What’s your KatRisk Score?
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by Joseph Rickert
KatRisk, a Berkeley based catastrophe modeling company specializing in wind and flood risk, has put three R and Shiny powered interactive demos on their website. Together these provide a nice introduction to the practical aspects of weather based risk modeling and give a good indication of the kinds of data that are important. Two of the models, the US & Caribbean Hurricane Model and the Asia Typhoon Model, provide a tremendous amount of information but they require a little bit of background knowledge to understand the data required to drive them, and the computed loss statistics.
The Flood Data Lookup Model, however, can really hit home for anybody. Just bring up the model, type in the address of the location of interest and press the red “Geocode” button to get the associated longitude and latitude. Then click on the “Get Data” button. The resulting information will give you an idea of the level of risk for the property and let you know what a 100 year flood and 500 year flood would look like. Next, switch to the “Flood Map” tab and press the “Get Map” button to see some of the information overlayed on a Google map.
Not being able to resist the opportunity to have Google Maps google Google, I thought it would be interesting to see how bad things could get at the Googleplex.
Uh oh! The Googleplex gets a pretty high KatRisk score. A 100 year flood would put the place under 7 feet of water!
Not to worry though: Google has already completed their first round of feasibility tests for a navy. (Nobody does long range planning like Google.)
The KatRisk models are based on R code that makes heavy use of data.table for fast table look ups of the risk results. As the company says on their website:
KatRisk has developed a suite of analytic tools to make it easy to access our data and models. We use open source software tools including R Shiny for our web applications. By using R shiny we can develop on-line products that can also easily be deployed to a client site. Our software is completely open, so if you decide to host our analytical tools you will be able to see all of the details in easy to understand and modify R code.
For some details on the underlying analytics have a look at this previous post that was based on a talk Dag Lohmann gave to the Bay Area UseR Group last year.
So, go ahead and compute your KatRisk score, but please do be mindful of the company's request not to run the model for more than 3 locations in one day.
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