In the last session yesterday, Inez Fung gave the Charney Lecture: Progress in Earth System Modeling since the ENIAC Calculation. But I missed it as I had to go pick up the kids. She has a recent paper that seems to cover some of the same ground, and allegedly the lecture was recorded, so I’m looking forward to watching it once the AGU posts it. And this morning, Joanie Keyplas gave the Rachel Carson Lecture: Ocean Acidification and Coral Reef Ecosystems: A Simple Concept with Complex Findings. She also has a recent paper covering what I assume was in her talk (again, I missed it!). Both lectures were recorded, so I’m looking forward to watching them once the AGU posts them.
I made it to the latter half of the session on Standards-Based Interoperability. I missed Stefano Nativi‘s talk on the requirements analysis for GIS systems, but there’s lots of interesting stuff on his web page to explore. However, I did catch Olga Wilhelmi presenting the results of a community workshop at NCAR on GIS for Weather, Climate and Impacts. She asked some interesting questions about the gathering of user requirements, and we chatted after the session about how users find the data they need (here’s an interesting set of use cases). I also chatted with Ben Domenico from Unidata/UCAR about open science. We were complaining about how hard it is at a conference like this to get people to put their presentation slides on the web. It turns out that some journals in the geosciences have explicit policies to reject papers if any part of the results have already been presented on the web (including in blogs, powerpoints, etc). Ben’s feeling is that these print media are effectively dead, and had some interesting thoughts about moving to electronic publishing, althoug we both worried that some of these restrictive policies might live on in online peer-review venues. (Ben is part of the THREDDS project, which is attempting to improve the way that scientists find and access datasets).
Down at the ESSI poster session, I bumped into Peter Fox, whom I’d met at the EGU meeting last month. We both chatted to Benjamin Branch, about his poster on spatial thinking and earth sciences, and especially how educators approach this. Ben’s PhD thesis looks at all the institutional barriers that prevent changes in high school curricula, all of which mitigate against the nurturing of cross-disciplinary skills (like spatial reasoning) necessary for understanding global climate change. We brainstormed some ideas for overcoming these barriers, including putting cool tools in the students hands (e.g. Google Maps mashups of interesting data sets; or idea that Jon had for a Lego-style constructor kit for building simplified climate models). I also speculated that if the education policy in the US prevents this kind of initiative, we should do it in another country, build it to a major success, and then import it back into the US as a best practice model. Oh, well, I can dream.
Next I chatted to Dicky Allison from Woods Hole, and Tom Yoksas from Unidata/UCAR. Dicky’s poster is on the MapServer project, and Tom shared with us the slides from his talk yesterday on the RAMADDA project, which is intended as a publishing platform for geosciences data. We spent some time playing with the RAMADDA data server, and Tom encouraged us to play with it more, and send comments back on our experiences. Again, most of the discussion was about how to facilitate access to these data sets, how to keep the user interface as simple as possible, and the need for instant access – e.g. grabbing datasets from a server while travelling to a conference, without having to have all the tools and data loaded on a large disk first. Oh, and Tom explained the relationship between NCAR and UCAR, but it’s too complicated to repeat here.
Here’s an aside. Browsing the UCAR pages, I just found the Climate Modeller’s Commandments. Nice.
This afternoon, I attended the session “A Meeting of the Models“, on the use of Multi-model Ensembles for weather and climate prediction. First speaker was Peter Houtekamer, talking about the Canadian Ensemble Prediction Systems (EPS). The key idea of an ensemble is that it samples across the uncertainty in the initial conditions. However, challenges arise from the incomplete understanding of the model-error. So the interesting questions are how to sample adequately across the space, to get a better ensemble spread. The NCEP Short-Range Ensemble Forecast System (SREF), claimed to be the first real-time operational regional ensemble prediction system in the world. Even grander is TIGGE, in which the output of lots of operational EPS’s are combined into an archive. The volume of the database is large (100s of ensemble members), and you really only need something like 20-40 members to get converging scores (he cites Talagrand for this) (aside: Talagrand diagrams are an interesting way of visualizing model spread). NAEFS combines 20-member American (NCEP) and 20-member Canadian (MSC) operational ensembles forecasts, to get a 40-member ensemble. Nice demonstration of how NAEFS outperforms both of the individual ensembles from which it is constructed. Multi-centre ensembles improve the sampling of model error, but impose a big operational cost: data exchange protocols, telecommunications costs, etc. As more centres are added, there are likely to be diminishing returns.