Tuesday, September 16, 2014

August GISS Temp up by 0.18°C

GISS has posted its August estimate for global temperature anomaly. It rose from 0.52°C in July to 0.7°C in August. TempLS rose by 0.1°C, which I commented was in line with the rise in SST. GISS once again is jumpier, and like TempLS is back to the high levels of April/May.

The comparison maps are below the jump.

Monday, September 15, 2014

Trend Map to show why Cowtan&Way is needed.

Nearly a year ago, Cowtan and Way published an important paper on modifying HADCRUT 4. HADCRUT is a global index put out by the UK Met Office and UEA. It uses gridding, and has many grid cells which have no data. These are just not included in the average. The arithmetic effect of this is that the empty cells are given the value of the remaining cells in the average, which for HADCRUT is the hemisphere average.

Normally this might not matter much, because the missing areas are on average, average. But recently the Arctic, with much missing area, has been warming rapidly, and HADCRUT has been missing that. One C&W remedy was to use kriging interpolation. Another was to make a hybrid with UAH satellite tropospheric measures, which covers lot of the missing region. Importantly, they got similar results, with a trend that seemed to allow properly for the Arctic warming.

I wrote follow-up posts on C&W here, here and here. One observation was that latitude averaging would be better than hemispheric, since infilling with the latitude average was likely to be closer. And that gave results somewhat similar to C&W.

I'm going to develop this. But meanwhile, I want to show visually just what C&W does. I have made a WebGL active plot, which shows with shading the trends over various user-chosen time intervals. For HADCRUT, I explicitly infilled cells with the Hemisphere average. I show C&W with kriging - no infill is needed. So areas with little data will show with the hemisphere average trend. With WebGL it is inonvenient to color cells as rectangles, so I have used shading. The plot and discussion are below.
Update: I have converted to showing grid cells as rectangles, which I think is clearer

Thursday, September 11, 2014

Extended Trend Viewer

I have been maintaining regularly an active trend viewer. A reduced image looks like this:

The triangle shows with color shading the trend from any starting year to end year, in a range that you can choose (from 1999, 1989, 1960 or 1900 to now). There are settings that show just trend, trend with significance masked, or CI's (upper or lower) or t-values. And there are now 15 datasets - monthly temperature series.

Each triangle has an accompanying plot of the time series. The active aspect is that you can choose a time range, and numerical information about the trend will be shown, and colored markers will show the trend line on the graph. You can choose either by clicking in the triangle, or using controls in the graph.

I have now added four new data sets. They are from Cowtan and Way, BEST Land/Ocean, NOAA SST, and a new TempLS set. I'll describe each in detail, and give links to the sources.

Wednesday, September 10, 2014

TempLS global temp up 0.1°C in August

TempLS rose in August; from 0.515°C (July) to 0.613°C. This largely reflects the strong rise in SST. It's often forgotten that a land/ocean index is mostly SST. Anyway, TempLS is back up to about where it was in May. The tropospheric indices went down by a little over 0.1°C.

Saturday, September 6, 2014

Fragility of the "pause"

This post relates to a technical meaning of the pause, often dwelt on on skeptic sites. Some number of years for which the global temperature trend to present has been negative or zero. Of course the pause itself should be more broadly defined as a period where the trend is substantially less than some expected value. But the zero trend seems to attract people, so I thought some prognosis of it might be interesting.

Actual zero trend tends to get mixed up with trend not significantly different from zero. I'll stay away from the latter as I think it is a misuse of statistical significance (SS). If you have SS, you can infer something. If you don't, you can only infer that a test has failed. Maybe too much noise; maybe an inadequate test.

Werner Brozek runs monthly articles at WUWT. He looks at a variety of indices, and notes the number of years of zero trend. He also looks at SS tests, which I think are misplaced. Anyway, something is happening there. The pause given by most indicators is shrinking.

Lord Monckton runs monthly posts with titles like Global Temperature Update – No global warming for 17 years 11 months. He is always referring to the MSU-RSS index, which is not surface, but lower troposphere. Dr Spencer, who manages the other LT index from UAH, wrote about how UAH and RSS are diverging, and advised:
"But, until the discrepancy is resolved to everyone’s satisfaction, those of you who REALLY REALLY need the global temperature record to show as little warming as possible might want to consider jumping ship, and switch from the UAH to RSS dataset."
Lord M is following that advice, as we shall see. Indeed, from 18 years ago to present, RSS has zero trends. But as you'll see below, all other indices have trends from 0.5°/Century to 1°/Century. No 18 year pause there.

Anyway, I took a number of indices (most sources, graphs and some tables here), and plotted for each index the trend from time x in the past to now (July 2014). I've plotted the last 18 years, to match Lord M, skipping post-2012 since short trends are large and variable and mess up scales. Here is a resulting plot:

The skeptic convention is that the pause goes back to the earliest crossing of the x axis. So for example HADCRUT 4 would be "paused" since about 2001, and you can see Lord M's 18 years for RSS. You can also see why he likes RSS. It really is an outlier. Interestingly, UAH is almost an outlier in the other direction, with a pause of about six years. The surface measures are fairly consistent.

Thursday, September 4, 2014

SST alarmism - seas are warm

I was reading Bob Tisdale at WUWT, an article titled: "Alarmism Warning – Preliminary Monthly Global Sea Surface Temperatures at Record High Levels".
With explanation: "An “alarmism warning” indicates alarmism is imminent."
And continuing:
"We’re not just talking a record high for the month of August…we’re talking a record high for any month during the satellite era."

Now I'm always anxious to alert readers to imminent alarmism, so I advise reading Bob warily. But I thought I should find out more, and as usual, Bob has an impressive pile of graphs. Here's my take.

Bob breaks it down into regions, emphasising the North Pacific as the standout for warmth, with North Atlantic second. For good detail on that, Moyhu has a WebGL plot (choose your day), and for the N Pacific (and elsewhere), current movies. But I'm more interested in the global SST.

Actually, Bob's plots there are comprehensive. But I'd like to show longer and shorter scales, and a comparison with Hadcrut 4 surface temp and UAH lower troposphere. So here is a composite plot. You can switch between year ranges (1850-now, 1980-now, and 2005-now) and smoothing (none, running annual mean). For all but the longest range, NOAA SST means OI SST, anomaly relative to 1971-2000, and includes August 2014. For the long range, it is this file.

Saturday, August 30, 2014

TempLS and NOAA are converging

TempLS is a program for (mostly) global average temperature indexing, which I wrote in 2010. It used a least squares linear model approach (described here) which has since been taken up by BEST. Here is a description of the early development.

For over three years I have now been using TempLS to calculate every month an average, based on newly announced values of GHCN V3 unadjusted and ERSST. I aim to get the new index out before the majors, to test its predictive skill. I then write up a comparison with GISS, which is usually the next to come out. I also track them with graphs and numbers at the Latest Data page.

In December 2012 I wrote a review of the first seventeen months, and how well other indices had correlated with TempLS and with each other. TempLS fitted in to the general picture quite well, but had been particularly close to the NOAA index. This is not surprising because I use GHCN and ERSST, as does NOAA, although I use the unadjusted GHCN.

I have been thinking of updating this review, but in the meantime I had noticed something odd. The NOAA index and TempLS have been coming very close indeed (both curves bold):