TheClimateChanger

Really looks like El Nino might be the saving grace - hopefully anyways. Could not imagine what the PDSI could end up if we saw a 1934-type summer setup? Would be something ridiculous like -10 to -15 nationally.

El Niño may end up being the saving grace for the current drought situation. The April contiguous U.S. PDSI came in at -7.56 — the lowest April value on record and the 4th lowest monthly value of any month, behind only July 1934, August 1934, and March 2026. So while there was a slight improvement from March’s -7.85, the national drought signal remains historically extreme. The scary counterfactual is: what if this pattern carried into summer and then paired with a 1934-type heat regime — or something even hotter in today’s warmer baseline climate? PDSI is not a linear “temperature gauge,” so I would not casually forecast -10. But entering the warm season already near -8 leaves very little margin. A major summer heat dome, high evaporative demand, and continued precipitation deficits could push national drought severity into territory that is difficult to contextualize historically. In other words: even modest improvement matters here. Without a pattern change, this is the kind of setup you really do not want to stress-test.

I also think we need to recover the polymath instinct. Historically, a lot of important thinkers crossed boundaries between business, politics, science, history, law, and the arts. We’ve moved toward extreme specialization, which has benefits, but also creates blind spots. AI makes it possible for more people to responsibly cross those boundaries again — not by replacing expertise, but by helping them read, calculate, compare, and test assumptions across fields. That’s the spirit of the piece: not “I’m the final authority,” but “let’s make the assumptions visible enough that more people can examine them.”

I think I follow. I agree that access to more data does not automatically produce better analysis — people and institutions can still overread, cherry-pick, or filter evidence through assumptions. But that is exactly why I wanted to start with a narrow, checkable example. I’m not claiming one CET reanalysis settles the whole medieval climate debate. I’m saying Lamb’s specific annual estimate is often treated with more authority than it deserves, and when you test the seasonal assumptions behind it, the result changes substantially. So the point is not “everyone with data is right.” It is almost the opposite: even influential reconstructions should be broken down, tested, and made transparent enough that non-specialists can see where the assumptions enter.

What did you think of the analysis?

I'll do an expanded analysis on Substack at some point. Here's GLERL satellite data for 1995-2025 for all of the lakes.

https://www.weather.gov/buf/LakeTemp

NWS Buffalo.

That sounds logical, but it’s not how the real Earth behaves. A true global average does have a seasonal cycle, and it’s not a sampling problem—it’s physics. The key issue is that the hemispheres aren’t equal. The Northern Hemisphere has a lot more land, and land heats and cools much faster than oceans. The Southern Hemisphere is mostly ocean, which responds slowly and dampens temperature swings. So when the Northern Hemisphere warms in summer, it pushes the global average up more strongly than the Southern Hemisphere can offset during its winter. The result is a real, global annual oscillation. If both hemispheres were identical (same land/ocean mix, same heat capacity), then yes—your cancellation idea would work. But they’re not, so it doesn’t. Also, every independent global dataset—NASA GISS, NOAA, HadCRUT—shows the same seasonal wiggle. That wouldn’t happen if it were just “Iowa with a fancy name.” So the graph is doing two things at once: The up-and-down is the seasonal cycle (dominated by Northern Hemisphere land) The overall rise is the long-term warming trend Seeing both together is exactly what you’d expect from a properly constructed global temperature record.

Lol, what's up with these June contract temperatures?

Indeed. Looks like May flips the script a bit though with a rather chilly look, at least to start.

Well, it’s clear that there’s a long-term warming trend on top of oscillations like El Niño–Southern Oscillation—and it’s especially noticeable over the past decade. ENSO explains short-term variability, not the rising baseline.

Yes—strong El Niños do cause short-term spikes in global temperature. But ENSO is an internal oscillation—it redistributes heat, it doesn’t create it. Over time, those effects average out. The fact that each ‘step up’ tends to land higher than the last is the signal of underlying greenhouse warming. That’s exactly the kind of ‘stair-step’ behavior that James Hansen has pointed to.

I don't know. Recent heating seems to be overpowering any natural variability/oscillations. Obviously, not every year is warmer than the previous, but the change seems to be more pronounced over the past several years - and I would expect that trend to continue at least through next year with the likely strong El Nino.

One angle I don’t see discussed much is how “feels like” temperatures are changing relative to actual air temperature. We usually focus on raw temperature trends, but that’s not necessarily what people experience. In winter, wind chill matters; in summer, humidity does. So I pulled PIT data back to 1960 and looked at mean “feels like” temperatures (wind chill in winter, heat index in summer) alongside the air temperature trends. A couple of interesting contrasts: January: Mean “feels like” temperature is increasing at ~10–11°F per century, versus about ~6–7°F per century for air temperature. So winters aren’t just warming — they’re becoming less harsh even faster than the thermometer suggests. July: The heat index trend is also higher than the air temperature trend (by roughly ~1°F/century on average). But that actually understates the real effect. Nighttime heat indices are typically equal to the air temperature (they’re not additive until you get into ~80°F+ conditions), so averaging over the full day mutes the signal. That implies that daytime heat indices are likely increasing on the order of ~2–3°F/century in addition to the air temperature trend.

Here are the trends since 1960 by month, sorted May to April. Month Trend (°F/decade) Trend (°F/century) May +0.60 +6.0 Jun +0.47 +4.7 Jul +0.56 +5.6 Aug +0.45 +4.5 Sep +0.54 +5.4 Oct +0.42 +4.2 Nov +0.22 +2.2 Dec +0.92 +9.2 Jan +0.68 +6.8 Feb +0.94 +9.4 Mar +0.60 +6.0 Apr +0.74 +7.4