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The Honest Broker Profile picture
@RogerPielkeJr
Dec 9, 2021 • 9 tweets • 3 min read • Read on X
Scrolly
Laugh or cry?
New AI tool for climate misinformation

“Ultimately, our goal is the Holy Grail of fact-checking, which is being able to detect and debunk misinformation in real time. Ideally, I would have social media platforms using it to detect misinformation in real time.”
What counts as "climate misinformation"?
Let's have a look

"Denialist keywords include references to
extremes in the past, extremes not
increasing or extremes not linked to
climate change."
More denialist claims

Includes "damages/deaths from extreme weather aren’t increasing"
Includes "extreme weather linked to non-climate change phenomena (like ENSO)"
More denialist claims

Includes "Future generations will be richer and better able to adapt"
More denialist claims

"Carbon Capture & Sequestration (CCS) is unproven/expensive"
More denialist claims

"Nuclear power is safe/good for society/economy/environment"
More denialist claims

Criticism of Skeptical Science 🤣
If there was ever any doubt that these guys want to control public debate & silence those with differing views that's gone

Wash Post: washingtonpost.com/weather/2021/1…

Nature Reports: nature.com/articles/s4159…

Fun times!
PS. These are the folks behind the new AI tool for detecting the denialists among us

forbes.com/sites/rogerpie…

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More from @RogerPielkeJr

The Honest Broker Profile picture
Jan 11
🧵
The percentage of a percentage trick is increasingly common & leads to massive confusion

Here a undetectable difference of 0.01 events per year per decade is presented as the difference between a 31% and 66.4% increase (in the *likelihood* of the event, not the event itself) Image
The resulting confusion is perfectly predictable

Here is a reporter (NPR) explaining completely incorrectly:
"The phenomenon has grown up to 66% since the mid-20th century"

False Image
Also, the numbers in the text and figure do not appear to match up
I asked Swain about this over at BlooSkeye Image
Read 4 tweets
The Honest Broker Profile picture
Dec 22, 2024
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, 2024
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, 2024
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, 2024
🧵
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, 2024
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

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