Significant acceleration of global heating since 2015

 From the Potsdam Climate Institute

Global warming has accelerated since 2015, according to a new study by the Potsdam Institute for Climate Impact Research (PIK). After accounting for known natural influences on global temperature, the research team detected a statistically significant acceleration of the warming trend for the first time. Over the past ten years, the estimated warming rate has been around 0.35°C per decade, depending on the dataset, compared with just under 0.2°C per decade on average from 1970 to 2015. This recent rate is higher than in any previous decade since the beginning of instrumental records in 1880.

Global warming rate (in °C per decade) from the Berkeley Earth global temperature data: The blue line shows the linear trends for the time before and after 2015 (light blue the uncertainty range). The red line shows the linear trend for 10‐year windows of the data, at 1-year intervals. Figure: PIK

“We can now demonstrate a strong and statistically significant acceleration of global warming since around 2015,” says Grant Foster, a US statistics expert and co-author of the study, which was published today in the scientific journal Geophysical Research Letters. 
 
“We filter out known natural influences in the observational data, so that the ‘noise’ is reduced, making the underlying long-term warming signal more clearly visible,” Foster added.
 
Short-term natural fluctuations in global temperature caused by El Niño, volcanic eruptions, and solar cycles can mask changes in the long-term rate of warming. In their data analysis, which is based on measurement data, the two researchers work with five large, established global temperature data sets (NASA, NOAA, HadCRUT, Berkeley Earth, ERA5).
 
“The adjusted data show an acceleration of global warming since 2015 with a statistical certainty of over 98 percent, consistent across all data sets examined and independent of the analysis method chosen,” explains Stefan Rahmstorf, PIK researcher and lead author of the study. 

After correcting for the effects of El Niño and the solar maximum, 2023 and 2024, which were exceptionally warm years, become somewhat cooler, but remain the two warmest years since the beginning of instrumental records. In all datasets, the acceleration begins to become apparent in 2013 or 2014. To test whether the warming rate has changed since the 1970s, the research team applied two statistical approaches: a quadratic trend analysis and a piecewise linear model that objectively determines the timing of any change in the warming rate.

The study does not investigate the specific causes of the observed acceleration. However, climate models show that an increasing rate of warming is fundamentally within the scope of current climate modelling, according to the authors.
 
“If the warming rate of the past 10 years continues, it would lead to a long-term exceedance of the 1.5° limit of the Paris Agreement before 2030,” says Stefan Rahmstorf. “How quickly the Earth continues to warm ultimately depends on how rapidly we reduce global CO₂ emissions from fossil fuels to zero."

We face catastrophe unless we cut emissions.  We should replace coal and gas with wind, solar and batteries as fast as we can.  We should stop the sale of petrol (gasoline)/diesel cars, lorries and buses now, because it will take 15 years for the existing vehicle fleet to be replaced.  And before you fall to the floor and start chewing the carpet, there are electric alternatives to every petrol or diesel car from small city cars, through utes (pick-up trucks), light vans through semi-trailers and buses.  We need to replace all oil/gas heating with heat pumps.  Is mankind too frigging feckless to act?

Global warming *has* accelerated

 From Open Mind (Tamino)

I won't repeat the whole article.  Read it in full here.

My paper with Stefan Rahmstorf showing that global warming has accelerated was published in Geophysical Research Letters today. The main result is that global warming is NOT proceeding at the same old rate it has been since 1975. It’s going faster.

In this data set [from Berkeley Earth], 2025 turned out to be the 3rd-warmest year on record (as in the other data sets except NASA, where it came in 2nd). When I adjust the data to remove the estimated impact of el Niño, volcanic eruptions, and solar variation, I get this:

The trend is unaffected, but the noise level is much reduced, which enables us to estimate warming rates with less uncertainty. I’ve added a red line to this graph which is a modified LOWESS smooth of the adjusted data.

To test for acceleration we isolated the data since 1975, and the simplest way to test for it is to fit a parabola to the data; if the quadratic term is statistically significant, we can reject the null hypothesis, that the signal is just a straight line. Of course we must correct for autocorrelation of the noise, but still the quadratic term turns out to be strongly significant. We can safely reject the null hypothesis: there has been acceleration.

According to this model, the warming rate right now is the slope at the endpoint of the parabola, which is 0.28 ± 0.05 °C per decade (i.e. between 0.23 and 0.33 °C per decade, 95% CI). I will emphasize that this is the “best estimate” and those are the correct uncertainty levels IF (and this is a BIG IF) the data actually follow a parabola plus stationary noise. If not (which is the overwhelmingly likely case), we can consider the estimate good but not best, and the uncertainty levels are a lower bound on the actual uncertainty.

Another test for acceleration is to find the best fit of a continuous piecewise-linear function which is allowed to change slope at a time chosen by changepoint analysis. This is a challenge to evaluate statistically because we have to allow for autocorrelation and account for the extra degree of freedom to choose the changepoint time. But it can be done, and the best-fit model again turns out to be strongly statistically significant.

Both those models serve excellently to demonstrate the presence of acceleration. But I doubt they are best to estimate what the warming rate is right now, and what it will be in the near future. For that, I offer yet another model, which I will apply to the data since 1880, a continuous piece-wise linear fit (PLF) which is allowed to change its slope every 15 years from 1905 through 2010. I call this model “PLF15”

The PLF15 model not only estimates the signal value, it conveniently gives us an estimate of the average warming rate over each segment between the knots. I can plot the warming rate itself (which for this model is constant during each segment) along with light blue shading to show the uncertainty range.

All these graphs plot the warming rate in °C per year, but when quoting numbers I have followed the custom these days to talk about the rate in °C per decade. According to this analysis, the current estimated rate is 0.31 ± 0.07 °C/decade.

Which estimate is best? I don’t know, but I do know that even 0.24 °C per decade will take us past 2 °C right around the year 2050. The whole point of the Paris agreement is: DON’T GO THERE. My advice: fasten your seat belt, things are going to get ugly.

We need to redouble efforts to cut emissions, or things will get very ugly.  What can we do?

• Set a renewable energy target in every country.  The percentage of renewables+nuclear needs to rise by 6-8% a year, at least.  This will cut emissions by 27% (emissions from electricity generation are +-30% of total global emissions) within a decade.  We may not yet be able to go above 90 or 95% renewables in the grid, because we don't have long-term storage to offset periods of dunkelflaute, but we will have cut most emissions from electricity generation.  
• We must tax imports from countries which do not have an R.E.T. or a price on carbon.  (See my posts on a carbon border tax)
• We need to accelerate the replacement of petrol/diesel vehicles (ICEVs) with EVs.  This is a problem, because even when we reach 100% of sales being EVs, it will take 10-20 years for all ICEVs on the roads to be replaced.  This is too long.  Most countries are nowhere near 100% EV sales.   We could, for example, ban the import of new or second-hand ICEVs, or slap 100% taxes on them.   Ethiopia has already done this.  This policy should apply to two and three-wheeled vehicles, too.  Countries which do this deserve reduced carbon border taxes.
• In rich countries, we need to replace oil- or gas-based household and industrial heating with heat pumps.  Because they have high up-front costs, they will require government subsidy to start the revolution rolling.

All of these combined will cut emissions by 50 to 60%.  If we also switch to low-emission steel and cement, the emissions cuts could reach 70%.

That will leave (mostly) agriculture.  Put that in the too-hard basket for now--people love their meat too much to give it up.  But it won't go away.  When we've cut emissions by 70%, agriculture will dominate what's left over.  And action will no longer be postponable.

Our planet is warming twice as fast as we thought

 A video from Just Have a Think.  He discusses a paper by Grant Foster and Stefan Ramsdorf, which confirms that the rate of global warming has accelerated from 0.2 degrees C per decade to 0.4 degrees C.   One of the authors of this paper is Grant Foster, who is "Tamino'", and I've commented on his pieces published on his blog "Open Mind" several times over the last few years.  See this, and this, and this.

Just Have A Think  explains quite well the techniques used to prove their point.  He cautions that just because temperatures have been rising twice as fast as they were between 1970 and 2010 over the last decade, it doesn't mean that they will necessarily continue to do that.  

On the other hand they might, and they might even accelerate.  Just being prudent and cautious would suggest that we should accelerate our attempts to slash emissions, especially since wind and solar power and batteries and EVs have fallen so much in cost. 

A chart from the paper referred to in the video, showing the unadjusted and the adjusted (for volcanic eruptions, El Niño, and the sunspot cycle) time series from 5 different estimates of the average global temeperature anomaly.

Rise in world's temperatures accelerates

 Open Mind (Tamino) produced a previous piece about the acceleration in the rise in global temperatures, which I reported on here.  He has returned to the analysis, and confirms his position in his latest post. 

I now have global temperature data through October of this year from NASA, NOAA, and ERA5, as well as data through September from HadCRU and Berkeley. I’ve translated them to “since pre-industrial” values using one of the methods in the IPCC special report on 1.5°C. Then I computed yearly averages (this year is incomplete so values for 2024 are year-so-far averages)

There are two clear episodes in this plot: before and after 1975. Before, GMST was fluctuating but not trending either way; since, it has been trending consistenly up and fluctuating. As for its rate of increase, for four and a half decades (from 1975 until 2020) temperature seemed to rise at a pace (about 0.02°C per year) that was unchanging, and statistics couldn’t deny it.

But the last two years (2023 and 2024) have been “off the charts,” so to speak. For the data from ERA5, the value for 2024 year-so-far is already above 1.5°C, which is exactly what the Paris agreement seeks to avoid.

I investigated the rate of warming, and how it may have changed over time, in two ways. First, I fit a modified lowess smooth which I’ve programmed to estimate the rate as well as the value. Second, I computed a piecewise linear fit (PLF) with knots at 1975 and 2010. Both models (lowess and PLF) were fit to the monthly-average data, but in the graphs that follow I’ll plot yearly averages so the graphs will be less cluttered. Here’s how the PLF model fits the data from NASA:

PLF = piecewise linear fit 

 

[....]

For the 45-year period from 1975 through 2009, the average warming rate according to NASA data is just about 0.018°C/yr. For the 15-year period since 2010, it has been a lot faster at 0.031°C/yr. Statistically, the difference is significant at over 99% confidence.

I have also adjusted all the data sets, to compensate for the influence of el Niño, volcanic eruptions, and solar variations, with a method not unlike that of Foster & Rahmstorf (2011). Here are the adjusted temperatures, together with their PLF fit, for the data from NASA:

This chart shows the temperature anomaly adjusted for El Niño/La Niña and for vulcanism. 
PLF = piecewise least fit.

The rate from 1975 to 2010 now seems to be only 0.017°C/yr, and after 2010, the best estimate is 0.033°C/yr. These aren’t much different from the estimates using the raw data, although the uncertainties are now smaller so the confidence intervals are narrower.

Falling emissions (which of course we don't have--emissions continue to rise) do NOT mean that temperatures will start falling.  The RISE in the temperature anomaly is proportional to the LEVEL of emissions.  In other words, for temperatures to stop rising, we need to reduce emissions to zero.  If we halve emissions, the increase in temperature anomaly will halve, but that only reduces it to what it was before this recent acceleration, 0.17 degrees per decade.  

There are positive signs that emissions will peak soon.  Wind and solar continue to expand exponentially.  The costs of battery storage are plunging, and the recent first commercial solid-state battery points to continued and sustained cost declines and efficiency improvements.  Yet, even if we completely switch ALL electricity generation and ALL land transport to carbon-free methods, that will still only halve emissions.  If we were to start cutting emissions by 5% a year, compound, it would take us 40 years to reduce emissions to 10% of current levels.  Assuming we did this (but we are not) temperatures would rise for the next decade by 0.33 degrees, for the decade after by 0.17, by the decade after that by 0.l2 degrees and for the final decade by 0.06.  Roughly.  In other words, temperatures would rise by another 0.33+0.17+0.12+0.06, or ~0.7 degrees, making the rise since 1850-1900, the traditional "pre-industrial" starting point 2.2 degrees.

We face catastrophe, and still we dither and phaff.  The Right is dead against doing anything at all to slash emissions, and the Left argues with itself about what to do.  Meanwhile, we are lied to by corporations and governments, and protesters go to jail while oil execs are fêted.

Warming rate probably accelerating

 Another in depth statistical analysis from Open Mind (Tamino).  I won't repeat the whole article (best to read it for yourself).   In essence, what he does is look at the change in the temperature anomaly over 30 years, the conventional measure of climate change (because shorter periods are too susceptible to fluctuations from natural climate cycles such as, for example, El Niño/La Niña).    This chart shows what that looks like:

Note that the change over the 30-year span has been centred at 15 years,
which is why it apparently ends at 2009.

He then adjusts the data for volcanic eruptions, El Niño, and the sunspot cycle to test whether the change in trend since 2000 is statistically significant, and concludes that it is.

But wait, there’s more. We know the cause of some of the fluctuation, and we can adjust the data by removing our best estimate of those known factors. In particular, we can remove an estimate of the influence of volanic eruptions, solar variations, and the el Niño southern oscillation, and I’ve done so by a modified version of the method of Foster & Rahmstorf.

Comparing this graph of adjusted data since 1946, to the graph of raw data over the same time (the third graph in this post), two things are obvious. First, the level of scatter (of random fluctuation) is quite a bit less for the adjusted data than for the raw. Second, the “obvious” simple model for the raw data (a linear spline with two straight-line setments) isn’t so obvious for the adjusted data.

The same analysis used on the raw data, returns different results on the adjusted. This is mainly because the uncertainty levels are so much reduced. The warming rate for NASA data, for example, now looks like this:

Again, the change has been centred midway on the 30-year span

The final 30-year estimate suggests the rate was definitely bigger then 0.02°C/year, while the earlier rate is definitely less. Also, the statistical tests (fitting a parabola and a linear spline) now are definitely significant at 95% confidence.

Using adjusted rather than raw data, the same is true for all five data sources. While the significance is weakest for HadCRU and strongest for NOAA, it’s over 95% confidence for all of them. My conclusion is that recent acceleration of global warming isn’t just likely, it’s confirmed.

There is still room for doubt, if you doubt that the adjusted data represent things correctly then the recent apparent acceleration may be just random accident. All told, I find that too unlikely.

See also this piece I did, based on Open Mind's analysis: 

Terrifying acceleration in global heating

We are heading towards climate catastrophe, and still we do not act, stumbling blindly to the precipice.

Terrifying acceleration in global heating

Open Mind (Tamino) has again posted an analysis of global temperature data, confirming that global temperatures are accelerating.  I analysed his previous post here.

Way back in 2011 I co-authored a paper with Stefan Rahmstorf (Foster & Rahmstorf 2011, hereafter FR11) in which we adjusted global temperature in order to remove (as best we could) the influence of factors we knew were only temporary, and not man-made. Specifically, these are volcanic eruptions (whose aerosols cool the planet), the El Niño Southern Oscillation (ENSO, which warms the world in its positive el Niño phase and cools in its negative la Niña phase), and solar variations (when the sun gets hotter or colder, so does the Earth). These exogenous factors make global temperature fluctuate, but don’t really get anywhere; removing their influence makes the global warming part clearer.

I’ve updated my method for doing so, and extended the time span it covers, so I’d like to share some of the changes to methodology. But before I do I’ll cut right to the chase: doing so removes a lot of the fluctuation in global temperature, so that yearly averages since 1950, which look like this for five prominent global-temperature data sets:

end up looking like this:

He then discusses his analytical technique in depth (read it here).  His conclusions are:

Perhaps the main result of FR11 was that the adjusted data showed no sign of acceleration or deceleration, contradicting ideas that global warming had stopped or even slowed; the evidence didn’t support that. But the new adjusted data do not contradict the recent acceleration which the raw data suggest, in fact they confirm it, mainly because the uncertainty in trend estimates is so greatly reduced that the rate change (acceleration) is easier to demonstrate statistically.

Yes, it appears that the rate of global warming has increased.

We face catastrophe.  You can clearly see how the slope of the (adjusted) temperature curve is steepening.   It looks more like an exponential than a linear slope.  In other words, it could easily go on steepening, with the decadal rise in temperature accelerating even further, from 0.3 to 0.4 or 0.5 degrees C over the next two decades.  Why aren't we panicking?

Global warming accelerates to 0.3 degrees per decade

 From Open Mind (Tamino)

July 2023 was the hottest month in history, maybe even the hottest in the last 120,000 years. The months that followed broke monthly records by surprisingly large margins. It’s no wonder that 2023 has turned out to be the hottest year we’ve seen, and not just by a little.

Here are yearly average temperature anomalies for the whole planet, from 1950 through 2023, according to HadCRU, the Hadley Centre/Climate Research Unit in the U.K. (they haven’t yet reported their value for December 2023, so that year’s value is the January-through-November year-to-date average):

Each dot shows a year’s average, with the solid red line a smoothed version. The smooth shows is a good estimate of the background value, and reveals how climate has changed (temperature-wise), while the actual yearly values (black dots) fluctuate about that background value.

We know some of the things that contribute to those fluctuations. Volcanic eruptions, for instance, can fill the atmosphere with reflective aerosols which take years to settle out of the air, all the while cooling the planet. The el Niño southern oscillation (ENSO) tracks changes in how the ocean and atmosphere exchange heat; in its el Niño phase the surface gets noticeably warmer, but in its opposite la Niña phase the world tends to be cooler. The sun, of course, is the ultimate source of heat for our climate, and when it shines hotter, Earth heats up, but when the sun cools (relative to itself, of course) the Earth follows. These factors can be accounted for, at least approximately, and removed from the temperature data to define adjusted data, which will (we hope) give us a clearer picture of the changes which are due to other things — like greenhouse gas emissions.

Such has been done in peer-reviewed scientific research, and I’ve updated the procedure to include more recent data as well as alternative methods. In my latest version, the estimated contribution of each factor to the HadCRU temperature series looks like this:

The influence of volcanic eruptions, in brown, shows the cooling from the three large volcanic eruptions during this time, especially the massive explosion of Mt. Pinatubo in the 1990s. Solar variations, in red, have had only a small influence on Earth’s temperature because the solar variations themselves are small. The ENSO, in blue, has sometimes warmed (the el Niño phase) and sometimes cooled (the la Niña phase).

Add them all together, we have an estimate of the total influence of these factors on global temperature:

 

We can use this to estimate what global temperature would have been without these factors; just subtract this estimate from the observed data to yield adjusted data. When I do so, then compute yearly averages to yeild adjusted yearly average temperature anomalies for the whole planet from 1950 through 2023 according to HadCRU, I get this:

 

Each dot shows a year’s average, with the solid red line showing a smoothed version.

I’m mainly interested in the rate at which temperature is rising, so I took the original (un-adjusted) data and analyzed it with my modified lowess smooth, which is what I used to generate the solid red lines (smoothed values) in the above graphs. I’ve custom-designed it for this kind of analysis, so it reports, for each moment of time, not only the estimated value and its uncertainty, but the estimated rate of change (just what I’m looking for) and its uncertainty.

When I apply it to the HadCRU data, and choose the “time scale” (a free parameter in the analysis) so it will mimic rates of change on a 20-year time scale, it yields this:

The solid blue line shows the estimated rate of warming, the light blue shading shows its uncertainty range (±2σ). There is an obvious change in the rate around the year 1970; before that the rate was near zero (within the uncertainty range), but afterward is assuredly positive. This agrees with what we see in the first graph, that the smoothed value changes very little (zero rate from 1950 to 1970), then rises steadily until the present (rate about +0.02 °C/yr until now).

There is also a rise in the main estimate (solid blue line) starting around 2010, which suggests that the rate of warming may have increased lately (i.e. recent acceleration), but the uncertainty range is wide enough that it still includes the value +0.02°C/yr which had been observed already for decades.

Conclusion: since 1950, the data show at least two different warming rates: near zero from 1950 until about 1970, then about +0.02 °C/yr until now. There is evidence of a recent increase, but the evidence is inconclusive.

What about the trend in the adjusted data, i.e. apart from the factors that make those incessant fluctuations? I can apply the same analysis and get this:

 

Much is essentially the same as with the original, raw data: there is undoubtedly a change in rate around 1970, and there is evidence of another change around 2010. But this time the uncertainty range is narrower, the uncertainties are a lot smaller, and the evidence for recent change is now conclusive.

Conclusion: since 1950 the adjusted data show at least three different warming rates: near zero from 1950 until about 1970, then about +0.02 °C/yr until around 2010, and about +0.027 °C/yr since. Not just the above analysis, but other statistical tests confirm that although the uncertainty in the current rate is considerable, we conclude with confidence that it’s faster than it was during the preceding decades. Global warming picks up speed.

That’s using the data from HadCRU, and the story is the same when using data from NASA (the GISTemp data from the Goddard Institute for Space Studies), from NOAA (the National Oceanic and Atmospheric Administration), from the Berkeley Earth surface temperature project, or the ERA5 data from Europe’s Copernicus Climate Service.

James Hansen and others published a new paper recently, claiming that not only will global warming, in the very near future, proceed faster than expected, it is already doing so — that the pace of global warming had accelerated. Temperature increase after 2010, it suggests, will be at 0.027°C/yr, 50% faster than the lazy 0.018°C/yr it had been rising for decades before that. As a result, we have less than a decade until we cross the much-discussed threshold of 1.5°C above pre-industrial, so any idea of keeping global warming below that limit is “deader than a doornail.”

 

[Read more here; Tamino lists some of the caveats of his analysis.]

We are still not doing enough to slash emissions.  Remember, even if emissions peak this year, the rise in temperatures is proportional to the level of emissions.  For temperatures to stop rising, we need to cut emissions to zero.   On top of which, even if CO2 emissions have peaked,  methane emissions have accelerated.  Methane is 82 times as potent a greenhouse gas (over 10 years) as CO2.  

Canada wildfires

 From Open Mind

Generally, I’ve stopped reacting to climate deniers’ idiotic claims, like the garbage firehose that is the “WattsUpWithThat” blog. Truly, I have better things to do. But this one is so ridiculous, it’s hard to pass up.

Here’s the theme: P. Gosselin claims that all the talk about the severity of Canada’s wildfire this year is hype. He titles his post “Canada Forest Fires Trend Has Gone Down Since 2000, Data Defy Alarmist Claims.” He supports his claim by showing this graph (of the NUMBER of wildfires in Canada each year since 2000):

It’s actually a common tactic of climate deniers, to make a false claim (i.e. tell a lie) and support it with a graph which doesn’t really address the point. Here’s the graph that does address the point (from the same data source), the AREA burned in Canada each year since 2000:

It seems that this year Canada hasn’t had many more fires than previously, but the ones it has had …

So … why do I bother to mention this? Because this is where republican politicians get their scientific beliefs.

Climate denial: the republican party way.

Correlation between CO2 forcing and temperature

 From Open Mind (Tamino)

There are certain claims (some false) about the correlation (or not) between CO2 in the atmosphere and global temperature. Several folks have pointed out that we shouldn’t really be looking at the correlation between temperature and CO2, but between temperature and CO2 forcing.

This is the climate forcing due to a given concentration of CO2 in the atmosphere, and it turns out to be a logarithmic function of the CO2 concentration. It can be put in many (equivalent) forms, but the one I will choose is:

F = log₂(CO₂/280),

where CO2 is in units of parts per million (ppm) and the climate forcing is in units of doublings of CO2 (that’s why the logarithm is taken to base-2). Note that if the CO2 concentration is 280 (its pre-industrial value) then the climate forcing is zero, so this is the climate forcing due to CO2 concentration relative to pre-industrial.

For CO2 data, I used the yearly averages since 1958 of measurements at the Mauna Loa atmospheric observatory, and from 1880 to 1958 an interpolated dataset from the Law Dome ice core in Antarctica. The CO2 data looks like this:

I started with 1880 because I’m using the global temperature data from NASA:

Here’s CO2 climate forcing .vs. global temperature:

The correlation coefficient between the two variables is a whopping 0.9467, but what really counts is its statistical significance (which is not guaranteed by a large coefficient). In this case the significance is undeniable (with a p-value < 10-15).

Perhaps most notable is the slope of the correlation. That’s why I chose units of “doublings of CO2” for the climate forcing: because this slope is an estimate of the climate sensitivity, the amount of global warming (relative to pre-industrial) we expect from a doubling of CO2 (relative to pre-industrial).

That value (2.4 deg.C per doubling) is close to the mean of what the climate models have to say.

Big change in sea level rise

 From Open Mind (Tamino)

The most interesting thing about Frederikse et al. is that not only do they publish a new sea level reconstruction based on tide gauge data, to reckon how much sea level has risen, they also attempt to reckon where that sea level rise came from.

Here’s their estimate of sea level since 1900:

And here’s what it says about the rate of sea level rise, according to my usual analysis: a lowess smooth in red, and PLF (Piece-wise Linear Fit) in blue:

Several things are clear. First, the rate of sea level rise has changed over the years, sometimes faster (the 1910s, 1930s, 1940s, 1990s, 2000s), sometimes apparently not even rising (the 1920s, 1960s), but the 2010s are “off the chart,” a colorful way of saying that sea level rise was significantly faster than previous decades.

The latest rate, according to these data, is about 5 mm/yr. Over a century, that’s half a meter (about 20 inches). That’s the global amount, lots of places will see more or less because of local conditions (particularly, vertical land movement). It seems to me to be extremely unlikely, downright implausible in fact, that the average over this century will be less than that.

Perhaps more important is that Frederikse et al. also attempted to quantify the causes of sea level rise. Mainly, those are put in three categories: steric (thermal expansion of sea water), melting of land ice (glaciers and ice sheets), and terrestrial water storage (TWS). The contribution of land ice melt is further subdivided into three categories: glaciers, Greenland, and Antarctica.

Here is their estimate of each factor’s contribution to sea level rise since 1900:

Glacier melt has raised sea level more since 1900 than any other factor, but has not shown much recent sign of acceleration, and appears to be slower now than in the first half of the century. Greenland melt was also a major factor in the early 20th century, and has shown signs of both deceleration and acceleration with high rates recently. Steric change caused sea level fall in the first decade of the 1900s, but has risen steadily since and is now moving fast. TWS has caused an overall drop in sea level since 1900, of about 10 mm. Antarctica has countered with about 10 mm net contribution to sea level rise, but took quite a while to get started.

I applied the same analysis to the contributions, as I did to the sea level data itself. Fascinating results emerge, and the most striking is the rate of sea level rise/fall due to Antarctic ice melt:

This leads me to suspect that much of the reason behind the enhanced rate of sea level rise in the last decade is that after nearly a century of inaction, Antarctica has started to kick in.

In the long run (to the end of this century and beyond), we don’t expect TWS to be a major factor. Thermal expansion will continue, as fast or faster than now but not tremendously so; it takes a long time for heat to penetrate deep into the ocean. Glaciers will keep melting, but probably not much faster than now if at all. The fact is that even if we melt all the world’s alpine glaciers and the extra heat penetrates far into the ocean, we’ll still only get about 1 meter of sea level rise, and it will take a long time — longer than this century — for that to happen.

Then there are the big boys: Greenland and Antarctica. If all of Greenland melts there’s 7 meters of sea level rise, and if Antarctica goes, over 50.

Greenland and Antarctica aren’t going to melt this century. But they might dramatically increase the rate at which they discharge ice into the ocean. According to Richard Alley, a leading glaciologist, this tends to happen where the ice and the ocean meet, and the two phenomena which bring it about are the disintegration of floating ice sheets, and calving-cliff retreat.

When an ice sheet disintegrates it tends to happen quickly; we’ve seen the picture of the Larsen B ice shelf falling apart in a matter of days, after having survived many thousands of years. When it did, it no longer acted as a “buttress” to hold back land-based ice from reaching the sea. The flow rate just about doubled — in the twinkling of an eye, geologically speaking.

Computing how it works is straightforward, in that we know all the physics. It’s also impossible, in that there are too many variables and processes to keep track of them all, even with a supercomputer. So, models are developed to simulate processes, and they’re getting better — we’ve actually learned a lot — but according to Richard Alley, we still have a lot to learn before we’re ready to make reliable predictions.

When the rates at which ice is discharged double or triple, if that happens in enough places — and especially in east Antarctica — the rate of sea level rise could become terrifyingly high. Imagine 30 mm/yr — six times the present rate — more than an inch per year. That’s 3 meters per century, and 3 meters is about 10 feet so goodbye, Miami. Goodbye, New Orleans. Goodbye, a lot of places.

And, according to Richard Alley … this is what keeps him up at night.

Hurricane Ida: Climate change made a monster storm

 From Open Mind

Warm sea water is what powers hurricanes. Usually, sea surface temperature (SST) in the Gulf of Mexico needs to exceed 29°C to intensify a hurricane, and every fraction of a degree above 29°C increases the chance — dramatically — of not just intensifying, but super-charging it, creating a “monster storm.”

Which makes one wonder … if a storm passes by, what are the odds the sea surface temperature (SST) will exceed 29°C? Or more? Have the odds changed over time? Of course SST isn’t the only factor at play, only fools say so, but only bigger fools deny its impact on tropical storms.

To learn more about the history of SST in the area visited by hurricane Ida during her journey from Cuba to New Orleans, I selected the region from longitude 92°W to 85°W, latitude 23°N to 30°N, and retrieved daily data for SST in that region from 1981 through Aug. 2 of this year, from the OI (optimal interpolation) v2 dataset.

There’s an obvious annual cycle (hotter in summer, colder in winter), and if we remove it to define anomaly we get this:

The red line is a trend estimate from least-squares regression, and indicates that SST has increased since 1981, by about 0.85°C. It’s overwhelmingly “statistically significant.”

For sea surface temperature and its impact on hurricanes, that amount of warming is HUGE. It’s easy to dismiss it as “quite small” with an offhand “less than 1°C.” But if you really know hurricanes, you know that “every fraction of a degree counts” is, if anything, an understatement. An increase of a “mere” 1°C is nothing like “quite small.”

Of course that’s anomaly, not temperature itself, and it’s for the entire year, not the summer months when temperatures are highest. I split the time span into four decades, from 1981 to 1991, 1991 to 2001, 2001 to 2011, and 2011 to 2021. Then I estimated the probability density function (pdf) during the summer months (Jun/Jul/Aug/Sep) for each decade by two methods: a histogram, and with a smoothed estimate (kernel smooth). I got this for the four decades:

It’s obvious; the chance of meeting or exceeding that 29°C threshhold has increased, particularly from the 1981-1991 decade to the 2011-2021 decade.

If we look at the survival function (1 minus the cumulative distribution function), not only does it give the probability of meeting or exceeding any given value, it’s straightforward to estimate uncertainty ranges for those probabilities (shaded regions surrounding solid lines):

Between the 1981-1991 decade, and 2011-2021, the chance of meeting (or exceeding) the 29°C threshhold went from about 42%, to over 70%. The chance of meeting (or exceeding) 29.5°C, offering much more energy to the storm, went from about 18% to just over 50%. As for the 30°C limit — big trouble in hurricane town — the odds go from a mere 3% chance to a whopping 21%, a 7-fold increase.

It's perfectly obvious to everybody (except those whose salaries and bonuses depend on it not being obvious, like oil company executives and marketing people) that there is a global climate emergency.  It's equally obvious that it's only going to get worse, because too little is being done to reduce emissions.  What will it take?

US heat―where are we vulnerable

From Open Mind 

My investigations suggest that the strongest influence on extreme heat is the increase in average temperature during summer; the shape of the distribution can change, and that has an effect, but change in the average value dominates. So I decided to look at how summertime heat has changed in each climate division of the conterminous USA (i.e. the “lower 48 states”), according to the data for high temperature from NOAA.

For each division, I fit a smooth curve (lowess smooth), then estimated the “summer warming” as the difference between the smoothed values now (i.e. in 2021) and at the start (i.e. in 1895). Some of them show considerable warming, in fact the northeast corner of Utah has warmed by a whopping 6.05°F:

Although most climate divisions show summer warming, not all of them do; in fact in Alabama there’s a division which shows cooling by -2.39°F:

Whichever divisions in the USA have warmed by the most, are most at risk for never-before-seen extreme heat. And here they are as red dots (bigger dots, bigger risk), with blue dots indication regions which have shown net summer cooling (rather than heating) since 1895:

Two regions stand out as being at greatest risk. First is the entire U.S. west, westward of longitude 100°W. Second is the northeast coast, northward of Washington D.C.

Coronavirus: red states vs blue

Another telling use of data from Open Mind (Tamino):

Of the 50 U.S. states, 24 have democratic governors — let’s call them “blue states” — and 26 “red states” have republican governors. The blue states have a considerably larger population, so let’s compare the case load of COVID-19 per capita (specifically, cases per day per million population). Democrat-governor states in blue, republican-governor states in red.

This is NOT natural

One hears it all the time from the ignorant.  "There have always been climate fluctuations".  "It's just a natural cycle".  And so on and so on.

It is NOT natural.  And it's MUCH BIGGER than any previous climate fluctuations.

Chart from Open Mind (Tamino)

Oz's summer from hell

It's summer in the southern hemisphere.  Officially, Oz's summer lasts from the beginning of December to the end of February, but we've having been having record heat across the continent.  Last summer (December 2018 to February 2019) was a record, by a long way.    The statistical probability is that this year will not be another record; a zag tends to follow a zig.  But in fact it's been so incredibly hot this year so far that it is entirely possible that there will be another record this year.  Either way, the key variable to watch is the steadily rising trend. 

Meanwhile one of the many cretins on the rabid right wing of the ruling denialist coalition government wants an official enquiry into whether the Bureau of Meteorology is making the figures up, despite our lived experience.  We know it is hotter than ever, we know that there is a record drought, we know that our rivers are dying, and we know that this is the earliest massive bushfires have ever occurred.

The chart comes from Open Mind (Tamino):

Source: Open Mind
The observation with the black ring around it is the Dec 2018-Feb 2019 summer.