I’m attending a workshop this week in which some of the initial results from the Fifth Coupled Model Intercomparison Project (CMIP5) will be presented. CMIP5 will form a key part of the next IPCC assessment report – it’s a coordinated set of experiments on the global climate models built by labs around the world. The experiments include hindcasts to compare model skill on pre-industrial and 20th Century climate, projections into the future for 100 and 300 years, shorter term decadal projections, paleoclimate studies, plus lots of other experiments that probe specific processes in the models. (For more explanation, see the post I wrote on the design of the experiments for CMIP5 back in September).

I’ve been looking at some of the data for the past CMIP exercises. CMIP1 originally consisted of one experiment – a control run with fixed forcings. The idea was to compare how each of the models simulates a stable climate. CMIP2 included two experiments, a control run like CMIP1, and a climate change scenario in which CO2 levels were increased by 1% per year. CMIP3 then built on these projects with a much broader set of experiments, and formed a key input to the IPCC Fourth Assessment Report.

There was no CMIP4, as the numbers were resynchronised to match the IPCC report numbers (also there was a thing called the Coupled Carbon Cycle Climate Model Intercomparison Project, which was nicknamed C4MIP, so it’s probably just as well!), so CMIP5 will feed into the fifth assessment report.

So here’s what I have found so far on the vital statistics of each project. Feel free to correct my numbers and help me to fill in the gaps!

CMIP
(1996 onwards)
CMIP2
(1997 onwards)
CMIP3
(2005-2006)
CMIP5
(2010-2011)
Number of Experiments 1 2 12 110
Centres Participating 16 18 15 24
# of Distinct Models 19 24 21 45
# of Runs (Models X Expts) 19 48 211 841
Total Dataset Size ?? ?? 36 TeraByte 3.3 PetaByte
Total Downloads from archive ?? ?? 1 PetaByte
Number of Papers Published 47 595
Users ?? ?? 6700

[Update:] I’ve added a row for number of runs, i.e. the sum of the number of experiments run on each model (in CMIP3 and CMIP5, centres were able to pick a subset of the experiments to run, so you can’t just multiply models and experiments to get the number of runs). Also, I ought to calculate the total number of simulated years that represents (If a centre did all the CMIP5 experiments, I figure it would result in at least 12,000 simulated years).

Oh, one more datapoint from this week. We came up with an estimate that by 2020, each individual experiment will generate an Exabyte of data. I’ll explain how we got this number once we’ve given the calculations a bit more of a thorough checking over.

As today is the deadline for proposing sessions for the AGU fall meeting in December, we’ve submitted a proposal for a session to explore open climate modeling and software quality. If we get the go ahead for the session, we’ll be soliciting abstracts over the summer. I’m hoping we’ll get a lively session going with lots of different perspectives.

I especially want to cover the difficulties of openness as well as the benefits, as we often hear a lot of idealistic talk on how open science would make everything so much better. While I think we should always strive to be more open, it’s not a panacea. There’s evidence that open source software isn’t necessarily better quality, and of course, there’re plenty of people using lack of openness as a political weapon, without acknowledging just how many hard technical problems there are to solve along the way, not least because there’s a lack of consensus over the meaning of openness among it’s advocates.

Anyway, here’s our session proposal:

TITLE: Climate modeling in an open, transparent world

AUTHORS (FIRST NAME INITIAL LAST NAME): D. A. Randall1, S. M. Easterbrook4, V. Balaji2, M. Vertenstein3

INSTITUTIONS (ALL): 1. Atmospheric Science, Colorado State University, Fort Collins, CO, United States. 2. Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States. 3. National Center for Atmospheric Research, Boulder, CO, United States. 4. Computer Science, University of Toronto, Toronto, ON, Canada.

Description: This session deals with climate-model software quality and transparent publication of model descriptions, software, and results. The models are based on physical theories but implemented as software systems that must be kept bug-free, readable, and efficient as they evolve with climate science. How do open source and community-based development affect software quality? What are the roles of publication and peer review of the scientific and computational designs in journals or other curated online venues? Should codes and datasets be linked to journal articles? What changes in journal submission standards and infrastructure are needed to support this? We invite submissions including experience reports, case studies, and visions of the future.

This week, I’m featuring some of the best blog posts written by the students on my first year undergraduate course, PMU199 Climate Change: Software, Science and Society. This post is by Harry, and it first appeared on the course blog on January 29.

Projections from global climate models indicate that continued 21st century increases in emissions of greenhouse gases will cause the temperature of the globe to increase by a few degrees. These global changes in a few degrees could have a huge impact on our planet. Whether a few global degrees cooler could lead to another ice age, a few global degrees warmer enables the world to witness more of nature’s most terrifying phenomenon.

According to Anthony D. Del Genio the surface of the earth heats up from sunlight and other thermal radiation, the amount of energy accumulated must be offset to maintain a stable temperature. Our planet does this by evaporating water that condenses and rises upwards with buoyant warm air. This removes any excess heat from the surface and into higher altitudes. In cases of powerful updrafts, the evaporated water droplets easily rise upwards, supercooling them to a temperature between -10 and -40°C. The collision of water droplets with soft ice crystals forms a dense mixture of ice pellets called graupel. The densities of graupel and ice crystals and the electrical charges they induce are two essential factors in producing what people see as lightning.

Ocean and land differences in updrafts also cause higher lightning frequencies. Over the course of the day, heat is absorbed by the oceans and hardly warms up. Land surfaces, on the other hand, cannot store heat and so they warm significantly from the beginning of the day. The great deal of the air above land surfaces is warmer and more buoyant than that over the oceans, creating strong convective storms as the warm air rises. The powerful updrafts, as a result of the convective storms, are more prone to generate lightning.

According to the general circulation model by Goddard Institute for Space Studies, one of the two experiments conducted indicates that a 4.2°C global warming suggests an increase of 30% in global lightning activity. The second experiment indicated that a 5.9°C global cooling would cause a 24% decrease in global lightning frequencies. The summaries of the experiments signifies a 5-6% change in global lightning frequency for every 1°C of global warming or cooling.

As 21st century projections of carbon dioxide and other greenhouse gases emission remain true, the earth continues to warm and the ocean evaporates more water. This is largely because the drier land surface is unable to evaporate water at the same extent as the oceans, causing the land to warm more. This should cause stronger convective storms and produce higher lightning occurrence.

Greater lightning frequencies can contribute to a warmer earth. Lightning provides an abundant source of nitrogen oxides, which is a precursor for ozone production in the troposphere. The presence of ozone in the upper troposphere acts as a greenhouse gas that absorbs some of the infrared energy emitted by earth. Because tropospheric ozone traps some of the escaping heat, the earth warms and the occurence of lightning is even greater. Lightning frequencies creates a positive feedback process on our climate system. The impact of ozone on the climate is much stronger than carbon, especially on a per-molecule basis, since ozone has a radiative forcing effect that is approximately 1,000 times as powerful as carbon dioxide. Luckily, the presence of ozone in the troposphere on a global scale is not as prevalent as carbon and its atmospheric lifetime averages to 22 days.

"Climate simulations, which were generated from four Global General Circulation Models (GCM), were used to project forest fire danger levels with relation to global warming."

Lightning occurs more frequently around the world, however lightning only affects a very local scale. The  local effect of lightning is what has the most impact on people. In the event of a thunderstorm, an increase in lightning frequencies places areas with high concentration of trees at high-risk of forest fire. Such areas in Canada are West-Central and North-western woodland areas where they pose as major targets for ignition by lightning. In fact, lightning accounted for 85% of that total area burned from 1959-1999. To preserve habitats for animals and forests for its function as a carbon sink, strenuous pressure on the government must be taken to ensure minimized forest fire in the regions. With 21st century estimates of increased temperature, the figure of 85% of area burned could dramatically increase, burning larger lands of forests. This is attributed to the rise of temperatures simultaneously as surfaces dry, producing more “fuel” for the fires.

Although lightning has negative effects on our climate system and the people, lightning also has positive effects on earth and for life. The ozone layer, located in the upper atmosphere, prevents ultraviolet light from reaching earth’s surface. Also, lightning causes a natural process known as nitrogen fixation. This process has a fundamental role for life because fixed nitrogen is required to construct basic building blocks of life (e.g. nucleotides for DNA and amino acids for proteins).

Lightning is an amazing and natural occurrence in our skies. Whether it’s a sight to behold or feared, we’ll see more of it as our earth becomes warmer.

This week, I’m featuring some of the best blog posts written by the students on my first year undergraduate course, PMU199 Climate Change: Software, Science and Society. The first is by Terry, and it first appeared on the course blog on January 28.

A couple of weeks ago, Professor Steve was talking about the extra energy that we are adding to the earth system during one of our sessions (and on his blog). He showed us this chart from the last IPCC report in 2007 that summarizes the various radiative forces from different sources:

Notice how aerosols account for most of the negative radiative forcing. But what are aerosols? What is their direct effect, their contribution in the cloud albedo effect, and do they have any other impact?

More »

Ever since I wrote about peak oil last year, I’ve been collecting references to “Peak X”. Of course, the key idea, Hubbert’s Peak applies to any resource extraction, where the resource is finite. So it’s not surprising that wikipedia now has entries on:

And here’s a sighting of a mention of Peak Gold.

Unlike peak oil, some of these curves can be dampened by the appropriate recycling. But what of stuff we normally think of as endlessly renewable:

  • Peak Water – it turns out that we haven’t been managing the world’s aquifers and lakes sustainably, despite the fact that that’s where our freshwater supplies come from (See Peter Gleick’s 2010 paper for a diagnosis and possible solutions)
  • Peak Food – similarly, global agriculture appears to be unsustainable, partly because food policy and speculation have wrecked local sustainable farming practices, but also because of population growth (See Jonathan Foley’s 2011 paper for a diagnosis and possible solutions).
  • Peak Fish – although overfishing is probably old news to everyone now.
  • Peak Biodiversity (although here it’s referred to as Peak Nature, which I think is sloppy terminology)

Which also leads to pressure on specific things we really care about, such as:

Then there is a category of things that really do need to peak:

And just in case there’s too much doom and gloom in the above, there are some more humorous contributions:

And those middle two, by the wonderful Randall Monroe make me wonder what he was doing here:

I can’t decide whether that last one is just making fun of the the singularity folks, or whether it’s a clever ruse to get people realize Hubbert’s Peak must kick in somewhere!