So the standard is “net gain,” and a net gain greater than (or less than) 0.1 Kelvin means not basically flat?
My linear regressions based on NOAA data (I was stupid and lost the citation for where I downloaded it) have 0.005-0.007 K/year since 1880; 0.1 to 0.2 K in a decade is beating the trend.
I took the liberty of downloading the GISTEMP data, which I suspect are very similar to the NOAA data (because the GISTEMP series also starts at 1880, and I dimly remember reading somewhere that the GISS gets land-based temperature data from the NOAA). Regressing anomaly on year I get an 0.00577 K/year increase since 1880, consistent with Robin’s estimate. R tells me the standard error on that estimate is 0.00011 K/year.
However, that standard error estimate should be taken with a pinch of salt for two reasons: the regression’s residuals are correlated, and it is unlikely that a linear model is wholly appropriate because global warming was reduced mid-century by sulphate emissions. Caveat calculator!
(ETA: I just noticed you wrote ‘these,’ so I thought you might be interested in the trend for the past decade as well. Regressing anomaly on year for the past 120 monthly GISTEMP temperature anomalies has a trend of 0.0167 ± 0.0023 K/year, but the same warning about that standard error applies.)
I have no idea. Varying the starting point from ten to thirty years ago with Feb 2010 as the endpoint puts the slope anywhere in the range [-0.0001,0.2], so it must be fairly large on the scale of a decade.
My linear regressions based on NOAA data (I was stupid and lost the citation for where I downloaded it) have 0.005-0.007 K/year since 1880; 0.1 to 0.2 K in a decade is beating the trend.
What are the uncertainties on each of these?
I took the liberty of downloading the GISTEMP data, which I suspect are very similar to the NOAA data (because the GISTEMP series also starts at 1880, and I dimly remember reading somewhere that the GISS gets land-based temperature data from the NOAA). Regressing anomaly on year I get an 0.00577 K/year increase since 1880, consistent with Robin’s estimate. R tells me the standard error on that estimate is 0.00011 K/year.
However, that standard error estimate should be taken with a pinch of salt for two reasons: the regression’s residuals are correlated, and it is unlikely that a linear model is wholly appropriate because global warming was reduced mid-century by sulphate emissions. Caveat calculator!
(ETA: I just noticed you wrote ‘these,’ so I thought you might be interested in the trend for the past decade as well. Regressing anomaly on year for the past 120 monthly GISTEMP temperature anomalies has a trend of 0.0167 ± 0.0023 K/year, but the same warning about that standard error applies.)
I have no idea. Varying the starting point from ten to thirty years ago with Feb 2010 as the endpoint puts the slope anywhere in the range [-0.0001,0.2], so it must be fairly large on the scale of a decade.
Your regression package doesn’t report uncertainties? (Ideally this would be in the form of a covariance matrix.)
My regression package is a tab-deliminated data file, a copy of MATLAB, and least-squares.