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The Honest Broker Profile picture
@RogerPielkeJr
Oct 2, 2020 • 4 tweets • 2 min read • Read on X
Important article by @SolomonMg and colleagues

Projecting Confidence: How the Probabilistic Horse Race Confuses and Demobilizes the Public | The Journal of Politics: Vol 82, No 4 journals.uchicago.edu/doi/abs/10.108…
I discussed the pathological potential of horse race election predictions a little ways back

amp.theguardian.com/science/politi…
Ungated link here:
Just look at this
Remarkable

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More from @RogerPielkeJr

The Honest Broker Profile picture
Dec 22
The new hurricane damage time series trick

Step 1: create Frankenstein dataset w/ an increasing trend where there was not an increasing trend before

Step 2: Attribute the increasing trend to climate change

Step 3: Use Frankenstein dataset to impeach other research w/ no trend Image
The reason that the blue and red numbers are different is that they are different measures of hurricane losses

E.g., the red numbers include inland NFIP damage
The blue numbers do not, on purpose, because NFIP only started in 1968

They are apples and oranges
Now 3 peer-reviewed papers (PNAS, JAMC, BAMS) make this most basic of errors by replacing and splicing NOAA BDD to the MWR/NHC time series

Predictably all three papers find an increasing trend in normalized hurricane damage even though landfalling hurricanes are not increasing Image
Read 6 tweets
The Honest Broker Profile picture
Dec 21
A Frankenstein dataset results from splicing together two time series found online

Below is an example for US hurricane damage 1900-2017
Data for 1980-2017 was replaced with a different time series in the green box
Upwards trend results (red ---)

Claim: Due to climate change! Image
The errors here are so obvious and consequential that it is baffling that the community does not quickly correct course

Read about it here
Is my analysis flawed?
osf.io/preprints/osf/…
The IPCC AR6 cited a paper misusing the Frankenstein hurricane loss dataset to suggest that NOAA's gold standard hurricane "best track" dataset may be flawed

JFC - Using flawed economic loss data to suggest that direct measurements of hurricanes are in error! Image
Read 6 tweets
The Honest Broker Profile picture
Nov 2
We’ve reached the point where an IPCC author is openly rejecting the conclusions of the IPCC out of concern over how their political opposition is correctly interpreting the AR6

The integrity of the IPCC on extreme events is now under attack
The IPCC explains that a trend in a particular variable is DETECTED if it is outside internal variability and judged with >90% likelihood

For most (not all) metrics of extreme weather detection has not been achieved

That’s not me saying that, but IPCC AR6 Image
The IPCC also assesses that for most (but not all) metrics of extreme weather the signal of a change in climate will not emerge from internal variability with high confidence (ie, >90%) by 2050 or 2100, even assuming the most extreme changes under RCP8.5 Image
Read 6 tweets
The Honest Broker Profile picture
Oct 31
🧵
You won't believe this

The US National Academy of Sciences has a new study committee on Extreme Event Attribution

Among its sponsors are the Bezos Earth Fund and Robert Litterman

Who are they? . . . Image
Image
The Bezos Earth Fund sponsors World Weather Attribution, an advocacy group promoting the connection of weather events w/ fossil fuels in support of press coverage & lawsuits

Robert Litterman is on the board of Climate Central which founded WWA & collaborates on climate advocacy Image
The fact that a NAS committee is funded by political advocates is crazy enough

But that is not all

On the committee itself are individuals from two climate advocacy groups

One . . . the Union of Concerned Scientists which is working to use attribution to support lawsuits . . . Image
Read 7 tweets
The Honest Broker Profile picture
Jul 18
1/3
Climate science is broken

I provided PNAS with irrefutable evidence that a paper it published used a fatally flawed “dataset” compiled by interns for corporate marketing

I asked for a retraction

PNAS investigated & found no problems at all with the dataset

The PNAS reply belowImage
Image
I documented how the “dataset” was created (including contributions of two of my former students)

It was never intended for scientific research, just for selling insurance products

In the next Tweet I’ll link to my post with all of the details

If climate science cannot pass this simple test, it has a serious problemImage
Full analysis

rogerpielkejr.substack.com/p/apples-orang…
Read 4 tweets
The Honest Broker Profile picture
Feb 23
I have been digging into methodological and data errors in Grinsted et al. 2019, some of which you can see in the thread below

This nerdy thread on US hurricane loss data documents how bad data gets created (surely accidentally) . . .
A time series of base (i.e., current-year) loses was first compiled from annual reports published in the Monthly Weather Review by Chris Landsea in 1989 for 1949-1989

I extended the data using same methods to 1996

Chris and I extended back to 1900 for Pielke and Landsea 1998 Image
Then, Pielke et al. 2008 extend the dataset to 2005, again using the same methods

The heavy lifting was done by my then-student Joel Gratz

Joel graduated and went to an insurance company called ICAT . . . Image
Read 5 tweets

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