California, Temperatures, and Acres Burned

California, Temperatures, and Acres Burned

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Guest Post by Willis Eschenbach

Inspired by the work done by Robert Rohde attempting to link May to October temperatures and rainfall to fires, I thought I’d take a look at the acres burned over the years. Rohde compared the rainfall and temperature records and highlighted the largest fires. However, this gives only a few data points. I wanted a larger view of the situation.

So instead of major fires, I looked at the areas burned every year, which are available here. There is complete data from 1959 to 2016, and the last two years are available here and here.

The first thing I did was run a multiple regression on the data, using both May to October temperature and May to October rainfall to see how well they would predict the area burned. To my great surprise, I found out that rainfall is not significantly correlated with the area burned. Here is that result:

               Estimate Std. Error t value Pr(>|t|)    
(Intercept)   -13393785    2502402  -5.352 1.61e-06
Temperature      203834      35791   5.695 4.52e-07
Rainfall         -46812      35591  -1.315    0.194

Temperature is significant (right-hand column, p-value 4.52e-7), but rainfall is far from significant (p-value = .19). So I ignored rainfall for the rest of the analysis.

Next, I graphed the acres burned, and ran a linear regression on the data. Figure 1 shows that result:

Figure 1. Total areas burned by year, 1959-2018 (red line) and linear least squares trend line (blue line).

Note that the p-value of the line is quite good (right column, p-value = .00000004). The R^2 value (bottom line) shows that the straight line explains 41% of the variance in the acres burned.

Then I looked at the connection between temperature and acres burned. Figure 2 shows that result:

Figure 2. Total areas burned by year, 1959-2018 (red line) and acreage estimated from the variation in May – Oct temperatures (blue line).

Curiously, that looks a lot better than the straight line … but note that there is only a slight increase in the amount of variance explained (44% variance explained by temperature versus 41% for the straight line). This proves once again that our eyes are tuned to see patterns even when none are there … consider the constellations of the night sky as a prime example.

Finally, I looked at the errors in the temperature based estimate of the acres burned. Figure 3 shows the difference between the temperature-based estimate of the area burned and the actual acreage burned.

Figure 3. Errors of the estimate.Total areas burned by year, 1959-2018, minus the acreage estimated from the variation in May-Oct temperatures. The red line is a seven years Full-Width Half Maximum (FWHM) Gaussian average of the data. The vertical dotted blue line shows that in 1994, logging was stopped in much of the state in a vain attempt to protect the Spotted Owl.

Here is the oddity of the Figure 3 graph. In the first part of the record, up to the early part of the 21st Century, the temperature generally overestimates the acres burned.

But since then, the temperature has greatly underestimated the number of acres burned.

This is clear evidence that the recent large wildfires are not due to the variations in temperature as is widely claimed.

Conclusions

• Using variations in May to October rainfall do not improve the estimate of the acreage burned. In other words, May to October rainfall doesn’t add anything to an estimate done using May to October temperature alone.

• The variations in May to October temperature are only slightly better than a straight line in estimating the variations in area burned.

• The recent very large areas burned are not the result of variations in May to October temperature. As I pointed out in my last post, the decade over decade changes in temperature are nowhere near large enough to explain the recent increase in the area burned. We must look elsewhere for the causes of these large fires.

h/t to Steven Mosher for pointing out the Rohde analysis.


I’m home now, and the smoke is not too bad. Not as bad as it was in the Central Valley or in San Francisco on the way back here. We’re in the yellow area on the California coast north of San Francisco. Smoke map available here, click on “Vertically Integrated Smoke” or “Near Surface Smoke”.

Figure 4. Smoke map. Red is the thickest smoke. The Camp Fire is burning north-east of Sacramento.

My best wishes and hopes for the future for all of those affected by the fires, and my condolences for those who have lost friends, family, or homes.

Regards,

w.

PS—My usual request. When you comment, please quote the exact words you are referring to, so we can all be clear on what you are discussing.

Superforest,Climate Change

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