Saturday, November 22, 2014

Update on 2014 warmth.

A month ago I posted plots to see whether some global indoces might show record warmth in 2014. The troposphere indices UAH and RSS are not in record territory. But others are. NOAA has just come out with an increased value for October, so a record there is very likely. The indices here all improved their prospects in October. HADCRUT is still to come.

In the previous post, I noted that the reanalysis data for November showed a considerable dip mid-month, corresponding to the North America freeze. November will probably be cooler than October - my guess is more like August.

Plots are below. NOAA and HADCRUT look very likely to reach a record, and also the TempLS indices. Cumulatively GISS is currently just above the 2010 average, but warm months are keeping the slope positive.

Update - just something I noticed. About 3 months ago I commented how closely NOAA and TempLS were tracking. TempLS has since produced a new version, mesh-based, which tracks GISS quite closely. But the relation between old TempLS, now called TempLS grid, and NOAA is still remarkably close. Last month, both rose by 0.042°C. The previous month, small rises - TLS by 0.012 and NOAA by 0.014.

Tuesday, November 18, 2014

A "new" surface temperature index (reanalysis).

I've been looking at reanalysis data sets. These provide a whole atmosphere picture of recent decades of weather. They work on a grid like those of numerical weather prediction programs, or also GCM's. They do physical modelling which "assimilates" data from a variety of sources. They typically produce a 200 km horizontal grid of six-hourly data (maybe hourly if you want) at a variety of levels, including surface.

Some are kept up to date, within a few days, and it is this aspect that interests me. They are easily integrated over space (regular grid, no missing data). I do so with some nervousness, because I don't know why the originating organizations like NCAR don't push this capability. Maybe there is a reason.

It's true that I don't expect an index which will be better than the existing. The reason is their indirectness. They are computing a huge amount of variables over whole atmosphere, using a lot of data, but even so it may be stretched thin. And of course, they don't directly get surface temperature, but the average in the top 100m or so. There are surface effects that they can miss. I noted a warning that Arctic reanalysis, for example, does not deal well with inversions. Still, they are closer to surface than UAH or RSS-MSU.

But the recentness and resolution is a big attraction. I envisage daily averages during each month, and WebGL plots of the daily data. I've been watching the recent Arctic blast in the US, for example.

So I've analysed about 20 years of output (NCEP/NCAR) as an index. The data gets less reliable as you go back. Some goes back to the start of space data; some to about 1950. But for basically current work, I just need a long enough average to compute anomalies.

So I'll show plots comparing this new index with the others over months and years. It looks good. Then I'll show some current data. In a coming post, I'll post the surface shaded plots. And I'll probably automate and add it to the current data page.

Sunday, November 16, 2014

October GISS unchanged, still high

GISS has posted its October estimate for global temperature anomaly. It was 0.76°C, the same as the revised September (had been 0.77°C). TempLS mesh was also almost exactly the same (0.664°C). TempLS grid, which I expect to behave more like HADCRUT and NOAA, rose from 0.592°C to 0.634°C.

The comparison maps are below the jump.

Saturday, November 15, 2014

Lingering the pause

As I predicted, the Pause, as measured by periods of zero or less trend in anomaly global temperature, is fading. And some, who were fond of it, have noticed. In threads at Lucia's, and at WUWT, for example.

Now I don't think there's any magic in a zero trend, and there's plenty of room to argue that trends are still smaller than expected. Lucia wants to test against predictions, which makes sense. But I suspect many pause fans prefer their numbers black and white, and we'll hear more about periods of trend not significantly different from zero. So the pause lingers.

We already have. A while ago, when someone objected at WUWT to Lord M using exclusively the RSS record of long negative trend, Willis responded
"Sedron, the UAH record shows no trend since August 1994, a total of 18 years 9 months."
When I and Sedron protested that the UAH trend over that time was 1.38°C/century, he said:
"I assumed you knew that everyone was talking about statistically significant trends, so I didn’t mention that part."

And that is part of the point. A trend can fail a significance test (re 0) and still be quite large. Even quite close to what was predicted. I posted on this here.

I think we'll hear more of some special candidates, and the reason is partly that the significance test allows for autocorrelation. Some data sets have more of that than others. SST has a lot, and I saw HADSST3 mentioned in this WUWT thread. So below the fold, I'll give a table of the various datasets, and the Quenouille factor that adjusts for autocorrelation. UAH and the SSTs do stand out.

Here is a table of cases you may hear cited (SS=statistically significant re 0):
DatasetNo SS trend since...PeriodActual trend in that time
UAHJune 199618 yrs 4 mths1.080°C/Century
HADCRUT 4June 199717 yrs 3 mths0.912°C/century
HADSST3Jan 199519 yrs 9 mths0.921°C/Century

These trends are not huge, but far from zero.

Wednesday, November 12, 2014

Seasonal insolation

This post was started by some recent posting at WUWT. It's about the expected thermal effect of the Earth's eccentric orbit. It produces a variable total solar insolation for the planet, which one might expect to be reflected in temperatures. A few days ago, Willis contrasted the small solar cycle fluctuation which this much larger oscillation, suggesting that if we couldn't detect the orbital effect then the solar cycle couldn't be much. And just now, Stan Robertson at WUWT took up the idea, looking for the eccentricity in annual global anomaly indices.

I've also wondered the effect of eccentricity. But when you think about anomalies, it is clear that they subtract out any annual cycle. So the effect can't be found there. And in fact it's going to be hard to disentangle it from axis tilt effect. A GCM could of course run alternatively with a circular orbit, which would determine it.

Anyway, someone posted a plot of average daily insolation against time of year and latitude. That is, at TOA, or for an airless Earth. I was surprised that the maximum for the year was at the solstice at the relevant Pole. I found a good plot and the relevant maths in Wikipedia. So I'll show that below the jump, with a brief version of the math, and a plot of variation with latitude at the solstice. It isn't even monotonic.

Monday, November 10, 2014

Update on GHCN and TempLS early reporting

About a month ago, I posted on a proposed new scheme for reporting monthly averages with a mesh version of TempLS. The idea was to report continuously as data (land source GCHN) came in. I wondered how reliable the very early estimates might be. I was quite optimistic.

So, wouldn't you know, November is the first month in my experience when GHCN didn't keep to their regular schedule. Normally there are daily updates from month start, with the largest in the first day or two. But this month, nothing at all until the 8th. Sure enough, my program faithfully produced an average (0.589°C) based on SST alone; it's been told now not to do that again.

Anyway, the data has arrived, and is up on the latest data page. October (with GHCN) was 0.664°C; almost exactly the same as September, which was pretty warm. For once, there was little cold in N America, and W Europe was warm. The main cold spot was Russia/Kazakhstan.

Saturday, November 8, 2014

GCM's are models

I'd like to bring together some things I expound from time to time about GCM's and predictions. It's a response to why didn't GCMs predict the pause? Or why can't they get the temperature right in Alice Springs?

GCM's are actually models. Suppose you were designing the Titanic. You might make a scale model, which, with suitably scaled dimensions (Reynolds number etc) could be a good model indeed. It would respond to various forcings (propellor thrust, wind, wave motion) just like the real boat. You would test it with various scenarios. Hurricanes, maybe listing, maybe even icebergs. It can tell you many useful things. But it won't tell you whether the Titanic will hit an iceberg. It just doesn't have that sort of information.

So it is with GCM's. They too will tell you how the Earth's climate will respond to forcings. You can subject them to scenarios. But they won't predict weather. They aren't initialized to do that. And, famously, weather is chaotic. You can't actually predict it for very long from initial conditions. If models are doing their job, they will be chaotic too. You can't use them to solve an initial value problem.