Teach your children well

I don’t know the young man behind this, but I know his dad. Be proud.

Climate change education is essential to help young people face the future.

Sea Level in New York City — Part 2

In the last post I discussed sea level at New York City, and showed this graph of yearly averages with a PLF fit (piecewise linear fit):

Sea Level in New York City

The New York Panel on Climate Change (NPCC) recently unveiled their latest projections for future sea level rise in New York City. You can view their presentation here, but in my opinion it’s very boring.

There has been a lot of confusion about their projections, for example this headline in the New York Post: “Sea levels around NYC could surge up to 13 inches in 2030s due to climate change: state study.” The first sentence of the story informs us that “Sea levels surrounding New York City are expected to rise at least 6 to 9 inches in the 2030s and potentially up to 13 inches in some areas due to climate change, according to state projections.” I suspect that the New York Post simply misunderstood the projections, which do not claim a rise of at least 6 to 9 inches during the 2030s.

A later New York Post opinion piece seems to equate the projection to “as much as 13 inches by the year 2030,” meaning sea level rise of 13 inches in the next 6 years. That is of course a silly idea, but I’m tempted to suspect that the author actually did know what bullshit that particular misinterpretation is. Of course Anthony Watts went with the same misinterpretation.

Open Thread

New blog posts will be slow coming this week, because I’m busy doing science. First, the new adjusted temperature data and the methods to produce it should be published in the peer-reviewed literature, and in my opinion, soon. Second, I’m researching computer models with some other climate scientists, mainly to study what the models say about how Earth’s warming rate changes over time. I can personally assure you that none of us is trying to avoid hot models; we’re trying to understand them.

In the meantime, here’s an open thread.

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Optimism of the Will

Regular readers already know that I will continue to focus on the science of climate change, but occasionally share something on the policy side.

In a most outstanding interview, Kevin Anderson states that “We have to eliminate fossil fuel use, for 1.5°C, at a global level, we have to eliminate all fossil fuel use by 2040 at the very latest.” He adds that if we are true to the idea of equity, then rich nations must lead the way so “For 1.5°C it means the wealthy countries, that we need to be zero-emissions, zero-fossil-fuel use, by about 2030.”

Accelerations

Looking at global temperature anomaly since 1950 (data from NOAA), it clearly shows acceleration around the year 1975. For the 25 years prior to that, it’s hard to say whether it was rising or falling but it surely wasn’t going either way very fast. Since 1975, the trend has risen steadily.

Adjusted Data to play with

In the last post I discussed the changes I’ve made to my method for adjusting temperature data, to compensate for volcanic eruptions, the el Niño southern oscillation, and solar variations. It seems that some readers like to play with data (perhaps even as much as I do), and I’ve decided to post the data so you can play with it.

Adjusted Global Temperature Data

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:

What’s Up With That?

The “CO2 Coalition” has prepared a report claiming that in Wyoming,

“… high daily temperatures peaked during the Dust Bowl years of the 1930s and have been in a 90-year decline.”

To back up this claim they show this graph:

Pre-Industrial Sclerosponges

I never heard of sclerosponges until a paper came to my attention which uses their skeletons to estimate temperature in the Ocean Mixed Layer (OML). The authors do so using sclerosponges from the Carribean sea, specifically, using the ratio of Strontium to Calcium in those skeletons as a proxy for temperature. This yields OML temperature estimates going back nearly 300 years, and they show persuasively that OML (ocean mixed layer) temperature tracks sea-surface temperature (SST) extremely well during their calibration period. They even make the case that OML temperature in the Carribean sea tracks global SST extremely well.

And that enables them to estimate SST going back almost 300 years. Here’s how their new estimate of SST anomaly (plotted as red triangles) compares to the HadSST4 data set for SST anomaly (plotted as blue x’s):