For sure you’ve seen the headlines declaring 2024 likely to be the Hottest year ever. If you’re like me, your response is: That’s not the way it’s going down where I live. Fortunately there is a website that allows anyone to check their personal experience with the weather station data nearby. weatherspark.com provides data summaries for you to judge what’s going on in weather history where you live. In my case a modern weather station is a few miles away April 2024 Weather History at Montréal–Mirabel International Airport. The story about April 2024 is evident below in charts and graphs from this site. There’s a map that allows you to find your locale.
First, consider above the norms for April from the period 1980 to 2016.
Then, there’s April 2024 compared to the normal observations.
The graph shows April had some warm days, some cool days and overall was pretty normal. But since climate is more than temperature, consider cloudiness.
Woah! Most of the month was cloudy, which in spring means blocking the warming sun from hitting the surface. And with all those clouds, let’s look at precipitation:
So, a major snowstorm April 3-4, 12 days when it rained, including heavy rain, and a couple of thunderstorms. Given what we know about the hydrology cycles, that means a lot of heat removed upward from the surface.
So the implications for April temperatures in my locale.
There you have it before your eyes. Mostly Cool, Cold and
Very Cold, with freezing on numerous mornings.
Only five days with a few hours of comfortable temperatures.
Summary:
Claims of hottest this or that month or year are based on averages of averages of temperatures, which in principle is an intrinsic quality and distinctive to a locale. The claim involves selecting some places and time periods where warming appears, while ignoring other places where it has been cooling.
Remember: They want you to panic. Before doing so, check out what the data says in your neck of the woods. For example, NOAA declared that March 2024 was “Earth’s Warmest March on Record.”
Fig. 1: Common Era temperature reconstructions
featured in IPCC reports since 2001.
Source Esper et al 2024 Note: In each graph, instrumental global annual mean land and marine temperatures are shown in a red spike, while lower resolution proxy estimates are in blue.
Common Era temperature variability has been a prominent component in Intergovernmental Panel on Climate Change reports over the last several decades and was twice featured in their Summary for Policymakers. A single reconstruction of mean Northern Hemisphere temperature variability was first highlighted in the 2001 Summary for Policymakers, despite other estimates that existed at the time. Subsequent reports assessed many large-scale temperature reconstructions, but the entirety of Common Era temperature history in the most recent Sixth Assessment Report of the Intergovernmental Panel on Climate Change was restricted to a single estimate of mean annual global temperatures. We argue that this focus on a single reconstruction is an insufficient summary of our understanding of temperature variability over the Common Era. We provide a complementary perspective by offering an alternative assessment of the state of our understanding in high-resolution paleoclimatology for the Common Era and call for future reports to present a more accurate and comprehensive assessment of our knowledge about this important period of human and climate history.
Fig. 5: Standard deviations in observed temperature data
and Common Era temperature reconstructions.
Estimates for the observed and reconstructed temperatures are determined over the 1878-2000 CE (blue), 1001-1877 CE (orange) and 1-1000 CE (gray) periods. Instrumental records shown on the left side include mean annual temperatures averaged over 90°S-90°N land and marine areas (global), mean annual temperatures averaged over 0°−90°S land and marine areas (SH), and mean summer (JJA) temperatures averaged over 30°−90°N land-only areas (NH).
While interpretations of the similarities and differences across the various domains and reconstructions, as shown in Fig. 5, remains the subject of important and interesting research, diagnosing the differences is not the focus of our commentary herein. Our primary concern is that substantial uncertainty exists. The consequence is that there are notable differences in the representation of large-scale estimates of CE temperature variability, as shown in Figs. 2 and 3, that were overlooked and poorly communicated by the 2021 IPCC WGI report. Both the different summary of the global P2k19 ensemble provided in Figs. 2b and 3c, and the inclusion of the additionally available NH and SH temperature reconstruction estimates in Fig. 3, imply substantial uncertainties in large-scale temperature reconstructions that better summarize the existing challenges associated with the science.
Fig. 3: Reconstructions of large-scale temperature variability
over the last 2000 years published since AR5 of the IPCC.
Reconstructions variably target seasonal to annual mean temperatures in the (a) Northern Hemisphere (Sch15, Sto15, Wil16, Xin16, Gui17, Bün20), and annual temperatures for the (b) Southern Hemisphere (Neu14) and (c) globally (P2k19; as shown in Fig. 2) over varying periods of the Common Era (see Table 1 for details). All reconstructions were smoothed using a 20-year low-pass filter and temperatures are shown as anomalies from their 1850–1900 means. Hemispheric and global means of land and ocean temperatures derived from HadCRUT5 instrumental analysis1 are also shown in each respective panel from 1850-2020 (red). Instrumental temperatures were also referenced to zero mean in the 1850–1900 interval and filtered with a 20-year lowpass filter. These instrumental representations are all consistent with the 2021 IPCC report.
Conclusions and future priorities
We propose that a visualization of the contemporary research, as in Fig. 3, offers a more accurate depiction of the uncertainty and temporal evolution of CE temperature variability compared to any single reconstruction. A general feature of Fig. 3 is that long-term trends during the second millennium CE are more coherent and robust, but major discrepancies still exist during the first millennium CE. These uncertainties in the first millennium are the product of severe reductions in the availability of high-resolution proxy records, which affects all large-scale temperature reconstructions. The SH also remains grossly under-sampled.
It is therefore premature, and possibly incorrect, to conclude that
the first millennium was free of centennial-scale temperature trends
and that the decadal variations were systematically smaller
than during subsequent centuries, as detailed in the 2021 SPM.
Regarding global temperature reconstructions specifically, we also highlight the following limitations that must continue to be contextualized in consensus reports on CE temperature reconstructions:
(i) warm season biases due to the dominance of tree-ring records during the CE, (ii) spatial biases in proxy sampling, with a persistent lack of high-resolution proxy records from the tropics and SH, which are needed for accurately representing lower-latitude and SH temperatures over the past 2000 years, (iii) the likely loss of variability when including time-uncertain and smoothed proxies in a large-scale reconstruction, (iv) the potential limited ability of conventional tree-ring records to capture millennial-scale trends in climate, and (v) the need to more accurately estimate reconstruction uncertainties that reflect changes in replication and statistical model fidelity of the underlying proxy network back in time (a constant uncertainty range back in time is unlikely to accurately represent the increasing uncertainties that exist).
With any set of methods, however, their outcome is ultimately dependent on the data that they incorporate and the assumptions that underpin the statistical model. A major initiative to produce new high-resolution proxy records that span the entire CE is therefore necessary if we are to fundamentally improve our understanding of pre-instrumental temperature variations at policy-relevant timescales. It otherwise remains uncertain how warm and cold first millennium CE temperatures actually were and what caused these earlier changes at hemispheric to global scales, with implications for our understanding of the true range of externally and internally forced variability.
The first graph appeared in the IPCC 1990 First Assessment Report (FAR) credited to H.H.Lamb, first director of CRU-UEA. The second graph was featured in 2001 IPCC Third Assessment Report (TAR) the famous hockey stick credited to M. Mann.
The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.
As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Now we have an usual El Nino warming spike of uncertain cause, but unrelated to steadily rising CO2.
For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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.
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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions, with some cooling the last two months.
Update August 3, 2021
Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT
March 2024 El Nino Persists While Oceans Cool, Land Warms
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 heard a lot about 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings, continuing into October, but with cooling since.
UAH has updated their tlt (temperatures in lower troposphere) dataset for March 2024. Posts on their reading of ocean air temps this month precedes updates from HadSST4. I posted last month on SSTs using HadSST4 Ocean Cools as El Nino Recedes February 2024. 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.
Sometimes air temps over land diverge from ocean air changes. November 2023 was notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions. As a result the Global Ocean and Land anomaly result remained little changed. Last month in February 2024, both ocean and land air temps went higher driven by SH, while NH and the Tropics cooled slightly, resulting in Global anomaly matching October 2023 peak. Now in March Ocean anomalies cooled while Land anomalies rose everywhere.
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 changed 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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4. For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for March. 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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October. That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June. After an upward spike in July, ocean air everywhere cooled in August and also in September.
After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.7C, with the largest increases in April to July, and continuing through adding to a new high January 2024. NH also spiked upward to a new high, while Global ocean rise was more modest due to slight SH cooling. In February, NH and Tropics cooled slightly, while greater warming in SH resulted in a small Global rise. Now in March both NH and SH cooled, pulling down the Global anomaly despite a persisting peak in the Tropics.
Land Air Temperatures Tracking 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.
Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land. Land temps are dominated by NH with a 2021 spike in January, then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH.
Remarkably, in 2023, SH land air anomaly shot up 2.1C, from -0.6C in January to +1.5 in September, then dropped sharply to 0.6 in January 2024, matching the SH peak in 2016. Now in February and March SH anomaly jumped up nearly 0.7C, and Tropics went up to a new high of 1.5C, pulling up the Global land anomaly to match 10/2023.
The Bigger Picture UAH Global Since 1980
The chart shows monthly Global anomalies starting 01/1980 to present. The average monthly anomaly is -0.04, for this period of more than four decades. 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. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed
With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Then in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016. December and January were down slightly, and now March is matching the October peak. Where it goes from here, up or down further, remains to be seen, though there is evidence that El Nino is weakening.
The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.
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, nearly 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 HadSST4, but are now showing the same pattern. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.
As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Now we have an usual El Nino warming spike of uncertain cause, but unrelated to steadily rising CO2.
For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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.
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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions, with some cooling the last two months.
Update August 3, 2021
Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT
February 2024 SH Warming Overcomes Cooling Elsewhere
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 heard a lot about 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings, continuing into October, but with cooling since.
UAH has updated their tlt (temperatures in lower troposphere) dataset for February 2024. Posts on their reading of ocean air temps this month comes just after updated records from HadSST4. I posted yesterday on SSTs using HadSST4 Ocean Cools as El Nino Recedes February 2024. 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.
Sometimes air temps over land diverge from ocean air changes. November 2023 was notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions. As a result the Global Ocean and Land anomaly result remained little changed. Last month in February 2024, both ocean and land air temps went higher driven by SH, while NH and the Tropics cooled slightly, resulting in Global anomaly matching October 2023 peak.
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 changed 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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4. For comparison we can also 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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October. That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June. After an upward spike in July, ocean air everywhere cooled in August and also in September.
After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.7C, with the largest increases in April to July, and continuing through adding to a new high January 2024. NH also spiked upward to a new high, while Global ocean rise was more modest due to slight SH cooling. Now in February, NH and Tropics have cooled slightly, while greater warming in SH resulting in a small Global rise.
Land Air Temperatures Tracking 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 extraordinary departures by SH land. Land temps are dominated by NH with a 2021 spike in January, then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH.
Remarkably, in 2023, SH land air anomaly shot up 2.1C, from -0.6C in January to +1.5 in September, then dropped sharply to 0.6 in January 2024, matching the SH peak in 2016. Now in February SH anomaly jumped up nearly 0.4C, pulling up the Global land anomaly despite continuing cooling elsewhere.
The Bigger Picture UAH Global Since 1980
The chart shows monthly Global anomalies starting 01/1980 to present. The average monthly anomaly is -0.04, for this period of more than four decades. 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. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed
With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Then in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016. December and January were down slightly, and now February is matching the October peak. Where it goes from here, up or down further, remains to be seen, though there is evidence that El Nino is weakening.
The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.
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, nearly 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 HadSST4, but are now showing the same pattern. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.
As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Now we have an usual El Nino warming spike of uncertain cause, but unrelated to steadily rising CO2.
For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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.
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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions, with some cooling the last two months.
Update August 3, 2021
Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT
January 2024 El Nino Spikes Higher While Land Cools
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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings, continuing into October, but with cooling since.
UAH has updated their tlt (temperatures in lower troposphere) dataset for January 2024. Posts on their reading of ocean air temps this month preceded updated records from HadSST4. I last posted on SSTs using HadSST4 Ocean Warming Spike Recedes December 2023. 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.
Sometimes air temps over land diverge from ocean air changes. November 2023 was notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions. As a result the Global Ocean and Land anomaly result remained little changed. Now again in January 2024, ocean temps went higher driven by El Nino and NH, while all land regions cooled except for Tropics.
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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4. For comparison we can also 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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October. That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June. After an upward spike in July, ocean air everywhere cooled in August and also in September.
After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.7C, with the largest increases in April to July, and continuing through adding to a new high January 2024. NH also spiked upward to a new high, while Global ocean rise was more modest due to slight SH cooling.
Land Air Temperatures Tracking 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 extraordinary departures by SH land. Land temps are dominated by NH with a 2021 spike in January, then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH.
Remarkably, in 2023, SH land air anomaly shot up 2.1C, from -0.6C in January to +1.5 in September, then dropped sharply, now down to 0.6 in January 2024. NH land temps have also dropped 0.3C down to 1.0C, resulting in Global land temps cooling to 0.9C, matching the peak in Feb. 2016. Land in the Tropics was unchanged in January, down slightly from its October peak.
The Bigger Picture UAH Global Since 1980
The chart shows monthly Global anomalies starting 01/1980 to present. The average monthly anomaly is -0.05, for this period of more than four decades. 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. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed
With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016. December and January are down slightly, but where it goes from here, up or down further, remains to be seen.
The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.
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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.
As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Now we have an usual El Nino warming spike of uncertain cause, but unrelated to steadily rising CO2.
For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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.
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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions, with some cooling the last two months.
Update August 3, 2021
Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT
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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings, continuing into October, but with cooling since.
UAH has updated their tlt (temperatures in lower troposphere) dataset for December 2023. Posts on their reading of ocean air temps this month preceded updated records from HadSST4. I last posted on SSTs using HadSST4 November 2023 Ocean Warmth Persists Due to Tropics 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.
Sometimes air temps over land diverge from ocean air changes. November 2023 was notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions. As a result the Global Ocean and Land anomaly result remained little changed. Now in December, all regions cooled except for Tropics.
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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4. For comparison we can also 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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October. That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June. After an upward spike in July, ocean air everywhere cooled in August and also in September.
After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.5C, with the largest increases in April to July, and continuing through to December 2023. But now both SH and NH have dropped in December, pulling the global average back down despite the El Nino spike in the Tropics.
Land Air Temperatures Tracking 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 extraordinary departures by SH land. Land temps are dominated by NH with a 2021 spike in January, then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH.
Remarkably, in 2023, SH land air anomaly shot up 2.1C, from -0.6C in January to +1.5 in October, then dropped to 0.7 in November, 0.76 in December. Tropical land temps are up 1.6 since January and NH Land air temps rose 0.9, mostly since May. Now in December SH land air temps are little changed while the drop in NH brought the Global anomaly down despite another uptick in Tropical land temps.
The Bigger Picture UAH Global Since 1980
The chart shows monthly Global anomalies starting 01/1980 to present. The average monthly anomaly is -0.05, for this period of more than four decades. 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. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed
With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016. December is down slightly, but where it goes from here, up or down further, remains to be seen.
The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.
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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
This post is about proving that CO2 changes in response to temperature changes, not the other way around, as is often claimed. In order to do that we need two datasets: one for measurements of changes in atmospheric CO2 concentrations over time and one for estimates of Global Mean Temperature changes over time.
Climate science is unsettling because past data are not fixed, but change later on. I ran into this previously and now again in 2021 and 2022 when I set out to update an analysis done in 2014 by Jeremy Shiers (discussed in a previous post reprinted at the end). Jeremy provided a spreadsheet in his essay Murray Salby Showed CO2 Follows Temperature Now You Can Too posted in January 2014. I downloaded his spreadsheet intending to bring the analysis up to the present to see if the results hold up. The two sources of data were:
Uploading the CO2 dataset showed that many numbers had changed (why?).
The blue line shows annual observed differences in monthly values year over year, e.g. June 2020 minus June 2019 etc. The first 12 months (1979) provide the observed starting values from which differentials are calculated. The orange line shows those CO2 values changed slightly in the 2020 dataset vs. the 2014 dataset, on average +0.035 ppm. But there is no pattern or trend added, and deviations vary randomly between + and -. So last year I took the 2020 dataset to replace the older one for updating the analysis.
Now I find the NOAA dataset starting in 2021 has almost completely new values due to a method shift in February 2021, requiring a recalibration of all previous measurements. The new picture of ΔCO2 is graphed below.
The method shift is reported at a NOAA Global Monitoring Laboratory webpage, Carbon Dioxide (CO2) WMO Scale, with a justification for the difference between X2007 results and the new results from X2019 now in force. The orange line shows that the shift has resulted in higher values, especially early on and a general slightly increasing trend over time. However, these are small variations at the decimal level on values 340 and above. Further, the graph shows that yearly differentials month by month are virtually the same as before. Thus I redid the analysis with the new values.
Global Temperature Anomalies (ΔTemp)
The other time series was the record of global temperature anomalies according to RSS. The current RSS dataset is not at all the same as the past.
Here we see some seriously unsettling science at work. The purple line is RSS in 2014, and the blue is RSS as of 2020. Some further increases appear in the gold 2022 rss dataset. The red line shows alterations from the old to the new. There is a slight cooling of the data in the beginning years, then the three versions mostly match until 1997, when systematic warming enters the record. From 1997/5 to 2003/12 the average anomaly increases by 0.04C. After 2004/1 to 2012/8 the average increase is 0.15C. At the end from 2012/9 to 2013/12, the average anomaly was higher by 0.21. The 2022 version added slight warming over 2020 values.
RSS continues that accelerated warming to the present, but it cannot be trusted. And who knows what the numbers will be a few years down the line? As Dr. Ole Humlum said some years ago (regarding Gistemp): “It should however be noted, that a temperature record which keeps on changing the past hardly can qualify as being correct.”
Given the above manipulations, I went instead to the other satellite dataset UAH version 6. UAH has also made a shift by changing its baseline from 1981-2010 to 1991-2020. This resulted in systematically reducing the anomaly values, but did not alter the pattern of variation over time. For comparison, here are the two records with measurements through December 2023.
Comparing UAH temperature anomalies to NOAA CO2 changes.
Here are UAH temperature anomalies compared to CO2 monthly changes year over year.
Changes in monthly CO2 synchronize with temperature fluctuations, which for UAH are anomalies now referenced to the 1991-2020 period. As stated above, CO2 differentials are calculated for the present month by subtracting the value for the same month in the previous year (for example June 2022 minus June 2021). Temp anomalies are calculated by comparing the present month with the baseline month.
The final proof that CO2 follows temperature due to stimulation of natural CO2 reservoirs is demonstrated by the ability to calculate CO2 levels since 1979 with a simple mathematical formula:
For each subsequent year, the co2 level for each month was generated
CO2 this month this year = a + b × Temp this month this year + CO2 this month last year
Jeremy used Python to estimate a and b, but I used his spreadsheet to guess values that place for comparison the observed and calculated CO2 levels on top of each other.
In the chart calculated CO2 levels correlate with observed CO2 levels at 0.9986 out of 1.0000. This mathematical generation of CO2 atmospheric levels is only possible if they are driven by temperature-dependent natural sources, and not by human emissions which are small in comparison, rise steadily and monotonically.
Comment: UAH dataset reported a sharp warming spike starting mid year, with causes speculated but not proven. In any case, that surprising peak has not yet driven CO2 higher, though it might, but only if it persists despite the likely cooling already under way.
Previous Post: What Causes Rising Atmospheric CO2?
This post is prompted by a recent exchange with those reasserting the “consensus” view attributing all additional atmospheric CO2 to humans burning fossil fuels.
The IPCC doctrine which has long been promoted goes as follows. We have a number over here for monthly fossil fuel CO2 emissions, and a number over there for monthly atmospheric CO2. We don’t have good numbers for the rest of it-oceans, soils, biosphere–though rough estimates are orders of magnitude higher, dwarfing human CO2. So we ignore nature and assume it is always a sink, explaining the difference between the two numbers we do have. Easy peasy, science settled.
What about the fact that nature continues to absorb about half of human emissions, even while FF CO2 increased by 60% over the last 2 decades? What about the fact that in 2020 FF CO2 declined significantly with no discernable impact on rising atmospheric CO2?
These and other issues are raised by Murray Salby and others who conclude that it is not that simple, and the science is not settled. And so these dissenters must be cancelled lest the narrative be weakened.
The non-IPCC paradigm is that atmospheric CO2 levels are a function of two very different fluxes. FF CO2 changes rapidly and increases steadily, while Natural CO2 changes slowly over time, and fluctuates up and down from temperature changes. The implications are that human CO2 is a simple addition, while natural CO2 comes from the integral of previous fluctuations. Jeremy Shiers has a series of posts at his blog clarifying this paradigm. See Increasing CO2 Raises Global Temperature Or Does Increasing Temperature Raise CO2 Excerpts in italics with my bolds.
The following graph which shows the change in CO2 levels (rather than the levels directly) makes this much clearer.
Note the vertical scale refers to the first differential of the CO2 level not the level itself. The graph depicts that change rate in ppm per year.
There are big swings in the amount of CO2 emitted. Taking the mean as 1.6 ppmv/year (at a guess) there are +/- swings of around 1.2 nearly +/- 100%.
And, surprise surprise, the change in net emissions of CO2 is very strongly correlated with changes in global temperature.
This clearly indicates the net amount of CO2 emitted in any one year is directly linked to global mean temperature in that year.
For any given year the amount of CO2 in the atmosphere will be the sum of
all the net annual emissions of CO2
in all previous years.
For each year the net annual emission of CO2 is proportional to the annual global mean temperature.
This means the amount of CO2 in the atmosphere will be related to the sum of temperatures in previous years.
So CO2 levels are not directly related to the current temperature but the integral of temperature over previous years.
The following graph again shows observed levels of CO2 and global temperatures but also has calculated levels of CO2 based on sum of previous years temperatures (dotted blue line).
Summary:
The massive fluxes from natural sources dominate the flow of CO2 through the atmosphere. Human CO2 from burning fossil fuels is around 4% of the annual addition from all sources. Even if rising CO2 could cause rising temperatures (no evidence, only claims), reducing our emissions would have little impact.
Addendum:
Roland Van den Broek made the valid point in his comments below that any two data sets generally trending positive will show a high degree of correlation, not proving any causation. Certainly, UAH reports rising GMA (Global Mean Anomalies) and MLO reports rising CO2. Note however that Δ GMA predicts Δ CO2 with a correlation of 0.9986. For comparison, I generated GMA from CO2 differentials, resulting in a lower correlation of 0.6030. I conclude that Δ CO2 ⇒ Δ GMA is spurious, while Δ GMA ⇒ Δ CO2 is real.
With Winter Solstice due this week (December 21) the shortest NH day of the year demonstrates the sun’s role in seasonal climate change. I am reposting an analysis looking into global warming in relation to our empirical knowledge of solar orbital patterns.
From Previous Post When Is It Warming?
On June 21, 2015 E.M. Smith made an intriguing comment on the occasion of Summer Solstice (NH) and Winter Solstice (SH):
“This is the time when the sun stops the apparent drift in the sky toward one pole, reverses, and heads toward the other. For about 2 more months, temperatures lag this change of trend. That is the total heat storage capacity of the planet. Heat is not stored beyond that point and there can not be any persistent warming as long as winter brings a return to cold.
I’d actually assert that there are only two measurements needed to show the existence or absence of global warming. Highs in the hottest month must get hotter and lows in the coldest month must get warmer. BOTH must happen, and no other months matter as they are just transitional.
I’m also pretty sure that the comparison of dates of peaks between locations could also be interesting. If one hemisphere is having a drift to, say, longer springs while the other is having longer falls, that’s more orbital mechanics than CO2 driven and ought to be reflected in different temperature trends / rates of drift.” Source: Summer Solstice is here at chiefio
Notice that the global temperature tracks with the seasons of the NH. The reason for this is simple. The NH has twice as much land as the Southern Hemisphere (SH). Oceans have greater heat capacity and thus do not change temperatures as much as land does. So every year when there is almost a 4 °C swing in the temperature of the Earth, it follows the seasons of the NH. This is especially interesting because the Earth gets the most energy from the sun in January presently. That is because of the orbit of the Earth. The perihelion is when the Earth is closest to the sun and that currently takes place in January.
Observations and Analysis:
At the time my curiosity was piqued by Chiefio’s comment, so I went looking for data to analyze to test his proposition. As it happens, Berkeley Earth provides data tables for monthly Tmax and Tmin by hemisphere (NH and SH), from land station records. Setting aside any concerns about adjustments or infilling I did the analysis taking the BEST data tables at face value. Since land surface temperatures are more variable than sea surface temps, it seems like a reasonable dataset to analyze for the mentioned patterns. In the analysis below, all years refers to data for the years 1877 through 2013. Tmax Records
NH and SH long-term trends are the same 0.07C/decade, and in both there was cooling before 1979 and above average warming since. However, since 1950 NH warmed more strongly, and mostly prior to 1998, while SH has warmed strongly since 1998. (Trends below are in C/yr.)
Tmax Trends
NH Tmax
SH Tmax
All years
0.007
0.007
1998-2013
0.018
0.030
1979-1998
0.029
0.017
1950-1979
-0.003
-0.003
1950-2013
0.020
0.014
Summer Comparisons:
NH summer months are June, July, August, (6-8) and SH summer is December, January, February (12-2). The trends for each of those months were computed and the annual trends subtracted to show if summer months were warming more than the rest of the year (Trends below are in C/yr.).
Month less Annual
NH
Tmax
NH Tmax
NH Tmax
SH Tmax
SH Tmax
SH Tmax
Summer Trends
6
7
8
12
1
2
All years
-0.002
-0.004
-0.004
0.000
0.003
0.002
1998-2013
0.026
0.002
0.006
0.022
0.004
-0.029
1979-1998
0.003
-0.004
-0.003
-0.014
-0.029
0.001
1950-1979
-0.002
-0.002
-0.005
0.004
0.005
-0.005
1950-2013
-0.002
-0.003
-0.002
-0.002
-0.002
-0.002
NH summer months are cooler than average overall and since 1950. Warming does appear since 1998 with a large anomaly in June and also warming in August. SH shows no strong pattern of Tmax warming in summer months. A hot December trend since 1998 is offset by a cold February. Overall SH summers are just above average, and since 1950 have been slightly cooler.
Tmin Records
Both NH and SH show Tmin rising 0.12C/decade, much more strongly warming than Tmax. SH shows average warming persisting throughout the record, slightly higher prior to 1979. NH Tmin is more variable, showing a large jump 1979-1998, a rate of 0.25 C/decade (Trends below are in C/yr.).
Trends
NH Tmin
SH Tmin
All years
0.012
0.012
1998-2013
0.010
0.010
1979-1998
0.025
0.011
1950-1979
0.006
0.014
1950-2013
0.022
0.014
Winter Comparisons:
SH winter months are June, July, August, (6-8) and NH winter is December, January, February (12-2). The trends for each of those months were computed and the annual trends subtracted to show if winter months were warming more than the rest of the year (Trends below are in C/yr.).
Month less Annual
NH Tmin
NH Tmin
NH Tmin
SH Tmin
SH Tmin
SH Tmin
Winter Trends
12
1
2
6
7
8
All years
0.007
0.008
0.007
0.005
0.003
0.004
1998-2013
-0.045
-0.035
-0.076
-0.043
-0.024
-0.019
1979-1998
-0.018
-0.005
0.024
0.034
0.008
-0.008
1950-1979
0.008
0.005
0.007
0.008
0.012
0.013
1950-2013
0.001
0.007
0.008
-0.001
-0.002
0.002
NH winter Tmin warming is stronger than SH Tmin trends, but shows quite strong cooling since 1998. An anomalously warm February is the exception in the period 1979-1998. Both NH and SH show higher Tmin warming in winter months, with some irregularities. Most of the SH Tmin warming was before 1979, with strong cooling since 1998. June was anomalously warming in the period 1979 to 1998.
Summary
Tmin did trend higher in winter months but not consistently. Mostly winter Tmin warmed 1950 to 1979, and was much cooler than other months since 1998.
Tmax has not warmed in summer more than in other months, with the exception of two anomalous months since 1998: NH June and SH December.
Conclusion:
I find no convincing pattern of summer Tmax warming carrying over into winter Tmin warming. In other words, summers are not adding warming more than other seasons. There is no support for concerns over summer heat waves increasing as a pattern.
It is interesting to note that the plateau in temperatures since the 1998 El Nino is matched by winter months cooler than average during that period, leading to my discovering the real reason for lack of warming recently.
The Real Reason for the Pause in Global Warming?
These data suggest warming trends are coming from less cold overnight temperatures as measured at land weather stations. Since stations exposed to urban heat sources typically show higher minimums overnight and in winter months, this pattern is likely an artifact of human settlement activity rather than CO2 from fossil fuels.
Thus the Pause (more correctly the Plateau) in global warming is caused by end of the century completion of urbanization around most surface stations. With no additional warming from additional urban heat sources, temperatures have remained flat for more than 15 years.
Note on Data:
I thought about updating this analysis, but discovered that the BEST tables have not been updated since 2018. The sources have also moved, now located here:
The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.
As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020).
For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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.
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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions.
Update August 3, 2021
Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT
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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings. Now in November the high persisted due to another rise in ocean air temps in all regions, while land air temps cooled everywhere, most strongly in SH.
UAH has updated their tlt (temperatures in lower troposphere) dataset for November 2023. Posts on their reading of ocean air temps this month preceded updated records from HadSST4. I last posted on SSTs using HadSST4 October 2023 Ocean Cooling Off. 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.
Sometimes air temps over land diverge from ocean air changes. November 2023 is notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions. As a result the Global Ocean and Land anomaly result remained little changed.
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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4. For comparison we can also 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. 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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October. That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June. After an upward spike in July, ocean air everywhere cooled in August and also in September.
After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.4C, with the largest increases in April to July, and continuing in Autumn 2023. NH also warmed to 0.83C in the last 9 months, while SH ocean air rose about the same. Global Ocean air November 2023 now exceeds the 2016 peak by 0.2C, the main difference being the much higher rise in SH anomalies since June. The strength of the El Nino will determine the pattern in coming months.
Land Air Temperatures Tracking 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 November is below.
Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land. Land temps are dominated by NH with a 2021 spike in January, then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH.
Remarkably, in 2023, SH land air anomaly shot up 1.6C, from -0.56C in January to +1.03 in October, then dropped to 0.7 in November. Tropical land temps are up 1.6 since January and NH Land air temps rose 0.9, mostly since May. Now in November NH land air temps are little changed and Tropical land temps down nearly 0.2C.
The Bigger Picture UAH Global Since 1980
The chart shows monthly Global anomalies starting 01/1980 to present. The average monthly anomaly is -0.05, for this period of more than four decades. 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. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed.
With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October/November peak exceeds the sharp April peak of the El Nino 1998 event. It also surpasses the February peak in 2016. Where it goes from here, up or down, remains to be seen.
The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.
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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposed again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there is warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.
As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020).
For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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.
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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming along with higher land air temps.
Update August 3, 2021
Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT
October 2023 Update New Warming Spike Led by Tropics High
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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings. Now in October a new high resulted from a major rise in ocean air temps in all regions, along with higher land air temps in NH and Tropics.
UAH has updated their tlt (temperatures in lower troposphere) dataset for October 2023. Posts on their reading of ocean air temps this month preceded updated records from HadSST4. I last posted on SSTs using HadSST4 September 2023 Ocean Warming Crests, Solar Coincidence? 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. Sometimes air temps over land diverge from ocean air changes. For example in October 2023, a new warming high was driven by ocean air temps despite SH land temps dropping back down. The Tropics and NH showed warming in both land and sea air.
In October, as shown later on, Global ocean air reached a record high peak with all regions warming, especially Tropics. Land air temps rose in NH and Tropics, with a SH dropping down. Thus the land + ocean Global UAH temperature is now exceeding the 2016 peak.
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 change in priorities, updates are now exclusive to HadSST4. For comparison we can also 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. 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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October. That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June. After an upward spike in July, ocean air everywhere cooled in August and also in September.
After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.26C, with the largest increases in April to July 2023. NH also warmed 0.7C in the last 4 months, while SH ocean air rose the same. Global Ocean air October 2023 is now exceeding 2016, the main difference being the much higher rise in SH anomalies since April. The strength of the El Nino will determine the latter part of this year.
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 September is below.
Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land. Land temps are dominated by NH with a 2021 spike in January, then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH.
Remarkably, in 2023, SH land air anomaly shot up 1.5C, from -0.56C in January to +0.93 in July, then dropped to 0.53 in August. In September SH shot up again to 1.5C. Tropical land temps are up 1.48 since January and NH Land air temps rose 0.9, mostly since May. Despite SH land air dropping in October, the consolidated rise greatly exceeds the upward spikes peaking in 2016.
The Bigger Picture UAH Global Since 1980
The chart shows monthly Global anomalies starting 01/1980 to present. The average monthly anomaly is -0.06, for this period of more than four decades. 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. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed.
With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October peak exceeds the sharp April peak of the El Nino 1998 event. It also surpasses the February peak in 2016. Where it goes from here, up or down, remains to be seen.
The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.
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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
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