World of CO2 Infographics

This post is to announce that Raymond Inauen of RIC-Communications has a website up for the public to access a series of infographics regarding CO2 and climate science.  As seen above, the website is  here:

The World of CO2

 

Readers will be aware of previous posts on the four themes to be discovered.  Raymond introduces this resource in this way:

WELCO₂ME

Would you like to learn more about CO₂ so you can have informed conversations about climate policy and future energy investments? Or would you rather pass judgment on CO₂ after learning about the basics? Then this is the website for you.

There are 29 infographic images that can be downloaded in four PDF files.  Thanks again, Raymond for your interest and efforts to make essential scientific information available to one and all.

Ocean Temps Warm Slightly December 2022

 

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through December 2022.  A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016. 

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean.

Then in 2022, another strong NH summer spike peaked in August, but this time both the Tropic and SH were countervailing, resulting in only slight Global warming, later receding to the mean.   Oct./Nov. temps dropped  in NH and the Tropics took the Global anomaly below the average for this period. Now in December an uptick in SH has lifted the Global anomaly slightly above the mean.

A longer view of SSTs

To enlarge image open in new tab.

The graph above is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino. 

The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  Now in 2021-22 there are again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, now in October and November by deeper cooling in NH and Tropics.

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.

The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020, dropping down in 2021.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The heavy blue line shows that 2022 started warm, dropped to the bottom and stayed near the lower tracks.  Note the strength of this summer’s warming pulse, in September peaking to nearly 24 Celsius, a new record for this dataset. In November the SSTs were closer to the middle.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies will likely decline in coming months, along with ENSO also weakening will probably determine a cooler outcome.

Footnote: Why Rely on HadSST4

HadSST is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST4 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

Footnote Rare Triple Dip La Nina Likely This Winter

Here’s Where a Rare “Triple Dip La Niña” Might Drop the Most Snow This Winter Ski Mag

The unusual weather phenomenon might result in the snowiest season in years for some parts of the country.

The long-range winter forecast could be good news for skiers living in the certain parts of the U.S. and Canada. The National Oceanic and Atmospheric Administration (NOAA) estimates that the chance of a La Niña occurring this fall and early winter is 86 percent, and the main beneficiary is expected to be mountains in the Northwest and Northern Rockies.

If NOAA’s predictions pan out, this will be the third La Niña in a row—a rare phenomenon called a “Triple Dip La Niña.” Between now and 1950, only two Triple Dips have occurred.

Smith also notes that winters on the East Coast are similarly tricky to predict during La Niña years. “In the West, you’re simply looking for above-average precipitation, which typically translates to above-average snowfall, but in the East, you have temperature to worry about as well … that adds another complication.” In other words, increased precip could lead to more rain if the temperatures aren’t cooperative.

The presence of a La Niña doesn’t always translate to higher snowfall in the North, either, as evidenced by last ski season, which saw few powder days.

However, in consecutive La Niña triplets, one winter usually involves above-average snowfall. While this historical pattern isn’t tied to any documented meteorological function, it could mean that the odds of a snowy 2022’-’23 season are higher, given the previous two La Niñas didn’t deliver the goods.

 

 

Temps Cause CO2 Changes, Not the Reverse. 2023 Update

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:

Temperature anomalies from RSS here:  http://www.remss.com/missions/amsu

CO2 monthly levels from NOAA (Mauna Loa): https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html

Changes in CO2 (ΔCO2)

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 2022.

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 0.9985 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.

Previous Post:  What Causes Rising Atmospheric CO2?

nasa_carbon_cycle_2008-1

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.

For a possible explanation of natural warming and CO2 emissions see Little Ice Age Warming Recovery May be Over
Resources:

CO2 Fluxes, Sources and Sinks

Who to Blame for Rising CO2?

Fearless Physics from Dr. Salby

In this video presentation, Dr. Salby provides the evidence, math and charts supporting the non-IPCC paradigm.

Footnote:  As CO2 concentrations rose, BP shows Fossil Fuel consumption slumped in 2020, Then Recovered

See also 2022 Update: Fossil Fuels ≠ Global Warming

Zero Warming: Chilling UAH Temps December 2022

The post below updates the UAH record of air temperatures over land and ocean.  But 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  Now at year end 2022, we have again global temp anomaly matching zero warming since 1995. (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 ~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. 

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

image-8

 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

December Update Big Chilling of Land and Sea 

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020-21 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 was fully dissipated with chilly temperatures in all regions. May NH land and SH ocean showed temps matching March, reversing an upward blip in April, and then June was virtually the mean since 1995.

UAH has updated their tlt (temperatures in lower troposphere) dataset for December 2022. Posts on their reading of ocean air temps this month came ahead of updated records from HadSST4.  I have previously posted on SSTs using HadSST4 Ocean Temps Dropping November 2022 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.  However, in December temps in all land and ocean regions dropped sharply.

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 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.   Now in December 2022, sharp cooling everywhere brings the global anomaly to zero.

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 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. Land temps dropped sharply for four months, even more than did the Oceans. March and April 2022 saw some warming, reversed In May when all land regions cooled pulling down the global anomaly. In July, Tropics and SH land rose sharply, NH slightly, pulling up the Global land anomaly. Note the sharp drop in SH land temps in August and September, while NH Land rose, leaving the Global anomaly unchanged. Nov. and Dec. saw steep declines in air temps over land.

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.   A small upward bump in 2021 has been reversed with temps having returned close to the mean as of 2/2022.  March and April brought warmer Global temps, reversed in May and the June anomaly was almost zero. With the sharp drop in Nov. and Dec. temps, there is only about 0.1C increase since 1980.

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.  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.

 

Today’s Mildly Icy Climate in Perspective

 

Raymond at RiC-Communications has produced the above poster on the theme expounded in a previous post In Celebration of Our Warm Climate, reprinted below. The above image is available in high resolution pdf format at his website The last ice age and its impact.

His other science infographic projects are:

The World of CO2

The World of Climate Change

The World of Energy

Legacy and social media keep up a constant drumbeat of warnings about a degree or two of planetary warming without any historical context for considering the significance of the alternative.  A poem of Robert Frost comes to mind as some applicable wisdom:

The diagram at the top shows how grateful we should be for living in today’s climate instead of a glacial icehouse. (H/T Raymond Inauen)  For most of its history Earth has been frozen rather than the mostly green place it is today.  And the reference is to the extent of the North American ice sheet during the Last Glacial Maximum (LGM).

To see this geologically recent glacial period in perspective, consider the maps created by paleo climatologist Christopher Scotese, leader of the Paleomap Project.

The animation below shows how the planet surface changed over the past millions of years (Ma means Millions of years Ago). 

Note that in 66 Ma Earth was a “hothouse” with little ice and green polar land masses.  By 50 Ma cooling resulted in polar ice caps and glaciers. By 14 Ma both Greenland and Antarctica are ice covered. 18Ka a severe “icehouse” world is evidenced by the Laurentian icecap. Then the Modern world appears with the ice retreating, but still covering the two poles. Continental drifts are also shown by India starting as an island and later joining Asia, and by Africa isolated but later approaching Europe.

For further context consider that geologists refer to our time as a “Severe Icehouse World”, among the various conditions in earth’s history, as diagramed below by Christopher Scotese. Referring to the Global Mean Temperatures, it appears after many decades, we are slowly rising to “Icehouse World”, which would seem to be a good thing.

His compete evidence and analysis can be reviewed in his article Some thoughts on Global Climate Change: The Transition from Icehouse to Hothouse.  In that essay Scotese shows where we are presently in this cycle between icehouse and hothouse.

As of 2015 earth is showing a GMT of 14.4C, compared to pre-industrial GMT of 13.8C.  According to the best geological evidence from millions of years of earth’s history, that puts us in the category “Severe Icehouse.”  So, thankfully we are warming up, albeit very slowly. Moreover, progress toward a warming world means flattening the profile at the higher latitudes, especially the Arctic.  Equatorial locations remain at 23C throughout the millennia, while the gradient decreases in a warmer world.

We have many, many centuries to go before the earth can warm up to the “Greenhouse” profile, let alone get to “Hothouse.” Regional and local climates at higher latitudes will see slightly warming temperatures and smaller differences from equatorial climates. These are facts based on solid geological evidence, not opinions or estimates from computer models.

It is still a very cold world, but we are moving in the right direction. Stay the course.

Instead of fear mongering over a bit of warming, we should celebrate our good fortune, and do our best for humanity and the biosphere.  Matthew Ridley takes it from there in a previous post.

Background from previous post The Goodness of Global Warming

LAI refers to Leaf Area Index.

As noted in other posts here, warming comes and goes and a cooling period may now be ensuing. See No Global Warming, Chilly January Land and Sea.  Matt Ridley provides a concise and clear argument to celebrate any warming that comes to our world in his Spiked article Why global warming is good for us.  Excerpts in italics with my bolds and added images.

Climate change is creating a greener, safer planet.

Global warming is real. It is also – so far – mostly beneficial. This startling fact is kept from the public by a determined effort on the part of alarmists and their media allies who are determined to use the language of crisis and emergency. The goal of Net Zero emissions in the UK by 2050 is controversial enough as a policy because of the pain it is causing. But what if that pain is all to prevent something that is not doing net harm?

The biggest benefit of emissions is global greening, the increase year after year of green vegetation on the land surface of the planet. Forests grow more thickly, grasslands more richly and scrub more rapidly. This has been measured using satellites and on-the-ground recording of plant-growth rates. It is happening in all habitats, from tundra to rainforest. In the four decades since 1982, as Bjorn Lomborg points out, NASA data show that global greening has added 618,000 square kilometres of extra green leaves each year, equivalent to three Great Britains. You read that right: every year there’s more greenery on the planet to the extent of three Britains. I bet Greta Thunberg did not tell you that.

The cause of this greening? Although tree planting, natural reforestation, slightly longer growing seasons and a bit more rain all contribute, the big cause is something else. All studies agree that by far the largest contributor to global greening – responsible for roughly half the effect – is the extra carbon dioxide in the air. In 40 years, the proportion of the atmosphere that is CO2 has gone from 0.034 per cent to 0.041 per cent. That may seem a small change but, with more ‘food’ in the air, plants don’t need to lose as much water through their pores (‘stomata’) to acquire a given amount of carbon. So dry areas, like the Sahel region of Africa, are seeing some of the biggest improvements in greenery. Since this is one of the poorest places on the planet, it is good news that there is more food for people, goats and wildlife.

But because good news is no news, green pressure groups and environmental correspondents in the media prefer to ignore global greening. Astonishingly, it merited no mentions on the BBC’s recent Green Planet series, despite the name. Or, if it is mentioned, the media point to studies suggesting greening may soon cease. These studies are based on questionable models, not data (because data show the effect continuing at the same pace). On the very few occasions when the BBC has mentioned global greening it is always accompanied by a health warning in case any viewer might glimpse a silver lining to climate change – for example, ‘extra foliage helps slow climate change, but researchers warn this will be offset by rising temperatures’.

Another bit of good news is on deaths. We’re against them, right? A recent study shows that rising temperatures have resulted in half a million fewer deaths in Britain over the past two decades. That is because cold weather kills about ’20 times as many people as hot weather’, according to the study, which analyses ‘over 74million deaths in 384 locations across 13 countries’. This is especially true in a temperate place like Britain, where summer days are rarely hot enough to kill. So global warming and the unrelated phenomenon of urban warming relative to rural areas, caused by the retention of heat by buildings plus energy use, are both preventing premature deaths on a huge scale.

Summer temperatures in the US are changing at half the rate of winter temperatures and daytimes are warming 20 per cent slower than nighttimes. A similar pattern is seen in most countries. Tropical nations are mostly experiencing very slow, almost undetectable daytime warming (outside cities), while Arctic nations are seeing quite rapid change, especially in winter and at night. Alarmists love to talk about polar amplification of average climate change, but they usually omit its inevitable flip side: that tropical temperatures (where most poor people live) are changing more slowly than the average.

My Mind is Made Up, Don’t Confuse Me with the Facts. H/T Bjorn Lomborg, WUWT

But are we not told to expect more volatile weather as a result of climate change? It is certainly assumed that we should. Yet there’s no evidence to suggest weather volatility is increasing and no good theory to suggest it will. The decreasing temperature differential between the tropics and the Arctic may actually diminish the volatility of weather a little.

Indeed, as the Intergovernmental Panel on Climate Change (IPCC) repeatedly confirms, there is no clear pattern of storms growing in either frequency or ferocity, droughts are decreasing slightly and floods are getting worse only where land-use changes (like deforestation or building houses on flood plains) create a problem. Globally, deaths from droughts, floods and storms are down by about 98 per cent over the past 100 years – not because weather is less dangerous but because shelter, transport and communication (which are mostly the products of the fossil-fuel economy) have dramatically improved people’s ability to survive such natural disasters.

The effect of today’s warming (and greening) on farming is, on average, positive: crops can be grown farther north and for longer seasons and rainfall is slightly heavier in dry regions. We are feeding over seven billion people today much more easily than we fed three billion in the 1960s, and from a similar acreage of farmland. Global cereal production is on course to break its record this year, for the sixth time in 10 years.

Nature, too, will do generally better in a warming world. There are more species in warmer climates, so more new birds and insects are arriving to breed in southern England than are disappearing from northern Scotland. Warmer means wetter, too: 9,000 years ago, when the climate was warmer than today, the Sahara was green. Alarmists like to imply that concern about climate change goes hand in hand with concern about nature generally. But this is belied by the evidence. Climate policies often harm wildlife: biofuels compete for land with agriculture, eroding the benefits of improved agricultural productivity and increasing pressure on wild land; wind farms kill birds and bats; and the reckless planting of alien sitka spruce trees turns diverse moorland into dark monoculture.

Meanwhile, real environmental issues are ignored or neglected because of the obsession with climate. With the help of local volunteers I have been fighting to protect the red squirrel in Northumberland for years. The government does literally nothing to help us, while it pours money into grants for studying the most far-fetched and minuscule possible climate-change impacts. Invasive alien species are the main cause of species extinction worldwide (like grey squirrels driving the red to the margins), whereas climate change has yet to be shown to have caused a single species to die out altogether anywhere.

Of course, climate change does and will bring problems as well as benefits. Rapid sea-level rise could be catastrophic. But whereas the sea level shot up between 10,000 and 8,000 years ago, rising by about 60 metres in two millennia, or roughly three metres per century, today the change is nine times slower: three millimetres a year, or a foot per century, and with not much sign of acceleration. Countries like the Netherlands and Vietnam show that it is possible to gain land from the sea even in a world where sea levels are rising. The land area of the planet is actually increasing, not shrinking, thanks to siltation and reclamation.

Environmentalists don’t get donations or invitations to appear on the telly if they say moderate things. To stand up and pronounce that ‘climate change is real and needs to be tackled, but it’s not happening very fast and other environmental issues are more urgent’ would be about as popular as an MP in Oliver Cromwell’s parliament declaring, ‘The evidence for God is looking a bit weak, and I’m not so very sure that fornication really is a sin’. And I speak as someone who has made several speeches on climate in parliament.

No wonder we don’t hear about the good news on climate change.

 

 

Ocean Temps Dropping November 2022

 

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through November 2022.  A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016. 

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean. Now in 2022, another strong NH summer spike has peaked in August, but this time both the Tropic and SH are countervailing, resulting in only slight Global warming, now receding to the mean.  Now dropping Oct./Nov. temps in NH and the Tropics have taken the Global anomaly below the average for this period. Note that 2022/11 Tropical SSTs are 0.8C below their peak in 2015.

A longer view of SSTs

To enlarge image open in new tab.

The graph above is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino. 

The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  Now in 2021-22 there are again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, now in October and November by deeper cooling in NH and Tropics.

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.

The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020, dropping down in 2021.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The heavy blue line shows that 2022 started warm, dropped to the bottom and stayed near the lower tracks.  Note the strength of this summer’s warming pulse, in September peaking to nearly 24 Celsius, a new record for this dataset. Now in November the SSTs are closer to the middle.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies will likely decline in coming months, along with ENSO also weakening will probably determine a cooler outcome.

Footnote: Why Rely on HadSST4

HadSST is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST4 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

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USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

Footnote Rare Triple Dip La Nina Likely This Winter

Here’s Where a Rare “Triple Dip La Niña” Might Drop the Most Snow This Winter Ski Mag

The unusual weather phenomenon might result in the snowiest season in years for some parts of the country.

The long-range winter forecast could be good news for skiers living in the certain parts of the U.S. and Canada. The National Oceanic and Atmospheric Administration (NOAA) estimates that the chance of a La Niña occurring this fall and early winter is 86 percent, and the main beneficiary is expected to be mountains in the Northwest and Northern Rockies.

If NOAA’s predictions pan out, this will be the third La Niña in a row—a rare phenomenon called a “Triple Dip La Niña.” Between now and 1950, only two Triple Dips have occurred.

Smith also notes that winters on the East Coast are similarly tricky to predict during La Niña years. “In the West, you’re simply looking for above-average precipitation, which typically translates to above-average snowfall, but in the East, you have temperature to worry about as well … that adds another complication.” In other words, increased precip could lead to more rain if the temperatures aren’t cooperative.

The presence of a La Niña doesn’t always translate to higher snowfall in the North, either, as evidenced by last ski season, which saw few powder days.

However, in consecutive La Niña triplets, one winter usually involves above-average snowfall. While this historical pattern isn’t tied to any documented meteorological function, it could mean that the odds of a snowy 2022’-’23 season are higher, given the previous two La Niñas didn’t deliver the goods.

 

 

Seven Ways Climate Reparations Are Absurd

Dan Hannan explains at Washington Examiner Demands for ‘climate reparations’ are laughable Excerpts in italics with my bolds.

The demands for climate reparations from wealthy countries are so absurd, so unscientific, and so offensive to natural justice that it is difficult to know where the criticism should begin.

The argument is that, since countries that industrialized earlier produced a lot of carbon a hundred years ago, they now owe a debt to poorer states. Naturally, this argument appeals to assorted Marxists, anti-colonialists, and shakedown artists, and COP27 has been dominated by insolent demands for well-run states to pony up.

Some, including Austria, Belgium, and Denmark, have capitulated. No doubt others will follow. These days, once something is framed as poor-versus-rich or darker-skinned-versus-lighter-skinned or ex-colony-versus-ex-colonizer, the pressure becomes irresistible. Nevertheless, it is worth running through the absurdities in play.

First, the claims are rooted in indignation rather than science. For example, Pakistan, which leads the G-77 group of poorer states and is leading the campaign, claims that its floods are a product of climate change. But might Pakistan look a little closer to home? Although Europe and North America have seen significant reforestation over the past half-century, Pakistan has gone in the other direction. A third of its landmass was forest when it became independent in 1947. Now, it is one-twentieth, and the rains run straight off the mountains into silted-up reservoirs that then overflow, whence the floods.

But never mind all that — blame the colonialists, eh?

Second, there is the utter refusal to acknowledge what wealthier countries are already doing. I don’t just mean in terms of making direct monetary transfers — though, sticking with Pakistan for a moment, Britain has been borrowing around $400 million a year to give to that country, which pleads poverty while funding a nuclear weapons program. No, I mean in terms of impoverishing themselves through drastic action on carbon emissions. Britain has cut its carbon dioxide production by nearly half since 1990, largely by closing down its coal mines. Pakistan has more than 100 coal mines in operation.

But, again, blame the colonialists, eh?

Third, there is the ingratitude. One of the things I used to resent about the European Parliament was the entitled and hectoring way in which representatives of poorer countries (they were usually very rich people) would call for bigger transfers. “This is unacceptable,” they would say of whatever offer the Brits, the Dutch, or the Germans put on the table. Fine, I’d think, don’t accept it, then. Yet the numbers only ever got bigger. Look, I’m sorry to be blunt about this, but a 2-degree rise in temperature is far less menacing for Britain or Canada than it is for most countries.

The least-threatened countries are doing the heaviest lifting by far.
But don’t expect any gratitude.

Fourth, there is the implication that industrialization, the miracle that released our species from 10,000 years of backbreaking labor, is regrettable. In truth, as well as giving us longer, healthier, and freer lives, the wealth released over the past 200 years of specialization and exchange is cleaning up the environment. The air and water are purer in London than in Lahore because GDP is higher. For the same reason, natural disasters have become far less lethal. The 1950 floods in Pakistan killed many more people than this year’s, because they hit a poorer country.

Fifth, there is the related assumption that rich countries owe their wealth to exploitation, that one nation’s gain must mean another’s loss. This is palpable nonsense. The enrichment of a country, other things being equal, is good news for all of its trading partners. And countries get wealthy not by conquering others (a process that is always expensive) but by pursuing the right policies, such as secure property rights, low taxes, independent courts, light regulations, and free trade.

If you tax successful countries to pay unsuccessful ones, you will end up with
fewer of the former and more of the latter.

Sixth, and most preposterously, there is the ugly collectivism that lurks behind every shakedown attempt, from the return of artworks to slavery reparations. Our criminal justice system, like every Abrahamic religion, is based on the idea that we are individually responsible for our actions. But when it comes to these scams, we are all suddenly defined by ancestry or skin color.

It is precisely because Western nations broke out of that dispensation that they became rich in the first place. And it was by copying their individualist outlook that other countries were able to catch them up. Far from complaining about industrialization, the rest of the world should thank us for having developed capitalism, and they should seek to emulate it.

Postscript: Absurdity Seven

Climate reparations are a legal quagmire.  From Hulme et al. (2011):

At the heart of the loss and damage (L&D) agenda is the idea of attribution—that specific losses and damages in developing countries can be “associated with the impacts of climate change,” where “climate change” means human-caused alterations to climate. It is therefore not just any L&D that qualify for financial assistance under the Convention; it is L&D attributable to or “associated with” a very specific causal pathway.

Developing countries face some serious difficulties—at best, ambiguities—
with this approach to directing climate adaptation finance.

Investment in climate adaptation, they claim, is most needed “… where vulnerability to meteorological hazard is high, not where meteorological hazards are most attributable to human influence”. Extreme weather attribution says nothing about how damages are attributable to meteorological hazard as opposed to exposure to risk; it says nothing about the complex political, social and economic structures which mediate physical hazards.

And separating weather into two categories — ‘human-caused’ weather and ‘tough-luck’ weather – raises practical and ethical concerns about any subsequent investment allocation guidelines which excluded the victims of ‘tough-luck weather’ from benefiting from adaptation funds.

Contrary to the claims of some weather attribution scientists, the loss and damage agenda of the UNFCCC, as it is currently emerging, makes no distinction between ‘human-caused’ and ‘tough-luck’ weather. “Loss and damage impacts fall along a continuum, ranging from ‘events’ associated with variability around current climatic norms (e.g., weather-related natural hazards) to [slow-onset] ‘processes’ associated with future anticipated changes in climatic norms” (Warner et al., 2012:21). Although definitions and protocols have not yet been formally ratified, it seems unlikely that there will be a role for the sort of forensic science being offered by extreme weather attribution science.

See also: Climate Loss and Damage, Legal House of Cards

 

 

Climatists, Spare Us Your Guilt Trip!

An example of climate hysteria comes from the usual suspects published at the usual venue, Inside Climate News. Polar Ice Is Disappearing, Setting Off Climate Alarms

Excerpts below with my bolds: The short-term consequences of Arctic (and Antarctic) warming may already be felt in other latitudes. The long-term threat to coastlines is becoming even more dire.

“When you’re taking out 30, 40, almost 50 percent of the ice cover, that’s a big change in the environment,” Meier said. “Whether we’re seeing it yet, there’s still some debate, but whether there will be an effect as we continue to lose ice, I think that’s pretty obvious.”

“There’s no evidence that anything is recovering here,” said Mark Serreze, the director of the NSIDC. “What we’ve seen historically is a downward trend in ice extent in all months. Superimposed on that are the ups and downs of natural variability. We’re going to continue to head downward.

“We are looking at an ice-free Arctic Ocean sometime in the 2040s,” said Serreze. “There’s no evidence that we’ve seen anything like this before.”

Ted Scambos, lead scientist with the National Snow and Ice Data Center, said that while the current pace of melting is not alarming, a series of papers “has led to a realization that the West Antarctic Ice Sheet may already be in an irreversible retreat.

Greenland is melting, too—for now, it’s the biggest threat. “Greenland has become Loserville,” said Jason Box, who tracks ice for the Geological Survey of Denmark and Greenland.

“New observations from many different sources confirm that ice-sheet loss is accelerating,” the United States Global Change Research Program said in its comprehensive special report on climate science. “Up to 8.5 feet of global sea level rise is possible by 2100” in a worst-case emissions scenario. That’s almost 2 feet more than scientists expected just a few years ago.

“So we’re guaranteed significant sea level rise no matter what we do, even under the optimistic Paris scenario,” Box said. “We had better prepare.”

These warnings of wolves are starting to sound the same: “It never happened before, is not happening now, but it will surely destroy us in the future if we don’t do something.”

Meanwhile the facts on the ground are not alarming: For example September minimums:

More details at 16 yr. Plateau September Arctic Ice 2022

And the refreezing is faster than unusual:


These outrageous appeals by alarmists in the face of contrary facts remind me of the story defining the term “chutzpuh.” A young man is convicted of killing his parents, and later appears before the judge for sentencing. Asked to give any last words, he replies: “Go easy on me, your Honor, I’m an orphan.”
alcoholics-anonymous-logo-e1497443623248

Fortunately, there is help for climate alarmists. They can join or start a chapter of Alarmists Anonymous. By following the Twelve Step Program, it is possible to recover and unite in service to the real world and humanity.

Step One: Fully concede (admit) to our innermost selves that we were addicted to climate fear mongering.

Step Two: Come to believe that a Power greater than ourselves causes weather and climate, restoring us to sanity.

Step Three: Make a decision to study and understand how the natural world works.

Step Four: Make a searching and fearless moral inventory of ourselves, our need to frighten others and how we have personally benefited by expressing alarms about the climate.

Step Five: Admit to God, to ourselves, and to another human being the exact nature of our exaggerations and false claims.

Step Six: Become ready to set aside these notions and actions we now recognize as objectionable and groundless.

Step Seven: Seek help to remove every single defect of character that produced fear in us and led us to make others afraid.

Step Eight: Make a list of all persons we have harmed and called “deniers”, and become willing to make amends to them all.

Step Nine: Apologize to people we have frightened or denigrated and explain the errors of our ways.

Step Ten: Continue to take personal inventory and when new illusions creep into our thinking, promptly renounce them.

Step Eleven: Dedicate ourselves to gain knowledge of natural climate factors and to deepen our understanding of nature’s powers and ways of working.

Step Twelve: Having awakened to our delusion of climate alarm, we try to carry this message to other addicts, and to practice these principles in all our affairs.

Summary:

With a New Year a month away, let us hope that many climate alarmists take the opportunity to turn the page by resolving a return to sanity. It is not too late to get right with reality before the cooling comes in earnest.

This is your brain on climate alarm.  Just say No!

Land Warms UAH Temps October 2022

The post below updates the UAH record of air temperatures over land and ocean.  But 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  (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 ~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. 

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

image-8

 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

October Update Mild Warming of 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 2020-21 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 was fully dissipated with chilly temperatures in all regions. May NH land and SH ocean showed temps matching March, reversing an upward blip in April, and then June was virtually the mean since 1995.

UAH has updated their tlt (temperatures in lower troposphere) dataset for October 2022. Posts on their reading of ocean air temps this month came after  updated records from HadSST4.  So I have already posted on SSTs using HadSST4 NH Leads Ocean Cooler October 2022. 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.  However, July showed air temps over all ocean regions warmed sharply, lifting up Global ocean temps. Then in August air over both land and ocean cooled off again. Now in September both land and ocean in SH dropped sharply offsetting slight warming elsewhere.

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.   In October NH cooled, the Tropics changed little, and a spike in SH was enough to mildly warm the Global anomaly.

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 October 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. Land temps dropped sharply for four months, even more than did the Oceans. March and April 2022 saw some warming, reversed In May when all land regions cooled pulling down the global anomaly. In July, Tropics and SH land rose sharply, NH slightly, pulling up the Global land anomaly. Note the sharp drop in SH land temps in August and September, while NH Land rose, leaving the Global anomaly unchanged. Now in October NH and SH land temps spiked warming the Global land anomaly.

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.   A small upward bump in 2021 has been reversed with temps having returned close to the mean as of 2/2022.  March and April brought warmer Global temps, reversed in May and the June anomaly was almost zero. The upward spike in July was almost 0.3C, lower in August and September and a slight rise in October.

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.  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.

 

NH Leads Ocean Cooler October 2022

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through October 2022.  A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016. 

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean. Now in 2022, another strong NH summer spike has peaked in August, but this time both the Tropic and SH are countervailing, resulting in only slight Global warming, now receding to the mean.  October shows a small SH rise, not enough to offset a sharp drop in NH and slight Tropics cooling.

A longer view of SSTs

Open image in new tab to enlarge.

The graph above is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino. 

The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  Now in 2021-22 there are again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, now in October by NH and Tropics cooling.

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.

The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020, dropping down in 2021.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The heavy blue line shows that 2022 started warm, dropped to the bottom and stayed near the lower tracks.  Note the strength of this summer’s warming pulse, in September peaking to nearly 24 Celsius, a new record for this dataset. Now in October the SSTs are still high but closer to the middle.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies will likely decline in coming months, along with ENSO also weakening will probably determine a cooler outcome.

Footnote: Why Rely on HadSST4

HadSST is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST4 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

Footnote Rare Triple Dip La Nina Likely This Winter

Here’s Where a Rare “Triple Dip La Niña” Might Drop the Most Snow This Winter Ski Mag

The unusual weather phenomenon might result in the snowiest season in years for some parts of the country.

The long-range winter forecast could be good news for skiers living in the certain parts of the U.S. and Canada. The National Oceanic and Atmospheric Administration (NOAA) estimates that the chance of a La Niña occurring this fall and early winter is 86 percent, and the main beneficiary is expected to be mountains in the Northwest and Northern Rockies.

If NOAA’s predictions pan out, this will be the third La Niña in a row—a rare phenomenon called a “Triple Dip La Niña.” Between now and 1950, only two Triple Dips have occurred.

Smith also notes that winters on the East Coast are similarly tricky to predict during La Niña years. “In the West, you’re simply looking for above-average precipitation, which typically translates to above-average snowfall, but in the East, you have temperature to worry about as well … that adds another complication.” In other words, increased precip could lead to more rain if the temperatures aren’t cooperative.

The presence of a La Niña doesn’t always translate to higher snowfall in the North, either, as evidenced by last ski season, which saw few powder days.

However, in consecutive La Niña triplets, one winter usually involves above-average snowfall. While this historical pattern isn’t tied to any documented meteorological function, it could mean that the odds of a snowy 2022’-’23 season are higher, given the previous two La Niñas didn’t deliver the goods.