2021 Starts with Cool Land and Sea

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With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with all regions heading down.

UAH has updated their tlt (temperatures in lower troposphere) dataset for January.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Note:  UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021.  In the charts below, the trends and fluctuations remain the same but the anomaly values change with the baseline reference shift.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

After a technical enhancement to HadSST3 delayed March and April updates, May resumed a pattern of HadSST updates mid month.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for January. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the new and current dataset.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

To enlarge open image in new tab.

Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. End of 2020 November and December ocean temps plummeted in NH and the Tropics. In January SH dropped sharply, pulling the Global anomaly down despite an upward bump in NH. Both SH and the Tropics are now as cold as any time in the last five years, and all regions are comparable to to 2015 prior to the 2016 El Nino event.

Land Air Temperatures Tracking Downward in Seesaw Pattern

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for January is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a 2020 spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months.  In December all of that was wiped out. Then January showed a sharp drop in SH, but a rise in NH more than offset, pulling the Global anomaly upward. All regions are roughly comparable to early 2015, prior to the 2016 El Nino.

The Bigger Picture UAH Global Since 1995

The chart shows monthly anomalies starting 01/1995 to present.  The average anomaly is 0.04, since this period is the same as the new baseline, lacking only the first 4 years.  1995 was chosen as an ENSO neutral year.  The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20, with temps now returning again to the mean.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

Big Chill Over Land and Sea with 2020 End

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with all regions heading down.

UAH has updated their tlt (temperatures in lower troposphere) dataset for December.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

After a technical enhancement to HadSST3 delayed March and April updates, May resumed a pattern of HadSST updates mid month.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for December. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the new and current dataset.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

Note 2020 is warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. Now in 2020 November and December ocean temps are plummeting in NH and the Tropics, while SH is little changed. Both NH and the Tropics are now as cold as any time in the last five years, and all regions are comparable to to 2015 prior to the 2016 El Nino event.

Land Air Temperatures Tracking Downward in Seesaw Pattern

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for December is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months. Now in December all of that has been wiped out. All regions are comparable to early 2015, prior to the 2016 El Nino.

The Bigger Picture UAH Global Since 1995

The chart shows monthly anomalies starting 01/1995 to present.  The average anomaly is 0.18, which was typical after the 1998 El Nino ended, and again after the smaller 2010 event. The 2016 El Nino matched 1998 with NH after effects lasting longer, followed by the NH warming 2019-20, with temps now returning again to the mean.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

Setting the Global Temperature Record Straight

Figure 4. As in Fig. 3 except for seasonal station and global anomalies. As noted in the text, the inhabitants of the Earth experience the anomalies as noted by the black circles, not the yellow squares.

The CO2 Coalition does the world a service by publishing a brief public information about the temperature claims trumpeted in the media to stir up climate alarms.  The pdf pamphlet is The Global Mean Temperature Anomaly Record  How it works and why it is misleading by Richard S. Lindzen and John R. Christy.  H/T John Ray.  Excerpts in italics with my bolds.

Overview

At the center of most discussions of global warming is the record of the global mean surface temperature anomaly—often somewhat misleadingly referred to as the global mean temperature record. This paper addresses two aspects of this record. First, we note that this record is only one link in a fairly long chain of inference leading to the claimed need for worldwide reduction in CO2 emissions. Second, we explore the implications of the way the record is constructed and presented, and show why the record is misleading.

This is because the record is often treated as a kind of single, direct instrumental measurement. However, as the late Stan Grotch of the Laurence Livermore Laboratory pointed out 30 years ago, it is really the average of widely scattered station data, where the actual data points are almost evenly spread between large positive and negative values.

The average is simply the small difference of these positive and negative excursions, with the usual problem associated with small differences of large numbers: at least thus far, the approximately one degree Celsius increase in the global mean since 1900 is swamped by the normal variations at individual stations, and so bears little relation to what is actually going on at a particular one.

The changes at the stations are distributed around the one-degree global average increase. Even if a single station had recorded this increase itself, this would take a typical annual range of temperature there, for example, from -10 to 40 degrees in 1900, and replace it with a range today from -9 to 41. People, crops, and weather at that station would find it hard to tell this difference. However, the increase looks significant on the charts used in almost all presentations, because they omit the range of the original data points and expand the scale in order to make the mean change look large.

The record does display certain consistent trends, but it is also quite noisy, and fluctuations of a tenth or two of a degree are unlikely to be significant. In the public discourse, little attention is paid to magnitudes; the focus is rather on whether this anomaly is increasing or decreasing. Given the noise and sampling errors, it is rather easy to “adjust” such averaging, and even change the sign of a trend from positive to negative.

The Global Temperature Record and its Role

The earth’s climate system is notoriously complex. We know, for example, that this system undergoes multiyear variations without any external forcing at all other than the steady component of the sun’s radiation (for example, the El Niño Southern Oscillation and the Quasibiennial Oscillation of the tropical stratosphere). We know, moreover, that these changes are hardly describable simply by some global measure of temperature. Indeed, what is presented is actually something else. You may have noticed that it is referred to as the global mean temperature anomaly.

What is being averaged is the deviation of the surface temperature from some 30-year mean at stations non-randomly scattered around the globe. As we will soon see, this average bears rather little relation to the changes at the individual stations. Moreover, as noted by Christy and McNider (2017), the temperature anomaly of the lower troposphere (measured by satellites) relative to the surface temperature is much better sampled and represents the “more climate-relevant quantity of heat content, a change in which is a [theorized] consequence of enhanced GHG forcing.”

However imprecise and lightly-relevant the surface temperature is to the physics of the issue, the narrative of a global warming disaster uses the record as the first in a sequence of often comparably questionable assumptions. The narrative first claims that changes in this dubious metric are almost entirely due to variations in CO2, even though there are quite a few other factors whose common variations are as large as or larger than the impact of changes in CO2 (for example, modest changes in the area of upper and lower level clouds or changes in the height of upper level clouds).

Then the narrative asserts that changes in CO2 were primarily due to man’s activities. There is indeed evidence that this link is likely true for changes over the past two hundred years. However, over Earth’s history, there were radical changes in CO2 levels, and these changes were largely uncorrelated with changes in temperature.

Presentations of the Global Mean Temperature Anomaly Record

In order to obscure the fact that the global means are small residues of large numbers whose precision is questionable, the common presentations plot the global mean anomalies without the scattered points and expand the scale so as to make the changes look large. These expanded graphs of global means are shown in Figures 5 and 6.

Figure 6. Global seasonal anomalies of temperature from Fig. 4 without station anomalies. Note
the range here is -0.8 to +1.2 °C, or 9 times less than Figs. 2 and 4.

The frequently cited trends are evident in these graphs–most notably, the pre-CO2 warming from 1920-1940 and the warming that has been attributed to man from 1978-1998. We also see a reduced rate from 1998 (best seen in Fig. 6) until the major El Niño of 2016 occurred. Even if one could attribute all the 1978-1998 warming to the increases in CO2 , the slowdown clearly shows that there is something going on that is at least as large as the response to CO2 . This contradicts the IPCC attribution studies that assume, based on model results, that other sources of variability since 1950 are negligible.

Note that the results in Figures 5 and 6 are quite noisy, with large interseasonal and interannual fluctuations. This noise contributes to the uncertainty of the values, in addition to the usual sampling errors. The graphs one usually sees are a lot smoother looking than what we see in Figures 5 and 6; these have resulted from taking running means over 5 or more years. The results of such smoothing are shown in Figure 7 (smoothed over 11 years) and 8 (smoothed over 21 seasons, or about 5 years). They look much cleaner and presumably more authoritative than the unsmoothed results or the scatter diagrams, but this tends to disguise the uncertainty, which is likely on the order of 0.1-0.2 degrees. (For example, Figure 7 substantially disguises the pause following 1998; Figure 8 does this less because it is averaged over only about 5 years.)

Obviously, warmings or coolings of a tenth or two of a degree are without significance since possible adjustments can easily lead to changes of sign from positive to negative, yet in the popular literature much is made of such small changes. Like with sausage, you might not want to know what went into these graphs, but, in this case, it is important that you do.

Some Concluding Remarks

An examination of the data that goes into calculating the global mean temperature anomaly clearly shows that any place on earth is almost as likely, at any given time, to be warmer or cooler than average. The anomaly is the small residue of the generally larger excursions we saw in Figures 1 and 2. This residue (which is popularly held to represent “climate”) is also much smaller than the temperature variations that all life on Earth regularly experiences. Figure 9 illustrates this for 14 major cities in the United States.

Indeed, the 1.2 degree Celsius global temperature change in the past 120 years, depicted as alarming in Figure 7, is only equivalent to the thickness of the “Average” line in Figure 9. As the figure shows, the difference in average temperature from January to July in these major cities ranges from just under ten degrees in Los Angeles to nearly 30 degrees in Chicago. And the average difference between the coldest and warmest moments each year ranges from about 25 degrees in Miami (a 45 degree Fahrenheit change) to 55 degrees in Denver (a 99 degree Fahrenheit change)

Figure 9. Temperature Changes People Know How to Handle

At the very least, we should keep the large natural changes in Figure 9 in mind, and not attribute them to the small residue, the global mean temperature anomaly, or obsess over its small changes.

See Also  Temperature Misunderstandings

Clive Best provides this animation of recent monthly temperature anomalies which demonstrates how most variability in anomalies occur over northern continents.

 

 

Nov. 2020 Ocean Air Temps Cooling

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With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for November 2020.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

HadSST3 results will be posted later this month.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for November. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI). In 2015 there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the latest and current dataset, Version 6.0.

The graph above shows monthly anomalies for ocean temps since January 2015. After all regions peaked with the El Nino in early 2016, the ocean air temps dropped back down with all regions showing the same low anomaly August 2018.  Then a warming phase ensued peaking with NH and Tropics spikes in February, and a lesser rise May 2020. As was the case in 2015-16, the warming was driven by the Tropics and NH, with SH lagging behind.

Since the peak in February 2020, all ocean regions have trended downward in a sawtooth pattern, returning to a flat anomaly in the three Summer months, close to the 0.4C average for the period.  A small rise occurred in September, mostly due to SH. In October NH spiked, coincidental with all the storm activity in north Pacific and Atlantic.  Now in November that NH warmth is gone, and the global anomaly declined due also to dropping temps in the Tropics

Land Air Temperatures Showing Volatility.

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for November 2020 is below.

Here we see the noisy evidence of the greater volatility of the Land temperatures, along with extraordinary departures, first by NH land with SH often offsetting.   The overall pattern is similar to the ocean air temps, but obviously driven by NH with its greater amount of land surface. The Tropics synchronized with NH for the 2016 event, but otherwise follow a contrary rhythm.

SH seems to vary wildly, especially in recent months.  Note the extremely high anomaly November 2019,  cold in March 2020, and then again a spike in April. In June 2020, all land regions converged, erasing the earlier spikes in NH and SH, and showing anomalies comparable to the 0.5C average land anomaly this period.  After a relatively quiet Summer, land air temps rose Globally in September with spikes in both NH and SH. In October, the SH spike reversed, but November NH land is showing a warm spike, pulling up the Global anomaly slightly.  Next month will show whether NH land will cool off as rapidly as did the NH ocean temps.

The longer term picture from UAH is a return to the in for the period starting with 1995.  2019 average rose and caused 2020 to start warmly, but currently lacks any El Nino or NH warm blob to sustain it.

These charts demonstrate that underneath the averages, warming and cooling is diverse and constantly changing, contrary to the notion of a global climate that can be fixed at some favorable temperature.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, NH in July more than 1C lower than the 2016 peak.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

Oct. Ocean Air Temps Steady, Despite NH Storm Spike

banner-blog
With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for October 2020.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

HadSST3 results were delayed with February and March updates only appearing together end of April.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for October. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI). In 2015 there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the latest and current dataset, Version 6.0.

The graph above shows monthly anomalies for ocean temps since January 2015. After all regions peaked with the El Nino in early 2016, the ocean air temps dropped back down with all regions showing the same low anomaly August 2018.  Then a warming phase ensued peaking with NH and Tropics spikes in February, and a lesser rise May 2020. As was the case in 2015-16, the warming was driven by the Tropics and NH, with SH lagging behind.

Since the peak in February 2020, all ocean regions have trended downward in a sawtooth pattern, returning to a flat anomaly in the three Summer months, close to the 0.4C average for the period.  A small rise occurred in September, mostly due to SH. Now in October NH spiked, coincidental with all the storm activity in north Pacific and Atlantic.  The global anomaly declined slightly due to dropping temps in SH and Tropics.

Land Air Temperatures Showing Volatility

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for October 2020 is below.

 

Here we see the noisy evidence of the greater volatility of the Land temperatures, along with extraordinary departures, first by NH land with SH often offsetting.   The overall pattern is similar to the ocean air temps, but obviously driven by NH with its greater amount of land surface. The Tropics synchronized with NH for the 2016 event, but otherwise follow a contrary rhythm.

SH seems to vary wildly, especially in recent months.  Note the extremely high anomaly last November, cold in March 2020, and then again a spike in April. In June 2020, all land regions converged, erasing the earlier spikes in NH and SH, and showing anomalies comparable to the 0.5C average land anomaly this period.  After a relatively quiet Summer, land air temps rose Globally in September with spikes in both NH and SH. Now in October, the SH spike has been reversed, driving down the Global anomaly.

The longer term picture from UAH is a return to the mean for the period starting with 1995.  2019 average rose and caused 2020 to start warmly, but currently lacks any El Nino or NH warm blob to sustain it.

These charts demonstrate that underneath the averages, warming and cooling is diverse and constantly changing, contrary to the notion of a global climate that can be fixed at some favorable temperature.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, NH in July more than 1C lower than the 2016 peak.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

Sept. Ocean Air Temps Steady, Land Temps Spike

banner-blog
With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for September 2020.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

HadSST3 results were delayed with February and March updates only appearing together end of April.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for September. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI). In 2015 there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the latest and current dataset, Version 6.0.

The graph above shows monthly anomalies for ocean temps since January 2015. After all regions peaked with the El Nino in early 2016, the ocean air temps dropped back down with all regions showing the same low anomaly August 2018.  Then a warming phase ensued peaking with NH and Tropics spikes in February, and a lesser rise May 2020. As was the case in 2015-16, the warming was driven by the Tropics and NH, with SH lagging behind. Since the peak in February 2020, all ocean regions have trended downward in a sawtooth pattern, returning to a flat anomaly in the three Summer months, close to the 0.4C average for the period.  A small rise occurred in September, mostly due to SH.

Land Air Temperatures Showing Volatility

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for September 2020 is below.

Here we see the noisy evidence of the greater volatility of the Land temperatures, along with extraordinary departures, first by NH land with SH often offsetting.   The overall pattern is similar to the ocean air temps, but obviously driven by NH with its greater amount of land surface. The Tropics synchronized with NH for the 2016 event, but otherwise follow a contrary rhythm.  SH seems to vary wildly, especially in recent months.

Note the extremely high anomaly last November, cold in March 2020, and then again a spike in April. In June 2020, all land regions converged, erasing the earlier spikes in NH and SH, and showing anomalies comparable to the 0.5C average land anomaly this period.  After a relatively quiet Summer, land air temps rose Globally in September with spikes in both NH and SH.

The longer term picture from UAH is a return to the mean for the period starting with 1995.  2019 average rose and caused 2020 to start warmly, but currently lacks any El Nino or NH warm blob to sustain it.

These charts demonstrate that underneath the averages, warming and cooling is diverse and constantly changing, contrary to the notion of a global climate that can be fixed at some favorable temperature.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, NH in July more than 1C lower than the 2016 peak.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

Potsdam Does a New Hockey Stick Trick

The paper is Setting the tree-ring record straight by Josef Ludescher, Armin Bunde, Ulf Büntgen & Hans Joachim Schellnhuber.  The title is extremely informative, since the trick is to flatten the tree-ring proxies, removing any warm periods to compare with the present.  Excerpts below with my bolds.

Abstract

Tree-ring chronologies are the main source for annually resolved and absolutely dated temperature reconstructions of the last millennia and thus for studying the intriguing problem of climate impacts. Here we focus on central Europe and compare the tree-ring based temperature reconstruction with reconstructions from harvest dates, long meteorological measurements, and historical model data. We find that all data are long-term persistent, but in the tree-ring based reconstruction the strength of the persistence quantified by the Hurst exponent is remarkably larger (h≅1.02) than in the other data (h= 0.52–0.69), indicating an unrealistic exaggeration of the historical temperature variations. We show how to correct the tree-ring based reconstruction by a mathematical transformation that adjusts the persistence and leads to reduced amplitudes of the warm and cold periods. The new transformed record agrees well with both the observational data and the harvest dates-based reconstructions and allows more realistic studies of climate impacts. It confirms that the present warming is unprecedented.

Discussion

Figure 1a shows the tree-ring based reconstruction (TRBR) of central European summer temperatures (Büntgen et al. 2011), together with its 30 year moving average that reveals the long-term temperature variations in the record. Particularly large temperature increases occurred between 1340 and 1410 and between 1820 and 1870 that even are comparable in amplitude with the recent warming trend since 1970, indicating that the recent (anthropogenic) warming may not be unprecedented.

Tree ring-based reconstruction of the central European temperatures in the last millennium. a The reconstructed June-August temperatures in units of the records standard deviation. The red line depicts the moving average over 30 years. b, c The DFA2 fluctuation functions F(s) and the WT2 fluctuation functions G(s), respectively, for the reconstructed data from a, for monthly observational data (Swiss temperatures from Berkeley Earth, station data from Prague) and the MPI-ESM-P-past1000 model output for central European summer temperatures, from top to bottom. For the TRBR and model data, the time scale s is in years, while for the two observational records, it is in months. Note that in the double logarithmic presentation, the asymptotic slopes (Hurst exponents h) for the reconstruction data (h≅1) and the observational and model data (h≅0.6) differ strongly

To correct the enhanced long-term persistence in the TRBR, we are interested in a mathematical transformation of the data, which lowers the natural long-term persistence while leaving the gross features of the record, the positions of the warm and cold periods, unchanged. We performed the following mathematical transformation to change the original TRBR Hurst exponent h0=1.03 to h1=0.60 and thus to be in line with the observational, harvest and model data. Since this transformation is only suitable for altering a record’s natural long-term persistence, i.e., in the absence of external trends, we transformed the TRBR data between 1000 and 1990, before the current anthropogenic trend became relevant.

Figure 4a compares the transformed TRBR data (blue) with h1=0.6 with the original TRBR data (black). The bold lines are the 30-year moving averages. The figure shows that by the transformation the structure of the original TRBR data is conserved, but the climate variations characterized by the depths of the minima and the heights of the maxima are reduced.

Original and transformed tree-ring proxy temperature record. a Compares the original TRBR record for the period 1000–1990, where the Hurst exponent h is 1.03 (black), with the transformed TRBR record, where h≡h1=0.6 (blue). For better visibility, the transformed TRBR record has been shifted downward by 5 units of its standard deviation. b How the magnitudes of the cold periods in the transformed TRBR record decrease with decreasing Hurst exponent h1. The magnitudes are quantified by the differences of the 30 year moving averages between the beginning and the end of the respective periods. c Compares the 30-year moving averages of the original and the transformed TRBR record (h=0.6) with the 30-year moving average of the observational temperatures from Switzerland. The comparison shows that the transformed TRBR record fits quite nicely with the observational data

To see how the strength of the long-term variations in the transformed TRBR data depends on their Hurst exponent h1h1, we have determined, in the 30-year moving average, the temperature differences in 4 periods (1415–1465, 1515–1536, 1562–1595, 1793–1824) where the greatest changes between 1350 and 1950 occur. The result is shown in Fig. 4b. The figure shows that the temperature difference between the beginning and the end of each period decreases continuously with decreasing h. For h around 0.6, the temperature differences are roughly halved.

Conclusion

Since tree ring-based reconstructions play an important role in the understanding of past temperature variability, we suggest the use of the Hurst exponent as a standard practice to assess the reconstructions’ low-frequency properties and to compare the determined values with the Hurst exponents of other respective time series (observational, harvest dates, models). If deviations from the expected values are detected, the data should be transformed to adjust the Hurst exponent. This will lead to a more realistic reconstruction of the record’s low-frequency signal and thus to a better understanding of the climate variations of the past.

My Comment

Wow!  Just Wow!  The Mann-made Hockey Stick was found bogus because it was produced by grafting a high-resolution instrumental temperature record on top of a low-resolution tree ring proxy record.  Now climatists want to erase four bumps in the Medieval period lest they appear comparable to contemporary temperatures sampled minute by minute.  A simple tweaking of a formula achieves the desired result.  Fluctuations which were decadal are now smoothed and cannot compete with modern annual and monthly extremes.  Well done! (extreme snark on)

Background:  See Return of the Hockey Stick

N. Atlantic August 2020

RAPID Array measuring North Atlantic SSTs.

For the last few years, observers have been speculating about when the North Atlantic will start the next phase shift from warm to cold. The way 2018 went and 2019 followed suggested this may be the onset.  However, 2020 started out against that trend and is matching 2016 the last warm year.  First some background.

. Source: Energy and Education Canada

An example is this report in May 2015 The Atlantic is entering a cool phase that will change the world’s weather by Gerald McCarthy and Evan Haigh of the RAPID Atlantic monitoring project. Excerpts in italics with my bolds.

This is known as the Atlantic Multidecadal Oscillation (AMO), and the transition between its positive and negative phases can be very rapid. For example, Atlantic temperatures declined by 0.1ºC per decade from the 1940s to the 1970s. By comparison, global surface warming is estimated at 0.5ºC per century – a rate twice as slow.

In many parts of the world, the AMO has been linked with decade-long temperature and rainfall trends. Certainly – and perhaps obviously – the mean temperature of islands downwind of the Atlantic such as Britain and Ireland show almost exactly the same temperature fluctuations as the AMO.

Atlantic oscillations are associated with the frequency of hurricanes and droughts. When the AMO is in the warm phase, there are more hurricanes in the Atlantic and droughts in the US Midwest tend to be more frequent and prolonged. In the Pacific Northwest, a positive AMO leads to more rainfall.

A negative AMO (cooler ocean) is associated with reduced rainfall in the vulnerable Sahel region of Africa. The prolonged negative AMO was associated with the infamous Ethiopian famine in the mid-1980s. In the UK it tends to mean reduced summer rainfall – the mythical “barbeque summer”.Our results show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres – the intergyre region. This a major influence on the wind patterns and the heat transferred between the atmosphere and ocean.

The observations that we do have of the Atlantic overturning circulation over the past ten years show that it is declining. As a result, we expect the AMO is moving to a negative (colder surface waters) phase. This is consistent with observations of temperature in the North Atlantic.

Cold “blobs” in North Atlantic have been reported, but they are usually winter phenomena. For example in April 2016, the sst anomalies looked like this

But by September, the picture changed to this

And we know from Kaplan AMO dataset, that 2016 summer SSTs were right up there with 1998 and 2010 as the highest recorded.

As the graph above suggests, this body of water is also important for tropical cyclones, since warmer water provides more energy.  But those are annual averages, and I am interested in the summer pulses of warm water into the Arctic. As I have noted in my monthly HadSST3 reports, most summers since 2003 there have been warm pulses in the north Atlantic, and 2020 is another of them.

The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N.  The graph shows the warmest month August beginning to rise after 1993 up to 1998, with a series of matching years since.  The El Nino years of 2010 and 2016 are obvious, now matched by 2020, but without the Pacific warming.

Because McCarthy refers to hints of cooling to come in the N. Atlantic, let’s take a closer look at some AMO years in the last 2 decades.

The 2020 North Atlantic Surprise
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line was at the bottom of all these tracks.  2019 began slightly cooler than January 2018, then tracked closely before rising in the summer months.  Through December 2019 tracked warmer than 2018 but cooler than other recent years in the North Atlantic.

In 2020 following a warm January, N. Atlantic temps in February, March and April were the highest in the record. Now Summer 2020 temps are as as 2016 and 2017.  That is a concern for the current hurricane season, along with the lack of a Pacific El Nino providing wind shear against developing tropical storms.

More recently, temps in higher Atlantic latitudes (45N to 65N) have warmed rapidly, as shown in this graph and map from Tropical Tidbits (Levi Cowan)

Footnote:  Levi Cowan’s Tropical Tidbits is an excellent source of information regarding tropical storm activity, even before disturbances are assigned names, as well as ones like tropical storm Paulette now in mid-Atlantic moving toward the US east coast.

August Land and Ocean Air Temps Stay Cool

banner-blog
With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for August 2020.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

HadSST3 results were delayed with February and March updates only appearing together end of April.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for August. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI). In 2015 there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the latest and current dataset, Version 6.0.

The graph above shows monthly anomalies for ocean temps since January 2015. After all regions peaked with the El Nino in early 2016, the ocean air temps dropped back down with all regions showing the same low anomaly August 2018.  Then a warming phase ensued with NH and Tropics spikes in February and May 2020. As was the case in 2015-16, the warming was driven by the Tropics and NH, with SH lagging behind. Since the peak in January 2020, all ocean regions have trended downward in a sawtooth pattern, returning to a neutral anomaly in June, close to the 0.4C average for the period. July and August are little changed with NH and SH offsetting slight bumps.

Land Air Temperatures Showing Volatility

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for August 2020 is below.

 

Here we see the noisy evidence of the greater volatility of the Land temperatures, along with extraordinary departures, first by NH land with SH often offsetting.   The overall pattern is similar to the ocean air temps, but obviously driven by NH with its greater amount of land surface. The Tropics synchronized with NH for the 2016 event, but otherwise follow a contrary rhythm.  SH seems to vary wildly, especially in recent months.  Note the extremely high anomaly last November, cold in March 2020, and then again a spike in April. In June 2020, all land regions converged, erasing the earlier spikes in NH and SH, and showing anomalies comparable to the 0.5C average land anomaly this period.

After an upward bump In July SH, land air temps in August returned to the same flat result from the prior month.

The longer term picture from UAH is a return to the mean for the period starting with 1995.  2019 average rose and caused 2020 to start warmly, but currently lacks any El Nino or NH warm blob to sustain it.

These charts demonstrate that underneath the averages, warming and cooling is diverse and constantly changing, contrary to the notion of a global climate that can be fixed at some favorable temperature.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, NH in July more than 1C lower than the 2016 peak.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

It’s Heat Records Silly Season

Photo illustration by Slate. Photos by Thinkstock.

A glance at the news aggregator shows the silly season is in full swing.  A partial listing of headlines proclaiming the hottest whatever.

  • Record-crushing heat, fire tornadoes and freak thunderstorms: The weather is wild in the West The Washington Post15:50
  • Tesla asks owners to help ‘relieve stress on grid’ during heat wave in California, charge… Electrek15:47
  • Death Valley’s 130-degree Heat Wave May Have Set a 107-year Record Travel & Leisure
  • Newsom Signs Emergency Proclamation to Free Up Energy Amid Heat Wave NBC Bay Area, California14:10
  • Dozens of heat records set to be broken this week as Western heat wave continues CNN14:10
  • Okanagan weather: Mid-30 degree heat to continue for early part of week Global News13:58
  • Heat Wave To Continue Through Thursday In San Diego County Patch13:40
  • Death Valley hits an insane 130 degrees, threatens heat records CNET13:18
  • Sunday brings more record highs as heat lingers Ventura County Star, California EU13:08
  • As West Coast Faces Historic Heat Wave & Energy Shortages, Governor Newsom Signs Heat Emergency Proclamation to Free Up … California State Portal (Press Release)13:00
  • California in grip of extreme weather: Broiling heat, fire tornadoes, lightning, blackouts Los Angeles Times11:29
  • Heat Wave Harvey? Push To Name Extreme Heat Events Warming Up KUER-FM11:20
  • Heat warnings posted for parts of B.C. as temperature records tumble The Globe and Mail10:49
  • Heat warnings issued for most of Alberta CBC.ca10:46
  • US heat wave leads to ‘hottest temperature ever’ and firenados CBBC Newsround07:34
  • 2019 State of the Climate Report: Peak greenhouse gases and record heat EarthSky06:56
  • Should We Name Heat Waves Like We Name Hurricanes? Planet Friendly News06:41
  • Meteorologists are extending the heat warning Prague Monitor04:35
  • Worst Heat Wave in Years Sets Three Temperature Records in LA County NBC Los Angeles02:35
  • Worst Heat in 70 Years Threatens to Take Down California’s Grid BNN Bloomberg02:15
  • Heat Wave Grips S. Korea KBS World Radio00:54
  • Records Tumble As San Francisco Bay Area Swelters Under Stifling Heat Wave CBS San Francisco23:31 Sun, 16 Aug
  • Sofia Richie Beats Southern California Heat Wave At The Beach In Pink Thong Bikini The Inquisitr23:25 Sun, 16 Aug
  • After Record Breaking Heat, A Gradual Cooldown In Washington Patch23:21 Sun, 16 Aug
  • Heat waves, tropical nights to continue this week The Korea Herald22:47 Sun, 16 Aug
  • Thunderstorms and excessive heat fuel wildfires in California CBS News22:21 Sun, 16 Aug
  • Heat wave grips South Korea as monsoon season ends Bernama22:14 Sun, 16 Aug
  • Las Vegas reaches 113 again, ties 1939 record as heat wave continues Las Vegas Review-Journal22:04 Sun, 16 Aug
  • This past decade was the hottest decade in Earth’s history CNN03:50 Fri, 14 Aug
  • Last Decade Was Earth’s Hottest On Record UNILAD13:27 Thu, 13 Aug
    111-Degree High Forecasted Next Week, Would Be One Of
  • Sacramento’s Hottest Days Ever CBS Sacramento13:27 Thu, 13 Aug
  • NWS warns this will be the ‘hottest weekend of the year’ in… San Antonio Express, Texas11:46 Thu, 13 Aug
  • July 2020 was record hot for N. Hemisphere, 2nd hottest for planet National Oceanic and Atmospheric Administration10:59 Thu, 13 Aug
  • London is experiencing its hottest weather since the ’60s Time Out London10:49 Thu, 13 Aug
  • Record shattered for hottest week in Dutch history NL Times10:29 Thu, 13 Aug
  • Belgium records hottest week in history Anadolu Agency10:00 Thu, 13 Aug
  • The 2010s were Earth’s hottest decade on record TheJournal.ie07:25 Thu, 13 Aug
  • Last year was one of the hottest since records began, ending the hottest decade SBS22:21 Wed, 12 Aug
  • 2019 the hottest year on earth since records began, ending the hottest decade SBS21:51 Wed, 12 Aug
  • Last decade was hottest on record as climate crisis accelerates The Independent21:25 Wed, 12 Aug
  • Hottest night in 25 YEARS recorded in Reading Reading Chronicle14:03 Wed, 12 Aug
  • London sees hottest stretch since 1960s BBC12:09 Wed, 12 Aug
  • Last decade was Earth’s hottest on record as climate crisis accelerates The Guardian11:56 Wed, 12 Aug

Time for some Clear Thinking about Heat Records (Previous Post)

Here is an analysis using critical intelligence to interpret media reports about temperature records this summer. Daniel Engber writes in Slate Crazy From the Heat

The subtitle is Climate change is real. Record-high temperatures everywhere are fake.  As we shall see from the excerpts below, The first sentence is a statement of faith, since as Engber demonstrates, the notion does not follow from the temperature evidence. Excerpts in italics with my bolds.

It’s been really, really hot this summer. How hot? Last Friday, the Washington Post put out a series of maps and charts to illustrate the “record-crushing heat.” All-time temperature highs have been measured in “scores of locations on every continent north of the equator,” the article said, while the lower 48 states endured the hottest-ever stretch of temperatures from May until July.

These were not the only records to be set in 2018. Historic heat waves have been crashing all around the world, with records getting shattered in Japan, broken on the eastern coast of Canada, smashed in California, and rewritten in the Upper Midwest. A city in Algeria suffered through the highest high temperature ever recorded in Africa. A village in Oman set a new world record for the highest-ever low temperature. At the end of July, the New York Times ran a feature on how this year’s “record heat wreaked havoc on four continents.” USA Today reported that more than 1,900 heat records had been tied or beaten in just the last few days of May.

While the odds that any given record will be broken may be very, very small, the total number of potential records is mind-blowingly enormous.

There were lots of other records, too, lots and lots and lots—but I think it’s best for me to stop right here. In fact, I think it’s best for all of us to stop reporting on these misleading, imbecilic stats. “Record-setting heat,” as it’s presented in news reports, isn’t really scientific, and it’s almost always insignificant. And yet, every summer seems to bring a flood of new superlatives that pump us full of dread about the changing climate. We’d all be better off without this phony grandiosity, which makes it seem like every hot and humid August is unparalleled in human history. It’s not. Reports that tell us otherwise should be banished from the news.

It’s true the Earth is warming overall, and the record-breaking heat that matters most—the kind we’d be crazy to ignore—is measured on a global scale. The average temperature across the surface of the planet in 2017 was 58.51 degrees, one-and-a-half degrees above the mean for the 20th century. These records matter: 17 of the 18 hottest years on planet Earth have occurred since 2001, and the four hottest-ever years were 2014, 2015, 2016, and 2017. It also matters that this changing climate will result in huge numbers of heat-related deaths. Please pay attention to these terrifying and important facts. Please ignore every other story about record-breaking heat.

You’ll often hear that these two phenomena are related, that local heat records reflect—and therefore illustrate—the global trend. Writing in Slate this past July, Irineo Cabreros explained that climate change does indeed increase the odds of extreme events, making record-breaking heat more likely. News reports often make this point, linking probabilities of rare events to the broader warming pattern. “Scientists say there’s little doubt that the ratcheting up of global greenhouse gases makes heat waves more frequent and more intense,” noted the Times in its piece on record temperatures in Algeria, Hong Kong, Pakistan, and Norway.

Yet this lesson is subtler than it seems. The rash of “record-crushing heat” reports suggest we’re living through a spreading plague of new extremes—that the rate at which we’re reaching highest highs and highest lows is speeding up. When the Post reports that heat records have been set “at scores of locations on every continent,” it makes us think this is unexpected. It suggests that as the Earth gets ever warmer, and the weather less predictable, such records will be broken far more often than they ever have before.

But that’s just not the case. In 2009, climatologist Gerald Meehl and several colleagues published an analysis of records drawn from roughly 2,000 weather stations in the U.S. between 1950 and 2006. There were tens of millions of data points in all—temperature highs and lows from every station, taken every day for more than a half-century. Meehl searched these numbers for the record-setting values—i.e., the days on which a given weather station saw its highest-ever high or lowest-ever low up until that point. When he plotted these by year, they fell along a downward-curving line. Around 50,000 new heat records were being set every year during the 1960s; then that number dropped to roughly 20,000 in the 1980s, and to 15,000 by the turn of the millennium.

From Meehl et al 2009.

This shouldn’t be surprising. As a rule, weather records will be set less frequently as time goes by. The first measurement of temperature that’s ever taken at a given weather station will be its highest (and lowest) of all time, by definition. There’s a good chance that the same station’s reading on Day 2 will be a record, too, since it only needs to beat the temperature recorded on Day 1. But as the weeks and months go by, this record-setting contest gets increasingly competitive: Each new daily temperature must now outdo every single one that came before. If the weather were completely random, we might peg the chances of a record being set at any time as 1/n, where n is the number of days recorded to that point. In other words, one week into your record-keeping, you’d have a 1 in 7 chance of landing on an all-time high. On the 100th day, your odds would have dropped to 1 percent. After 56 years, your chances would be very, very slim.

The weather isn’t random, though; we know it’s warming overall, from one decade to the next. That’s what Meehl et al. were looking at: They figured that a changing climate would tweak those probabilities, goosing the rate of record-breaking highs and tamping down the rate of record-breaking lows. This wouldn’t change the fundamental fact that records get broken much less often as the years go by. (Even though the world is warming, you’d still expect fewer heat records to be set in 2000 than in 1965.) Still, one might guess that climate change would affect the rate, so that more heat records would be set than we’d otherwise expect.

That’s not what Meehl found. Between 1950 and 2006, the rate of record-breaking heat seemed unaffected by large-scale changes to the climate: The number of new records set every year went down from one decade to the next, at a rate that matched up pretty well with what you’d see if the odds were always 1/n. The study did find something more important, though: Record-breaking lows were showing up much less often than expected. From one decade to the next, fewer records of any kind were being set, but the ratio of record lows to record highs was getting smaller over time. By the 2000s, it had fallen to about 0.5, meaning that the U.S. was seeing half as many record-breaking lows as record-breaking highs. (Meehl has since extended this analysis using data going back to 1930 and up through 2015. The results came out the same.)

What does all this mean? On one hand, it’s very good evidence that climate change has tweaked the odds for record-breaking weather, at least when it comes to record lows. (Other studies have come to the same conclusion.) On the other hand, it tells us that in the U.S., at least, we’re not hitting record highs more often than we were before, and that the rate isn’t higher than what you’d expect if there weren’t any global warming. In fact, just the opposite is true: As one might expect, heat records are getting broken less often over time, and it’s likely there will be fewer during the 2010s than at any point since people started keeping track.

This may be hard to fathom, given how much coverage has been devoted to the latest bouts of record-setting heat. These extreme events are more unusual, in absolute terms, than they’ve ever been before, yet they’re always in the news. How could that be happening?

While the odds that any given record will be broken may be very, very small, the total number of potential records that could be broken—and then reported in the newspaper—is mind-blowingly enormous. To get a sense of how big this number really is, consider that the National Oceanic and Atmospheric Administration keeps a database of daily records from every U.S. weather station with at least 30 years of data, and that its website lets you search for how many all-time records have been set in any given stretch of time. For instance, the database indicates that during the seven-day period ending on Aug. 17—the date when the Washington Post published its series of “record-crushing heat” infographics—154 heat records were broken.

 

That may sound like a lot—154 record-high temperatures in the span of just one week. But the NOAA website also indicates how many potential records could have been achieved during that time: 18,953. In actuality, less than one percent of these were broken. You can also pull data on daily maximum temperatures for an entire month: I tried that with August 2017, and then again for months of August at 10-year intervals going back to the 1950s. Each time the query returned at least about 130,000 potential records, of which one or two thousand seemed to be getting broken every year. (There was no apparent trend toward more records being broken over time.)

Now let’s say there are 130,000 high-temperature records to be broken every month in the U.S. That’s only half the pool of heat-related records, since the database also lets you search for all-time highest low temperatures. You can also check whether any given highest high or highest low happens to be a record for the entire month in that location, or whether it’s a record when compared across all the weather stations everywhere on that particular day.

Add all of these together and the pool of potential heat records tracked by NOAA appears to number in the millions annually, of which tens of thousands may be broken. Even this vastly underestimates the number of potential records available for media concern. As they’re reported in the news, all-time weather records aren’t limited to just the highest highs or highest lows for a given day in one location. Take, for example, the first heat record mentioned in this column, reported in the Post: The U.S. has just endured the hottest May, June, and July of all time. The existence of that record presupposes many others: What about the hottest April, May and June, or the hottest March, April, and May? What about all the other ways that one might subdivide the calendar?

Geography provides another endless well of flexibility. Remember that the all-time record for the hottest May, June, and July applied only to the lower 48 states. Might a different set of records have been broken if we’d considered Hawaii and Alaska? And what about the records spanning smaller portions of the country, like the Midwest, or the Upper Midwest, or just the state of Minnesota, or just the Twin Cities? And what about the all-time records overseas, describing unprecedented heat in other countries or on other continents?

Even if we did limit ourselves to weather records from a single place measured over a common timescale, it would still be possible to parse out record-breaking heat in a thousand different ways. News reports give separate records, as we’ve seen, for the highest daily high and the highest daily low, but they also tell us when we’ve hit the highest average temperature over several days or several weeks or several months. The Post describes a recent record-breaking streak of days in San Diego with highs of at least 83 degrees. (You’ll find stories touting streaks of daily highs above almost any arbitrary threshold: 90 degrees, 77 degrees, 60 degrees, et cetera.) Records also needn’t focus on the temperature at all: There’s been lots of news in recent weeks about the fact that the U.K. has just endured its driest-ever early summer.

“Record-breaking” summer weather, then, can apply to pretty much any geographical location, over pretty much any span of time. It doesn’t even have to be a record—there’s an endless stream of stories on “near-record heat” in one place or another, or the “fifth-hottest” whatever to happen in wherever, or the fact that it’s been “one of the hottest” yadda-yaddas that yadda-yadda has ever seen. In the most perverse, insane extension of this genre, news outlets sometimes even highlight when a given record isn’t being set.

Loose reports of “record-breaking heat” only serve to puff up muggy weather and make it seem important. (The sham inflations of the wind chill factor do the same for winter months.) So don’t be fooled or flattered by this record-setting hype. Your summer misery is nothing special.

Summary

This article helps people not to confuse weather events with climate.  My disappointment is with the phrase, “Climate Change is Real,” since it is subject to misdirection.  Engber uses that phrase referring to rising average world temperatures, without explaining that such estimates are computer processed reconstructions since the earth has no “average temperature.”  More importantly the undefined “climate change” is a blank slate to which a number of meanings can be attached.

Some take it to mean: It is real that rising CO2 concentrations cause rising global warming.  Yet that is not supported by temperature records.
Others think it means: It is real that using fossil fuels causes global warming.  This too lacks persuasive evidence.
WFFC and Hadcrut 2018Over the last five decades the increase in fossil fuel consumption is dramatic and monotonic, steadily increasing by 234% from 3.5B to 11.7B oil equivalent tons. Meanwhile the GMT record from Hadcrut shows multiple ups and downs with an accumulated rise of 0.74C over 53 years, 5% of the starting value.

Others know that Global Mean Temperature is a slippery calculation subject to the selection of stations.

Graph showing the correlation between Global Mean Temperature (Average T) and the number of stations included in the global database. Source: Ross McKitrick, U of Guelph

Global warming estimates combine results from adjusted records.
Conclusion

The pattern of high and low records discussed above is consistent with natural variability rather than rising CO2 or fossil fuel consumption. Those of us not alarmed about the reported warming understand that “climate change” is something nature does all the time, and that the future is likely to include periods both cooler and warmer than now.

Background Reading:

The Climate Story (Illustrated)

2020 Update: Fossil Fuels ≠ Global Warming

Man Made Warming from Adjusting Data

What is Global Temperature? Is it warming or cooling?