If 1ยฐC Destroys 20% of GDP, Why Did Nobody Notice?

A new working paper from the National Bureau of Economic Research makes a rather astonishing claim. According to Adrien Bilal and Diego Kรคnzig in โ€œThe Macroeconomic Impact of Climate Change: Global vs. Local Temperature,โ€:

โ€œ1ยฐC warming reduces world GDP by over 20% in the long run.โ€

From Watts Up With That?

By Charles Rotter

Charles Rotter

If 1ยฐC Destroys 20% of GDP, Why Did Nobody Notice?

A new working paper from the National Bureau of Economic Research makes a rather astonishing claim. According to Adrien Bilal and Diego Kรคnzig in โ€œThe Macroeconomic Impact of Climate Change: Global vs. Local Temperature,โ€:

โ€œ1ยฐC warming reduces world GDP by over 20% in the long run.โ€

That is not a marginal adjustment to the literature. It is a tenfold escalation.

The authors go further:

โ€œClimate change of 2ยฐC by 2100 leads to a present-value welfare loss of more than 30% and a Social Cost of Carbon (SCC) in excess of $1,200 per ton.โ€

If these numbers are even approximately correct, the implications are staggering. Carbon pricing would not merely be prudent. It would be radically underpriced. Climate change would not be a gradual background risk; it would already rank among the largest macroeconomic shocks in modern history.

And yet a simple question arises.

If 1ยฐC of warming destroys 20% of global GDP, why did nobody notice?

The Hidden Great Depression

Since roughly 1960, global average temperature has risen about 1ยฐC. Over the same period:

  • World GDP per capita has risen roughly three- to four-fold.
  • Global poverty rates have collapsed.
  • Agricultural yields have increased dramatically.
  • Life expectancy has surged.
  • Extreme weather mortality has fallen sharply.

According to the paperโ€™s own counterfactual exercise:

โ€œWorld GDP per capita would be more than 20% higher today had no warming occurred between 1960 and 2019.โ€

In other words, we are living through the equivalent of a permanent Great Depression relative to a hypothetical non-warming baseline โ€” we just failed to detect it.

This is an extraordinary claim. And extraordinary claims demand extraordinary evidence.

The Methodological Pivot: Global vs. Local Temperature

For decades, most empirical climate-economy research has relied on local temperature variation across countries. Those studies typically find that a permanent 1ยฐC increase reduces GDP by about 1โ€“3%.

Bilal and Kรคnzig argue that this approach understates damages because panel regressions with time fixed effects remove global effects. They instead exploit time-series variation in global mean temperature, constructing โ€œglobal temperature shocksโ€ and tracing their impact on world GDP .

Using this approach, they estimate that a 1ยฐC shock leads to a 14โ€“18% decline in GDP within six years . They then scale these responses to infer that a permanent 1ยฐC rise reduces long-run GDP by roughly 20โ€“34% .

But here is the quiet detail doing enormous work:

The actual shocks observed in the data are on the order of 0.1โ€“0.2ยฐC .

The authors extrapolate from these small, transitory fluctuations to a permanent 1ยฐC structural shift โ€” five to ten times larger than anything directly observed.

That scaling requires strong linearity assumptions and assumes that short-run natural variability is a valid proxy for long-run anthropogenic warming. That is not a trivial assumption.

The Identification Problem No One Can Escape

Global temperature is a single, highly persistent time series.

So is global GDP.

Even after filtering and controlling for oil prices, recessions, and interest rates, the identifying variation remains one-dimensional and global.

There is only one planet.

Panel studies using local variation at least benefit from cross-country differences. A global time series does not. Any unobserved global shock correlated with temperature fluctuations can contaminate the estimates.

Robustness checks cannot fully resolve that structural limitation.

The Missing Side of the Ledger: Benefits of Mild Warming

Perhaps the most striking omission in the paperโ€™s narrative is the asymmetric treatment of potential benefits from modest warming and rising COโ‚‚ concentrations.

The authors argue that global temperature shocks strongly predict extreme events . That may be so. But the paper largely treats warming as a one-directional negative productivity shock.

The historical record is more complex.

1. Agricultural Productivity

The Green Revolution dramatically boosted crop yields beginning in the 1960s. But yield gains did not occur in a vacuum. CO2 is not a pollutant to plants. It is a fundamental input.

Numerous agronomic experiments have shown that elevated CO2 concentrations:

  • Increase photosynthetic rates
  • Improve water-use efficiency
  • Raise crop yields under many conditions

At moderate temperature increases โ€” particularly in colder regions โ€” growing seasons lengthen, frost days decline, and marginal land becomes cultivable.

Global cereal yields have increased more than threefold since 1960. That does not prove warming caused it, but it does complicate the narrative that warming is a dominant macroeconomic drag.

2. Global Greening

Satellite observations over the past several decades show a measurable increase in global leaf area index โ€” often referred to as โ€œglobal greening.โ€ A substantial fraction of this increase is attributed to CO2 fertilization.

More vegetation implies:

  • Greater biomass
  • Enhanced carbon uptake
  • Expanded agricultural potential in some regions

Again, this does not negate climate risks. But if a 1ยฐC warming were destroying 20% of global GDP, one might expect to observe broad productivity deterioration, not simultaneous global greening and rising agricultural output.

A World That Doesnโ€™t Look Like a Collapsing Economy

The paperโ€™s structural model projects dramatic capital destruction and productivity collapse. Under a 3ยฐC scenario, GDP per capita falls more than 50% by 2100 .

Yet the historical 1ยฐC warming so far coincided with:

  • Rising total factor productivity
  • Massive capital accumulation
  • Rapid technological diffusion
  • Urbanization and industrialization

For the 20% figure to hold, global growth absent warming would have needed to be even more explosive than the already unprecedented growth actually observed.

That is possible in theory. But it implies that climate change has already suppressed a vast, unseen economic boom.

That suppression is not evident in macroeconomic data outside the model.

The Compounding Multiplier Effect

The large Social Cost of Carbon โ€” over $1,200 per ton โ€” is not independent evidence. It is the arithmetic consequence of assuming very large productivity losses.

If you assume:

  • 20โ€“30% GDP loss per 1ยฐC
  • Persistent productivity decay
  • Capital destruction amplification

Then a massive SCC follows automatically.

The policy conclusion depends entirely on the initial damage estimate.

What Would We Expect to See?

If warming of 1ยฐC truly reduces GDP by 20%, one would expect:

  • Visible stagnation in global output growth
  • Clear productivity deterioration in temperature-sensitive sectors
  • Widespread agricultural decline
  • Reduced capital formation
  • Reversal in living standards

Instead, the post-1960 world experienced the largest sustained rise in human prosperity in history.

This does not prove warming is beneficial. It does suggest that claims of massive hidden losses should face an unusually high evidentiary bar.

The Core Question Remains

The paper is sophisticated. It is technically ambitious. It presents numerous robustness checks.

But at its core lies a striking empirical tension:

A 1ยฐC warming since 1960 allegedly reduced world GDP by roughly 20%.

Yet the observable world economy looks nothing like one operating 20% below potential due to climate deterioration.

Skepticism in its proper sense is not reflex dismissal. It is disciplined suspension of judgment pending adequate evidence.

When a new study multiplies climate damages by ten relative to established research, that is not a small revision. It is a paradigm shift.

If 1ยฐC destroys 20% of GDP, the world should look poorer than it does โ€” not greener, more productive, and dramatically wealthier.

Before rewriting climate policy around a tenfold escalation in estimated damages, we should ensure the model explains not only filtered impulse responses โ€” but the actual economic history of the last half-century.

Because if a Great Depression has already occurred without anyone noticing, the burden of proof rests squarely with those claiming it.

UAH v6.1 Global Temperature Update for July 2025: +0.36 deg. C

The Version 6.1 global average lower tropospheric temperature (LT) anomaly for July 2025 was +0.36 deg. C departure from the 1991-2020 mean, down from the June 2025 anomaly of +0.48 deg. C.

Graph showing UAH satellite-based temperature anomalies for the global lower atmosphere from 1979 to July 2025, indicating a +0.36 deg. C anomaly for July 2025.

From Roy Spencer, PhD

August 2nd, 2025 by Roy W. Spencer, Ph. D.

The Version 6.1 global average lower tropospheric temperature (LT) anomaly for July 2025 was +0.36 deg. C departure from the 1991-2020 mean, down from the June 2025 anomaly of +0.48 deg. C.

Line graph showing UAH satellite-based temperature anomalies of the global lower atmosphere from 1979 to July 2025, indicating a July 2025 anomaly of +0.36 deg. C.

The Version 6.1 global area-averaged linear temperature trend (January 1979 through July 2025) remains at +0.16 deg/ C/decade (+0.22 C/decade over land, +0.13 C/decade over oceans).

The 0.12 deg. C drop in global average temperature anomaly since last month was dominated by the extra-tropical Southern Hemisphere, which fell from +0.55 deg. C in June to +0.10 deg. C in July.

The following table lists various regional Version 6.1 LT departures from the 30-year (1991-2020) average for the last 19 months (record highs are in red).

YEARMOGLOBENHEM.SHEM.TROPICUSA48ARCTICAUST
2024Jan+0.80+1.02+0.58+1.20-0.19+0.40+1.12
2024Feb+0.88+0.95+0.81+1.17+1.31+0.86+1.16
2024Mar+0.88+0.96+0.80+1.26+0.22+1.05+1.34
2024Apr+0.94+1.12+0.76+1.15+0.86+0.88+0.54
2024May+0.78+0.77+0.78+1.20+0.05+0.20+0.53
2024June+0.69+0.78+0.60+0.85+1.37+0.64+0.91
2024July+0.74+0.86+0.61+0.97+0.44+0.56-0.07
2024Aug+0.76+0.82+0.69+0.74+0.40+0.88+1.75
2024Sep+0.81+1.04+0.58+0.82+1.31+1.48+0.98
2024Oct+0.75+0.89+0.60+0.63+1.90+0.81+1.09
2024Nov+0.64+0.87+0.41+0.53+1.12+0.79+1.00
2024Dec+0.62+0.76+0.48+0.52+1.42+1.12+1.54
2025Jan+0.45+0.70+0.21+0.24-1.06+0.74+0.48
2025Feb+0.50+0.55+0.45+0.26+1.04+2.10+0.87
2025Mar+0.57+0.74+0.41+0.40+1.24+1.23+1.20
2025Apr+0.61+0.77+0.46+0.37+0.82+0.85+1.21
2025May+0.50+0.45+0.55+0.30+0.15+0.75+0.99
2025June+0.48+0.48+0.47+0.30+0.81+0.05+0.39
2025July+0.36+0.49+0.23+0.45+0.32+0.40+0.53

The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for July, 2025, and a more detailed analysis by John Christy, should be available within the next several days here.

The monthly anomalies for various regions for the four deep layers we monitor from satellites will be available in the next several days at the following locations:

Lower Troposphere

Mid-Troposphere

Tropopause

Lower Stratosphere

Not All That Sensitive

The sensitivity of the surface to changes in absorbed radiation is a central, critical question in climate science. The claim is that the change in global average temperature is equal to the change in absorbed radiation times the โ€œequilibrium climate sensitivityโ€, abbreviated as ECS. The ECS is assumed to be a constant.

ChatGPT

From Watts Up With That?

Guest Post byย Willis Eschenbach

For no particular reason, I got to thinking about the non-global nature of the incoming energy. And this led me to consider the sensitivity of the surface to changes in the radiation absorbed by the surface.

The sensitivity of the surface to changes in absorbed radiation is a central, critical question in climate science. The claim is that the change in global average temperature is equal to the change in absorbed radiation times the โ€œequilibrium climate sensitivityโ€, abbreviated as ECS. The ECS is assumed to be a constant.

However, despite hundreds of thousands of dollars, work-hours, and computer-hours dedicated to determining the value of the ECS, the uncertainty about its value has only continued to increase.

Figure 1. This figure shows a variety of ways that the Equilibrium Climate Sensitivity (ECS) has been estimated. The dotted lines show the uncertainty of the earliest estimates of the ECS, which was said to be between 1.5 and 4.5 degrees C per doubling of CO2 (2xCO2).

Initially, back in the 1970s, the equilibrium climate sensitivity was claimed to be between 1.5 and 4.5 ยฐC of warming from an increase of 3.7 W/m2 in downwelling radiation. This 3.7 W/m2 is the assumed value of the increase in downwelling radiation from a doubling of CO2 (2xCO2).

This can also be expressed as the change of temperature from a one watt per square meter increase in downwelling radiation. The original central estimate of 3 W/m2 per 2xCO2 is the same as 3/3.7 โ‰ˆ 0.8 ยฐC for each radiation increase of 1 W/m2.

However, as you can see in the graphic above, over time, the estimates of the ECS have grown wider and wider. Now, they range from 0.37 degrees C warming resulting from a doubling of CO2 (2xCO2), up to 8.1 degrees C per 2xCO2. This is the same as a range of 0.1 to 2.2 W/m2 for each additional 1 W/m2 of radiation.

I know of no other field of science where this is true, where endless studies of a central constant in the field only show wider and wider uncertainty. To me, this can only mean that the underlying theory is incorrect โ€ฆ but I digress.

Now, the ECS is said to be the climate sensitivity after years of adjusting to the change in radiation. This is because the claim is that the warming is much larger and slower than direct calculations indicate. Mainstream scientists say that various feedbacks increase the warming due to increased radiation, with cloud feedbacks and water vapor feedbacks being the main culprits.

This is discussed in the IPCC AR6 Working Group 1 Chapter 7. They say that the central estimate for the net cloud feedback is 0.42 W/m2 for every 1ยฐC of warming, and that the central estimate for water vapor feedback is another 1.8 W/m2.

In other words, the IPCC says that for every 1 W/m2 increase in radiation, the feedbacks increase that by another 2.22 W/m2. This means that the warming should be far larger than youโ€™d expect just from the underlying increase in radiation.

Keep this in mindโ€”the standard theory says that the warming should be greater than no-feedback warming.

So to start with โ€ฆ if there were no feedbacks, what warming would we expect to occur?

To investigate this question, I started by taking a look at the total radiation being absorbed by the surface. This is the sum of the absorbed sunlight, which is the total sunlight hitting the surface less reflections from the surface, along with the downwelling thermal radiation from the atmosphere. Hereโ€™s a map of the global distribution of the total surface absorbed radiation.

Figure 2. Average Mar 2000 โ€“ Feb 2024 of the total absorbed surface radiation, which is the sum of longwave radiation (โ€œLWโ€, thermal radiation from the atmosphere) and shortwave radiation (โ€œSWโ€, solar radiation).

As a 24/7 average, the surface gets about half a kilowatt per square meter. In Figure 2, you can see the reflective nature of the desert and the poles, which lead to less radiation being absorbed.

Next, I looked at the total change in absorbed surface radiation over the 24-year period of the CERES dataset. Below you can compare the changes in absorbed radiation (top) with the changes in temperature.

Figure 3. Changes in total absorbed surface radiation (top) and changes in surface temperature (bottom) over the period March 2000 to February 2024.

Note that in a number of areas, the changes in absorbed radiation correlate with the surface temperature changes. Also note that, as expected, increasing radiation leads to increasing temperature.

How much would we expect this increase in radiation to increase the temperature? This can be determined from the Stefan-Boltzmann equation, which states that radiation is proportional to the fourth power of the temperature. Using the CERES data and the S-B equation allows us to calculate just what heating weโ€™d expect to occur from that increase in absorbed radiation. Below is the result.

Figure 4. Theoretical change in temperatures from a uniform 1 W/m2 increase in absorbed surface radiation.

This shows that the expected warming is 0.19ยฐC for each 1 W/m2 increase in absorbed radiation (or 0.7 W/m2 per 2xCO2). However, because a given increase in radiation warms cold areas more than warm areas, the warming ranges from 0.15ยฐC per 1 W/m2 (0.6ยฐC per 2xCO2) in the warmest ocean areas up to 0.44ยฐC per 1 W/m2 (1.6 W/m2 per 2xCO2) in Antarctica.

So thatโ€™s our theoretical warming. And the prevailing theory says we should see much greater warming than the theoretical warming due to the feedbacks described above.

To gain further understanding, I looked at how much the observed temperature actually changed in response to the changes the absorbed radiation. Figure 5 below shows the change in temperature that corresponds to a one W/m2 increase in radiation.

Figure 5. Change in the surface temperature for each 1 W/m2 increase in absorbed surface radiation. CERES data from March 2000 โ€“ February 2024.

Now, this reveals a surprise. The climatastrophists keep saying that as the radiation absorbed by the surface increases, the temperature perforce must increase.

And for most of the world this is true, although at greatly different rates as we can see in Figure 5.

But in the area of the โ€œPacific Warm Poolโ€ north of Australia, and the area of the Inter-Tropical Convergence Zone (ITCZ) just above the Equator, the opposite is trueโ€”as the amount of radiation absorbed by the surface increases, the temperature goes down, not up.

I say this is a result of the combined effects of the temperature-threshold driven emergence of both tropical cumulus cloud fields and tropical thermally driven thunderstorms. These cool the surface in a host of ways, and exert a huge negative feedback on temperature increases.

But for the purposes of this post, the mixture of phenomena driving this important oddity are not the focus. Iโ€™m simply looking at the actual response of the surface temperature to changes in absorbed surface radiation. Most places it increases โ€ฆ but not everywhere.

Next, I looked at the trend data in a different way. I looked at a scatterplot of the trend shown in Figure 5 versus the average surface temperature. I also included the theoretically expected temperature change versus the average surface temperature.

Figure 4. Scatterplot, sensitivity of surface temperature to surface absorbed radiation. Actual average, actual land, and actual sea are calculated based on the CERES data. Theoretical results and average are based on the use of the Stefan-Boltzmann equation on the CERES data.

Now, this is quite interesting for a number of reasons.

First, in every case, the results are below the theoretical calculations. This is a clear indication that far from the globe having a strong positive net feedback to any warming, the net feedback is negative.

Next, this data covers 24 years, nearly a quarter century. So this is not the instantaneous sensitivity of the surface to absorbed radiation.

However, itโ€™s likely that the longer-term warming would be greater than shown in Figure 4. In other words, if the amount of absorbed surface radiation were to suddenly stop increasing, the world would continue to warm for a bit.

So โ€ฆ how much will it warm? Well, in my post Lags and Leads, I showed that we can calculate the warming based on the length of time by which the surface warming lags the absorption of the radiation at the surface. As you might expect, this is greater for the ocean than for the land, due to the greater thermal mass of the ocean.

Per the CERES data, the lag in the land warming is about ten days, and the lag in the ocean warming is much larger, about four times that. Using the formula from โ€œLags and Leadsโ€ linked to above, this would increase the land warming by about 2%, and it would increase the ocean warming by about 30%.

So here is the data shown in Figure 4 above, but with the values adjusted as discussed above to account for delayed warming. Iโ€™ve also included the lowest four ECS values from Figure 1 at the head of the post. (The values in that figure have been divided by 3.7 to give them in units of ยฐC per W/m2 rather than ยฐC per 2xCO2.)

Figure 5. As in Figure 4, but with the values adjusted to give the eventual change in the temperature. Purple dots show the lowest four of the ECS estimates shown in Figure 1 at the head of the post (values converted from ยฐC/2xCO2 to ยฐC per W/m2).

Even with these adjustments, the sensitivity of the temperature to absorbed radiation is still well below the theoretical global average. In addition, the four lowest values from Figure 1 are also below the theoretical blackbody values.

And because it is based on observations, this graph includes all possible feedbacks, including cloud feedbacks, cloud aerosol feedbacks, water vapor feedbacks, and all the rest. It is based on how much the surface temperature actually has changed with an increase of 1 W/m2 in absorbed surface radiation.

So Iโ€™ll go out on a limb and say that this value of 0.11ยฐC per W/m2 (0.4ยฐC per doubling of CO2) is a reasonable estimate for the Equilibrium Climate Sensitivity. It includes all feedbacks known and unknown, is adjusted for the different thermal lags in the ocean and the land, it is in the range of the four smallest ECS estimates from mainstream climate studies, and it is quite close to three of those ECS estimates.

As Figure 5 shows, like the four smallest ECS estimates in Figure 1, the net feedback to the warming is negative. We know this because everywhere on the Earth, the warming is less than weโ€™d experience with a blackbody planet.

This negative feedback is as weโ€™d expect, given the remarkable stability of the global surface temperature, which only increased by about 0.2% over the entire 20th Century. Twenty-five years ago, that surprising stability was what first drew me to start studying the climate. If the feedback were positive, there would be much larger variations in the Earthโ€™s temperature.

Finally, it could be argued that this is NOT the equilibrium climate sensitivity (ECS), because Iโ€™ve used the change in radiation absorbed at the surface, while the ECS is based on the change in top-of-atmosphere (TOA) downwelling โ€œgreenhouse effectโ€ radiation (GHE).

As Ramanathan first noted, the TOA GHE radiation can be calculated as the amount of surface upwelling thermal radiation minus the amount of TOA upwelling thermal radiation. And this GHE radiation is closely related to the downwelling radiation absorbed by the surface. Figure 7 shows that relationship.

Figure 7. Absorbed downwelling longwave radiation at the surface, and top of atmosphere (TOA) โ€œgreenhouse effectโ€ downwelling longwave radiation

Because they are so similar, and because the downwelling longwave radiation at the surface is only part of the total absorbed radiation, this will make little difference to the ECS I calculated.

 The CERES data shows that for every 1 W/m2 increase in TOA downwelling greenhouse radiation, as weโ€™d expect, the surface downwelling radiation increases by on the order of one W/m2 (1.1 ยฑ .14 W/m2 per W/m2). So any change in my calculated ECS will be small.

And with that, further affiant sayeth naught.


Fog this morning, which is good news because itโ€™s been hot and I still have another acre to mow. Protip: When your age has two digits and starts with a 7 or above, if you slow down โ€ฆ

โ€ฆ you stop.

And wonder of wonders, a bobcat just walked into the back acreage, what a lovely being!

My very best to all,

w.

Youโ€™ve Heard It Before: Quote the exact words you are commenting on. I can defend my words. I canโ€™t defend your interpretation of my words.