Thursday, March 13, 2014

TempLS global temp down 0.20°C in February


TempLS dropped substantially in February, from 0.486°C to 0.287°C. This was a little larger than the drop in the satellite indices. Again the cold spots were N America and Central Asia; warm in NE Europe.

I have made some modifications to the current data page, including a user-scalable graph.

Here is the spherical harmonics plot of the temperature distribution:



Here is the map of the 4335 stations reporting to date:



Monday, March 10, 2014

Interactive graphics gallery

A lot of new graphics has appeared here in the last year or so, so I made a new graphics gallery. It's here, or linked among the pages top right. It is itself a Javascript gadget, and shows the main graphics types, grouped by key technology (eg WebGL, Google Maps etc). You see the graphics frame at the top, and below is the explanation. The examples shown have the same format; graphic at the top, and scroll down for text. Choose a class, then one of the examples in the list below.

I won't show the gadget in this post, but below the jump is some of the detailed explanation from the page.

Graphics gallery

On this page, I have gathered graphics produced over the last three years on Moyhu. They are listed mainly by programming technique. Clicking on the "Classes" button brings up a new list of examples below. Clicking on an example shows in the frame on the right the main graphic, and below the text that was associated with it. At the bottom on the right is a link to the original post/page where it appeared.
Also at the bottom left are two buttons + and -, which allow you to expand and contract the frames. For large plots, you may want to expand the frame and unzoom the screen with Ctrl-. Ctrl+ restores.

History of methods

An important point here is that no server is used. What you see is the effect of HTML/Javascript code that you download and implement via your browser.
I use R for most arithmetic and data handling, and for static plots and images (usually png). My first advance was using Javascript for showing multiple pictures in one place, under user control. This is related to my first serious purpose here - getting more information in one place. That then bumps up against download time, so another advance was using the then new XMLHTTPRequest, which allows extra data to be downloaded on demand.
At about the same time, HTML with its 2d canvas became available. This gives JS-controlled drawing and shading. Another serious purpose was to allow proper spherical projection, with a sphere you can rotate to examine. In early times I did this with about eight perspectives with fixed images, with JS switching. But the canvas, later augmented with WebGL, gave continuous control with zooming. That's the top feature here.

The climate plotter combines the use of the canvas and JS information handling capability. Along the way, I've also experimented with the Google Maps API, mainly for met stations, and Google Earth KML files, using folders to allow large information sets.

Classes

  • WebGL
    This is a browser implementation of OpenGL. It allows a Google Earth capability; you can rotate the sphere like a trackball, and zoom. Often you can click (or Shift-click) to bring up information about the closest station. The color is Gouraud shading on a triangular mesh.
  • Animations
    These are mostly SST animations taken as screenshots from the WebGL, with possible additions.
  • HTML 5 shadingThe applications here are spherical projections and data plotting. But it is very versatile.
  • Active graphs
    Everything in the gallery is active. Included here are conventional graphs which can be superimposed under user control, the trend viewer, which shows a color plot of possible trends, but allows the time series to show the chosen trend lines, and the climate plotter.
  • Javascript
    Everything here uses JS. I've put in this class the smaller scale visuals, with the element of user control and information density.
  • Google Map apps
    I found this more useful than KML, as it gave better user control. It embeds groups of met stations in a Maps environment; you can click on the markers to pop up balloons of information. The most mabitious app is the station history, which attaches a stripped down climate plotter to allow you to plot and process station temp data.
  • KML Google Earth
    If you have a GE plugin installed, this should come to life (slowly). The plug-in version has some drawbacks, the main one being that it doesn't show a folder menu, which these KML files get much of their utility from. However, it does show the stations and you can still click for info. If it doesn't work, you can click at the top. This will download the KML or KMZ file, and start up GE, if you have it installed. Then you can use the folders.

    There's a who;e world of GE API programming - this may get better.





Saturday, March 1, 2014

McIntyre, Mann, and the Gaspe cedars

Sixteen years later, people are still arguing about Mann's 1998 Nature paper (MBH98) on multiproxy (112) reconstructions. McIntyre and McKitrick (M&M) wrote a paper in Energy and Environment in 2005, and I find myself still arguing about that.

The 2005 paper was a major resource for Congressman Barton's 2006 inquisition of Mann. One of its featured criticisms was the Gaspe dataset, number 53, and in particular the fact that Mann had padded some missing data from 1400 to 1403 with the 1404 value. And Barton directed Mann et al to explain.

One thing not often now mentioned is that in that paper, M&M actually did what many other critics should have done. They repeated the calculation with their criticism made good, to see what effect it had. This was in their Figure 1. They showed the effect of marking those four Gaspe years as missing, and then the effect of using a centered mean rather than Mann's famous calibration mean. They got a surprisingly large difference, which has been much cited in recent days. This post reports on my investigation of that surprise.

Barton got statistician Wegman to report, and his report was heavily based on the M&M 2005 papers. He said of this
"In MBH98, the first four years of both of these series were extrapolated. The extrapolation has the effect of depressing early 15th century results, and was not disclosed by Mann et al. until a later paper, "
This depressing effect was based on the M&M calculation reported in their Fig 1.

I'll show that the effect of padding those four years was limited to just those four years, and is minor. The effect Wegman describes was due to a coding rule in which M&M in effect removed the effect of Gaspe not just the four years in question, but all years from 1400-1450.

I have previously criticized the use Wegman made of the M&M 2005 GRL code for supposedly showing how noise could generate hockey sticks. There there was a clearly deliberate selection of the top 100, ordered by "hockey stick index", from which the displayed samples were chosen. In the case described here, there is no indication that the amplification of the effect was deliberate. In fact, M&M say they are following a policy of Mann's. However, the effect as presented is misleading, in that the change shown is due to the application of a rule rather than the actual effect of the padding.


M&M Fig 1, seen in perspective

Here is the original M&M05 Fig 1

The top panel shows their MBH emulation, which they say appears to be completely accurate. The second shows supposed effect of replacing the 1400-1403 years of proxy 53 (Gaspe) by NA, the R marker for missing. There is a moderate deviation in the years 1400-1450.

The bottom panel shows the effect of changing the offest mean to centered. I'll say more about that in a future post.

I'm rerunning the M&M code, so I'll show that my version does indeed reproduce that plot. I've used a bit of color:


Now I'll plot the same data but superimposed. This emphasises that the Gaspe deviation affects the years 1400-1450.

I've made the panel 3 plot faint, since it isn't the current subject.

For the remaining plots, I'll focus on the years 1400-1450. Here is again the data from panels 1 and 2

Padding with numbers

Mann used the 1404 value (0.723) to pad, and as Wegman suggests, this was a low point. The range from 1404-1450 was from 0.618 to 1.351. So I tried using 1.351, and got this:



This compares Mann's padding with the effect of padding with that max. It isn't very different at all, even using the max, and if you focus on the annual non-smoothed values, only the 1400-1403 values are changed. Much less effect than with NA.

What the M&M code does.


The recon work is done in a function NHbeta() in the file ee2005functions.r. They loop over the 11 periods, of which the last is 1400-1450. For each period they set up a "roster" of proxies that will be used. The statement defining it is:
roster<-!is.na(proxy[period[k+1],])

Here period[k+1] points to the first data point in the period, ie year 1400. So by setting the 1400 value to NA, the program removes Gaspe entirely for that period. They might as well have set the values from 1400-1449 to NA. In fact, I checked that doing that has the same effect.

Conclusion

Padding as Mann did with the Gaspe cedars had a very small, local effect. The M&M sffort to replace with missing values triggered a large response. But it was an artefact.





Tuesday, February 25, 2014

Links for Mann legal matters


I have been collecting links for various documents associated particularly with the current libel case of Mann vs CEI/NRO/Steyn. I've been arguing about that on the usual blogs (Lucia,CA,WUWT). I don't want to canvass the arguments here, but just to collect links to relevant documents. For case docs, I've tried to source the very good DC Slapp Law site linked above, partly because its pdf's are selectable.

So here is a table of links. I'll try to add to them over time.

Update. I searched for and copied the case index as at 25 Feb from the SC site. That copy is also linked (top line). Then I stripped down and numbered the calendar, which is in a frame at the bottom. I've shown the corresponding numbers in the links, where they correspond to an event in the calendar. If you click on them, the list in the lower frame will move to show the corresponding numbered item. That gives more info than my brief and informal tags.







Monday, February 17, 2014

January GISS Temp up by 0.1°C



GISS LOTI went from 0.60°C in December to 0.70°C in January, similar to the change in MSU RSS (lower troposphere). This is larger the TempLS rise of 0.04°C, which was similar to UAH.


Again, NW and Arctic N America were very warm; Eastern N America was very cold. Europe and N China warm; N Siberia cold. Here is the GISS map for Dec 2013:



And here, with the same scale and color scheme, is the earlier TempLS map:



Previous Months

December 2013
November
October
September
August
July
June
May
April
March
February
January
December 2012
November
October
September
August
July
June
May
April
March
February
January
December 2011
November
October
September
August 2011

More data and plots

Thursday, February 13, 2014

TempLS global temp up 0.04°C in January


TempLS showed a small rise in January, from 0.48°C to 0,52°C. The satellite TLT from UAH also showed a rise
Update: I'm also keeping the GHCN/ERSST stations worldview updated. It gives a more comprehensive view of temperatures in Jan and before.

Here is the spherical harmonics plot of the temperature distribution:



Warm in Central Asia, Arctic, including Alaska, and Europe. Cold in Eastern US, N Siberia. A markedly striped by latitude pattern.

Here is the map of the 4214 stations reporting to date:


Thursday, January 23, 2014

Heat Wave in Victoria

Update - I've extended the table of temperature extremes below
Tennis fans everywhere will know that we had a pretty torrid heat wave last week, the first week of the Australian Open. It wasn't our hottest, but it went for four days. In Melbourne max temperatures were were 42.8,41.7, 43.9 and 43.9°C, or, if you prefer,109, 107, 111, 111°F. This forecast from the BoM explains what was happening; it happened as predicted, a bit warmer at the end. MikeH in comments noted this more complete report from B0M.

There's the usual argument about AGW. WUWT doesn't think so. In fact, they won't much concede that it was hot, and say it happens all the time here. So I thought I'd review in this post our summer temperature history, and also refute some notions that it's all happened before but been hushed up by "adjustments".


Monkey Mia, WA, From ABC

Data


The Bureau of Meteorology here has online daily data which is unadjusted. It's convenient to use, but not to download. For that I used GHCN Daily files which can be found here. They are unadjusted historic temperatures, derived from (and apparently identical to) BoM. Melbourne’s file is ASN00086071.dly; it has good coverage from June 1855 to Dec 2013. I supplemented it with current online data to date.. I extracted them to a CSV file which I've placed here.

Plots


I've plotted each summer (DJF) max temperatures from 1856 to 2014 (counting by the JF year).



1860
1870
1880
1890
1900
1910
1920
1930


1940
1950
1960
1970
1980
1990
2000
2010

You can switch from year to year using the top buttons, and go to any decade year with the radio buttons.

Our summers are made up of many pleasant days, with southerly winds, with heat when the wind blows from the North. Notably hot summers were in 1908, 1939, 1983, 2009. The last three had devastating wildfires on the hottest days, which I've linked. Big heat has bad consequences here. We lose towns, homes and people.

Table of extreme temperatures

Originally, I had here a list of the twenty hottest days in Melbourne since 1855. Following a suggestion in comments by SC M, I have updated to inclide tables of the 20 highest daily max, highest min, lowest max and lowest min. I've marked those occurring in the last five years in red. For highest max, there are seven. Click the buttons.

High Max  Low Max  High Min  Low Min



Adjustments?

In the WUWT thread I encountered over and over claims that BoM had rigged the records by adjusting old readings downwards. It's very hard to get specifics (typically the complainant just gives a link, which is often to a rant about GHCN, or GISS). Eventually it crystallised to complaints about Acorn. This is a recent homogenised set of data for 112 chosen stations, starting in 1910. The lead post in fact claimed that the BoM had discarded all data before 1910, which puzzled me.

But of course the data is not discarded. All the old unadjusted data is available from BoM, and also from GHCN. And it is what the BoM uses when talking about station extreme temperatures. If you go to the Melbourne climate page, for example, it will tell you that the hottest December day was 15 December 1876. That's not Acorn.

So how do we know these are really unadjusted? I've known since boyhood that Melb reached 114.1°F on Jan 13, 1939. That's what the record still says. But I checked others. The National Library has an old Melb (and others) newspapers here. I've checked a few of the reportewd high temps; the GHCN record linked here agrees with the contemporary reports. I think it's up to claimants of adjustment to give one example from this dataset.