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Time for the 2012 updates!
As has become a habit (2009, 2010, 2011), here is a brief overview and update of some of the most discussed model/observation comparisons, updated to include 2012. I include comparisons of surface temperatures, sea ice and ocean heat content to the CMIP3 and Hansen et al (1988) simulations.
This month’s open thread on climate science…
Last July (2012), I heard from a colleagues working at the edge of the Greenland ice sheet, and from another colleague working up at the Summit. Both were independently writing to report the exceptional conditions they were witnessing. The first was that the bridge over the Watson river by the town of Kangerlussuaq, on the west coast of Greenland, was being breached by the high volumes of meltwater coming down from the ice sheet. The second was that there was a new melt layer forming at the highest point of the ice sheet, where it very rarely melts.
A front loader being swept off a bridge into the Watson River, Kangerlussuaq, Greenland, in July 2012. Fortunately, nobody was in it at the time. Photo: K. Choquette
I’ve been remiss in not writing about these observations until now. I’m prompted to do so by the publication in Nature today (January 23, 2013) of another new finding about Greenland melt. This paper isn’t about the modern climate, but about the climate of the last interglacial period. It has relevance to the modern situation though, a point to which I’ll return at the end of this post.
I recently got an email from newly graduated Math(s) major (mildly edited):
I am someone with a deep-seated desire to help the planet remain as habitable as possible in the face of the trials humanity is putting it through. I’d like to devote my career to this cause, but am young and haven’t chosen a definitive career path yet. My bachelors is in pure math and I am considering graduate study in either applied math or statistics. I’m curious what you would recommend to someone in my position. Between getting, say, a PhD in statistics vs. one in applied math, what positions me best for a career in the climate science community? What are its acute needs, where are the job opportunities, and how competitive is it?
My response was as follows (also slightly edited):
As you may know I too started out as a mathematician, and then moved to more climate related applications only in my post-doc(s).
I can’t possibly give you ‘the’ answer to your question – but I do suggest working from the top down. What do you see specifically as something where someone like you could have maximum impact? Then acquire the skills needed to make that happen. If that seems too hard to do now, spend time on the developing your basic toolkits – Bayesian approaches to statistics, forward modeling, some high level coding languages (R, python, matlab etc.), while reading widely about applications.
One of the things I appreciated most in finding my niche was being exposed to a very large number of topics – which while bewildering at the start, in the end allowed me to see the gaps where I could be most useful. At all times though, I pursued approaches and topics that were somewhat aesthetically pleasing to me, which is to say, I didn’t just take up problems just for the sake of it.
I’ve found that I get more satisifaction from focusing on making some progress related to big problems, rather than finding complete solutions to minor issues, but this probably differs from person to person.
But what do other people think? How should people prepare to work on important problems? Are there any general rules? What advice did people give you when you were starting out? Was it useful, or not? Any advice – from existing researchers, graduate students or interested public – will be welcome.
This is Part 2 of my thoughts on the state of sea-level research. Here is Part 1.
A topic that keeps coming up in the literature is the discussion on a (roughly) 60-year cycle in sea level data; a nice recent paper on this is Chambers et al. in GRL (2012). One thing I like about this paper is its careful discussion of the sampling issue of the tide gauges, which means that variability in the tide gauges is not necessarily variability in the true global mean sea level (see Part 1 of this post). I want to add some thoughts on the interpretation of this variability. Consider this graph from my Response to Comments in Science (2007):
Fig. 1: Fifteen-year averages of the global mean temperature (blue, °C, GISS data) and rate of sea level rise (red, cm/year, Church&white data), both detrended.
D.P. Chambers, M.A. Merrifield, and R.S. Nerem, "Is there a 60-year oscillation in global mean sea level?", Geophysical Research Letters, vol. 39, pp. n/a-n/a, 2012. http://dx.doi.org/10.1029/2012GL052885
S. Rahmstorf, "Response to Comments on "A Semi-Empirical Approach to Projecting Future Sea-Level Rise"", Science, vol. 317, pp. 1866d-1866d, 2007. http://dx.doi.org/10.1126/science.1141283
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