Musing about Losing Earth

The NY Times Magazine has a special issue this weekend on climate change. The main article is “Losing the Earth” by Nathaniel Rich, is premised on the idea that in the period 1979 to 1989 when we basically knew everything we needed to know that climate change was a risk, and the politics had not yet been polarized, we missed our opportunity to act. Stated this way, it would probably

Model Independence Day

We hold these truths to be self-evident, that all models are created equal, that they are endowed by their Creators with certain unalienable Rights, that among these are a DOI, Runability and Inclusion in the CMIP ensemble mean. Well, not quite. But it is Independence Day in the US, and coincidentally there is a new discussion paper (Abramowitz et al) (direct link) posted on model independence just posted at Earth System Dynamics

30 years after Hansen’s testimony

“The greenhouse effect is here.” – Jim Hansen, 23rd June 1988, Senate Testimony The first transient climate projections using GCMs are 30 years old this year, and they have stood up remarkably well. We’ve looked at the skill in the Hansen et al (1988) (pdf) simulations before (back in 2008), and we said at the time that the simulations were skillful and that differences from observations would be clearer with a decade or two’s more data. Well, another decade has passed! How should we go

Nenana Ice Classic 2018

Another year, another ice out date. As in previous years, here’s an update of the Nenana Ice Classic time series (raw date, and then with a small adjustment for the calendrical variations in ‘spring’). One time series doesn’t prove much, but this is of course part of a much larger archive of phenomenological climate-related data that I’ve talked about before. This year the ice on the Tanana River went out on May 1st, oddly enough the same date as last year, after another very warm (but quite snowy) Alaskan winter. My shadow bet on whether any climate contrarian site will mention this dataset remains in play (none have

What did NASA know? and when did they know it?

If you think you know why NASA did not report the discovery of the Antarctic polar ozone hole in 1984 before the publication of Farman et al in May 1985, you might well be wrong. One of the most fun things in research is what happens when you try and find a reference to a commonly-known fact and slowly discover that your “fact” is not actually that factual, and that the real story is more interesting than you imagined… Here

O Say can you See Ice…

Some concerns about continued monitoring of sea ice by remote sensing were raised this week in Nature News an article in the (UK) Observer: Donald Trump accused of obstructing satellite research into climate change. The last headline is not really correct, but the underlying issues are real. What is this about? Since the late seventies, there have been almost continuous observations of polar sea ice by passive microwave sensing on multiple polar-orbiting satellites. This is the preferred technique since microwaves from the surface can penetrate clouds (which are abundant in the polar regions) and can

Data rescue projects

It’s often been said that while we can only gather new data about the planet at the rate of one year per year, rescuing old data can add far more data more quickly. Data rescue is however extremely labor intensive. Nonetheless there are multiple data rescue projects and citizen science efforts ongoing, some of which we have highlighted here before. For those looking for an intro into the subject, this 2014 article is an great introduction. Weather diary from the the Observatoire de Paris, written by Giovanni Cassini on 18th January 1789. I was asked this week whether there was a list of these projects, and with a bit of

Observations, Reanalyses and the Elusive Absolute Global Mean Temperature

One of the most common questions that arises from analyses of the global surface temperature data sets is why they are almost always plotted as anomalies and not as absolute temperatures. There are two very basic answers: First, looking at changes in data gets rid of biases at individual stations that don’t change in time (such as station

Joy plots for climate change

This is joy as in ‘Joy Division’, not as in actual fun. Many of you will be familiar with the iconic cover of Joy Division’s Unknown Pleasures album, but maybe fewer will know that it’s a plot of signals from a pulsar (check out this Scientific American article on the history). The length of the line is matched to the frequency of the pulsing so that successive pulses

Climate Sensitivity Estimates and Corrections

You need to be careful in inferring climate sensitivity from observations. Two climate sensitivity stories this week – both related to how careful you need to be before you can infer constraints from observational data. (You can brush up on the background and definitions here). Both cases – a “Brief Comment Arising” in Nature (that I led) and a new paper from Proistosescu and Huybers (2017) –

Nenana Ice Classic 2017

As I’ve done for a few years, here is the updated graph for the Nenana Ice Classic competition, which tracks the break up of ice on the Tanana River near Nenana in Alaska. It is now a 101-year time series tracking the winter/spring conditions in that part of Alaska, and shows clearly the long term trend towards earlier break up, and overall warming. 2017 was almost exactly on trend – roughly one week earlier than the average break up date a century ago. There was a short NPR piece on the significance again this week, but most of the commentary from last

Judy Curry’s attribution non-argument

Following on from the ‘interesting’ House Science Committee hearing two weeks ago, there was an excellent rebuttal curated by ClimateFeedback of the unsupported and often-times misleading claims from the majority witnesses. In response, Judy Curry has (yet again) declared herself unconvinced by the evidence for a dominant role for human forcing of recent climate changes. And as before she fails to give any quantitative argument to support her contention that human drivers are

Serving up a NOAA-thing burger

I have mostly been sitting back and watching the John Bates story go through the predictable news-cycle of almost all supposed ‘scandalous’ science stories. The patterns are very familiar – an initial claim of imperfection spiced up with insinuations of misconduct, coordination with a breathless hyping of the initial claim with ridiculous supposed implications, some sensible responses refuting the initial specific claims and demolishing the wilder extrapolations. Unable to defend the nonsense clarifications are made that the initial claim wasn’t about misconduct but merely about ‘process’ (for who can argue against better processes?). Meanwhile the misconduct and data falsification claims escape into the wild, get more exaggerated and lose all connection to any

2016 Temperature Records

To nobody’s surprise, all of the surface datasets showed 2016 to be the warmest year on record. Barely more surprising is that all of the tropospheric satellite datasets and radiosonde data also have 2016 as the warmest year. Coming as this does after the record warm 2015, and (slightly less definitively) record warm 2014, the three records in row might get you to sit up and pay attention. There a few more technical issues that are worth mentioning here. Impact of ENSO The contribution of El Niño to

Tuning in to climate models

There is an interesting news article ($) in Science this week by Paul Voosen on the increasing amount of transparency on climate model tuning. (Full disclosure, I spoke to him a couple of times for this article and I’m working on tuning description paper for the US climate modeling centers). The main points of the article are worth highlighting here, even if a few of the characterizations are slightly off. The basic thrust of the article is that

The Snyder Sensitivity Situation

Nature published a great new reconstruction of global temperatures over the past 2 million years today. Snyder (2016) uses 61 temperature reconstructions from 59 globally diverse sediment cores and a correlation structure from model simulations of the last glacial maximum to estimate (with uncertainties) the history of global temperature back through the last few dozen ice ages cycles. There are multiple real things to discuss about this – the methodology, the relatively small number of cores being used (compared to what could have been analyzed), the age modeling etc. – and

Why correlations of CO2 and Temperature over ice age cycles don’t define climate sensitivity

We’ve all seen how well temperature proxies and CO2 concentrations are correlated in the Antarctic ice cores – this has been known since the early 1990’s and has featured in many high-profile discussions of climate change. EPICA Dome C ice core greenhouse gas and isotope records. The temperature proxies are water isotope ratios that can be used to estimate Antarctic temperatures and, via a scaling, the global values. The CO2 and CH4 concentration changes can be converted to radiative forcing in W/m2 based on standard formulas. These two timeseries can be correlated and the regression (in ºC/(W/m2))

Predicting annual temperatures a year ahead

I have a post at Nate Silver’s 538 site on how we can predict annual surface temperature anomalies based on El Niño and persistence – including a (by now unsurprising) prediction for a new record in 2016 and a slightly cooler, but still very warm, 2017. The key results are summarized in the figures that

Australian silliness and July temperature records

Some of you that follow my twitter account will have already seen this, but there was a particularly amusing episode of Q&A on Australian TV that pitted Prof. Brian Cox against a newly-elected politician who is known for his somewhat fringe climate ‘contrarian’ views. The resulting exchanges were fun:

The Volcano Gambit

Anyone reading pundits and politicians pontificating profusely about climate or environmental science will, at some point, have come across the “volcano gambit”. During the discussion they will make a claim that volcanoes (or even a single volcano) produce many times more pollutant emissions than human activities. Often the factor is extremely precise to help give an illusion of science-iness and, remarkably, almost any pollutant can be referenced. This “volcano gambit” is an infallible sign

Nenana Ice Classic 2016

Just a quick note since I’ve been tracking this statistic for a few years, but the Nenana Ice Classic tripod went down this afternoon (Apr 23, 3:39 Alaska Standard Time). See the earlier post for what this is and why it says something about the climate (see posts on 2014 and 2015 results). With this unofficial time, this year places 4th earliest for the breakup of ice in the Tanana river. It is unsurprising that it was early given the exceptional warmth in Alaska this year. The exact ranking of years depends a little on

Comparing models to the satellite datasets

How should one make graphics that appropriately compare models and observations? There are basically two key points (explored in more depth here) – comparisons should be ‘like with like’, and different sources of uncertainty should be clear, whether uncertainties are related to ‘weather’ and/or structural uncertainty in either the observations or the models. There are unfortunately many graphics going around that fail to do this properly, and some prominent ones are

Marvel et al (2015) Part III: Response to Nic Lewis

The first post in this series gave the basic summary of Marvel et al (2015) (henceforth MEA15) and why I think it is an important paper. The second discussed some of the risible immediate media coverage. But there has also been an ‘appraisal’ of the paper by Nic Lewis that has appeared in no fewer than three other climate blogs (you can guess which). This is a response to the more interesting of his points. As is usual when people