This post follows on from Euan Mearns’ recent posts on record heat and the Ratpac data set. Its goals are:

To clarify some points regarding what the satellite and “surface” temperature records are really telling us.

To see if we can define which temperature sets are reliable and which aren’t.

To draw appropriate conclusions.

Figure 1 compares the HadCRUT4 global “surface temperature” series with the University of Alabama Huntsville (UAH) global “lower troposphere” series. This comparison is the one we’re used to seeing and indeed about the only one we ever see. It’s the basis of the dispute over which year was really the warmest on record, whether the Earth has warmed by 0.59°C since 1979, as indicated by the HadCRUT4 trend line, or by 0.41°C as indicated by the UAH trend line, and over the length of the post-1998 warming “pause” or “hiatus”, although I’m not going to get into that here:

Figure 1: HadCRUT4 “global surface” versus UAH “lower troposphere” series since the beginning of the satellite record in 1979.

This comparison, however, ignores a number of complications.

A brief note on data sets, sources and treatment before proceeding. Instead of comparing surface and satellite data globally this post compares them with the global data segregated into “land” and “ocean” components. The four temperature time series considered are:

CRUTEM4 (surface land) HadSST3 (surface 0cean) UAH lower troposphere v6.0 land (lower troposphere land) UAH lower troposphere v6.0 ocean (lower troposphere ocean)

The data for these four series are from KNMI Climate Explorer, as are the “land” and “sea” masks used to segregate the UAH global series into “land” and “ocean” components. The data for the Remote Sensing Systems (RSS) v 3.2 and the “raw” ICOADS series are also from KNMI. The HadAT and Ratpac radiosonde data sets discussed later in the text are referenced individually. All data are annual (Jan-Dec) means with the average of the 1979-1983 means set to zero so that all plots start at about the same level.

We begin with HadCRUT4. HadCRUT4 supposedly measures the Earth’s “surface temperature”, but the two surfaces at which it measures temperatures are quite different. About 30% of HadCRUT4 comes from surface air temperatures measured a nominal 5ft above the land surface (CRUTEM4) and the remaining 70% from sea water temperatures measured anywhere from a foot to maybe 50 ft below the sea surface (HadSST3), and as one might expect temperature trends in these two contrasting environments are quite different (Figure 2). Trend line gradients in fact show the global land warming by over twice as much as the global oceans (0.97°C vs 0.44°C since 1979):

Figure 2: CRUTEM4 “land” vs. HaSST3 “ocean”



Yet still we average CRUTEM4 and HadSST3 together to estimate “global surface temperatures” and assume that the result tells us how much the Earth’s “surface” has warmed. But the surface we define by averaging them doesn’t exist as a physically-identifiable entity. It consists of 70% sea water and 30% air – presumably in the form of bubbles – a medium which is found in limited quantities only on surf beaches and during storms at sea. (This problem wouldn’t exist if we had a data set providing surface air temperatures five feet above the sea surface that we could use instead of HadSST3, but we don’t).

The UAH satellite data, on the other hand, are measured at a continuous, coherent and physically-definable surface and we might therefore expect that they would show less variation. But they don’t. The lower troposphere also shows over twice as much warming over land as it does over the ocean (0.63°C vs. 0.27°C since 1979. According to Dr. Roy Spencer 17% of the UAH signal over land is a result of thermal emission from the land surface, but this causes only a “slight enhancement” of the land vs. ocean trend difference):

Figure 3: UAH “land” vs. UAH “ocean”. The series are segregated by applying the KNMI “land” and “sea” masks



These results show that the big difference in post-1979 warming isn’t between the surface and the lower troposphere at all; it’s between the land and the ocean. As always there are some wrinkles, but the bottom line is that a blanket comparison of global UAH with HadCRUT4 is not a good approach, as I noted to begin with.

And in passing I will briefly touch on one intriguing wrinkle. How long has the land been warming faster than the ocean? Obviously it can’t have been doing so indefinitely. Culled from the depths of my files is Figure 4, which compares the ICOADS ocean SST series with the GISS “meteorological station only” land surface air temperature series since 1880 and plots the difference between the two. The difference plot can be fitted closely with a sine curve with a period of 110 years and an amplitude of 0.63°C. Speculation is invited:

Figure 4: Surface air temperature (SAT) versus sea surface temperature (SST) since 1880. The SAT data are from GISS and the SST data from ICOADS.



Having got that out of the way we can now move on to the main part of the post. How reliable are the HadSST3, CRUTEM4 and UAH series? The best way of finding out is to take the raw data and reconstruct the series completely from scratch, but this is usually beyond the capacity of common mortals, although there is one case where I have in fact done it. The fallback position is to compare the three series with other independently-constructed versions to see how well they match. If they match there is at least a presumption that the series is recording real temperature variations.

We begin with HadSST3:

HadSST3 is arguably the most important of the data sets because it contributes 70% of the value of HadCRUT4. What do we have to compare it with? There are a number of other SST series that show similar results, such as ERSSTv4 and Reynolds OI v2, but the most diagnostic comparison is with the “raw” ICOADS SST data from which these series are constructed (although ICOADS is not exactly “raw” because reducing many millions of point-source SST readings to a common baseline involves a fair amount of statistical manipulation). And when we compare HadSST3 with ICOADS over the period of satellite record since 1979 we see no significant difference:

Figure 5: Raw ICOADS SST data vs. HadSST3



We can conclude from this that HadSST3 has not been adjusted to any significant extent over the period after 1979, although the same can’t be said for the period before 1979. In summary, HadSST3 is probably OK.

Next comes CRUTEM4:

It’s frequently claimed that CRUTEM4 is correct because its “sister” series, such as NCDC land, GISS and BEST, show similar amounts of warming. But all these series apply “homogenization” algorithms to the raw data, and numerous previous analyses, including several published here on Energy Matters, have shown that these algorithms sometimes have a regrettable tendency to manufacture warming where no warming exists. So the fact that CRUTEM4 compares with NCDC, BEST and GISS does not confirm that CRUTEM4 reflects real temperature trends.

What we need is an independently-constructed surface temperature series that uses the same raw data set to compare CRUTEM4 against, and some years ago I constructed one. It uses unadjusted GHCN v2 data from 801 very-carefully-selected surface temperature stations, all of which are guaranteed free of significant UHI gradients. I haven’t updated it since 2010 and probably never will because of the amount of work involved, but 2010 gets us most of the way. Figure 6 compares CRUTEM4 with two versions of my series:

Figure 6: CRUTEM4 vs. two surface air temperature series independently constructed from unadjusted GHCN v2 data by the writer



Why two versions? Because I’m unable to replicate the CRUTEM4 “land mask” exactly and these are limiting cases. The area-weighted series projects surface temperatures out over the ocean – i.e. into HadSST3 territory – and will therefore tend to underestimate land warming, while the station-weighted series will tend to overestimate it because of the concentration of stations in areas that have warmed more than the global average, particularly in mid-high northern latitudes. Both series, however, show less warming than CRUTEM3 – the area-weighted series about 0.1°C and the station-weighted series about 0.3°C projected out to 2015 – suggesting that CRUTEM4 may have overestimated land surface warming since 1979 by about 0.2°C.

But has it? Impossible to say. And what difference does it make if it has? Not that much. Subtracting 0.2°C reduces post-1979 CRUTEM4 warming from 0.94°C to around 0.75°C, still comfortably in excess of lower troposphere warming over land, and it lowers post-1979 HadCRUT3 “global” warming from 0.59°C to about 0.53°C, still considerably more than global lower troposphere warming and certainly nowhere near enough to shut down the IPCC.

My conclusion on CRUTEM4 is that it leaves a lot to be desired, but it isn’t demonstrably wrong to the point where we can reject it out of hand.

Last comes UAH:



Here I present two lines of evidence which demonstrate that the UAH lower troposphere series is robust, with the first being that Remote Sensing Systems (RSS) independently analyzes the same raw data and comes up with an almost identical result:

Figure 7: UAH vs. RSS lower troposphere series, global



The second is RSS’s comparison of raw and corrected RSS and UAH troposphere temperatures with the UKMO HadAT radiosonde data (available in text format here) shown in RSS’s Figure 4 and reproduced below as Figure 8. The HadAT radiosonde data show a warming trend of 0.189°C/decade compared to 0.181°C/decade for RSS and 0.175°C/decade for UAH. These numbers are essentially the same within limits of measurement error:

Figure 8: UKMO HadAT radiosonde data vs. raw and “sampled” versions of RSS and UAH lower troposphere temperatures. The HadAT plot is a weighted average of the HadAT data at different millibar levels to make it directly comparable with the coverage of the RSS/UAH microwave sounding units .



I could add a third line of evidence by comparing UAH/RSS with another radiosonde data set – NOAA Ratpac (data in text format here) which Euan Mearns discussed in detail in his recent eponymous post. Unfortunately Ratpac can’t be compared directly with UAH or RSS TLT because Ratpac data are given at specific millibar levels while UAH and RSS TLT are weight-averages over a range of millibar levels (as noted in the caption the HadAT plot shown in Figure 8 is a weighted average of different tropospheric levels). We can, however, compare it with HadAT at the 700mb level, which is in the most heavily-weighted portion of the TLT window. The two give effectively the same result:

Figure 9: HadAT vs. Ratpac radiosonde data, 700mb level.



In summary , the global UAH series is replicated by the RSS series, gives substantially the same results as the independently-derived HadAT radiosonde data set and HadAT also compares closely with the Ratpac radiosonde data set. It would be difficult to do much better. We can reasonably accept that the series is correct to within normally-accepted limits of error and go from there.

And where exactly do we go? Well, if the world insists on measuring the progress, or lack thereof, of “global” warming it needs a robust, coherent and global temperature data set to do it, and the only one it has is UAH (or RSS). UAH doesn’t measure temperatures at the surface, where global warming should ideally be measured, and it goes back only to 1979, but offsetting this defect is the fact that the surface data sets, in particular HadSST3, become progressively more corrupted by “adjustments” before 1979 to the point where their reliability before 1950/60 is questionable. And as shown in Figure 10 the Ratpac and HadAT2 radiosonde data might be good enough to allow us to project the series back to 1958 anyway (The 700mb data are plotted illustration purposes. “lower troposphere” temperatures would probably show less overall warming):

Figure 10: HadAT vs. Ratpac radiosonde data, 700mb level, all data since 1958.

But this of course isn’t going to happen. The world will continue to use the HadCRUT4 “surface temperature’ series as its global warming yardstick basically because it shows more global warming than the lower troposphere. But is this because HadCRUT4 overestimates surface warming or because the surface really has warmed more than the lower troposphere? I’ll leave that question open for discussion.