Catastrophic Losses in Canada - Have Flood Damages Increased Significantly Or Have Changing Data Sources Affected Trends?

Disaster Losses Are Up
Catastrophic loss trends have been reported regularly in Canada, often in relation to flood damages. These have often linked to climate change effects as well as other factors that may include aging infrastructure (not a significant factor in our mind), or urbanization and intensification (the true overriding factor in many urban centres). This post looks at how trends have changed in relation to changes in data sources.

GDP Adjusted Losses are Down
A blog post by the Institute for Catastrophic Loss Reduction (ICLR) discusses loss trend reporting by the Insurance Bureau of Canada. ICLR discusses but dismisses the calls for adjusting losses for growth, which is commonplace in Munich RE NatCatSERVICE analysis and reporting, and which is promoted by may others (this includes my paper in the Journal of Water Management Modelling which evaluated losses adjusted for net written premiums, and Roger Pielke Jr.'s work, such as reported here in Five Thirty Eight - see charts to the right - that also calls for evaluating trends considering GDP growth).

The ICLR notes "Normalizing disaster loss data to include such factors as growth in population, economic activity and building stock is not a simple undertaking. Further, there are many problems with using simple measures like GDP or insurance premium growth as a normalizer. For these and other reasons, I don’t want to go ‘there’ at this point ...".

So ICLR is content to us the following chart that does not include GDP adjustments:

Catastrophic Losses Flood Damages Canada
Losses in Canada Unadjusted for GDP Growth - 1983-2007 Data per IBC Survey, 2008- Data per CatIQ.

The ICLR notes a change in the data source for the above graph: "Bureau data begins at 1983. From that year to 2007, IBC uses data it collected itself through various company surveys conducted immediately after significant natural disaster events. It also uses various data from Property Claim Services (PCS), Swiss Re, Munich Re and Deloitte. After 2007, the Bureau only uses data from Catastrophe Indices and Quantification Inc. (CatIQ)."

How does the change in data affect reported losses? We can look at how the increase in losses has been reported, for example by the ICLR in 2016:

Catastrophic Loss Trends in Canada. Effects of change in data source on reported losses pre 2008.
Below the ICLR chart, the timing of the change in data is shown. This indicates that the change in reported annual losses from $400M average up to 2008 to $1B average after corresponds to the change in data source in 2008.

More recently the Intact Centre on Climate Adaptation (ICCA) has reported trends in losses on TVO's The Agenda as shown in the chart below:

Intact Centre on Climate Adaptation cites changes in insurable claims on TVO (chart shown), with ICLR's noted change in data sources added below (IBC data up to 2007 and CatIQ data from 2008 onward).

Again, the change in data is added below the ICCA chart. The lower losses of $200-500M up to 2008 and higher losses typically over $1B from 2009 onward correspond to this change in data source.

Adjusting for data sources or for GDP does not really change priorities for flood risk and catastrophic loss reduction. Better characterization of the GDP-adjusted trend can give us insight into the effectiveness of past mitigation efforts, more-resilient design standards that are common in modern practice. Without such GDP adjustment, one would think that everything is built as disaster-prone as it was in the past. Also, understanding the cause of the trend in losses will help focus adaptation or mitigation efforts in the proper place - if increases are explained by GDP growth as opposed to changes in extreme weather (shown to not be a factor) efforts will be placed on adaptation infrastructure built to old, less-resilient design standards as opposed to mitigation (e.g., GHG reduction).

A more wordy comment has been added to the ICLR blog post.

***

A paper Trend Analysis of Normalized Insured Damage from Natural Disasters, published in:
Climatic Change, 113 (2), 2012, pp. 215-237, by Fabian Barthel and Eric Neumayer, Department of Geography and Environment and The Grantham Research Institute on Climate Change and the Environment, London School of Economics and Political Science explores "Normalized" / GDP adjusted damages, exploring trends for different types of events.

As noted in their abstract:

"As the world becomes wealthier over time, inflation-adjusted insured damages from natural disasters go up as well. This article analyzes whether there is still a significant upward trend once insured natural disaster loss has been normalized. By scaling up loss from past disasters, normalization adjusts for the fact that a hazard event of equal strength will typically cause more damage nowadays than in past years because of wealth accumulation over time. A trend analysis of normalized insured damage from natural disasters is not only of interest to the insurance industry, but can potentially be useful for attempts at detecting whether there has been an increase in the frequency and/or intensity of natural hazards, whether caused by natural climate variability or anthropogenic climate change."

The following charts from the paper show an increase in deflated (non-normalized) damage losses over time, and virtually no change in normalized losses.

Global deflated insured losses from natural disasters
Global normalised insured losses from all disasters
Similarly, the following charts illustrate normalized trends for convective storm events (4165 disasters) showing a decrease, all storms including winter and other storms but excluding tropical cyclones (4369 disasters) showing a decarease, and for tropical cyclones (874 disasters) showing an increase.

Global normalized insured losses from convective events
Global normalized insured losses from all storm events except tropicalcyclones


Global normalized insured losses from tropical cyclones




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