Wednesday, August 31, 2011

JAXA Ice extent and JS

Everyone's eyes seem to be on the progress of the Acrtic ice melt. I've been posting daily data and plots here from the IJIS Site. I include an expanded section of the current region. However, there are different time regions that peoiple might like to look at more closely (eg September), and rather than a lot of different plots, I thought a JS-enhanced interactive plot might help. I'll use it on the daily site, but you can try it here.

There is an extra legend, top middle, describing four different time periods. Just click on the one you want to see.

Tuesday, August 16, 2011

A Javascript worldview for surface temp.

You may have noticed that I generally prefer simple spherical (orthographic) projections for displaying global fields. Even though it takes several projections to convey all the information.

But I use lat/lon maps for comparisons, and more recently, Hammer projections for comparison with NOAA and MP.

Spherical projections take up space, but this can be resolved by creating a poor man's Google Earth (OK, GE is free) with Javascript. In the plot below, of the July temperature data using GISS's colors and baseline (1951-80), you'll see a pattern of squares, top left. This corresponds to eight views. The directions are as if the earth was encased in a cube, with one apex above the N pole. The views are from the directions of the eight corners. N Pole is the square at the top, the next three are around near the Tropic of Cancer, etc. Just click - the red square marks where you are.
Picture below the jump

Sunday, August 14, 2011

GISS spatial map, July 2011

I said I'd compare the GISS spatial map for July 2011 with the TempLS fitted spherical harmonic version when the GISS map appeared. That has now happened. The patterns are similar, though TempLS seems to be somewhat warmer. That is partly because of the smoothing - some of the cold spots are localised, and tend to get smoothed over. Anyway, pictures below the jump.

Saturday, August 13, 2011

Comparisons of TempLS with reader MP's July 2011 plots.

In previous posts I've described the TempLS reconstruction of July 2011 global surface temperature. I noted also the new GISS average, and said that a comparison of the spatial plot would await GISS posting.

Commenter MP has been producing very impressive spatial plots using a Matlab script. I posted his movie of recent UAH LT temperatures here. In comments below you'll find the stills, and a wealth of other images linked by MP.

He has also done plots of GISS results, using GISS gridded data. I'll show below the jump his plots, and my spherical harmonics based reconstruction for comparison.

GISS July temp up 0.09°C.

The NASA GISS surface temp average anomaly for July is out - up 0.09°C, from 0.51°C to 0.60°C. Updated plot here. The TempLS calc gave a 0.003°C rise.

So far no spatial plot available - when it is I'll compare that with TempLS.

Thursday, August 11, 2011

Global surface temp for July - no change.

OK, that's the new TempLS result. The other surface indices haven't reported yet. Here is the plot comparing indices for the last four months, with all index anomalies relative to 1979-2000. Update - the linked image here is periodically updated, so it shows new figures as they arrive. GISS for July has been added.

And here is how the warmth was spread around:

Update - I haven't been properly clear here on anomaly bases. For the time series plots I used 1979-2000, so I could plot them all on one graph. For the spatial plot, I actually used the default - the average for the whole period, which was 1960-2011. Since I'm using GISS colors, it would be better to use the GISS period which is 1951-80. That will require exrending the calc back 10 years. It doesn't make much difference to the color plot; the change will be small relative to the range of monthly means, and one could simply adjust the color scale zero, leaving the plot unchanged.

There's a lot more to say about how this was done. Obviously, I'm using fairly early information. But the coverage is pretty good. We'll soon see how it holds up against the major indices. Details below the jump.

Tuesday, August 2, 2011

Global surface temperature coverage.

Global surface temperature coverage.

There have been articles in the blogosphere in recent years with titles something like "the dying of thermometers", and showing a plot something like this on the variation of GHCN stations over the years.

Raw station numbers aren't a good guide. GHCN was originally a grant-funded archiving exercise. It did not focus on even coverage - they largely archived what was available. The ongoing version of GHCN (since the mid 90's) relies on the submission of CLIMAT forms by countries, and this seems to be rationalised by area.

I was looking into the statistics of the cell weighting schemes I described in the previous post, and realised that these provided a good quantification of coverage over the years. In cell weighting I divide the surface into cells and calculate the number of stations reporting in each cell in each month. Empty cells represent coverage failure, so I've catalogued their occurrence. They are therefore a measure of coverage over time. Below the jump, I'll show how the global coverage of CRUTEM3, GHCN and HADSST2 has varied over the years. It has been generally improving.

Monday, August 1, 2011

Cell weighting schemes for the Earth.

I referred in my CRUTEM3 based reconstruction to two separate weighting schemes, involving dividing the Earth into cells in two different ways. I'll say more about that here. It also tells more about the strengths and weaknesses of the CRUTEM3 data set.

First TempLS CRUTEM3 reconstructions.

I've run TempLS V2.2 reconstructions using recently released CRUTEM station data. I've written about the station data here and here.

There are many comparisons I could do. For this post, I'll start by comparing the already published CRUTEM3 averages with the GISS equivalent. Then I'll show monthly averages calculated direectly (by TempLS) from the new data, compared with the published averages. Personally, I think the land/sea averages are much more significant, so I'll show the corresponding results there, using HADSST2 data.

As a general observation, I would say that my land reconstruction tracks fairly well, but rises significantly over the last decade. The TempLS calc makes no adjustments for UHI or anything else. The Land/Sea average shows the same tendency, but much less so.
Update - Steven Mosher has posted his RghcnV3 reconstruction from CRUTEM3 data, which showed similar recent variations,

All anomaly plots are set to a 1961-90 base period. I have used two weighting methods. Method 2 is just by inverse station density calculated from 5x5 lat/lon "rectangles". Method 0 is calculated using equal area rectangles, equivalent to 5x5 at the equator. This method, new in V2.2, is intended to be used with a scheme to redistribute weighting when cells are empty. That actually gave results which were noticeably different. I think it is actually the right thing to do, so the differencemay well be an improvement, but I need to check more to see that it isn't just a mistake.