New report about the near-term future climate of Texas. From the Office of the State Climatologist, @climatexas:
texas2036.org/texas-will-fac…
The average temperature of Texas is going up ✅. This will also lead to more extreme temperatures. Image
More extreme rain events ✅. Image
Trends in overall precipitation in the near-term are harder to forecast because of the impact of unforced variability (like El Ninos). However, the combination of variability in precipitation combined with higher temperatures will tend to produce more severe droughts. Image
More dangerous hurricane storm surges due to sea level rise, of course. Image
So, yeah, all of the bad things about TX weather are going to occur more frequently in the future.
In the future, Texans will spend more and more of their money running their AC, rebuilding from the last flood, and building new freshwater infrastructure, etc.

We will be poorer than in a world without climate change. This is a climate tax we're already paying.
It seems unlikely that anything humans could do would have much of an impact on the 2036 climate.
Nevertheless, humans do have a lot of control over what the TX and the planet will look like in 2100. Let's hope we take advantage of that opportunity.

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More from @AndrewDessler

1 Oct
I've been collecting "lessons I've learned communicating climate on Twitter" over the last 8 years and finally thought I'd write a 🧵. This is mainly aimed at younger scientists, but others might find it useful.
First, everyone should tweet about climate. Social change won't happen unless everyone agitates for it.
When you begin outreach, you may feel like you're not enough of an expert. If you're a typical academic, your expertise is a delta function: infinite knowledge about almost nothing.

If we only talked about what we actually research, most of us would have nothing to say.
Read 24 tweets
24 Sep
this is 100% right
tbh, I can't decide which I love more about my job: the short hours ...
Read 7 tweets
23 Sep
Cleaning my desk and finding a lot of interesting stuff. Turns out that things go from interesting to trash and back to interesting over 12 years.
I really need to clean off my desk more often. I am not sure this has been on my desk buried since 2007, but it’s possible.
Also on my desk: in 1989, Fred Singer sent this document to my father trying to get his support for this piece on “misuse of environmental science”. He gave it to me 10-15 years ago. I need to scan that in.
Read 8 tweets
22 Sep
Carbon cycle feedback, anyone?

California’s Wildfires Had an Invisible Impact: High Carbon Dioxide Emissions nytimes.com/2021/09/21/cli…
A carbon cycle feedback means that warming temperatures cause the release of more carbon dioxide (or other GHGs) and that this in turn causes more warming.

A warming climate leads to more forest fires, which release carbon into the atmosphere, is a classic carbon cycle feedback.
The other oft-discussed carbon cycle feedback is warming temperatures thawing permafrost, which then decays and releases GHGs into the atmosphere, leading to more warming.
Read 6 tweets
20 Sep
More on @ERCOT_ISO and the Texas grid. In a previous 🧵, we talked about how the supply of energy on the TX grid is very tight. This is not ERCOT's fault — it's a fault of the way the market is set up.

But that doesn't mean ERCOT is blameless. A 🧵:
ERCOT makes seasonal forecasts in order to ensure that supply is sufficient for the demand. You can find them here: ercot.com/gridinfo/resou…
For the last winter, we can compare these forecasts to forecasts we make from a large ensemble of climate model runs and to reality. More info can be found in the preprint written by my grad student, Jangho Lee (eartharxiv.org/repository/vie…).
Read 16 tweets
18 Sep
Why is Texas electricity both unreliable and expensive?

Let me tell you about some new research by my grad student, Jangho Lee.

A 🧵:
Using historical data we got from @ERCOT_ISO's web page, we developed a statistical model of electricity demand as a function of temperature and an inferred long-term trend of non-climate factors (e.g., population).
If we plug historical temperatures (ERA5) into the statistical model, we can reproduce almost exactly the historical power usage. This plot shows a comparison of seasonal maximum power:
Read 19 tweets

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