Adios, Global Warming

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The post below updates the UAH record of air temperatures over land and ocean.  But as an overview consider how recent rapid cooling has now completely overcome the warming from the last 3 El Ninos (1998, 2010 and 2016).  The UAH record shows that the effects of the last one are now gone as of April 2021. (UAH baseline is now 1991-2020).

UAH Global 1995to202104 w co2 overlayFor reference I added an overlay of CO2 annual concentrations as measured at Moana Loa.  While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~55 ppm, a 15% increase.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

 

gmt-warming-events

The animation is an update of a previous analysis from Dr. Murry Salby.  These graphs use Hadcrut4 and include the 2016 El Nino warming event.  The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4.  This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C.  Previously the 1997-98 El Nino produced a plateau increase of 0.4C.  Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate.  On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles. 

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See Also Worst Threat: Greenhouse Gas or Quiet Sun?

April Update Ocean and Land Air Temps Continue Down

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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 chilly temperatures setting in all regions.  Last month it was the ocean cooling off dramatically.

UAH has updated their tlt (temperatures in lower troposphere) dataset for April.  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. Unusually, last month showed air over land remained cool, while oceans dropped down further.

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.  Thus the cooling oceans now portend cooling land air temperatures to follow.  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 updates Spring 2020, May resumed a pattern of HadSST updates toward the following month end.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for April.  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.

UAH Oceans 202104Note 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. An additional drop in March has SH matching the coldest in this period. March drops in the Tropics and NH make those regions at their coldest since 01/2015.  In April despite an uptick in NH, the Global anomaly dropped further.

 

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 April is below.

UAH Land 202104

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.  In February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  March continued to show all regions roughly comparable to early 2015, prior to the 2016 El Nino.  Then in April NH land dropped sharply along with the Tropics, bringing Global Land anomaly down by nearly 0.2C.  With NH having most of the land mass, it’s possible the additional Polar Vortex events drove air temps downward last month.

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202104

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.

March 2021 Ocean Chill Deepens

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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 chilly temperatures setting in all regions.  Last month it was the ocean cooling off dramatically.

UAH has updated their tlt (temperatures in lower troposphere) dataset for March.  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. Unusually, last month showed air over land remained cool, while oceans dropped down further.

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.  Thus the cooling oceans now portend cooling land air temperatures to follow.  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 updates Spring 2020, May resumed a pattern of HadSST updates toward the following month end.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for February. 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.

UAH Oceans 202103

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. An additional drop in March has SH matching the coldest in this period. March drops in the Tropics and NH make those regions at their coldest since 01/2015.

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 March is below.

UAH Land 202103Here 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.  In February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  March continued to show all regions roughly comparable to early 2015, prior to the 2016 El Nino.  With NH having most of the land mass, it’s possible the February Polar Vortex event drove air temps downward last month.

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202103The 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.

Feb. 2021 Cooling Land, Warming 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 February.  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. Unusually, last month showed air over land chilled (Polar Vortex?) while oceans warmed slightly.

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 February. 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 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. In February the Tropics stayed cold, while both NH and SH rebounded with warming, pulling the Global anomaly up slightly.

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 February 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. Now in February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  All regions are roughly comparable to early 2015, prior to the 2016 El Nino.  With NH having most of the land mass, it’s possible the February Polar Vortex event drove air temps downward last month.

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.

Updated: Global Warming Ends 2021

The animation is an update of a previous analysis from Dr. Murry Salby.  These graphs use Hadcrut4 and include the 2016 El Nino warming event.  The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4.  This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C.  Previously the 1997-98 El Nino produced a plateau increase of 0.4C.  Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate.  On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles. Moreover, the UAH record shows that the effects of the last one are now gone as of January 2021. Updated to March 2021 (UAH baseline is now 1990-2020)

UAH Global 1995to202103

The 2016 El Nino persisted longer than 1998, and was followed by warming after effects in NH.  The monthly anomaly as 2021 begins is matching the 0.04C average since 1995, an ENSO neutral year prior to the second warming event discussed above. With a quiet sun and cooling oceans, the prospect is for cooler times ahead.

Postscript:  Article by Dr. Arnd Bernaerts regarding ENSO and Climate Models

At Oceans Govern Climate Arnd writes Instead of El Niño, La Niña 2020/21 came. 

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He summarizes in this way (in italics with my bolds):

Although ENSO is a long-known climate phenomenon, climatologists still follow the view of the meteorologists 100 years ago, according to which the atmosphere is at the center of all-weather events. They are generously willing to acknowledge that the oceans play an important role, but not that ocean temperatures and their contribution to atmospheric humidity are the most crucial factors. This can be seen in the example of ENSO. Although small in oceanic proportions, the weather above can have long distance effects. Once it happen, e.g. due to a lack of trade winds, the triggering cause remains the changes in equatorial water temperatures.

The attempt to use computer models and weather observation data, by atmosphere-ocean coupling, ENSO forecasts failed with the 2020/2021 forecast and will not achieve what would be necessary in the future either.

What is needed is twofold: (a) much more ocean data , and (b) acknowledging the supremacy of the oceans in climatic change matters. 

No ocean area is as intensive observed as the Equatorial Eastern Pacific (EEP), well over 40 years. Since recently the Tropical Pacific Observing System, TPOS 2020, sustained sampling network is the “backbone” of the system, (Details: WMO). Whether this system can even provide nearly enough oceanic data to make predictions about what is going on under the sea surface cannot be judged here, but it is unlikely and for a long time.

So the other problem remains, the climatologists’ narrow view on the atmosphere. The authors of the El Nino forecast for 2020/21 failed because they lacked the insight that without comprehensive marine data, their model calculations are at best speculations. At least this conclusion should be drawn from their dramatic false prognosis.

In conclusion climatology should realize, that any ocean space, whether in size of a few hundred square miles or as covered by ENSO, plays an important role in climate matters, and that the latter should be regarded as a gift, to understand the mechanism quicker, on who is driving the climate.

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.

Global Warming Ends

The animation is an update of a previous analysis from Dr. Murry Salby.  These graphs use Hadcrut4 and include the 2016 El Nino warming event.  The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4.  This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C.  Previously the 1994-98 El Nino produced a plateau increase of 0.4C.  Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate.  On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles. Moreover, the UAH record shows that the effects of the last one are now gone.

The 2016 El Nino persisted longer than 1998, and was followed by warming after effects in NH.  The monthly anomaly at 2020 year end is nearly the 0.18C average since 1995, an ENSO neutral year prior to the second warming event discussed above. With a quiet sun and cooling oceans, the prospect is for cooler times ahead.

Big Chill Over Land and Sea with 2020 End

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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 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.

John Christy Rebuts Climatist Fake Smear Job

The cancel culture is driven by fears that a contrary point of view might be truer than one’s own way of thinking.  Dissing the messenger, and deplatforming if possible, is easier than reflection and self-examination.  Thus has John Christy been attacked and recently responded in his quiet and reasonable manner.  The article at AL.com is John Christy: We don’t ‘attack science’.  Excerpts in italics with my bolds.

On Nov 2nd 2020 InsideClimate News (ICN) and AL.com published a fairly long (5,000 words!) profile on the climate research that Dr. Roy Spencer and I perform at The University of Alabama in Huntsville. They spent a good bit of time criticizing our satellite data as well as my personal life. The article seems schizophrenic at times, bouncing from highly critical assertions to a depiction of me as a sort of nice, hardworking, churchgoing Alabama scientist.

A major problem here is the technique of quoting antagonists of our work, without giving us a chance to respond. This is the modus operandi of advocacy-journalism. Add to that the numerous editorialized opinions such as, “… Christy’s data have been corrected repeatedly and his conclusions contradicted time and again …” A look at the record indicates this is not so.

But with all of the misleading claims, I’m able to forgive the reporters because they also say, “… he looks 69 going on 50 …” Awesome. How could a 69-year-old not love that?

Unfortunately, ICN ran the story as part of series called “The Anti-Scientists” that explores “the Trump Administration’s attacks on the science underlying environmental protections.” However, kudos to AL.com for including a link to my congressional testimony so the reader could hear my on-the-record story.

It should be clear to all that this agendized “hit-piece” (as we call it), is designed to discredit me, but the truth is, we don’t “attack science,” we “employ science.” Now, I’ve always been told, never pick a fight with someone who buys ink (cloud-storage) by the barrel (terabyte), but here it goes.

In 1990, Roy and I created and today still publish monthly values of the global temperature of three atmospheric layers from satellite measurements. A 1997 paper suggested our dataset had abrupt “downward” jumps. In response, we demonstrated the purported jumps were found in the sea water temperatures they used, not in the deep atmosphere we measured – so they were mixing apples and oranges. The next claim stating there are gaps in the satellite record is just false as every new satellite is directly calibrated to a satellite already in orbit. Later, scientists in Washington State misled the community with papers that (1) allegedly discovered “contamination” of one of our products by stratospheric influence, and (2) that our correction to account for the satellite’s east-west drift over time was wrong.

Neither complaint applied to our datasets. We had always published accurate representations of what our products measured including the stratospheric impact.

In fact, 12 years earlier we created one without the stratospheric influence to deal with this issue directly. The second complaint was moot because we had already adopted an advanced, observations-based adjustment for the east-west drift, while their proposed model-based correction had serious problems.

Early on, though, the very clever scientists at Remote Sensing Systems in California discovered two issues with our dataset, both of which were immediately remedied 15 and 20 years ago respectively with only very small impacts.

While we recognize no dataset is perfect, a detailed evaluation of our temperature products was published in 2018, demonstrating that ours outperforms other satellite products when compared against independent data. Why was this not mentioned?

Another scientist appears to refute our explicit conclusion that climate models are unrealistically aggressive in depicting the atmosphere’s warming rate. This is important because regulatory policies advocated in the media which include price-hikes for all our energy, are based on fears engendered by these models.

Again, our conclusion has stood the test of time, (that scientist published a similar result later). Even this year, more published studies continue to show climate models are poor tools for policy decision—they can’t reproduce the climate that has already happened, and they don’t agree with each other about the future.

Then, the clumsy attempt to connect me with an anti-evolution movement was misguided. The reporters would be chagrined to learn that I had testified before the Alabama State Board of Education advocating the removal of the “Evolution Disclaimer” from biology textbooks. Even the NY Times, of all places, took note and quoted me on the issue (Feb. 1, 2005.) So again, doing a little fact-checking rather than following today’s “jump-to-(my-biased)-conclusion” reporting style, would have saved us all some trouble.

Finally, a broader question to ask is this, “Why was so much effort and expense proffered to try to discredit a scientist like me?”

By the way, the title, “When Trump’s EPA needed a climate scientist, they called on Alabama’s John Christy” misinforms. I saw a federal notice asking for applications for the EPA Science Advisory Board and sent mine in, just like the others. I was eventually selected, based on my credentials, to be one of its 45 members.

But, the line that still carries the day for me is, ” … he looks 69 going on 50.”

Footnote:  Christy quote:

“The reason there is so much contention regarding “global warming” is relatively simple to understand: In climate change science we basically cannot prove anything about how the climate will change as a result of adding extra greenhouse gases to the atmosphere.

So we are left to argue about unprovable claims.”

John R. Christy | Climate science isn’t necessarily ‘settled’

See also: Christy’s Common Sense about Climate

Note: John Christy of the University of Alabama at Huntsville testified before the House of Representatives Natural Resources Committee on May 13, 2015, but his opening statement has been purged from the committee’s website.  In addition to the video above, his statement that day is available here.