August 2013 Global Surface (Land+Ocean) Temperature Anomaly Update

I figured today would be a good day to post this, with David Rose’s article in the “Sunday Mail” Met Office proof that global warming is still ‘on pause’ as climate summit confirms global temperature has stopped rising.  This post is available just in case someone wants to back David by linking this post once or twice in comments on that thread.   It’s really tough to miss the pause in the time-series graphs, and the trend graphs sock the message home.

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Initial Notes:  This post contains graphs of running trends in global surface temperature anomalies for periods of 12+ and 16+ years using the NCDC Global (Land and Ocean) Surface Temperature data.  They indicate that we have not seen a warming hiatus this long since the 1970s.

Much of the following text is boilerplate. It is intended for those new to the presentation of global surface temperature anomaly data.

GISS LAND OCEAN TEMPERATURE INDEX (LOTI)

Introduction: The GISS Land Ocean Temperature Index (LOTI) data is a product of the Goddard Institute for Space Studies.  Starting with their January 2013 update, it uses NCDC ERSST.v3b sea surface temperature data.  The impact of the recent change in sea surface temperature datasets is discussed here.  GISS adjusts GHCN and other land surface temperature data via a number of methods and infills missing data using 1200km smoothing. Refer to the GISS description here.   Unlike the UK Met Office and NCDC products, GISS masks sea surface temperature data at the poles where seasonal sea ice exists, and they extend land surface temperature data out over the oceans in those locations.  Refer to the discussions here and here. GISS uses the base years of 1951-1980 as the reference period for anomalies.  The data source is here.

Update:  The August 2013 GISS global temperature anomaly is +0.62 deg C.  It warmed (an increase of about 0.09 deg C) since July 2013.

GISS LOTI

NCDC GLOBAL SURFACE TEMPERATURE ANOMALIES

Introduction: The NOAA Global (Land and Ocean) Surface Temperature Anomaly dataset is a product of the National Climatic Data Center (NCDC).  NCDC merges their Extended Reconstructed Sea Surface Temperature version 3b (ERSST.v3b) with the Global Historical Climatology Network-Monthly (GHCN-M) version 3.2.0 for land surface air temperatures. NOAA infills missing data for both land and sea surface temperature datasets using methods presented in Smith et al (2008). Keep in mind, when reading Smith et al (2008), that the NCDC removed the satellite-based sea surface temperature data because it changed the annual global temperature rankings.  Since most of Smith et al (2008) was about the satellite-based data and the benefits of incorporating it into the reconstruction, one might consider that the NCDC temperature product is no longer supported by a peer-reviewed paper.

The NCDC data source is usually here.  NCDC uses 1901 to 2000 for the base years for anomalies.

Update:  The August 2013 NCDC global land plus sea surface temperature anomaly is also +0.62 deg C.  It increased 0.02 deg C since July 2013.

NCDC Global (Land and Ocean) Surface Temperature Anomalies

UK MET OFFICE HADCRUT4 (LAGS ONE MONTH)

Introduction: The UK Met Office HADCRUT4 dataset merges CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset.  CRUTEM4 is the product of the combined efforts of the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia. And HadSST3 is a product of the Hadley Centre.  Unlike the GISS and NCDC products, missing data is not infilled in the HADCRUT4 product.  That is, if a 5-deg latitude by 5-deg longitude grid does not have a temperature anomaly value in a given month, it is not included in the global average value of HADCRUT4. The HADCRUT4 dataset is described in the Morice et al (2012) paper here.  The CRUTEM4 data is described in Jones et al (2012) here. And the HadSST3 data is presented in the 2-part Kennedy et al (2012) paper here and here.  The UKMO uses the base years of 1961-1990 for anomalies.  The data source is here.

Update (Lags One Month):  The July 2013 HADCRUT4 global temperature anomaly is +0.51 deg C.  It increased (about 0.06 deg C) since June 2013.

HADCRUT4

152-MONTH RUNNING TRENDS

As noted in my post Open Letter to the Royal Meteorological Society Regarding Dr. Trenberth’s Article “Has Global Warming Stalled?”, Kevin Trenberth of NCAR presented 10-year period-averaged temperatures in his article for the Royal Meteorological Society. He was attempting to show that the recent hiatus in global warming since 2001 was not unusual.  Kevin Trenberth conveniently overlooked the fact that, based on his selected start year of 2001, the hiatus has lasted 12+ years, not 10.

The period from January 2001 to August 2013 is now 152-months long. Refer to the following graph of running 152-month trends from January 1880 to May 2013, using the GISS LOTI global temperature anomaly product. The last data point in the graph is the linear trend (in deg C per decade) from January 2001 to the current month. It is basically zero. That, of course, indicates global surface temperatures have not warmed during the most recent 152-month period. Working back in time, the data point immediately before the last one represents the linear trend for the 152-month period of December 2000 to July 2013, and the data point before it shows the trend in deg C per decade for November 2000 to June 2013, and so on.

152-Month Linear Trends

The highest recent rate of warming based on its linear trend occurred during the 152-month period that ended in late 2003, but warming trends have dropped drastically since then. Also note that about the early 1970s was the last time there had been a 152-month period without global warming—before recently.

195-MONTH RUNNING TRENDS

In his RMS article, Kevin Trenberth also conveniently overlooked the fact that the discussions about the warming hiatus are now for a time period of about 16 years, not 10 years—ever since David Rose’s DailyMail article titled “Global warming stopped 16 years ago, reveals Met Office report quietly released… and here is the chart to prove it”.  In my response to Trenberth’s article, I updated David Rose’s graph, noting that surface temperatures in April 2013 were basically the same as they were in June 1997.  We’ll use June 1997 as the start month for the running 16-year trends.  The period is now 195-months long. The following graph is similar to the one above, except that it’s presenting running trends for 195-month periods.

195-Month Linear Trends

The last time global surface temperatures warmed at the minimal rate of 0.03 deg C per decade for a 195-month period was the late 1970s.

The most widely used metric of global warming — global surface temperatures — the metric most often used in predictions of future gloom and doom, indicates that the rate of global warming has slowed drastically and that the duration of the hiatus in global warming is unusual during a period when global surface temperatures are allegedly being warmed from the hypothetical impacts of manmade greenhouse gases.

A NOTE ABOUT THE RUNNING-TREND GRAPHS

There is very little difference in the end point trends of 12+year and 16+year running trends if HADCRUT4 or NCDC products are used in place of GISS data. The major difference in the graphs is with the HADCRUT4 data and it can be seen in a graph of the 12+year trends.  I suspect this is caused by the updates to the HADSST3 data that have not been applied to the ERSST.v3b sea surface temperature data used by GISS and NCDC.

COMPARISON

The GISS, HADCRUT4 and NCDC global surface temperature anomalies are compared in the next three time-series graphs. The first graph compares the three global surface temperature anomaly products starting in 1979. Again, due to the timing of this post, the HADCRUT4 data lags the GISS and NCDC products by a month.  The graph also includes the linear trends.  Because the three datasets share common source data, (GISS and NCDC also use the same sea surface temperature data) it should come as no surprise that they are so similar.    For those wanting a closer look at the more recent wiggles and trends, the second graph starts in 1998, which was the start year used by von Storch et al (2013) Can climate models explain the recent stagnation in global warming?  They, of course found that the CMIP3 (IPCC AR4) and CMIP5 (IPCC AR5) models could NOT explain the recent hiatus.

The third comparison graph starts with Kevin Trenberth’s chosen year of 2001.  All three of those comparison graphs present the anomalies using the base years of 1981 to 2010.  Referring to their discussion under FAQ 9 here, according to NOAA:

This period is used in order to comply with a recommended World Meteorological Organization (WMO) Policy, which suggests using the latest decade for the 30-year average.

Comparison Starting in 1979

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Comparison Starting in 1998

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Comparison Starting in 2001

AVERAGE

The last graph presents the average of the GISS, HADCRUT and NCDC land plus sea surface temperature anomaly products. Again because the HADCRUT4 data lags one month in this update, the most current average only includes the GISS and NCDC products.  The flatness of the data since 2001 is very obvious, as is the fact that surface temperatures have rarely risen above those created by the 1997/98 El Niño.

Average of Global Land+Sea Surface Temperature Anomaly Products

SUPPLEMENTS TO CLIMATE MODELS FAIL

I published the post Models Fail: Land versus Sea Surface Warming Rates a few days after I published my ebook Climate Models Fail.  Though the graphs in the post were from the book, the Table and text were not. That method of showing and discussing the models’ failings occurred to me after I published Climate Models Fail.

I’ve decided to make available the additional posts about climate model failings, as they’re posted, as supplements to Climate Models Fail, in .pdf format.   So if you’d like a copy of the post Models Fail: Land versus Sea Surface Warming Rates in .pdf format, click here.  I’ll also include them as links on the post that introduced Climate Models Fail.