In a previous post I described how a global index could be created simply by integrating the surface temperature data provided by NCEP/NCAR. This data is to within last few days, and I've described here how numerical data is maintained on the latest data page.
As gridded data, I then sought to display the daily temperature anomalies (base 1994-2013) with WebGL, and that is shown here. I'm also planning to maintain this, on the latest data page if it does not drag out loading. Currently the daily data is just for 2014, although that is easily extended.
So it's below the fold. As usual, the Earth is a trackball that you can drag, zoom (right mouse) and orient (button). I'm trying a new way of choosing dates. High on right there is a tableau of small squares, each representing one day. Click on this to choose. It's all a bit small, but to the left of the Orient button, you'll see printed the date your mouse is on. So just move until the right day shows, and click.
Because temperature ranges are large, it has been quite hard to get the colors right. You might like to look at the recent North American cold spell for shades of blue. Incidentally, I see that the global average has slipped again, so November looks like a much cooler month than recently.
Great job! Any chance it is possible to append a calculated global anomaly for each day to go along with the widget?
ReplyDeleteDK, for the current month, that's on the table here. But yes, I'll try to include it in the map version.
DeleteThank you!
DeleteNick, back in April I was able to download your entire NCEP/NCAR daily global temperature anomaly data set, which I compared to the daily data since 2014 that I have downloaded from UM CCI. I came back to update my spreadsheet and now I can only find the NCEP/NCAR daily data for the last month. I would like to fill in the mid-April to mid-May gap in what I have downloaded. Do you still have the full daily data set online (or at least all of 2016 so far)?
ReplyDeleteInterestingly, I found in comparing the two data sets over 2014-2016 that the UM CCI anomaly estimates referenced to 1979-2000 visually (by graph) match very well your NCEP/NCAR anomaly estimates referenced to 1994-2013, without any adjustment for the different reference periods. I was a bit surprised to see this. It may simply be an artifact of the reference period difference being to small to detect visually within the "noise" between the two sets of estimates (I have not looked at the differences statistically). This comparison is somewhat like a precision check, but tells us little about the accuracy. It is my understanding that the NCAR/NCEP approach uses a more coarse grid than the UM CCI approach for the reanalyses, so the comparison is not quite apples to apples in that regard and the resolution difference might account for the "noise" in the comparison.
Bryan,
DeleteI keep the updated (daily) data zip file here. I'll put a link on the data page.
About the unexpected matching of the two data sets, I think the reason may be that CSFR had the version change in 2011, and I think older values are warm relative to present, so 1971-2000 would appear as a base comparable to 1994-2013 in NCEP/NCAR. I don't have much faith in NCEP homogeneity either.
please can u include Beirut station ?? OLBA
ReplyDelete