The Impromptu Climate Modeling Journal Club|
[Most Recent Entries]
Below are the 9 most recent journal entries recorded in
The Impromptu Climate Modeling Journal Club's LiveJournal:
|Wednesday, February 14th, 2007|
Hurricanes and global warming
I'm not a tropical meteorologist, but I've observed a lot of the "heat" around the debate on hurricanes and global warming at conferences. I came across this recent GRL paper and I thought it was really interesting. The authors explain how "both sides of the isle are right and wrong at the same time".
Latif, M., N. Keenlyside, and J. Bader (2007), Tropical sea surface temperature, vertical wind shear, and hurricane development, Geophys. Res. Lett., 34, L01710, doi:10.1029/2006GL027969.( short summaryCollapse )
|Thursday, January 18th, 2007|
It looks like the int'l panel on climate change will be releasing their next report, on updates to the physical science basis of climate modelling, on Feb 2. Anyone want to write about it?
(Their schedule appears to be releasing "The Physical Science Basis" on 2 Feb, "Impacts, Adaptation and Vulnerability" on 6 Apr, and "Mitigation of Climate Change" on 4 May. A synthesis report is due out in July.)
|Tuesday, July 25th, 2006|
Clarification about fig. 20
After talking with some people, I realized that the explanation of the critical figure 20 in the big paper was somewhere between "unclear" and "just plain wrong." This is the figure that actually summarizes predictions for the next 100 years, so it's probably worth looking at. :) Here's the right explanation.
First of all, separate the year into four seasons. If you take the daily temperature data for any spot on Earth and plot a histogram over a long period of time, you'll get a sum of two Gaussians plus a general blur; but if you select out just the data for summer (June-July-August) or winter (December-January-February) each of those is a single bell curve. (My post
about Lincoln, NE shows exactly this graph: the daily temperatures in Lincoln for every day during summer in the past 75 years or so. It's a pretty little bell curve with a mean of 90F and a sigma of about 8F. This sigma represents the average day-to-day
variation of temperatures.
(Now, that posting explained how a shift in the local mean temperature translates into a change in number of hot days per year. The result of that calculation was that raising the average temperature in Lincoln would increase the number of days above 95F [the temperature that kills corn] by roughly 1 week per summer for every 1C temperature change. So this is the function that turns a change in the average summertime temperature into a change in local farming conditions.)
Next, look at the graph in the top right of figure 20a. This graph shows the average year-to-year
variation. Take the average temperature for all the days in summer for each individual year; if you plot a histogram of those, you get another nice bell curve. The mean is in the same place as the mean of daily temperatures (90F) but the width of this bell curve represents how much each year differs from another. From looking at this plot, that difference for Lincoln is about 0.5C, which means that each summer is much like the rest.
Now, look at the third column of figure 20b. This shows the change in average temperatures, in degrees Celsius, for every spot on the earth in the five models. For Lincoln, this shows a change of between +4 and +12C, which means that the center of the average year's day-to-day bell curve (the same plot as in my post) would move 4-12C to the right. (Which, btw, would be really bad
The fourth column of figure 20b compares the third column with the year-to-year variations plotted in the top right graph; i.e., if that graph shows a 5 for some point on Earth, it means that the summer average temperatures for a year around 2100 in that spot would be a 5σ event by the standards of the past century -- i.e., an average temperature which on its own would have occurred once every 3.5 million years without climate change. In essence, this column tells you two things: first, that the climate changes predicted in column 3 are statistically significant anomalies (they represent average temperatures which normally would never, ever occur). Second, since the year-to-year variation of temperatures is what all the local plants, animals and people have adapted to, this plot tells you how far from regular experience the new situation will be.
So based on this, a value of 1 or 2 on a plot in the fourth column isn't too bad: 1 means "the average year will look like the sort of year that happens once every 6 years or so nowadays," and 2 means "the average year then will look like a once-in-44-years heat wave." Both can be uncomfortable (spoken just as a nasty heat wave is passing where I live), but neither is a disaster. To take Lincoln as the example again, the average year-to-year variation there is about 0.5C, so a change of 0.5 or 1C isn't a huge deal. As per my previous post, it means another week per summer of 95 degree heat, but things could be worse.
On the other hand, a value of 7 or more on this plot suggests something really bad. For Lincoln, again, this would mean a temperature change of 3.5C; that means that the average summer would have about 45 days per summer above 95F. Corn is adapted to growing in a climate whose mean varies by 0.5C from year to year, which means that the number of days above 95F is ranging between about 16 and 22; it can't survive with 45 days of that any more than it can survive in Antarctica. Similarly all the other plants living there, and animals, and so on...
Of course, other creatures are just fine with warmer temperatures. Malaria and sleeping sickness, for instance. (As is currently being demonstrated in Africa: Nairobi was built above where the malaria line used to be. Surprise!)
|Sunday, June 4th, 2006|
Hansen et al., continued!
OK, it's time for the long-promised second part of Hansen, et al.
. And this one is exciting, because it contains their projections of the climate model into the future!
It's possibly even more exciting because this part analyzes several scenarios for the future, all of which are achievable using only present-day technology but differ only in policy -- but the results range from "everything is OK" to, frankly, apocalyptic.( Speak, O crystal ball!Collapse )
|Thursday, May 18th, 2006|
|Thursday, May 11th, 2006|
New measurements of air pollution in the Arctic
reporting record high levels of tropospheric ozone and aerosols. (NB aerosols in the troposphere are a positive
forcing, since they reflect heat downwards, as opposed to ones in the stratosphere which reflect incoming light upwards)
|Thursday, May 4th, 2006|
|Wednesday, May 3rd, 2006|
Change of plans
After looking through the short paper, it doesn't make much sense as a first paper for us to look at; "Dangerous human-made interference with climate: A GISS modelE study.
" is a much more obvious first choice. (They run their gold-standard model from 1880 to 2100, with several scenarios for the future, and basically give an overview of everything) So I'll prep that one for the first journal club instead, and try to have it ready by this weekend.
BTW, related news story, and the federal study's decision was in no small part affected by this paper (rumor says): Federal study finds accord on warming
. The lead line reads:
A scientific study commissioned by the Bush administration concluded yesterday that the lower atmosphere was indeed growing warmer and that there was "clear evidence of human influences on the climate system." The finding eliminates a significant area of uncertainty in the debate over global warming, one that the administration has long cited as a rationale for proceeding cautiously on what it says would be costly limits on emissions of heat-trapping gases.
|Monday, May 1st, 2006|
The Impromptu Climate Modeling Journal Club (ICMJC) now exists. The point of this community is to have a chance to read through the literature, get to know what's going on in climate modeling, and in general make ourselves competent to talk about this as scientists and engineers, learn some stuff, and possibly get into a position to make useful contributions to the field.
To quote from the original post:
To that end, I've started to assemble a list of papers that seem to represent the current state-of-the-art in the field, and this list is sure to grow as I read through more of them and follow reference chains. In fact, I'm planning on posting something soon with a generally readable summary of one of them.
But this got me thinking: Learning a subject is better done with many people. Would anyone be interested in forming an impromptu online journal club to learn about climate modelling, climate change, and all things related? (For those of you who haven't participated in these before, what would be involved is everyone picking a paper, [or part of one for a really long paper] reading it thoroughly enough to write a good summary and explain everything that goes on in it, and then posting their summary and having a discussion about it. A typical rate is every week, someone else is responsible for a paper. It's a great way to learn a new technical subject.)
The minimum background for doing this seems to be a reasonable science or engineering background; from what I've read of the papers so far, they don't have a lot of obscure jargon beyond "stratosphere" and "sea ice," just a lot of graphs, plots, and discussion of how they got them. For those without a heavy tech background, it should still be possible (and fun, and interesting) to be part of the discussion.
So I've got a few suggested papers to start with, from the GISS-E group:
- Hansen et al., "Earth's energy imbalance: Confirmation and implications." Science 308, 1431-1435, doi:10.1126/science.1110252. [This is a short paper that I'll probably post about in a few days no matter what. This article was considered a "gold standard" model at the time, and it's still pretty recent.]
- Hansen et al., "Dangerous human-made interference with climate: A GISS modelE study." J. Geophys. Res., submitted. [This is a bigger paper, the Hansen groups latest systematic model-of-everything. I'm reading it right now and it looks like a good gateway to the rest of the literature]
- Hansen et al., "Efficacy of climate forcings." J. Geophys. Res. 110, D18104, doi:10.1029/2005JD005776. [This paper seems to be the one where they actually calculate and define a lot of the underlying parameters, like how much each type of substance affects each physical process. I suspect it will be very interesting]
- Schmidt et al., "Present day atmospheric simulations using GISS ModelE: Comparison to in-situ, satellite and reanalysis data.", J. Climate 19, 153-192, doi:10.1175/JCLI3612.1. [This paper is the standard reference on the GISS-E model, which appears to be the current standard climate modelling code used by international agencies. No idea how interesting the paper will be.]
I'll volunteer to lead the first of these: it's a short paper but going through it is going to require a bit more digging through the literature than usual to define terms.
In general, if you come across a paper you think we ought to cover, post a note about it to the list. If you want to volunteer to cover one, also post a note to the list. If nobody volunteers for too long, I may start hunting people down. :)