Thursday, March 26, 2015

GHCN Monthly data portal

I am planning to add station data to the GHCN V3 monthly portal. Not monthly data which would be cumbersome, but annual average. This is useful for plotting and trends.

There is a trial below. Each link leads to the NOAA GHCN station summary, as before, but the radio button brings up a page with a table of the annual averages, along with a brief metadata and a map (the station is in the middle). There is a table for unadjusted data, and below for adjusted. Both are then repeated in CVS format, for import into Excel. The table of links is searchable (Ctrl-F), and can take a while to load. I'll probably add a graphing and trend calculation capability.

Update - I see there is a browser issue. The new window shows in Firefox and Chrome, but not  IE. Safari seems OK, but takes a long time to load. Working on it.Fixed

Friday, March 20, 2015

Central Australian warming

I've been arguing again, at Climate Etc. Blogger Euan Mearns has a guest post in which he claims to demonstrate that stations within 1000km of Alice Springs show no warming.

I'll post about it here, because it illustrates the averaging fallacies I've been writing about regarding Steven Goddard and colleagues (also here). And also because "Alice Springs" is one of those words naysayers sometimes throw at you as if no further explanation is required (like Reykjavik). People who do that generally don't know what they are talking about, but I'm curious, since I've been there.

There are actually two issues - the familiar time series of averages of a varying set of stations, and anomalies not using a common time base. I'll discuss both.

Tuesday, March 17, 2015

February GISS up 0.04°C

late news, but I've already posted twice on February temp. This is the regular post comparing GISS with TempLS.

GISS rose from 0.75°C in Jan to 0.79°C as predicted by Olof and JCH. TempLS also rose by a small amount. Troposphere measures showed a small decline.

Friday, March 13, 2015

February TempLS was warm

China GHCN data was late, but is now in (report here). The global average temperature was 0.694°C, slightly up from Jan 0.674. A small rise, but January had already tied May 2014, which was the hottest month of last year. So it's a warm start to 2015. The last month warmer than Feb was Nov 2013.

 The map is pretty simple. A big warm band across Russia and NE Europe. Cold in E N America, but warm in the W and Akaska.

Tuesday, March 10, 2015

Derivatives and regression again

I've been writing about how a "sliding" trend may function as a estimate of derivative (and what might be better) here, here, here and here. There has been discussion, particularly commenter Greg. This post just catches up on some things that arose.

Thursday, March 5, 2015

Klotzbach revisited

Not a perfect title; it's actually my first comment on the 2009 GRL paper by Klotzbach, Pielke's, Christy et al. It was controversial at the time, but that was pre-Moyhu, or at least in very early days. And I hadn't paid it much attention. But it surfaced again today at Climate Etc, so I thought I should read it.

The paper is very lightweight (as contrarian papers can be). It argues that observed surface trends since 1979 actually exceed troposphere trends, as measured by the UAH and RSS indices, which CMIP etc modelling suggests that the troposphere should warm faster.

Now for global you can simply get those trends, and many more, with CIs from the Moyhu trend viewer. You might say, well, figuring out what the models said should be rated substantial. But they way oversimplified, were corrected at Real Climate (Gavin) and had to publish a corrigendum. There has been more discussion then and over the years. Here, for example, is a post at Climate Audit, with Gavin participating. But the audit didn't seem to pick up the CI issue, though other methods were discussed. Later a Klotzbach revisited WUWT post (my title echoes) two years ago; more on that from SKS here. And now another update.

But what no-one, AFAICS, has noticed is that the claims of statistical significance are just nuts. And significance is essential, because they have only one observation period. The claim originally, from the abstract, was:
"The differences between trends observed in the surface and lower-tropospheric satellite data sets are statistically significant in most comparisons, with much greater differences over land areas than over ocean areas."
I've noticed that the authors are quieter on this recently, and it may be that someone has noticed. But without statistical significance, the claims are meaningless.

Update: I think that the CI's they are quoting may relate to a different calculation. They computed the trends in Table 1, with CI's, and in Table 2 the differences. They say in the abstract that these are differences of trends, but the heading of Table 2, which is not very clear, could mean that they are computing the trends of the differences (a new regression) and giving CI's for that. That is actually a reasonable thing to do, but they should make it clear. I have got reasonably close to their numbers for comparisons with UAH, but not with RSS; it may be that the RSS data has changed significantly since 2009.

I'll describe this in more detail below the jump.

Tuesday, March 3, 2015

Early comment on global February

According to my NCEP/NCAR based index, February was globally pretty warm. Very warm indeed around the 12th, but a cool start and finish. The hotspot was Central Asia/Mongolia (daily eyeballing estimate). It ended up just a little cooler than October, which after May was warmest in 2014.

 I'll have a TempLS surface report in a few days.
Update. Preliminary TempLS (7 mar) is very warm indeed. In fact, warmest month ever (since 1900). But Canada, Australia, China, India still to come. Very warm in Russia and N and E Europe. Cold in E US/Can.
Update 8 Mar. Canada, Australia, India are in. Canada was cold.  TempLS has come back to 0.7,  below warmest ever  (March 2010 at 0.737°C). Still, since 2010 only Nov 2013 has been warmer, and only slightly. There is a little more data to come.