The Honest Broker Profile picture
Jun 14, 2021 11 tweets 4 min read Read on X
I was curious
So I graphed percent of CONUS in drought according to the US drought monitor, data is weekly from 1/2000
droughtmonitor.unl.edu/CurrentMap.aspx
Here from US EPA is the same data by drought category
epa.gov/climate-indica…
And here from EPA is a longer time series, 1895-2020 for CONUS
Note: On this graph up means wetter, down means dryer
epa.gov/climate-indica…
And here is the percent in drought (D0-D4) of the Colorado River Basin over Jan 2000 to present
droughtmonitor.unl.edu/CurrentMap.aspx
And here is Colorado River Basin drought 1901-2015
via McCabe et al 2020
journals.ametsoc.org/view/journals/…
And for a much longer perspective, here is Colorado River Basin drought over the past 1800 years
Also from McCabe et al 2020
TL;DR
Here are the conclusions of McCabe et al 2020
Well worth reading carefully
And here is what the US National Climate Assessment concluded on drought in 2018
nca2018.globalchange.gov/chapter/2/
PS
A side note
For accurately citing peer reviewed literature & US NCA on drought trends in 2013 Congressional testimony, I earned the distinction of being the only US researcher in history to be attacked by the president's science advisor (Holdren) in a White House blog post 😎
PPS
Holdren is still wrong
The IPCC, USNCA & peer reviewed literature that they rely on is still correct

Climate change is real, and aggressive mitigation & adaptation policies make good sense

The reality of climate change doesn't mean scientific integrity can be ignored

/END
Oh, I guess I should point out Holdren's false claims about me posted on White House website were basis for a subsequent Congressional investigation of me that turned my life upside down & almost ended my career
But I'm still here
And that kids is how I came to understand tenure

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More from @RogerPielkeJr

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
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
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
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
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
Read 4 tweets
Feb 23, 2024
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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