Data Comparisons

Place Holder: Table of Runs from AR4.

13 Comments

I’m going to be posting a few placeholder articles. There is no particular message in these, I’m just keeping track of some information for myself, and this is as convenient a place as any.

Today’s placeholder just compares tallies of SRES a1b runs at “The Climate Explorer” to the number listed on IPCC AR4 Table 10.1.

Here’s the table showing the number of runs for each scenario in the AR4

Figure 1:Table of AR4 Runs
Table of AR4 Runs

It’s possible to download most of these at
The Climate Explorer.

However, at the present time there are a few discrepancies for the SRES A1B cases:

  1. The IPCC lists 5 runs for GISS-ER. The GUI at The Climate Explorer permits you to download 1 run.
  2. The IPCC lists 7 runs for ncar_ccsm. The GUI at the climate explorer lists 5; when used, you can only download 3.
  3. The Climate Explorer permits users to download 1 run for ECHAM4 and 1 run for csiro_mk 3.5. Neither are on the table shown above.

I may be referring back to this after GISS and NOAA update their anomaly pages. 🙂

Update

I wanted to see if the data missing at “The Climate Explorer” is available at PCMDI. I fiddled around, found their “search” page, checked GISS-ER: They are available: giss_model_e_r sresa1b. So, at least I should be able to get them there. (The data at PCMDI are gridded. So, for the time being, I’m going to see if The Climate Explorer might sort out their issues.)

13 thoughts on “Place Holder: Table of Runs from AR4.”

  2. Hi Vincent–
    I read that. I think it’s interesting, but I have no particular views. I honestly don’t know what a “typical” climate model might have predicted for the Antarctic. (I know someone familiar with the literature would probably find a range of predictions and so be able to show whatever happened was “predicted”.

    The reason I focus on GMST is the IPCC broke down gave us the closest thing to concrete predictions for that. Most other things are so qualitative as to be nearly impossible to compare to later events.

  3. If you can’t get the issues with climate explorer ironed out, you could always write something in R to process the gridded data. That’s what I had to do before I found climate explorer. A bit annoying, but pretty straight forward.

  4. Chad– Yes. I checked and the data is available at PCMDI. I don’t use R, but averaging using other languages is not a problem. I’d just prefer if the climate explorer had it posted. I suspect they intend to be a complete set, so I figured I’d ask them. They might end up sorting it out. Less work for me. 🙂

  8. Lucia check with gavin. I recall when I looked at this stuff that there were notes about ModelE basically indicated that some results were stored at a different location.. There was a list of model errata ( some interesting errors noted there) I cannot remember where this was, sorry I’m usually pretty good about this, but asking gavin is the best bet.

  9. Pingback: Gavin Spins with Spaghetti Diagrams! | The Blackboard

  11. Sekerob (Comment#7295) December 17th, 2008 at 2:13 pm,

    Further analysis indicates the error in Jeff’s analysis was nowhere near that large, if in fact there was an error at all. The bootstrap version 2 data shows no significant shift in 1987, so correction for the change in the size of the observation hole must already be included in the data.

    The anomaly is -0.4 Mm2 out of 21 Mm2 total, btw, and is well within the range of variation observed from 1979 to 2000. Since the Antarctic sea ice always melts rapidly at this time of year, what does that have to do with the current global anomaly or its trend?

  12. If you write about the Climate Explorer “They might end up sorting it out.” please note that it is not “they”, but just me alone, on top of my real work, trying to be of service to climate researchers. A good way to say “thank you” is to acknowledge use of the Climate Explorer, and to cite one of the articles listed on the web site when you publish results for which you used it. That way I can justify to my boss the 10% of my time I spend on it (mainly Friday afternoons, evenings and commutes).

  13. Thanks Greet! Yes, now I know it’s just you. You’ve been a big help. I think your site is going to get more popular. With luck, we’ll get people to publish results in real journals.

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