Detecting changes in UK precipitation extremes using climate model projections: Implications for managing fluvial flood risk

2010 ◽  
Author(s):  
H.J. Fowler ◽  
R.L. Wilby ◽  
D. Cooley ◽  
R.R. Sain ◽  
M. Thurston
Keyword(s):  
Flood Risk ◽  
Climate Model ◽  
Precipitation Extremes

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>

Evaluation of extreme precipitation over the Nordic region using a convection-permitting regional climate model

2020 ◽  
Author(s):  
Erika Toivonen ◽  
Danijel Belušić ◽  
Emma Dybro Thomassen ◽  
Peter Berg ◽  
Ole Bøssing Christensen ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Precipitation Extremes ◽  
Nordic Region ◽  
Mesh Resolution ◽  
Grid Mesh

<p>Extreme precipitation events have a major impact upon our society. Although many studies have indicated that it is likely that the frequency of such events will increase in a warmer climate, little has been done to assess changes in extreme precipitation at a sub-daily scale. Recently, there is more and more evidence that <span>high-resolution convection-permitting models </span><span>(CPMs)</span> (grid-mesh typically < 4 km) can represent especially short-duration precipitation extremes more accurately when compared with coarser-resolution <span>regional climate model</span><span>s </span><span>(RCMs)</span><span>.</span></p><p>This study investigates sub-daily and daily precipitation characteristics based on hourly <span>output data from the HARMONIE-Climate model </span>at 3-km and 12-km grid-mesh resolution over the Nordic region between 1998 and 2018. The RCM modelling chain uses the ERA-Interim reanalysis to drive a 12-km grid-mesh simulation which is further downscaled to 3-km grid-mesh resolution using a non-hydrostatic model set-up.</p><p>The statistical properties of the modeled extreme precipitation are compared to several sub-daily and daily observational products, including gridded and in-situ gauge data, from April to September. We investigate the skill of the model to represent different aspects of the frequency and intensity of extreme precipitation as well as intensity–duration–frequency (IDF) curves that are commonly used to investigate short duration extremes from an urban planning perspective. The high grid resolution combined with the 20-year-long simulation period allows for a robust assessment at a climatological time scale <span>and enables us to examine the added value of high-resolution </span><span>CPM</span><span> in reproducing precipitation extremes over the Nordic </span><span>region</span><span>. </span><span>Based on the tentative results, the high-resolution CPM can realistically capture the </span><span>characteristics </span><span>of precipitation extremes, </span><span>for instance, </span><span>in terms of improved diurnal cycle and maximum intensities of sub-daily precipitation.</span></p>

Flood recurrence under climate change: a probabilistic flood risk assessment of critical infrastructure in the Danube basin

2020 ◽  
Author(s):  
Michel Wortmann ◽  
Kai Schröter
Keyword(s):  
Flood Risk ◽  
Climate Model ◽  
Critical Infrastructure ◽  
Insurance Industry ◽  
Danube River ◽  
Detailed Model ◽  
Flood Level ◽  
Basin Scale ◽  
The Future ◽  
The Impact

<p>Consistent information on fluvial flood risks in large river basins is typically sparse. This is especially true for the Danube River basin covering up to 14 countries and creating a patchwork of flood risk information across a populous and flood-prone region. As climatic changes have shown to increase flooding in the future, consistent basin-scale assessments prove vital to the insurance industry as well as municipal and infrastructural planning. The Future Danube Model (FDM) was designed to fill this gap complying to both insurance industry and climate science standards. That is, allowing for a reasonably detailed model scale (based on a 25m digital elevation model), stochastic sampling to create a large number of extreme events and flood event footprints (10k years), a thorough calibration and validation as well as the use of an ensemble of climate model output to drive the model under scenario conditions. The model is here used to assess the impact on critical infrastructure across the basin. Results indicate a marked increase in flood risk has already occurred when comparing the current climate period (2006-2035) to the reference period (1970-1999). Further increases are projected under a moderate and a business as usual scenario for the next climate period (2020-2049) and the end of the century (2070-2099). In large parts of the basin, the historical 100-year flood level, often used as a critical protection level for infrastructure, is projected to be equalled or exceeded every 50–10 years, while areas with a 100-year flood risk are projected to increase by 6-19%.</p>

Investigating the seasonal response of precipitation extremes to global warming using observations and large-ensembles of coupled climate models

2020 ◽  
Author(s):  
Andrew Williams ◽  
Paul O'Gorman
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Precipitation Extremes ◽  
Cmip5 Models ◽  
Historical Period ◽  
Societal Relevance ◽  
Coupled Climate Models

<p>Changes in extreme precipitation are amongst the most impactful consequences of global warming, with potential effects ranging from increased flood risk and landslides to crop failures and impacts on ecosystems. Thus, understanding historical and future changes in extreme precipitation is not only important from a scientific perspective, but also has direct societal relevance.</p><p>However, while most current research has focused on annual precipitation extremes and their response to warming, it has recently been noted that climate model projections show a distinct seasonality to future changes in extreme precipitation. In particular, CMIP5 models suggest that over Northern Hemisphere (NH) land the summer response is weaker than the winter response in terms of percentage changes.</p><p>Here we investigate changes in seasonal precipitation extremes using observations and simulations with coupled climate models. First, we analyse observed trends from the Hadley Centre’s global climate extremes dataset (HadEX2) to investigate to what extent there is already a difference between summer and winter trends over NH land. Second, we use 40 ensemble members from the CESM Large Ensemble to characterize the role played by internal variability in trends over the historical period. Lastly, we use CMIP5 simulations to explore the possibility of a link between the seasonality of changes in precipitation extremes and decreases in surface relative humidity over land.</p>

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>

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