This is a really important number & I haven't seen it mentioned anywhere
FEMA estimates that in 2021 we should expect $141B is catastrophe losses in the US, based on current exposure, historical event frequency & loss ratios
The FEMA loss estimation CANNOT be compared to the spectacularly awful NOAA billion dollar losses
For weather losses, FEMA uses data processed by ASU/SHELDUS off of NOAA Storm Data, as below
NOAA Storm Data uses a bespoke special sauce to gin up losses (read on...)
NOAA's billion $ loss database mixes together direct and indirect losses (like business interruption & commodity markets) as well as non-event costs (e.g., "disaster restoration and wildfire restoration")
They also "scale up" insured loss data, which guarantees double counting
NOAA also includes improperly a 10-15% scale-up of losses putatively based on Smith and Katz 2013 (side note: Rick Katz had the office next to mine at NCAR for 8 years)
This is not what their paper says to do - as it is a function of insurance participation rates
Whatevs
If NOAA were to take Smith and Katz seriously they would
(a) Not use crop losses
If NOAA were to take Smith and Katz 2013 seriously they would
(b) Not use just CPI-adjusted data
(In other words .. NOAA shouldn't be doing what they are doing!)
All that said
Understand that FEMA's expected annual loss estimates are serious - $141B/yr
NOAA's billion dollar disasters is bad science at best & political propaganda at worst
Don't confuse the two
What is a more accurate representation of US* weather disaster losses over time?
Here you go, enjoy!
Note: FEMA's $141B in 2021 equates to ~0.6% of GDP
*North America, but almost all are US
Interestingly, median North American weather losses 2010-2020 in Swiss Re dataset are $140B, while FEMA total expected losses for 2021 are $141B (not just weather)
This suggests to me that FEMA is low
Expected losses should be higher than 10-yr median due to growth alone
/END
PS. Just for fun I have graphed below NOAA Billion$ disaster losses as a % of Swiss Re total NA weather losses
2017 is ... interesting
Pop quiz: Over time, why might we see a greater proportion of total losses coming from billion$+ events? Is there an economist in the house?
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The idea it was perfect under Democrats, as @afreedma & other advocacy journos suggest, is simply wrong
The most recent NCA was totally capture by interest groups and companies that would benefit from the report - UCS, TNC, EDF, CAP, Stripe etc
Below just a few of its authors
@afreedma The head of the NCA5 stated publicly that she would never cite our work in the assessment, even though our work is by far the most cited research on economic losses in the US associated with floods, hurricanes, tornadoes
🧵Let's take a quick look at the implications of the regulations that have followed from the 2009 EPA endangerment finding
According to @C2ES_org the 2021 GHG standards for light vehicles would reduce projected CO2 emissions by a cumulative 3.1 billion tons to 2050 c2es.org/content/regula…
Over the next 25 years the world would emit 925 gigatons of CO2 assuming constant 2025 emissions and ~690Gt assuming emissions are cut in half by 2050
That means that the projected impact of the regulations would reduce global emissions by 0.0003% (constant) & 0.0004% (halved)
The idea that CO2 can be regulated out of the economy is flawed
If the purpose of CO2 regulation is to create a shadow carbon tax, then it is a horribly inefficent way to do that
Once again, all this leads us back to Congress and the need for smart energy & climate policy
🧵
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)
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
Also, the numbers in the text and figure do not appear to match up
I asked Swain about this over at BlooSkeye
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!
The errors here are so obvious and consequential that it is baffling that the community does not quickly correct course
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!
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
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