Tag Archives: John Christy

Data Watch: UAH Global Mean Temperature, June 2015 Release

On July 6th, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for June 2015 (here). The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite measurements.

June 2015: Anomaly +0.33 degrees Celsius This is the 3rd warmest June temperature recorded since the satellite record was started in December 1978 (36 June observations). The warmest June to date over this period was in 1998, with an anomaly of +0.56 degrees Celsius. Full data set available here (click for larger image).

UAH Global Temp July 2015 jpeg

The El Nino Southern Oscillation (ENSO) cycle is the main determinant of new temperature records over the medium term (up to 30 years) . The U.S. government’s Climate Prediction Centre currently has an El Nino advisory in effect and is forecasting that the current El Nino event is set to continue through into 2016 (update 9 July 2015 here):

Overall, there is a greater than 90% chance that El Niño will continue through Northern Hemisphere winter 2015-16, and around an 80% chance it will last into early spring 2016.

Given this background, I would expect the UAH anomalies to remain elevated for some time.

As background, five major global temperature time series are collated by different international agencies: three land-based and two satellite-based. The terrestrial readings are from NASA GISS (Goddard Institute for Space Studies), HadCRU (Hadley Centre/Climate Research Unit in the U.K.), and NCDC (National Climate Data Center). The lower-troposphere temperature satellite readings are from RSS (Remote Sensing Systems, data not released to the general public) and UAH (Univ. of Alabama at Huntsville).

The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here). Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjustment to a common base period.

Data Watch: UAH Global Mean Temperature April 2014 Release

On May 6th, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for April 2014.

The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite measurements.

April 2014: Anomaly +0.19 degrees Celsius

This is the 6th warmest April temperature recorded since the satellite record was started in December 1978 (35 April observations). The warmest April to date over this period was in 1998, with an anomaly of +0.66 degrees Celsius. Incidentally, April 1998 was also the warmest month ever recorded for this time series.

The El Nino Southern Oscillation (ENSO) cycle is the main determinant of when global mean temperature hits a new record over the medium term (up to 30 years). In this connection, the U.S. government’s Climate Prediction Center is now giving a 65% chance of an El Nino developing this summer or fall (here). Should this happen, I would expect the UAH anomalies to head back up into the 0.5s, 0.6s or higher.

As background, five major global temperature time series are collated: three land-based and two satellite-based. The terrestrial readings are from NASA GISS (Goddard Institute for Space Studies), HadCRU (Hadley Centre/Climate Research Unit in the U.K.), and NCDC (National Climate Data Center). The lower-troposphere temperature satellite readings are from RSS (Remote Sensing Systems, data not released to the general public) and UAH (Univ. of Alabama at Huntsville).

The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

The official link to the data at UAH can be found here, but most months we get a sneak preview of the release via the climatologist Dr Roy Spencer at his blog.

Spencer, and his colleague John Christy at UAH, are noted climate skeptics. They are also highly qualified climate scientists, who believe that natural climate variability accounts for most of recent warming. If they are correct, then we should see some flattening or even reversal of the upward trend within the UAH temperature time series over a long time period. To date, we haven’t (click for larger image).

UAH Global Temp Apr 14 jpeg

That said, we also haven’t seen an exponential increase in temperature either, which would be required for us to reach the more pessimistic temperature projections for end of century. However, the data series is currently too short to rule out such rises in the future. The Economist magazine published a very succinct summary of the main factors likely accounting for the recent hiatus in temperature rise (here).

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here).

Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjusting them to a common base period.

Data Watch: UAH Global Mean Temperature March 2014 Release

On April 7th, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for March 2014.

The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite measurements.

March 2014: Anomaly +0.17 degrees Celsius

This is the joint 7th warmest March temperature recorded since the satellite record was started in December 1978 (35 March observations). The warmest March to date over this period was in 2010, with an anomaly of +0.57 degrees Celsius.

The El Nino Southern Oscillation (ENSO) cycle is the main determinant of when global mean temperature hits a new record over the medium term (up to 30 years). In this connection, the U.S. government’s Climate Prediction Center is now giving a 50% chance of an El Nino developing this summer or fall (here). Should this happen, I would expect the UAH anomalies to head back up into the 0.5s, 0.6s or higher. The next update is on the 10th of April.

As background, five major global temperature time series are collated: three land-based and two satellite-based. The terrestrial readings are from NASA GISS (Goddard Institute for Space Studies), HadCRU (Hadley Centre/Climate Research Unit in the U.K.), and NCDC (National Climate Data Center). The lower-troposphere temperature satellite readings are from RSS (Remote Sensing Systems, data not released to the general public) and UAH (Univ. of Alabama at Huntsville).

The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

The official link to the data at UAH can be found here, but most months we get a sneak preview of the release via the climatologist Dr Roy Spencer at his blog.

Spencer, and his colleague John Christy at UAH, are noted climate skeptics. They are also highly qualified climate scientists, who believe that natural climate variability accounts for most of recent warming. If they are correct, then we should see some flattening or even reversal of the upward trend within the UAH temperature time series over a long time period. To date, we haven’t (click for larger image).

UAH March 14 jpeg

That said, we also haven’t seen an exponential increase in temperature either, which would be required for us to reach the more pessimistic temperature projections for end of century. However, the data series is currently too short to rule out such rises in the future. Surprisingly, The Economist magazine has just published a very succinct summary of the main factors likely accounting for the recent hiatus in temperature rise (here).

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here).

Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjusting them to a common base period.

Data Watch: UAH Global Mean Temperature February 2014 Release

On March 5th, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for February 2014.

The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite measurements.

February 2014: Anomaly +0.17 degrees Celsius

This is the 10th warmest February temperature recorded since the satellite record was started in December 1978 (35 January observations). The warmest February to date over this period was in 1998, with an anomaly of +0.65 degrees Celsius due to the super El Nino that year.

The El Nino Southern Oscillation (ENSO) cycle is the main determinant of when global mean temperature hits new records over the medium term (up to 30 years). In this connection, the U.S. government’s Climate Prediction Center is now giving a 50% chance of an El Nino developing this summer or fall (here). Should this happen, I would expect the UAH anomalies to head back up into the 0.5s, 0.6s or higher.

As background, five major global temperature time series are collated: three land-based and two satellite-based. The terrestrial readings are from NASA GISS (Goddard Institute for Space Studies), HadCRU (Hadley Centre/Climate Research Unit in the U.K.), and NCDC (National Climate Data Center). The lower-troposphere temperature satellite readings are from RSS (Remote Sensing Systems, data not released to the general public) and UAH (Univ. of Alabama at Huntsville).

The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

The official link to the data at UAH can be found here, but most months we get a sneak preview of the release via the climatologist Dr Roy Spencer at his blog.

Spencer, and his colleague John Christy at UAH, are noted climate skeptics. They are also highly qualified climate scientists, who believe that natural climate variability accounts for most of recent warming. If they are correct, then we should see some flattening or even reversal of the upward trend within the UAH temperature time series over a long time period. To date, we haven’t (click for larger image).

UAH Satellite Tempertures Feb 14 jpeg

That said, we also haven’t seen an exponential increase in temperature either, which would be required for us to reach the more pessimistic temperature projections for end of century. However, the data series is currently too short to rule out such rises in the future. Surprisingly, The Economist magazine has just published a very succinct summary of the main factors likely accounting for the recent hiatus in temperature rise.

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here).

Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjusting them to a common base period.

Data Watch: UAH Global Mean Temperature January 2014 Release

On February 5th, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for January 2014.

The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite readings.

January 2014: Anomaly +0.29 degrees Celsius

This is the joint 5th warmest January temperature recorded since the satellite record was started in December 1978 (35 January observations). The warmest January to date over this period was in 2010, with an anomaly of +0.56 degrees Celsius.  The U.S. cold snap was not of sufficient severity to show up in the global temperature record.

As background, five major global temperature time series are collated: three land-based and two satellite-based. The terrestrial readings are from NASA GISS (Goddard Institute for Space Studies), HadCRU (Hadley Centre/Climate Research Unit in the U.K.), and NCDC (National Climate Data Center). The lower-troposphere temperature satellite readings are from RSS (Remote Sensing Systems, data not released to the general public) and UAH (Univ. of Alabama at Huntsville).

The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

The official link to the data at UAH can be found here, but most months we get a sneak preview of the release via the climatologist Dr Roy Spencer at his blog.

Spencer, and his colleague John Christy at UAH, are noted climate skeptics. They are also highly qualified climate scientists, who believe that natural climate variability accounts for most of recent warming. If they are correct, then we should see some flattening or even reversal of the upward trend within the UAH temperature time series over a long time period. To date, we haven’t (click for larger image).

UAH Satellite Temps jpeg

That said, we also haven’t seen an exponential increase in temperature either, which would be required for us to reach the more pessimistic temperature projections for end of century. However, the data series is currently too short to rule out such rises in the future.

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here).

Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjusting them to a common base period.

Data Watch: UAH Global Mean Temperature December 2013 Release

On January 3rd, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for December 2013.

The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite readings.

December 2013: Anomaly +0.27 degrees Celsius

This is the joint 2nd warmest December temperature recorded since the satellite record was started in December 1978 (35 December observations). The warmest December to date over this period was December 2003, with an anomaly of +0.37 degrees Celsius.

As background, five major global temperature time series are collated: three land-based and two satellite-based. The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

The official link to the data at UAH can be found here, but most months we get a sneak preview of the release via the climatologist Dr Roy Spencer at his blog.

Spencer, and his colleague John Christy at UAH, are noted climate skeptics. They are also highly qualified climate scientists, who believe that natural climate variability accounts for most of recent warming. If they are correct, then we should see some flattening or even reversal of the upward trend within the UAH temperature time series over a long time period. To date, we haven’t (click for larger image).

UAH Dec 2014 jpeg

That said, we also haven’t seen an exponential increase in temperature either, which would be required for us to reach the more pessimistic temperature projections for end of century. However, the data series is currently too short to rule out such rises in the future.

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here).

Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjusting them to a common base period.

Data Watch: UAH Global Mean Temperature November 2013 Release

On December 3rd, Dr Roy Spencer released the University of Alabama-Huntsville (UAH) global average lower tropospheric temperature anomaly as measured by satellite for November 2013.

The anomaly refers to the difference between the current temperature reading and the average reading for the period 1981 to 2010 as per satellite readings.

November 2013: Anomaly +0.19 degrees Celsius

This is the joint 8th warmest November temperature recorded since the satellite record was started in December 1978 (34 November observations). The warmest November to date over this period was November 2009, with an anomaly of +0.39 degrees Celsius.

As background, five major global temperature time series are collated: three land-based and two satellite-based. The most high profile satellite-based series is put together by UAH and covers the period from December 1978 to the present. Like all these time series, the data is presented as an anomaly (difference) from the average, with the average in this case being the 30-year period from 1981 to 2010. UAH data is the earliest to be released each month.

The official link to the data at UAH can be found here, but most months we get a sneak preview of the release via the climatologist Dr Roy Spencer at his blog.

Spencer, and his colleague John Christy at UAH, are noted climate skeptics. They are also highly qualified climate scientists, who believe that natural climate variability accounts for most of recent warming. If they are correct, then we should see some flattening or even reversal of the upward trend within the UAH temperature time series over a long time period. To date, we haven’t (click for larger image).

UAH Satellite-Based Temperature November 2013 jpeg

That said, we also haven’t seen an exponential increase in temperature either, which would be required for us to reach the more pessimistic temperature projections for end of century. However, the data series is currently too short to rule out such rises in the future.

One of the initial reasons for publicising this satellite-based data series was due to concerns over the accuracy of terrestrial-based measurements (worries over the urban heat island effect and other factors). The satellite data series have now been going long enough to compare the output directly with the surface-based measurements. All the time series are now accepted as telling the same story (for a fuller mathematical treatment of this, see Tamino’s post at the Open Mind blog here).

Note that the anomalies produced by different organisations are not directly comparable since they have different base periods. Accordingly, to compare them directly, you need to normalise each one by adjusting them to a common base period.