GISTEMP -vs- HadCRUT“. Steven Goddard continues his voyage of discovery. Gosh, the GISTEMP data-set uses a somewhat different Arctic data than HadCRUT3 and has a different interpolation process! Gosh, the GISTEMP trend is rising faster than the HadCRUT3 trend! Gosh, GISTEMP is a lying trick!

Gosh, maybe there has been an amplified response to Global Warming in the Arctic? More nit-picking idiocy from Steven, who can barely recognize his own hand in front of his face.

3 thoughts on “GISTEMP -vs- HadCRUT

  1. Steve’s number-of-station coverage discussion is a curious response to the GISS paper (see section7) that is about something else: GISS’s shore extensions versus HadCRUT’s exclusions. GISS says it best:

    “…GISS and NCDC have 2005 as the warmest year in their analyses while HadCRUT has 1998 as the warmest year. Here we investigate differences arising from two factors that we think are likely to be important: (1) the way that temperature anomalies are extrapolated, or not extrapolated into regions without observing stations, and (2) the ocean data sets that are employed…”

    “A likely explanation for discrepancy in identification of the warmest year is the fact that the HadCRUT analysis excludes much of the Arctic, where warming has been especially large in the past decade, while GISS and NCDC estimate temperature anomalies throughout most of the Arctic…”

    “The HadCRUT approach area-weights temperature anomalies of the regions in each hemisphere that have observations, then the mean in each hemisphere are weighted equally to define the global result. Thus HadCRUT implicitly assumes that the Arctic area without observation has a temperature anomaly equal to the hemispheric mean anomaly. Given the pattern of large temperature anomalies, in the fringe Arctic areas with data (Figure12), this implicit estimate would seem to understate Arctic temperature anomalies…”

    So, one more time: Arctic temperature anomalies in GISS are extended from shore station readings. In HadCRUT it is, in effect, the hemispheric mean temperature anomaly. So GISS’s anomalies continue to trend above HadCRUT’s.

    (Hopefully, I won’t have to repeat this, again.)

  2. Anatomy of a Cherry-Pick.

    OK, let us imagine that you had predicted that a key climate metric, say arctic ice extent, would ‘continue to recover’ over the year, but a few weeks after you make this forecast, the observed value actually plummets more than two standard deviations….

    Some misdirection urgently needed; easy – let us arrange for the ice volume to grow. Here’s the drill:

    1. All a trend really requires is two datapoints, so we need to find a low start point. Now in 2007 the summer ice extent did this:

    so it should be the case that in the following winter refreeze, MOST of the ice would be be first year and therefore thinner than average. Here is what the NSIDC wrote in April 2008:

    Despite strong growth of new ice over the winter, sea ice is still in a general state of decline. The ice that grew over the past winter is relatively thin, first-year ice that is susceptible to melting away during the summer. In fact over 70% was first year ice (FYI) here’s the graph.

    So the thin ice of Spring 2008 gives us our low volume starting point. Excellent.

    2. Publish percentages, not absolute values. Analyse the percentage of ice of various thicknesses now and then, ignoring the fact that the ice has shrunk in extent since May 2008. Its only about 3% but every little helps. It’s not like we’re doing science here.

    3. Devise a novel methodology. Fortunately there are no long term observations of ice volume/thickness. What we do have is the US Navy Polar Ice Prediction model PIPS 2.0 (superceded by v3.0 in 2005 but that is classified, presuambly its sufficiently accurate to assist an enemy…). PIPS 2.0 gives us a colour coded map of thickness for any given day. So we can reverse-engineer this by counting pixels of different colours and devise a nonsense algorithm to get to volume. The advantage being that nobody reading the blog is likely to go to similar lengths to check our figures or choose different dates….

    [As an aside, last time Steven Goddard had a go at pixel-counting, it didn’t end well – scroll down to the Editor’s Note ]

    And we’re done, by careful choice of start date, by using percentages and rolling our own algorithm we can announce Arctic Ice Volume increases by 25%

    Which we can quote any time the inconvenient decline in extent comes up. Cool. Just hope nobody digs up the figures published by the University of Washington or reads the associated analysis Total Arctic Ice Volume for March 2010 is 20,300 km^3, the lowest over the 1979-2009 period and 38% below the 1979 maximum.

    If there is a less reliable climate science science blog than WUWT I am not aware of it. [Indeed. – Ben]


  3. Pingback: The Climate Change Debate Thread - Page 331

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