In mid-November NASA released an ultra-high-resolution computer model simulating how carbon dioxide in the atmosphere travels around the globe. It is visually stunning – all those colours and swirls and detail – see for yourself:
From the press release
“Scientists have made ground-based measurements of carbon dioxide for decades and in July NASA launched the Orbiting Carbon Observatory-2 (OCO-2) satellite to make global, space-based carbon observations. But the simulation – the product of a new computer model that is among the highest-resolution ever created – is the first to show in such fine detail how carbon dioxide actually moves through the atmosphere.”
“NASA | A year in the life of Earth’s CO2” – it happens to be 2006.
The carbon dioxide visualization was produced by a computer model called GEOS-5, […] the visualization is part of a simulation called a “Nature Run.” The Nature Run ingests real data on atmospheric conditions and the emission of greenhouse gases and both natural and man-made particulates. The model is then is left to run on its own and simulate the natural behavior of the Earth’s atmosphere. This Nature Run simulates May 2005 to June 2007.
Now, before we examine it in more detail, here’s a close up of the scale for the CO2. Most of the action is over a narrow 5ppmv range.
Let’s look first at the beginning and end of the video – January and December. Here they are side by side:
These are a year apart, but it is an annual cycle isn’t it? Was there something special about the CO2 concentrations in either January or December 2006? Should not January and December be in the same ball-park? Is is normal for there to be such variation? If not, why there was so little CO2 in the Arctic in December 2005/January 2006 compared to December 2006, or why so much in December 2006? What would January 2007 look like?
I get it that this is modelling emissions and their circulation in the atmosphere. I did think perhaps it was using sources and that sinks were not well factored in such that emissions were cumulative, however that is not the case. The Arctic, in fact the whole Northern Hemisphere, blood-red at the end of April, is clear again by the end of June.
The Northern Hemisphere bias is also telling – but I guess there are tons of data for that. I suppose what I really want to know is how much is “measured CO2” and how much is “fossil fuel use calculated CO2 production”.
Note the model includes volcanic sources, pink-white isolated plumes in the ocean, for example in the South Sandwich Islands. Never mind volcanic CO2, I guess it will be handy for SO2 if we have another Pinatubo or Bardarbunga starts to rival Laki.
As recently mentioned here at WUWT, the OCO-2 data is starting to become available. A recently released composite image has a different scale to the Nature Run model video> It spans 15ppm over a similar colour scale used by just 5ppm in the model, although at a higher level of CO2 reflecting the atmospheric increase in the intervening years:
The production of CO2 in the S. American and Southern African regions is striking, as is the sink in the Southern Ocean. As a comparison, here are three images from Nature Run over the same time scale of months. The middle one of the three, transiently, is about right.
Beautiful imagery, no doubt an achievement in modelling terms, now let’s get some of that real OCO-2 data into it.
You know what, it always seems that no matter how much we think we know, we forget how much we have yet to understand. Only a couple of days ago, yet another NASA lab published a paper (press release; abstract paywalled here) which estimates that tropical forests absorb 1.4 billion out of a total global absorption of 2.5 billion metric tons of carbon dioxide. This is considerably higher than previous estimates which assumed that boreal forests were the greater sink. But note that word “estimates”, yes, more models, although in this case combined with real data.
“Until our analysis, no one had successfully completed a global reconciliation of information about carbon dioxide effects from the atmospheric, forestry and modeling communities,” said co-author Joshua Fisher of JPL. “It is incredible that all these different types of independent data sources start to converge on an answer.”
I guess that’s the future – models combined with real data. Better than imagined data, but watch out for blending, mixing and homogenisation.