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And yet again the ECMWF's AI model has been hinting at robust tropical development whereas the operational model is anemic with it. At least in terms of tropical cyclone genesis the AI has been an overachiever relative to the operational model in terms of skill this year.

Here is a just published article on the sea ice volume declines. [Soriot et al. 2024] - Winter arctic sea ice volume decline: uncertainties reduced using passive microwave-based sea ice thickness And if I'm not mistaken the DMI sea ice volume summer minimum reached a new record low beating out 2012.

Svalbard went crazy. I don't typically highlight individual locations like this, but since it is in the Arctic where it can at least somewhat represent the melting tendency on the sea ice I thought it might be interesting enough.

I have a few reasons to be critical of Dr. Spencer, but to be fair to him he posted this on his blog today. I'm more concerned with the likes of Joe Bastardi and Ryan Maue. I’m even part of the supposed 97% that believes the climate system is warming partly (maybe even mostly) from our CO2 emissions.

August 2024 beat August 2023 in the UAH dataset. Here are the trends over periods of interest... 1st half: +0.14 C.decade-1 2nd half: +0.23 C.decade-1 Last 10 years: +0.39 C.decade-1 Last 15 years: +0.37 C.decade-1 Last 20 years: +0.30 C.decade-1 Last 25 years: +0.22 C.decade-1 Last 30 years: +0.18 C.decade-1 The warming rate acceleration is now +0.028 C.decade-2.

The 14 C is in reference to the ESS (Earth System Sensitivity). From the publication they say ECS (Equilibrium Climate Sensitivity) is 7 C. For those that don't know ESS is the amount the Earth warms after the slow feedbacks play out while ECS is only after the fast feedbacks play out. Fast feedbacks are on the order of 100 years while slow feedbacks are on the order of the 1000-10000 years. An example of a slow feedback is ice sheet melt out.

The winters of 12/13 and 13/14 were La Nada.

And that is gaslighting behavior. If you use raw data without correcting for known errors that is fraud. Plain and simple. And depending on the context, authority, etc. this fraud could even qualify as criminal behavior. For example, think of an NHC forecaster who publishes an official hurricane intensity that is grossly under/over estimated because he "only and always uses raw data no matter what". I trust that you understand all the ways dropsondes, buoys, flight level winds, SFMR, ADT, etc. can under/over estimate a tropical cyclone's intensity and that this example will resonate with you.

I'm going to stop you right there. That's straight up brazen fraudulent behavior.

I think it is telling that you only use raw data errors and all when it shows less warming than the corrected data, but refuse to use raw data when it shows more warming than the corrected data. And do you really think nobody knows what the global average temperature is? I want you to seriously sit and think on that before answering. Do you really want to plant you flag there? Or was that just an off-the-cuff remark made more out of frustration than true conviction.

No worries. I was not suggesting that you should make that statement in regard to the Chester County average. I was suggesting you do it for the global average.

Let's test your resolve then. Post on your twitter account that the warming is worse than scientists say because those scientists rewrote history to obscure the true nature and higher rate of the warming.

BTW...I had an absurd debate with Andy May over WUWT recently because he thinks global averages (whether sea level or temperature) are meaningless. Even when I pushed to get him to pull back from the claim he held firm. So his publishing of articles predicting that global warming had stopped is doubly ironic.

Which technically shows MORE warming than the traditional datasets during their overlap period. And furthermore the net effect of all adjustments globally actually results in LESS warming relative to the raw data. This is why I've asked @ChescoWx in the past if he really wants to hang his hat on the adjustment-bad argument and accept all of the consequences that go along with it.

The Kalshi prediction market shows a 28% chance of breaking the 2012 record.

Unsurprisingly global sea ice extent is at a record low for July 26th beating the previous record set in 2023.

I've been skeptical regarding research showing that the Hunga Tonga eruption had little impact on global average temperatures. It's probably time for me to throw in the towel. Hot off the press is yet another study showing no augmentation of the global average temperature. In fact, if anything, it may have slightly contributed a cooling influence. This is obviously more bad news for skeptics of global warming since Hunga Tonga was a factor that some used as evidence against Hansen's accelerated warming hypothesis. [Shoeberl et al. 2024]

It looks like Las Vegas is on track to have it's hottest month on record. If the official NWS forecast verifies and assuming I added everything up correctly they will end with an average of 99.2 F which would beat 2023's record of 97.3 F. Personal note...My family is wrapping up a vacation in the region. We started in California's central valley and drove into parts of Nevada, Arizona, and Utah and are flying back to St. Louis from Las Vegas. It has been brutally hot the whole time almost everywhere except for the slight reprieve while in the mountains. Death Valley was particularly insidious. Atypical of the region it was actually modestly humid so the heat index matched the temperature when we drove through. We were confused as we approached from Lone Pine, CA seeing runners. After a bit of research we realized we were unintentionally spectating the 2024 Badwater Ultramarathon where 100 of the word's toughest superhumans race from Badwater Basin (lowest point in CONUS) to Mt Whitney (highest point in CONUS) and is considered the world's hardest foot race. I tip my cap to those who participated in that race,

Dust bowl. It's effects were large and widespread easily encompassing the eastern states and impacting temperatures there. [Meehle et al. 2022]

I did a quick review of IPCC AR6 WGI chapter 5 regarding the carbon cycle. Based only off a cursory read I don't think they are expecting the land sink's ability to buffer carbon to wane until much later this century. So if we're already seeing signs that it's ability to take carbon is saturating then that's not good obviously.

That guy has a long history of contrarianism and misinformation. I give him credit for a testable prediction, but it's going to end up being wrong. BTW...it's ironic how contrarians flock to the idea that 150 MtH2O can cause so much warming while simultaneously scoffing at the nearly 100,000 MtCO2 that humans pumped into the atmosphere in the 2.5 years since the HT eruption. I'm not saying HT didn't have a measurable effect on the global average temperature. I've been pretty open to the idea that it may have. But to claim that it is the primary cause of the recent spike while suggesting that ENSO had little if any effect is absurd. I'm also disappointed with degreed meteorologists like @John Shewchuk who pop in from time to time on articles like that and in support of this kind of misinformation. John, having a genuine conversation with you is nearly impossible because of your challenges to fundamental and well established physical principals and laws, accusations that NOAA (who was at least at one time one of your customers) is wantonly committing fraud, and incessant gaslighting in general. I tag you here to give you the opportunity to defend yourself if you so desire.

Relevant to this discussion is [Menne & Williams 2009] which documents the pairwise homogenization algorithm. Like @chubbs said it is done for each station individually to identify the changepoints and quantify and correct the bias that it introduces. This technique was introduced so that GHCN (including USHCN and now nClimDiv) was robust enough to handle stations that did not have adequate metadata (like is available in the HOMR database) to know when significant changes occurred to them. Even in the US the HOMR database does not always capture every change to a station.

Can you give me an example of one of these ghost stations? I'd like to research that.

Relevant to this discussion is the way UHI works. UHI Effect - This is the increase in temperature as a result of land use changes. It is a real phenomenon. UHI Bias - This is the error that is introduced into spatial averages as a result of oversampling either urban or rural stations in a grid cell. This is not a real phenomenon. Instead it is an artifact of the methodology chosen. It is is really important to understand that while the UHI Effect is always positive the UHI Bias can either be positive or negative depending on which stations are oversampled. The movement of the Coatesville station to a more rural site introduces a negative UHI Bias on spatial averages. It is worth repeating and boldening. The UHI Bias can and often is negative. [Wickham et al. 2013] analyzed the bias UHI caused in the Berkeley Earth dataset. They concluded "We observe the opposite of an urban heating effect over the period 1950 to 2010, with a slope of -0.10 ± 0.24°C/100yr (2σ error) in the Berkeley Earth global land temperature average." This is statistically equivalent to no effect, however, if anything, it is more likely the effect biased the global average temperature trend too low. I'll point out that Berkeley Earth uses a unique methodology in which they do NOT perform any adjustments to station data and yet get essentially the same warming trend as every other global average temperature dataset.

With the June update the warming rates of nClimDiv and USCRN are +0.58 F/decade and +0.70 F/decade respectively over their overlap period. It is important to note that nClimDiv uses pairwise homogenization to identify changepoints and correct the biases they cause. USCRN does not perform adjustments of any kind. So for those who think NOAA's adjustments are the cause of the warming trend this is strong evidence that the hypothesis is false. In fact, the opposite may be occurring. NOAA's adjustments may still be inadequate to fully remove the low bias.