UPDATE to Figure 1: The color coding of the NCDC and HADCRUT trend lines were wrong. I corrected (switched) them. Thanks, Donald L. Klipstein.
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GISS prepares the land surface air temperature data for their Land-Ocean Temperature Index (LOTI) dataset, and they use sea surface temperature data from other sources. GISS recently switched to ERSST.v3b data from a combination of HADISST and Reynolds OI.v2 sea surface temperature datasets. The change was first reported by Paul Homewood at NotALotOfPeopleKnowThat in his post More on GISS Tampering. Paul’s follow-up post was cross posted at WattsUpWithThat on January 16th.
I decided to run a few comparison graphs to see if I could determine why GISS made the change. I’ll let you decide.
A BRIEF DISCUSSION OF THE SEA SURFACE TEMPERATURE DATASETS
INITIAL NOTE: The post An Overview of Sea Surface Temperature Datasets Used in Global Temperature Products needs to be updated, but it provides more detailed discussions of the ERSST.v3b, HADISST, and Reynolds OI.v2 data.
GISS formerly used HADISST sea surface temperature data before the satellite era and Reynolds OI.v2 during it, since December 1981. They’re now using the ERSST.v3b data from NOAA. The quality of ERSST.v3b is less than the Reynolds OI.v2 sea surface temperature data. The creators of the Reynolds OI.v2 called it “the truth” in a 2004 paper. Smith and Reynolds (2004) Improved Extended Reconstruction of SST (1854-1997) stated about the Reynolds OI.v2 data:
Although the NOAA OI analysis contains some noise due to its use of different data types and bias corrections for satellite data, it is dominated by satellite data and gives a good estimate of the truth.
In addition to data from ship inlets and buoys, which make up the ERSST.v3b source data before infilling, the Reynolds OI.v2 data also uses satellite-based data, so there’s less infilling. The GISS switch from Reynolds OI.v2 data to ERSST.v3b could be said to be a step down to something less than “the truth”.
Both the HADISST and ERSST.v3b datasets rely on a common source sea surface temperature dataset called ICOADS. I don’t believe either dataset has upgraded to the newer ICOADS version 2.5 data as of yet (the one employed in the new HADSST3 data). The source data is spatially incomplete. NOAA and the Hadley Centre use different methods to infill missing data in ERSST.v3b and HADISST data. One of the key differences is that the Hadley Centre reinserts the source data after the statistical processes used for infilling (see the HADISST overview here), while I have found nothing in the NOAA papers to indicate they reinsert source data. NOAA states they reinsert source data in their land surface air temperature product but not during their discussions of the sea surface temperature. See Smith et al (2008). Note: Smith et al (2008) was for the ERSST.v3 when it included satellite-based data. The satellite-based data was subsequently removed for political reasons and the dataset was renamed ERSST.v3b. Because the vast majority of Smith et al (2008) was a discussion of the inclusion of satellite-based data, and because there has been no documentation of the impacts of its removal, ERSST.v3b data is not based on a peer-reviewed paper.
That looks like two strikes against GISS for their switch to ERSST.v3b data: (1) they’re now using a lesser quality sea surface temperature dataset during the satellite era that (2) is not based on a peer-reviewed paper.
GISS has not updated their current analysis webpage, but I think it would be safe to assume GISS still masks out sea surface temperature data where there has ever been sea ice and replaces the sea surface temperature data there with land surface temperature data, which has more monthly variability and a higher long-term trend. The impact of this was discussed and illustrated the posts here and here. The first of those posts was cross posted at WattsUpWithThat here.
Enough with the background info. Let’s look at some graphs.
THE NEW GISS LOTI VERSUS THE OTHERS
INITIAL NOTE: All temperature anomalies presented in the post use the standard GISS base period of 1951 to 1980.
Figure 1 compares the new annual GISS Land Ocean Temperature Index (LOTI) to the products from UKMO Hadley Centre and NCDC for the period of 1979 to 2012. Not too surprisingly, GISS has the highest linear trend—but it’s not by much.
Figure 1
In Figure 2, I’ve added the old version of the GISS LOTI data (HADISST- & Reynolds OI.v2-based) to the mix and ended the comparison in 2011, the last full year of the older GISS LOTI data. The new GISS LOTI data has a slightly higher linear trend during that shortened period than the older version.
Figure 2
The long-term trends, starting in 1880 and ending in 2011, are illustrated in Figure 3. There’s little difference in the trends. But there is a difference between the older (HADISST-based) version of the GISS LOTI data and the other datasets from 1880 to the early 1910. The reason: the dip and rebound in HADISST data during that period is not as significant as it is in the others.
Figure 3
OLD VERSUS NEW
The old and new versions of the long-term GISS LOTI data are compared in Figure 4. Again, the trends are very similar, but the differences during the early decades are clearer now without the NCDC and Hadley Centre data.
Figure 4
Figure 5 shows the difference between the two datasets, with the old version subtracted from the new. That’s quite a change to the early data.
Figure 5
As shown in Figure 4 above, if the long-term datasets are compared starting 1880, the start year of the GISS data, there’s very little difference between them. But persons illustrating global surface temperature data don’t always start at the beginning. Sometimes they begin in 1900 and at other times they present the last 100 years. That’s when the additional dip and rebound during the early part of the 20th Century adds to the linear trend of the new GISS data. Refer to Figures 6 and 7. In both cases, the update adds about 9% to the long-term linear trends. No one should be surprised by that. Many people have said this many times before: every time a change is made to a temperature dataset, it always seems to add to the warming.
Figure 6
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Figure 7
And for those interested in the differences during the satellite-era of sea surface temperatures, refer to Figures 8 and 9. The newer data appears to cool less during the responses to the eruption of Mouth Pinatubo in 1991 and in response to the La Niña events of 1998/99/00 and 2007/08.
Figure 8
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Figure 9
EARLIER POST
GISS had added ERSST.v3b based data to their mapmaking webpage (not functional at present) back in 2010. In response, I had prepared a detailed post about the differences in the two sea surface temperature datasets in my post When Did GISS Add ERSST.v3b to Their Map Making Web Page?
OOPS – FORGOT TO PLUG MY BOOK
The hypothesis of manmade global warming depends on manmade greenhouse gases being the cause of the recent warming. But the satellite-era sea surface temperature record indicates El Niño and La Niña events are responsible for the warming of global sea surface temperature anomalies over the past 31 years, not manmade greenhouse gases. And ocean heat content data since 1955 indicate the tropical oceans warmed naturally to depths of 700 meters in response to La Niña events. I’ve searched sea surface temperature records for more than 4 years and the ocean heat content records for more than 3 years, and I can find no evidence of an anthropogenic greenhouse gas signal in those two datasets. That is, the warming of the global oceans has been caused by Mother Nature, not anthropogenic greenhouse gases.
I’ve recently published my e-book (pdf) about the phenomena called El Niño and La Niña. It’s titled Who Turned on the Heat? with the subtitle The Unsuspected Global Warming Culprit, El Niño Southern Oscillation. It is intended for persons (with or without technical backgrounds) interested in learning about El Niño and La Niña events and in understanding the natural causes of the warming of our global oceans for the past 30 years. Because land surface air temperatures simply exaggerate the natural warming of the global oceans over annual and multidecadal time periods, the vast majority of the warming taking place on land is natural as well. The book is the product of years of research of the satellite-era sea surface temperature data that’s available to the public via the internet. It presents how the data accounts for its warming—and there are no indications the warming was caused by manmade greenhouse gases. None at all.
Who Turned on the Heat? was introduced in the blog post Everything You Ever Wanted to Know about El Niño and La Niña… …Well Just about Everything. The Updated Free Preview includes the Table of Contents; the Introduction; the beginning of Section 1, with the cartoon-like illustrations; the discussion About the Cover; and the Closing.
Please buy a copy. (Paypal or Credit/Debit Card). You do not need to have a PayPal account. Simply scroll down to the purchase option Simply scroll down to the “Don’t Have a PayPal Account” purchase option. It’s only US$8.00.
SOURCES
The current GISS LOTI data can be found at the GISS website here. The older version is available through the Wayback Machine. And the following are links to the HADCRUT4 and NCDC datasets.
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Modern climatology seems to be stuck with three basic methods: creating paleo hockey-sticks, prolonging short-term trends to year 2100 and in between, cooling the past and warming the present of the instrumental records.
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The first graph appears to me to have the linear trends misstated.
Based on temperature anomaly according to the graph at the
endpoints of the lines, the red linear trend line’s slope appears to
me as .159 degree/decade, the green one appears as .156, and
the brown one appears as .150.
I suspect the HadCRUT3 and NCDC linear trend figures are
interchanged with each other.
I did some more looking at the first two graphs. Now it appears to
me that in the 1st graph, the green linear trend line should be brown,
and the brown linear trend line should be green.
Donald L. Klipstein: Thanks. I just checked the spreadsheet. You’re correct. I applied the wrong color to the HADCRUT and NCDC curves. I’ve corrected them.
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