Karen Clark has been engaged in making, implementing, and selling catastrophe models since the last Century. Okay, for decades. On her online site, www.karenclarkandco.com, this observation is written from that experience:
The catastrophe models have another important requirement, which is detailed data about the exposure at each location that could be affected by a catastrophe. For residential and commercial properties, this includes the replacement value, construction type, occupancy and other building specific details. Without this information or if this information is inaccurate, the models will not provide reliable results.
For more observations born of the experience of Karen Clark and Company, click here which will bring you to the first page of their web site, and click there on "catastrophe models" for the full posting.
A new computer model to predict the probability, consequences and necessary preventive measures for wildfires illustrates the need for reliable factual information in computer models in this report by Kirk Johnson, "Enlisting Computers to Help Fight Wildfires" p. A14, col. 1 (New York Times Nat'l Ed., Saturday, December 15, 2007). The computer model was caused by 8.9 million acres that burned in the United States this year. That is the second highest total -- and the year is not finished yet -- since 1960.
The reported wildfire computer model relies on soil moisture data provided by the United States Forest Service, images from Civil Air Patrol training flights, and analyses of ash from California wildfires. Those concerned with wildfires and their effects on people have made the wildfire computer model a priority for their own time and effort:
Building computer models is complex, scientists say, and there is not a lot of federal money to do it. Federal firefighting budgets have been stressed by recent major fires, scientists say, but a national expansion of the Grand County project could help decision makers set priorities. If 20 fires happened to be burning in several states, a modeling system could rank those fires according to criteria like the drift of the smoke and the potential impact on homes, businesses, water and wildlife. How many people and how much landscape might be affected by each fire, by each criterion, and at what cost?
The implications are pretty obvious for computer models used by many to predict the probability, consequences and necessary measures regarding Catastrophe Claims.
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