{"id":1817,"date":"2014-01-06T11:16:14","date_gmt":"2014-01-06T11:16:14","guid":{"rendered":"http:\/\/jeremyshiers.com\/blog\/?p=1817"},"modified":"2014-01-06T11:16:14","modified_gmt":"2014-01-06T11:16:14","slug":"uncertainties-in-global-temperature-data-at-least-0-5c-jan-2014","status":"publish","type":"post","link":"http:\/\/jeremyshiers.com\/blog\/uncertainties-in-global-temperature-data-at-least-0-5c-jan-2014\/","title":{"rendered":"Uncertainties In Global Temperature Data – At Least 0.5C – Jan 2014"},"content":{"rendered":"

Graphs of global temperatures in media rarely show uncertainties yet no measurement is completely accurate, \u00a0 \u00b10.5C uncertainty is a plausible minimum uncertainty for monthly average temperatures.\u00a0 UK Met Office say there has been a rise in temperature of 0.8C since 1880 and this is statistically significant.\u00a0 Uncertainties of \u00b10.5C mean this ‘statistical significance’ is not really significant at all.<\/p>\n

HadCRUT4, the temperature record produced by Met Office and Climate Research Unit at University of East Anglia, looks like this<\/p>\n

\"hadcrut4\"<\/a>A 2005 paper by P. Brohan, J. J. Kennedy, I. Harris, S. F. B. Tett & Phil Jones<\/a> estimated uncertainties in mean monthly temperatures as about<\/p>\n

0.2C\/\u221a60 = 0.03C<\/p>\n

The argument was based on an earlier paper by CK Folland, Phil Jones and others<\/a> which estimated the error in any single land temperature measurement was 0.2C (or more precisely they estimated the 2 \u03c3 measurement error was 0.4C).<\/p>\n

Brohan and mates argue<\/p>\n

The random error in a single thermometer reading is about 0.2\u000eC<\/em> [Folland et al 2001]; the monthly average will be based on <\/em>at least two readings a day throughout the month, giving 60 or more<\/em> values contributing to the mean.
\nSo the error in the monthly average will be at most<\/em> 0.2C\/\u221a60 = 0.03\u000eC and this will be uncorrelated with the value for any other station or<\/em> the value for any other month.<\/em><\/p>\n

Firstly to nit pick they don’t appear to have heard of February.<\/p>\n

Second the claim<\/p>\n

if there are 60 separate measurements of temperature at a weather station, where the measurement error of the thermometer is \u00b10.2C, then the error in the monthly mean is 0.2C\/\u221a60<\/p>\n

is simply wrong<\/strong>.\u00a0 It’s so wrong I don’t hedge with weasel words like, ‘in my opinion’.<\/p>\n

The reason it is wrong is this formula applies to repeated measurements of the exactly same quantity<\/strong>, e.g. measuring the resistance of a resistor.\u00a0 Why would anyone want to measure the resistance of the same resistor over and over again?<\/p>\n

To increase the accuracy of the overall measurement!<\/p>\n

Temperature measurements made at different times and days during a month are obviously not measuring the same thing, not least because temperature usually changes over time so the same quantity is obviously not being repeated measured.\u00a0 If you’re still not convinced would you say the error in the mean of 60 temperature measurements at 60 different locations (separated in space) should be less than the error of any single measurement.\u00a0 Why should 60 measurements separated in time (when the temperature may have changed) be different?<\/p>\n

This is usually taught in first year undergraduate science courses.<\/p>\n

Here are two books which discuss uncertainties in measurements<\/p>\n\n\n\n
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