Monday, December 24, 2012

Merry Christmas, and plans for the New Year

Merry Christmas to all, and hopefully, relief from floods and snow. Different problems here.

Last year I produced a graphics gallery at Christmas, and I was hoping to have an update here. But there are some new things coming, so I'll do it when they are out. They are mostly to do with my new enthusiasm for large data sets selectively downloaded in response to user requests (via XMLHTTPRequest). I tried here combining the Google Maps survey of station with the machinery of the climate plotter. I'd like to do the same with the globe plots. I'll add globe plots of GHCN temperature for at least a century of year averages, and over decades, and combine that with the trend data to make a universal globe plot.

I'm also thinking about how to put monthly data in the climate plotter. There are issues about handling seasonality, and there are the mechanics of keeping it updated. But I think that can be mechanised.

I'll also do some analysis of the ISTI data when it is out of beta.

Wishing you all well for the New Year.

Saturday, December 15, 2012

November GISS Temp unchanged from October

This isn't breaking news - I'm running late this month. But I wanted to give the usual comparison with TempLS. The GISS land/sea monthly anomaly was 0.68°C September; October had been readjusted down to this after initially 0.69°C. Time series and graphs are shown here

As usual, I compare the previously posted TempLS distribution to the GISS plot.

Friday, December 14, 2012

Universal station locator and history plotter

This is next in the series of things that can be done with XMLHTTPRequest. It merges the capability of the Google Maps display of stations with the machinery of the climate plotter. But the key new thing is that the station location information can be backed up with a store of temperature histories, which can be plotted on demand.

So what we have is a map which allows you to choose a category of stations to show with markers. The usual Google Maps interactivity works. You can choose from different data sets - currently there are GHCN, CRUTEM 4 and the new (and beta) ISTI. BEST will be there soon [Update - it's there now]. Mouse over the markers shows the name. But if you click, you not only get station information as before, but a plot of the annual temperatures in the record (for that data set). You can add to the plot, to, say, compare the records of different data sets. Or you can compare GHCN adjusted with unadjusted, or stations at different locations. And you can smooth and regress. There is an information window that shows the numbers.

Wednesday, December 12, 2012

November TempLS Global Temp down 0.02°C

I see GISS has already posted (no change) - you have to be early to get ahead of them lately. But I'll produce the normal pair of posts with TempLS results and then comparison.

The TempLS analysis, based on GHCNV3 land temperatures and the ERSST sea temps, showed a monthly average of 0.52°C for November, down from 0.54 °C in October. I had reported 0.52 °C for October, but late data raised it a bit. These are small changes. There are more details at the latest temperature data page.

Below is the graph (lat/lon) of temperature distribution for November. I've also included a count and map of the stations that have reported to this date.

Saturday, December 8, 2012

TempLS correlation with other indices.

Since June 2011 I've been posting monthly TempLS global averages, before the other surface indices appear. The purpose of this haste is partly to see how well it performs in comparison, uninfluenced by "peeking". Here is a recent monthly comparison, with links to earlier months. I post the data here.

So it's now time for a review on how well TempLS tracks. Along the way, I found some interesting results on how the main indices track each other.

Thursday, December 6, 2012

Using present expectation anomalies for station data.

As I foreshadowed in a recent post, for plotting recent monthly data I wanted to shift from anomalies based on a past period (1961-1990) to one based on the present. For each station and each month, I would use the present value of a weighted linear regression as the expectation, and the anomaly would be the deviation from that.

The reason was mainly that I suspected that irregular happenings in the history of the stations was distorting the anomaly base, and creating noise in the anomaly plot which isn't needed. In my most recent post I traced the prominent deviations due to Nitchequon and Shahr-e-kord to gaps in the record and noted big (and probably correct) adjustments made by GHCN. But I use unadjusted GHCN.

I've done it, and the monthly maps now use this basis. I think it has been very successful in removing this source of error. Of course, it also means that the (present) anomalies do not give any measure of AGW, since the expected value is zero. For that the right source is the trend map.

Below the jump, I'll illustrate the improvement.

Wednesday, December 5, 2012

Visualizing the need for homogenization

I've put up two recent posts which show temperature results for individual stations using a shaded mesh. One shows monthly anomalies relative to 1961-1990, or 1975, and the other shows trends. There's an interesting spatial consistency, with exceptions.

The exceptions may be climate. But they may also be the effects of things happening to stations. This is what homogenization is designed to overcome, and I think there are some good illustrations here.

I usually use GHCN unadjusted readings, mainly because people like to argue over adjustments, and I think for the headline effects they don't make much difference. But these spatial plots show that they can, and it's probably for the good.

Station trends - more

This is the second in the series of large datasets made available by XMLHTTPRequest. I had shown a globe map of station trends. I was limited to 3 time periods and even then there was some awkwardness because I had to use a single mesh to save download time.

Now I can do many periods, each with its own mesh. The resulting plot is shown below. All the periods end at present - I could do selected past periods too, but couldn't think of a scheme for preselecting.

I originally called this a cherrypickers guide, because it shows out the locations where the trends have been negative. But it also puts it in proportion - there are more positive trends than negative. The color scheme often obscures that, because I center the rainbow colors on the midpoint of the data, which is often well above the zero trend, which is down among the blues. I think the spatial homogeneity is worth noting. Nearby stations tend to warm and cool together.

Anyway, the plot is below the jump. Or you can go here to see it in a separate window. As with monthly data, you can select different time ranges, ask to see the nodes and mesh - just refresh when you've selected. Click on the small map to reorient the globe. Click on the main globe to bring up the data for the nearest station.

Update: I've put up corresponding data using GHCN adjusted. Check the box and refresh to see it.

Tuesday, December 4, 2012

On Anomalies for Stations

I've recently posted a map (one of a series) of monthly temperature anomalies for individual stations. I've been thinking about what kind of anomaly is really appropriate here.

Some skeptics don't like anomalies, and say only real temperatures should be plotted. But then the plot is dominated by the variations in altitude and latitude. In January it's cold in Moscow and warm in Booligal. We knew that. If you hear that it was 15°C in Rome last month, you'll ask "but what is it normally?".

You need the anomaly, because that's the real information in the month's readings. And a plot should show that. The anomaly is the difference between what is observed and what you expect.

But what expectation? More below the jump.

Monday, December 3, 2012

Monthly station surface temperature shown on globe

I've been discovering new things in Javascript. I have been much constrained by data download time. JS frowns on interactive downloading - you generally have to download all data initially, as part of the code. However, there is a newish feature, XMLHTTPRequest, which allows download in response to user choices (with restrictions on domains). This means I can make very large datasets available to select from. I've also found new ways of compacting them, which I'll write about later.

My initial exercise was the plot that I have sometimes shown for recent months (eg June). It's based solely on the data reported for that month (plus the anomaly base). But now you can select any month you like (currently only for this century). The data is downloaded when you ask, so there isn't a huge initial wait. It's a plot based purely on the station data for GHCN V3 unadjusted and ERSST. For SST a "station" is a 4°x4° lat/lon cell. A triangle mesh is fitted and used for color shading between stations.

As before, you can rotate the globe by selecting focus points on the top right map. You can magnify, display stations and mesh, and click to print numerical data (on the right). There are more details of that below.

The plot is below. You can also click here to see it in a separate tab/window. More discussion and user guidance follows.