Here’s Willis’ most recent summary of the ongoing dialogue on the Emanuel story.
OK, got the HadISST data … here’s the story. Emanuel used the HadISST data, smoothed three times (not four, as with the PDI data). Here’s the match:
At this point, we can do some actual analysis of the results … the three unsmoothed datasets, appended at the end of this post, have the following characteristics.
1) NONE of the three has a significant trend. The figures are as follows:
ITEM , Orig PDI , HadISST , Adj PDI
Trend z , -0.87 , 1.37 , -0.10
Kendall z , -1.26 , 1.58 , -0.62
The "Trend z" is the significance of the trend, using Nychka’s adjustment for autocorrelation:
The "Kendall z" is the significance of the trend, using Kendall’s non-parametric trend test. 2) The SST is related to both the adjusted and unadjusted PDI, as follows:
ITEM , Orig PDI vs HadISST , Adj PDI vs HadISST
r^2 , 0.21 , 0.25
p value , 0.01 , 0.002
The p value has been calculated using Bartletts formula for the effective N,
While these relationships are statistically significant, they are quite small.
3) The method of smoothing (pinning the end points and repeatedly using a 1-2-1 smoothing filter) distorts the results. By pinning1) While there is a significant trend in the HadISST in the area from 1949-2003, there is no significant trend 1931-2003.
4) While there is a small relationship between the September HadISST sea temperature and the original PDI (r^2 = 0.21, p = 0.01), the relationship drops to r^2 = 0.08, p=0.12 when we use the August to October HadISST sea temperature … looks like my original suspicions of cherry picking were correct.
5) the endpoints, the start and finish of the curve are held in place, and the smoothed curve is adjusted to meet them. Because the start and end points are low and high respectively for both the PDI and the SST, this converts a "U" shaped curve into more of a hockeystick shape, by pinning the start low and the end high …