Image:Cost-of-storms-by-decade.jpg

From Wikipedia, the free encyclopedia

Image
File history
File links

Cost-of-storms-by-decade.jpg‎ (28KB, MIME type: image/jpeg)

Origial figure, before suggestions resulting in the graph above. Note that neither figure yet includes historical data from 2000-2005. Revision requests included asking for confidence intervals, a greater level of significance, and a nonnegative domain.

1 Summary
2 Script to create
- 2.1 Application and source code
- 2.2 Thanks

[edit] Summary

The cost of extreme weather is rising rapidly and could reach four trillion dollars by 2020. source data: IPCC. Some of the increase is due to greater exposure such as building on the coast.

Later inferrior revision: The cost of extreme weather is rising rapidly and could reach 350 billion U.S. 2001 dollars per year by 2025. source data: IPCC, 2001. Some of the cost increase is due to added exposure such as building on the coast.

Note that the underlying cause (excees heat trapped in atmosphere by greenhouse gasses) more closely fits a sigmoid curve. The logistic sigmoid function or its functial neighbors (e.g., the Gompertz sigmoid) might produce a better extrapolation.

[edit] Script to create

[edit] Application and source code

decade <- c(1950, 1960, 1970, 1980, 1990)

billions <- c(3.5, 5, 7.5, 13, 40)

# from http://www.ipcc.ch/present/graphics/2001syr/large/08.17.jpg

new <- data.frame(decade = seq(1950, 2050, 1)) # for graph

lb <- log(billions) # enter log domain for nonnegative data

pm <- lm(lb ~ poly(decade, 2))

summary(pm)

"... on 2 degrees of freedom, adjusted R-squared: 0.9839, p-value: 0.00804"

clim <- predict(pm, new, interval = "confidence") # calculate confidence intervals

eclim <- exp(clim) # exit log domain

matplot(new$decade, eclim, lty = c(1, 3, 3), col = c("black", "brown", "brown"), type = "l", ylab = "billions", ylim=c(0,4000), xlab = "decade", xlim=c(1950,2020), main="average yearly inflation-adjusted U.S. dollar

cost of extreme weather events worldwide")

[edit] Thanks

Thanks to Marc Schwartz for the R commands to create graphs with confidence intervals.

I, the creator of this work, hereby release it into the public domain. This applies worldwide.
In case this is not legally possible,
I grant any entity the right to use this work for any purpose, without any conditions, unless such conditions are required by law.

File history

Legend: (cur) = this is the current file, (del) = delete this old version, (rev) = revert to this old version.
Click on date to download the file or see the image uploaded on that date.

(del) (cur) 02:17, 21 December 2005 . . Nrcprm2026 (Talk | contribs) . . 474×374 (28,538 bytes) (revision to Image:Cost-of-storms-by-decade.gif by James Salsman with 95% confidence intervals, in the nonnegative log domain, with 2 instead of 1 degrees of freedom, as requested at Talk:Global_warming#Image:Cost-of-storms-by-decade.gif)