposed GDP across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. For example, for the 100 year return period undefended (assuming no flood protection) hazard maps the percentage of total affected GDP of China ranges between 4.4 % and 10.5 % for fluvial floods. For the majority of the GFMs we see only a small increase in inundated area or exposed GDP for high return period undefended hazard maps compared to low return periods, highlighting major limitations in the models’ resolution and their output. The inclusion of industry models which currently model flooding at higher spatial resolution, and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. Pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 % points. Our study strongly highlights the importance of flood defenses for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of area of China) but locally detailed layer of structural defenses in high exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

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Estimate of Storm Induced Beach Erosion Through the ETS Approach

Volume 2: Structures, Safety and Reliability ◽

10.1115/omae2008-57749 ◽

2008 ◽

Author(s):

Rosaria E. Musumeci ◽

Carla Faraci ◽

Felice Arena ◽

Enrico Foti

Keyword(s):

Return Period ◽

Extreme Events ◽

Coastal Erosion ◽

Beach Erosion ◽

Coastal Protection ◽

Shoreline Retreat ◽

Submerged Breakwater ◽

The One

In the present paper the risk of beach erosion is evaluated by applying the Equivalent Triangular Storm (ETS). The selected case study is ‘La Plaja’ beach located in the South of Catania, Sicily. The proposed approach has shown that when the ETS model is applied, a shoreline retreat has been found which on average overestimates the one obtained by means of actual storm data of about 35%. The model has been applied for the determination of the return period of shoreline recession due to beach erosion during extreme events in order to recover risk maps, which can provide useful information in the planning of coastal interventions. Finally the model has been applied to predict the shoreline retreat in the presence of a submerged breakwater, confirming that the introduction of such coastal protection work strongly limits the risk of coastal erosion.

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Analysis of Problems Related to the Calculation of Flood Frequency Using Rainfall-Runoff Models: A Case Study in Poland

Sustainability ◽

10.3390/su12177187 ◽

2020 ◽

Vol 12 (17) ◽

pp. 7187

Author(s):

Dariusz Młyński

Keyword(s):

Sensitivity Analysis ◽

Return Period ◽

Maximum Flow ◽

High Sensitivity ◽

Flood Frequency ◽

Rainfall Runoff ◽

Model Quality ◽

Retention Capacity

This work aimed to quantify how the different parameters of the Snyder model influence the errors in design flows. The study was conducted for the Kamienica Nowojowska catchment (Poland). The analysis was carried out according to the following stages: determination of design precipitation, determination of design hyetograph, sensitivity analysis of the Snyder model, and quality assessment of the Snyder model. Based on the conducted research, it was found that the Snyder model did not show high sensitivity to the assumed precipitation distribution. The parameters depending on the retention capacity of the catchment had much greater impact on the obtained flow values. The verification of the model quality showed a significant disproportion in the calculated maximum flow values with the assumed return period.

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