Climate Change 2013

[frayadjacent]

The UN Intergovernmental Panel on Climate Change is in the midst of releasing its 5th assessment report on climate change, impacts, and mitigation.  The group that focuses on the physical science of climate change has produced a video summarizing this year's report.

"Climate Change 2013: The Physical Science Basis" (Watch on YouTube)

And here's a nice video visualizing some of the main conclusions from that report:

"Climate change the state of the science (data visualization)" (Watch on YouTube)

Some climate and global warming-related websites that I like:

• Skeptical Science: compares the arguments of global warming "skeptics" to what the peer-reviewed literature says.
• Real Climate: a general climate blog.  I'd say it's unintentionally geared toward people with some science background, though not necessarily climate science. 
• Climate and Capitalism: for my fellow left-wing weirdos.  :)

Comments

[frayadjacent]

awesome! And no, I don't think I've ever mentioned it before. :)

I study clouds and cloud feedbacks. Errors and uncertainties in clouds is the biggest source of uncertainty in climate projections. Climate models that produce a strong warming response to greenhouse gas increases have strong positive cloud feedbacks; one of the effects of global warming in these models is to change clouds in a way that amplifies the warming. on the other hand, climate models that produce a weak warming response tend to be the ones with negative or weakly positive cloud feedbacks, so the warming causes either little change in clouds or causes clouds to change in a way that partially offsets the greenhouse gas warming.* there are of course other differences among climate models, but that's the single greatest contributor to the range of global average warming that different models produce.

there isn't really an a priori way to know which models are most correct. the main approach is to try to improve how well models simulate the current climate and to do so for the right reasons, ie reasons grounded in physical understanding. but there are some major and persistent problems, e.g., most models don't produce enough clouds over the southern ocean, with pretty profound effects on the global energy balance. I was hired to work on that problem, specifically improving clouds over the southern ocean in a particular climate model.

*I'm happy to explain this further if you want, though I'm trying not to blather on too long about stuff you might already know or aren't that interested in!

[luzula]

Interesting! I have not worked much with mathematical modeling, but I would have guessed that you'd use historical data to see if the model works or not? I mean, there must be data for cloud cover for years back, right? Of course that wouldn't guarantee it predicted the future well. Is it that it's hard to take into account what will happen with higher greenhouse gas levels?

I like cloud-watching, and I've had to learn the different cloud types for my summer job, where I have to write down cloud types and coverage morning and evening. We can get some pretty cool altocumulus lenticularis clouds up there, for example. They look like giant UFO:s. *g*

[frayadjacent]

Yeah, for clouds we use satellite data, which of course has problems, for example trouble detecting low clouds if there are high clouds above them. But clever people who know a lot more about instrumentation than I do are always coming up with new ways to deal with this.

I'm actually not that good at cloud identification! I've gotten a bit better, it's definitely something that comes with practice. Lenticular clouds are awesome -- I even iconned em! :)