Novel use of climate model data for deriving future flood risk underwriting and risk selection data – A Hong Kong Case Study

2021 ◽  
Author(s):  
Rebecca Alexandre ◽  
Iain Willis
Keyword(s):  
Climate Change ◽  
Hong Kong ◽  
Flood Risk ◽  
Climate Model ◽  
Risk Mitigation ◽  
Flood Damage ◽  
Flood Frequency ◽  
Commercial Building ◽  
Model Data ◽  
Change Factors

<p>The re/insurance, banking and mortgage sectors play an essential role in facilitating economic stability. As climate change-related financial risks increase, there has long been a need for tools that contribute to the global industry’s current and future flood risk resiliency. Recognising this gap, JBA Risk Management has pioneered use of climate model data for rapidly deriving future flood risk metrics to support risk-reflective pricing strategies and mortgage analysis for Hong Kong.</p><p>JBA’s established method uses daily temporal resolution precipitation and surface air temperature Regional Climate Model (RCM) data from the Earth System Grid Federation’s CORDEX experiment. Historical and future period RCM data were processed for Representative Concentration Pathways (RCPs) 2.6 and 8.6, and time horizons 2046-2050 and 2070-2080 and used to develop fluvial and pluvial hydrological model change factors for Hong Kong. These change factors were applied to baseline fluvial and pluvial flood depths and extents, extracted from JBA’s high resolution 30m Hong Kong Flood Map. From these, potential changes in flood event frequency and severity for each RCP and time horizon combination were estimated.</p><p>The unique flood frequency and severity profiles for each flood type were then analysed with customised vulnerability functions, linking water depth to expected damage over time for residential and commercial building risks. This resulted in quantitative fluvial and pluvial flood risk metrics for Hong Kong.</p><p>Newly released, Hong Kong Climate Change Pricing Data is already in use by financial institutions. When combined with property total sum insured data, this dataset provides the annualised cost of flood damage for a range of future climate scenarios. For the first time, our industry has a tool to quantify baseline and future flood risk and set risk-reflective pricing for Hong Kong portfolios.</p><p>JBA’s method is adaptable for global use and underwriting tools are already available for the UK and Australia with the aim of improving future financial flood risk mitigation and management. This presentation will outline the method, provide a comparison of baseline and climate change flood impacts for Hong Kong and discuss the wider implications for our scientific and financial industries.</p>

scholarly journals Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2266 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Control Period ◽  
Flood Frequency ◽  
Climate Projections ◽  
The Future ◽  
Flood Quantiles ◽  
The Impact

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.

scholarly journals Atmospheric Blocking and Mean Biases in Climate Models

2010 ◽  
Vol 23 (23) ◽  
pp. 6143-6152 ◽  
Author(s):  
Adam A. Scaife ◽  
Tim Woollings ◽  
Jeff Knight ◽  
Gill Martin ◽  
Tim Hinton
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Small Scale ◽  
Model Data ◽  
Atmospheric Blocking ◽  
Intergovernmental Panel ◽  
Weather And Climate ◽  
Main Culprit

Abstract Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

Assessing the global risk of climate change to re/insurers using catastrophe models and hazard maps

2020 ◽  
Author(s):  
Sarah Jones ◽  
Emma Raven ◽  
Jane Toothill
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Flood Risk ◽  
River Flow ◽  
Climate Model ◽  
Flood Hazard ◽  
Insurance Industry ◽  
Global Climate Model ◽  
Hazard Maps ◽  
The Impact

<p>In 2018 worldwide natural catastrophe losses were estimated at around USD $155 billion, resulting in the fourth-highest insurance payout on sigma records, and in 2020 JBA Risk Management (JBA) estimate 2 billion people will be at risk to inland flooding. By 2100, under a 1.5°C warming scenario, the cost of coastal flooding alone as a result of sea level rise could reach USD $10.2 trillion per year, assuming no further adaptation. It is therefore imperative to understand the impact climate change may have on global flood risk and insured losses in the future.</p><p>The re/insurance industry has an important role to play in providing financial resilience in a changing climate. Although integrating climate science into financial business remains in its infancy, modelling companies like JBA are increasingly developing new data and services to help assess the potential impact of climate change on insurance exposure.</p><p>We will discuss several approaches to incorporating climate change projections with flood risk data using examples from research collaborations and commercial projects. Our case studies will include: (1) building a national-scale climate change flood model through the application of projected changes in river flow, rainfall and sea level to the stochastic event set in the model, and (2) using Global Climate Model data to adjust hydrological inputs driving 2D hydraulic models to develop climate change flood hazard maps.</p><p>These tools provide outputs to meet different needs, and results may sometimes invoke further questions. For example: how can an extreme climate scenario produce lower flood risk than a conservative one? Why may adjacent postcodes' flood risk differ? We will explore the challenges associated with interpreting these results and the potential implications for the re/insurance industry.</p>

Land-use change and floods: what do we need most, research or management?

2002 ◽  
Vol 45 (8) ◽  
pp. 183-190 ◽  
Author(s):  
Arne Tollan
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Flood Risk ◽  
Human Impacts ◽  
Management Strategies ◽  
Flood Management ◽  
Flood Damage ◽  
Flood Frequency ◽  
Small Scale ◽  
Infiltration Capacity

Land-cover change (urbanisation, deforestation, and cultivation) results in increased flood frequency and severity. Mechanisms include reduced infiltration capacity, lower soil porosity, loss of vegetation, and forest clearing, meaning lower evapotranspiration. Major research challenges lie in quantification of effects in terms of flood characteristics under various conditions, ascertaining the combined effects of gradual changes over long time periods, and developing model tools suitable for land-use management. Large floods during the 1990s gave a new focus on these problems. Reference is made to the Norwegian HYDRA research programme on human impacts on floods and flood damage. The paper concludes that land-use change effects on floods are most pronounced at small scale and for frequent flood magnitudes. Model simulations of effects of land-use change can now be used to reduce flood risk. Modern flood management strategies have abandoned the position that dams and dikes are the only answers to mitigating flood disasters. Today, the strategic approach is more often: do not keep the water away from the people, keep people away from the water. Flood management strategies should include flood warnings, efficient communication, risk awareness, civil protection and flood preparedness routines, effective land-use policies, flood risk mapping, … as well as structural measures.

scholarly journals Projecting flood hazard under climate change: an alternative approach to model chains

2013 ◽  
Vol 1 (6) ◽  
pp. 7357-7385 ◽  
Author(s):  
J. M. Delgado ◽  
B. Merz ◽  
H. Apel
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Emission Scenario ◽  
Flood Hazard ◽  
Global Climate ◽  
Global Climate Model ◽  
Flood Frequency ◽  
Frequency Model ◽  
Alternative Approach

Abstract. Flood hazard projections under climate change are typically derived by applying model chains consisting of the following elements: "emission scenario – global climate model – downscaling, possibly including bias correction – hydrological model – flood frequency analysis". To date, this approach yields very uncertain results, due to the difficulties of global and regional climate models to represent precipitation. The implementation of such model chains requires large efforts, and their complexity is high. We propose for the Mekong River an alternative approach which is based on a shortened model chain: "emission scenario – global climate model – non-stationary flood frequency model". The underlying idea is to use a link between the Western Pacific monsoon and local flood characteristics: the variance of the monsoon drives a nonstationary flood frequency model, yielding a direct estimate of flood probabilities. This approach bypasses the uncertain precipitation, since the monsoon variance is derived from large-scale wind fields which are better represented by climate models. The simplicity of the monsoon-flood link allows deriving large ensembles of flood projections under climate change. We conclude that this is a worthwhile, complementary approach to the typical model chains in catchments where a substantial link between climate and floods is found.

CMIP6 data documentation and citation in IPCC's Sixth Assessment Report (AR6)

2021 ◽  
Author(s):  
Martina Stockhause ◽  
Robin Matthews ◽  
Anna Pirani ◽  
Anne Marie Treguier ◽  
Ozge Yelekci
Keyword(s):  
Climate Change ◽  
Working Group ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Data ◽  
Intergovernmental Panel ◽  
Assessment Report ◽  
Data Usage ◽  
Group I

<p>The the amount of work and resources invested by the modelling centers to provide CMIP6 (Coupled Model Intercomparison Project Phase 6) experiments and climate projection datasets is huge, and therefore it is extremely important that the teams receive proper credit for their work. The Citation Service makes CMIP6 data citable with DOI references for the evolving CMIP6 model data published in the Earth System Grid Federation (ESGF). The Citation Service as a new piece of the CMIP6 infrastructure was developed upon the request from the CMIP Panel.</p><p>CMIP6 provides new global climate model data assessed in the IPCC's (Intergovernmental Panel on Climate Change) Sixth Assessment Report (AR6). Led by the Technical Support Unit of IPCC Working Group I (WGI TSU), the IPCC Task Group on Data Support for Climate Change Assessment (TG-Data) developed FAIR data guidelines, for implementation by the TSUs of the three IPCC WGs and the IPCC Data Distribution Centre (DDC) Partners. A central part of the FAIR data guidelines are the documentation and citation of data used in the report.</p><p>The contribution will show how CMIP6 data usage is documented in IPCC WGI AR6 from three angles: technical implementation, collection of CMIP6 data usage information from the IPCC authors, and a report users’ perspective.</p><p> </p><p>Links:</p><ul><li>CMIP6 Citation Service: http://cmip6cite.wdc-climate.de</li> <li>CMIP6: https://pcmdi.llnl.gov/CMIP6/</li> <li>IPCC AR6: https://www.ipcc.ch/assessment-report/ar6/</li> <li>IPCC AR6 WGI report: https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/</li> <li>IPCC TG-Data: https://www.ipcc.ch/data/</li> </ul>

The economic impacts of Climate Change to flood risk across the Central Asia Regional Economic Cooperation (CAREC)

2021 ◽  
Author(s):  
Iain Willis ◽  
Alex Shao ◽  
Sarah Optiz-Stapleton
Keyword(s):  
Climate Change ◽  
Central Asia ◽  
Flood Risk ◽  
Regional Climate ◽  
Flood Event ◽  
Quantile Mapping ◽  
Autonomous Region ◽  
Change Factors ◽  
Time Horizons ◽  
Intensity Duration Frequency

<p>This case study documents the application of multi-RCM derived Intensity-Duration-Frequency (IDF) curves to assess the changing nature of probabilistic flood risk in the CAREC region at future time horizons.</p><p>In this study, multi-model precipitation extremes under RCP4.5 and RCP8.5 at future climate horizons (e.g. 2040s and 2070s) are used to derive alternative views of flood risk and damage potential across the eleven countries (Afghanistan, Azerbaijan, China (Inner Mongolia Autonomous Region; Xinjiang Uyghur Autonomous Region), Georgia, Kazakhstan, Kyrgyz Republic, Mongolia, Pakistan, Tajikistan, Turkmenistan and Uzbekistan) within the Central Asia Regional Economic Cooperation (CAREC).</p><p>Multiple regional climate model (RCM) daily precipitation data from the Coordinated Regional Climate Downscaling Experiment (CORDEX) are first bias corrected through non-parametric quantile mapping. Quantile mapping is an approach used to reduce systematic biases in RCM precipitation, particularly extremes, by adjusting the historical modeled precipitation distributions against observations and carrying the transformation forward to adjust future projections. The bias-corrected projections are used to derive sub-country level Intensity-Duration-Frequency (IDF) curves before being combined with a 10,000 year stochastic simulation of river and surface water flood event set to derive change factors in baseline hydrology for river gauges and gridded precipitation points across Central Asia. These change factors have been used to create a series of alternative stochastic flood event sets for the various time horizons and emission scenarios, which in turn, are then analysed against the GED4ALL economic exposure data and a detailed taxonomy of fragility curves to assess the economic impact of climate change in all CAREC countries. The study captures the complex and non-linear relationship between climate change and flood risk across a diverse continent. In turn, focus is given to how these findings may affect key global planning horizons with regard to disaster risk financing and sustainable development. </p>

Appraising sustainable flood risk management in the Pearl River Delta's coastal megacities: a case study of Hong Kong, China

2013 ◽  
Vol 4 (4) ◽  
pp. 390-409 ◽  
Author(s):  
F. K. S. Chan ◽  
O. A. Adekola ◽  
G. Mitchell ◽  
A. T. McDonald
Keyword(s):  
Risk Management ◽  
Hong Kong ◽  
Flood Risk ◽  
Risk Mitigation ◽  
Storm Surges ◽  
Climatic Conditions ◽  
Flood Risk Management ◽  
Pearl River ◽  
The Pearl River

The Pearl River Delta (PRD) region has experienced rapid economic and population growth in the last three decades. The delta includes coastal megacities, such as Hong Kong. These low-lying urbanised coastal regions in the PRD are vulnerable to flood risks from unpredictable climatic conditions. These can result in increasing storm surges, rising sea level and intensified rainstorms causing coastal and inland flooding, all of which impact the delta. This paper has taken the coastal megacity of Hong Kong as a case, focusing on two study sites: Shenzhen River and Tai O town, chosen for their peculiar inland and coastal flood problems. A sustainable flood risk appraisal (SFRA) template was developed against which sustainable flood risk management (FRM) practices in these sites were benchmarked. Thirty-eight stakeholders were interviewed during this research in order to understand the current FRM practices, their barriers and their constraints. It was found that FRM in the case study currently focuses on hard engineering, while neglecting other important sustainability indicators. A SFRA practice that takes public participation, equity of flood preparedness and environmental friendly into account could be effective in achieving sustainable flood risk mitigation practices in Hong Kong and other coastal cities in the PRD.

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