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Contents:

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Page 3: June 2024 global surface air temperature overview
Page 4: June 2024 global surface air temperature overview versus June last 10 years
Page 5: June 2024 global surface air temperature compared to June 2023
Page 6: Temperature quality class 1: Lower troposphere temperature from satellites
Page 7: Temperature quality class 2: HadCRUT global surface air temperature
Page 8: Temperature quality class 3: GISS and NCDC global surface air temperature
Page 11: Comparing global surface air temperature and satellite-based temperature
Page 12: Global air temperature linear trends
Page 13: Global temperatures: All in one, Quality Class 1, 2 and 3
Page 15: Global sea surface temperature
Page 18: Ocean temperature in uppermost 100 m
Page 20: Pacific Decadal Oscillation (PDO)
Page 21: North Atlantic heat content uppermost 700 m
Page 22: North Atlantic temperatures 0-800 m depth along 59N, 30-0W
Page 23: Global ocean temperature 0-1900 m depth summary
Page 24: Global ocean net temperature change since 2004 at different depths
Page 25: La Niña and El Niño episodes, Oceanic Niño Index
Page 26: Zonal lower troposphere temperatures from satellites
Page 27: Arctic and Antarctic lower troposphere temperatures from satellites
Page 28: Arctic and Antarctic surface air temperatures
Page 31: Long Arctic annual surface air temperature series
Page 32: Long Antarctic annual surface air temperature series
Page 33: Temperature over land versus over oceans
Page 34: Troposphere and stratosphere temperatures from satellites
Page 35: Sea ice; Arctic and Antarctic
Page 39: Sea level in general
Page 40: Global sea level from satellite altimetry
Page 41: Global sea level from tide gauges (extended Holgate-9)
Page 42: This month’s selected sea level station (tide gauge): Port Louis, Mauritius
Page 44: Snow cover; Northern Hemisphere weekly and seasonal
Page 46: Greenland Ice Sheet net surface mass balance
Page 47: Atmospheric relative and specific humidity
Page 49: Atmospheric CO2
Page 50: Relation between annual change of atm. CO2 and La Niña and El Niño episodes
Page 51: Phase relation between atmospheric CO2 and global temperature
Page 52: Global air temperature and atmospheric CO2
Page 56: Latest 20-year QC1 global monthly air temperature change
Page 57: Sunspot activity and QC1 average satellite global air temperature
Page 57: Sunspot activity and average neutron counts
Page 59: Sunspot activity, ONI, and change rates of atmospheric CO2 and specific humidity
Page 60: Monthly lower troposphere temperature and global cloud cover
Page 61: Climate and history: 384-322 BC; Aristotle's views on weather and climate

June 2024 global surface air temperature overview
General: This newsletter contains graphs anddiagrams showing a selection of key meteorologicalvariables, updated to the most recent past month, if
possible. All temperatures are given in degrees
Celsius.
Traditionally, a 30 -year reference period is often usedby various meteorological institutions for comparison
purposes and are supposed to be updated throughthe end of each decade ending in zero (e.g., 19511980, 1961-1990, 1971-2000, etc.). The concept of anormal climate goes back to the first part of the 20th
century. At that time, lasting to about 1960, it was
generally believed that for all practical purpose’s
climate could be considered constant, no matter how
obvious year-to-year fluctuations might have been.
On this basis meteorologist decided to operate withan average or normal climate, defined by a 30-year
period, called the normal period, assuming that it wasof sufficient length to iron out all intervening
variations.
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In fact, using a 30-yr ‘normal’ period is rather
unfortunate, as observations clearly demonstratethat various global climate parameters (see, e.g., page20) are influenced by periodic changes of 50-70 years
duration. The frequently used 30-yr reference period
is roughly half this time interval and is therefore highly
unsuited as reference period. In the maps on page 4,
showing the geographical pattern of surface airtemperature anomalies, the last previous 10 years are
therefore used as reference period. This decadal
approach corresponds well to the typical memory
horizon for many people and is also adopted as
reference period by other institutions, e.g., the Danish
Meteorological Institute (DMI).
In many diagrams shown in this newsletter the thinline represents the monthly global average value, andthe thick line indicate a simple running 37-monthaverage, nearly corresponding to a three-year
average. The year 1979 has been chosen as starting
point in many diagrams, as this approximately
corresponds to both the beginning of satellite
observations and the onset of the late 20th century
warming period. However, most of the data series
have a longer record length, which may be inspected
in greater detail on www.climate4you.com.

June 2024 surface air temperature
General: For June 2024, the GISS data portal provided
AIRS interpolated surface air data, based on satellite
observations (p.4-5). According to the GISS and NCDC
records, the June global temperature anomaly wasslightly higher than the May anomaly. The UAH lower
troposphere satellite series show the Junetemperature anomaly to be lower than in May. The
AIRS v6 June global average temperature anomaly
compared to the average for the last 10 years shows
little change (diagrams p.4-5). All the above airtemperature records are registering the declining El
Niño episode in the Pacific Ocean (p.25).
The Northern Hemisphere surface temperature
anomality pattern (p.4) was characterised by regional
contrasts, mainly controlled by the dominant jet
stream position. Especially eastern Europe andwestern Russia were warm relative to the average forthe last 10 years. In contrast, western Europe, andmuch of Canada were relatively cold. Ocean wise,
much of the North Atlantic was relatively warm, while
the Greenland and Norwegian Seas were cold. The
Pacific Ocean was relatively cold, except for a region
centred around 40oN. PDO (p.20) remains negative.
Arctic Ocean surface air temperatures were above the
10-yr average.
Near the Equator temperatures were generally above
the 10-year average, but less so than in the previous
months. Apparently, ocean heat released during theprevious warm El Niño episode is still affecting many
Equatorial regions.
Southern Hemisphere temperatures were near or
below the 10-yr average for June (approachingsouthern hemisphere winter). Australia, New Zealandand southern South America were relatively cold. In
contrast, central South America was relatively warm.
East Antarctic had temperatures below the 10-yr
average, while much of West Antarctica was relatively
warm. A warm ocean region beyond the coast of West
Antarctica first time visible in the January 2024
anomaly pattern, has intensified further, and now
represents the highest positive global surface airtemperature anomaly in June 2024.

June 2024 global surface air temperature overview versus average June last 10 years

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June 2024 surface air temperature compared to the average of June over the last 10 years. Green-yellow-red colours indicate areas with higher
temperature than the 10-year average, while blue colours indicate lower than average temperatures. Data source: Remote Sensed Surface
Temperature Anomaly, AIRS/Aqua L3 Monthly Standard Physical Retrieval 1-degree x 1-degree V006 (https://airs.jpl.nasa.gov/), obtained
from the GISS data portal (https://data.giss.nasa.gov/gistemp/maps/index_v4.html).

June 2024 global surface air temperature compared to June 2023

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June 2024 surface air temperature compared to June 2023. Green-yellow-red colours indicate regions where the present month was warmer
than last year, while blue colours indicate regions where the present month was cooler than last year. Variations in monthly temperature fromone year to the next has no tangible climatic importance but may nevertheless be interesting to study. Data source: Remote Sensed Surface
Temperature Anomaly, AIRS/Aqua L3 Monthly Standard Physical Retrieval 1-degree x 1-degree V006 (https://airs.jpl.nasa.gov/), obtained
from the GISS data portal (https://data.giss.nasa.gov/gistemp/maps/index_v4.html).

Temperature quality class 1: Lower troposphere temperature from satellites, updated to June 2024
(see page 9 for definition of classes)

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Global monthly average lower troposphere temperature (thin line) since 1979 according to University of Alabama at Huntsville, USA. The thickline is the simple running 37-month average. Reference period 1991-2020.

Global monthly average lower troposphere temperature (thin line) since 1979 according to according to Remote Sensing Systems (RSS), USA.
The thick line is the simple running 37-month average.

Temperature quality class 2: HadCRUT global surface air temperature, updated to May 2024

7

Global monthly average surface air temperature (thin line) since 1979 according to the Hadley Centre for Climate Prediction and Research andthe University of East Anglia's Climatic Research Unit (CRU), UK. The thick line is the simple running 37-month average.

Temperature quality class 3: GISS and NCDC global surface air temperature, updated to June 2024

Global monthly average surface air temperature since 1979 according to according to the National Climatic Data Center (NCDC), USA. The
thick line is the simple running 37-month average.

8

Global monthly average surface air temperature (thin line) since 1979 according to according to the Goddard Institute for Space Studies (GISS),at Columbia University, New York City, USA, using ERSST_v4 ocean surface temperatures. The thick line is the simple running 37-monthaverage.

A note on data record stability and -quality:
The temperature diagrams shown above all have 1979
as starting year. This roughly marks the beginning of
the recent episode of global warming, aftertermination of the previous episode of global coolingfrom about 1940. In addition, the year 1979 also
represents the starting date for the satellite-based
global temperature estimates (UAH and RSS). For thethree surface air temperature records (HadCRUT,
NCDC and GISS), they begin much earlier (in 1850 and
1880, respectively), as can be inspected onwww.climate4you.com.

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For all three surface air temperature records, but
especially NCDC and GISS, administrative changes toanomaly values are quite often introduced, evenaffecting observations many years back in time. Somechanges from the recent past may be due to thedelayed addition of new station data or change ofstation location, while others probably have their
origin in changes of the technique implemented to
calculate average values from the raw data. It isclearly impossible to evaluate the validity of suchadministrative changes for the outside user of theserecords; it is only possible to note that such changes
quite often are introduced (se example diagram nextpage).
In addition, the three surface records represent a
blend of sea surface data collected by moving ships orby other means, plus data from land stations of partly
unknown quality and unknown degree ofrepresentativeness for their region. Many of the land
stations also has been moved geographically during
their period of operation, instrumentation have beenchanged, and they are influenced by changes in theirnear surroundings (vegetation, buildings, etc.). The
surface network is inherently heterogeneous (dense
over continents but sparse over oceans) and probably
contaminated by urbanization surrounding manymeasurement sites.
The satellite temperature records also have theirproblems, but these are generally of a more technicalnature and probably therefore better correctable. In

addition, the temperature sampling by satellites ismore regular and complete on a global basis than that
represented by the surface records. It is also
important that the sensors on satellites measuretemperature directly by microwave radiance (thereby
unobstructed by clouds), while most modern surface
temperature measurements are indirect, using
electronic resistance.
Everybody interested in climate science should
gratefully acknowledge the big efforts put into
maintaining the different temperature databases
referred to in the present newsletter. At the sametime, however, it is also important to realise that all
temperature records cannot be of equal scientificquality. The simple fact that they to some degree
differ shows that they cannot all be correct.
On this background, and for practical reasons,Climate4you therefore operates with three quality
classes (1-3) for global temperature records, with 1
representing the highest quality level:
Quality class 1: The satellite records (UAH and RSS).
Quality class 2: The HadCRUT surface record.
Quality class 3: The NCDC and GISS surface records.

The main reason for discriminating between the threesurface records is the following:
While both NCDC and GISS often experience quite
large administrative changes (see example on p.10),
and therefore essentially must be considered as
unstable records, the changes introduced to HadCRUT
are fewer and smaller. For obvious reasons, as thepast does not change, any record undergoing
continuing changes cannot describe the past correctly
all the time. Frequent and large corrections in a
database unavoidably signal a fundamental
uncertainty about what is likely to represent thecorrect values.
You can find more on the issue of lack of temporalstability on www.climate4you.com (go to: Global
Temperature, and then proceed to Temporal
Stability).

10

Diagram showing the monthly adjustments made since May 2008 by the Goddard Institute for Space Studies (GISS),
USA, as recorded by published anomaly values for the two months January 1910 and January 2000. AR5 indicatestiming of publication of IPCC report AR5 Climate Change 2013: The Physical Science Basis.

The administrative upsurge of the temperature
increase from January 1915 to January 2000 has
grown from 0.45 (reported May 2008) to 0.67oC(reported July 2024). This represents an about 49%
administrative temperature increase over this period,

meaning that a significant (about half) part of theapparent global temperature increases from January
1910 to January 2000 (as reported by GISS) is causedby administrative changes of the original data since
May 2008.

Comparing global surface air temperature and lower troposphere satellite temperatures;
updated to May 2024

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Plot showing the average of monthly global surface air temperature estimates (HadCRUT5, GISS and NCDC) andsatellite-based temperature estimates (RSS MSU and UAH MSU). The thin lines indicate the monthly value, while
the thick lines represent the simple running 37-month average, nearly corresponding to a running 3-yr average.
The lower panel shows the monthly difference between average surface air temperature and satellite
temperatures. As the base period differs for the different temperature estimates, they have all been normalised bycomparing to the average value of 30 years from January 1979 to December 2008.

Global air temperature linear trends updated to May 2024

Diagram showing the latest 5, 10, 20 and 30-yr linear annual global temperature trend, calculated as the slope of the linear
regression line through the data points, for two satellite-based temperature estimates (UAH MSU and RSS MSU).

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Diagram showing the latest 5, 10, 20, 30, 50, 70 and 100-year linear annual global temperature trend, calculated as the slopeof the linear regression line through the data points, for three surface-based temperature estimates (GISS, NCDC and
HadCRUT5).

All in one, Quality Class 1, 2 and 3; updated to May 2024

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Superimposed plot of Quality Class 1 (UAH and RSS) global monthly temperature estimates. As the base period differs for theindividual temperature estimates, they have all been normalised by comparing with the average value of the initial 120 months(30 years) from January 1979 to December 2008. The heavy black line represents the simple running 37 month (c. 3 year) meanof the average of both temperature records. The numbers shown in the lower right corner represent the temperature anomaly
relative to the individual 1979-2008 averages.

Superimposed plot of Quality Class 1 and 2 (UAH, RSS and HadCRUT) global monthly temperature estimates. As the base period
differs for the individual temperature estimates, they have all been normalised by comparing with the average value of the initial
120 months (30 years) from January 1979 to December 2008. The heavy black line represents the simple running 37 month (c. 3year) mean of the average of all three temperature records. The numbers shown in the lower right corner represent thetemperature anomaly relative to the individual 1979-2008 averages.

Superimposed plot of Quality Class 1, 2 and 3 global monthly temperature estimates (UAH, RSS, HadCRUT, GISS and NCDC). As
the base period differs for the individual temperature estimates, they have all been normalised by comparing with the averagevalue of the initial 120 months (30 years) from January 1979 to December 2008. The heavy black line represents the simple
running 37 month (c. 3 year) mean of the average of all five temperature records. The numbers shown in the lower right corner
represent the temperature anomaly relative to the individual 1979-2008 averages.

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Please see reflections on page 9 relating to the above three quality classes.

Satellite- and surface-based temperature estimates
are derived from different types of measurements
and comparing them directly as in the above diagrams
therefore may be somewhat ambiguous.
However, as both types of estimates often are
discussed together in various news media, the above
composite diagrams may nevertheless be of someinterest.
In fact, the different types of temperature estimatesappear to agree as to the overall temperature
variations on a 2-3-year scale, although on a shortertime scale there are often considerable differences
between the individual records. However, since about
2003 the surface records used to be drifting towards
higher temperatures than the combined satellite
record, but this overall tendency was much removedby the major adjustment of the RSS satellite series in2015 (see lower diagram on page 6).

The combined records (diagram above) suggest amodest global air temperature increase over the last
40 years, about 0.18oC per decade. It should be notedthat the apparent temperature increases since about
2003 at least partly is the result of ongoingadministrative adjustments (page 9-10). At the sametime, none of the temperature records consideredhere indicates any overall temperature decreaseduring the last 20 years.
The present temperature development does not
exclude the possibility that global temperatures may
begin to increase significantly later. On the other
hand, it also remains a possibility that Earth just now
is passing an overall temperature peak, and that
global temperatures may begin to decrease during
the coming 5-10 years.
As always, time will show which of these possibilities
is correct.

Global sea surface temperature, updated to June 2024

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Sea surface temperature anomaly on 27 June 2024 (upper map) and 2023 (lower map). Map source: Plymouth State Weather
Center. Reference period: 1977-1991.

Because of the large surface areas near Equator, thetemperature of the surface water in these regions is
especially important for the global atmospherictemperature (p. 6-8). In fact, 50% of planet Earth’s
surface area is located within 30oN and 30oS.
A mixture of relatively warm and cold water presently
dominates much of the global ocean surface, but withnotable variations from month to month. All suchocean surface temperature changes will be
influencing global air temperatures in the months tocome. A cold La Niña episode (Pacific Ocean) has
recently ended and was followed by a warm (nowending) El Niño episode (maps p.15 and diagramp.25).

The significance of short-term cooling or warming
reflected in air temperatures should never beoverstated. Whenever Earth experiences cold La Niña
or warm El Niño episodes major heat exchanges takeplace between the Pacific Ocean and the atmosphereabove, sooner or later showing up in estimates of the
global air temperature.
However, this does not necessarily reflect similarchanges in the total heat content of the atmosphereocean system. In fact, global net changes can be smalland such heat exchanges may mainly reflect
redistribution of energy between ocean andatmosphere. What matters is the overall temperaturedevelopment when seen over several years.

16

Global monthly average lower troposphere temperature over oceans (thin line) since 1979 according to University of Alabama at Huntsville,
USA. The thick line is the simple running 37-month average. Insert: Argo global ocean temperature anomaly from floats, displaced verticallyto make visual comparison easier. UAH reference period: 1991-2020.

Global monthly average sea surface temperature since 1979 according to University of East Anglia's Climatic Research Unit (CRU), UK. Baseperiod: 1961-1990. The thick line is the simple running 37-month average. Insert: Argo global ocean temperature anomaly from floats,displaced vertically to make visual comparison easier.

17

Global monthly average sea surface temperature since 1979 according to the National Climatic Data Center (NCDC), USA. Base period: 19012000. The thick line is the simple running 37-month average. Insert: Argo global ocean temperature anomaly from floats, displaced verticallyto make visual comparison easier.

Ocean temperature in uppermost 100 m, updated to March 2024

World Oceans vertical average temperature 0-100 m depth since 1955. The thin line indicates 3-month values, and the thick line represents
the simple running 39-month (c. 3 year) average. Data source: NOAA National Oceanographic Data Center (NODC). Base period 1955-2010.

18

Pacific Ocean vertical average temperature 0-100 m depth since 1955. The thin line indicates 3-month values, and the thick line represents thesimple running 39-month (c. 3 year) average. Data source: NOAA National Oceanographic Data Center (NODC). Base period 1955-2010.

Atlantic Ocean vertical average temperature 0-100 m depth since 1955. The thin line indicates 3-month values, and the thick line represents
the simple running 39-month (c. 3 year) average. Data source: NOAA National Oceanographic Data Center (NODC). Base period 1955-2010.

19

Indian Ocean vertical average temperature 0-100 m depth since 1955. The thin line indicates 3-month values, and the thick line represents thesimple running 39-month (c. 3 year) average. Data source: NOAA National Oceanographic Data Center (NODC). Base period 1955-2010.

Pacific Decadal Oscillation (PDO), updated to June 2024

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Monthly values of the Pacific Decadal Oscillation (PDO) since January 1979. The PDO is a long-lived El Niño-like pattern of Pacific climate
variability, and the data series goes back to January 1854. Base period: 1982-2002. The thin line indicates monthly PDO values, and the thickline is the simple running 37-month average. Data source: NOAA Physical Science Laboratory (version PDO ERSST V5 plotted above).

The PDO is a long-lived El Niño-like pattern of Pacificclimate variability, with data extending back to
January 1854. Causes for PDO are not currently
known, but even in the absence of a theoreticalunderstanding, PDO climate information improves
season-to-season and year-to-year climate forecasts
for North America because of its strong tendency for
multi-season and multi-year persistence. The PDO
also appears to be roughly in phase with global
temperature changes. Thus, from a societal impact’s
perspective, recognition of PDO is important because
it shows that "normal" climate conditions can varyover time periods comparable to the length of ahuman's lifetime.

The PDO illustrates how global temperatures are tied
to sea surface temperatures in the Pacific Ocean, thelargest ocean on Earth. When sea surface
temperatures are relatively low (negative phase
PDO), as it was from 1945 to 1977, global air
temperature often decreases. When Pacific Ocean
surface temperatures are high (positive phase PDO),
as from 1977 to 1998, global surface air temperatureoften increases.
A Fourier frequency analysis (not shown here) shows
the PDO record to be influenced by a significant 5.6year cycle, and feasibly also by a longer 18.6-year
long period, corresponding to the length of the lunar
nodal tide.

North Atlantic heat content uppermost 700 m, updated to June 2021

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Global monthly heat content anomaly (1018 Joules) in the uppermost 700 m of the North Atlantic (60-0W, 30-65N; see map above) ocean since
January 1955. The thin line indicates monthly values, and the thick line represents the simple running 37-month (c. 3 year) average. Data
source: National Oceanographic Data Center (NODC).

North Atlantic temperatures 0-800 m depth along 59oN, 30-0W, updated to December 2021

Time series depth-temperature diagram along 59 N across the North Atlantic Current from 30oW to 0oW, from surface to 800 m
depth. Source: Global Marine Argo Atlas. See also the diagram below.

22

Average temperature along 59 N, 30-0W, 0-800m depth, corresponding to the main part of the North Atlantic Current, using
Argo-data. Source: Global Marine Argo Atlas. Additional information can be found in: Roemmich, D. and J. Gilson, 2009. The
2004-2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program.
Progress in Oceanography, 82, 81-100.

Global ocean temperature 0-1900 m depth summary, updated to December 2021

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Summary of average temperature in uppermost 1900 m in different parts of the global oceans, using Argo-data. Source: Global
Marine Argo Atlas. Additional information can be found in: Roemmich, D. and J. Gilson, 2009. The 2004-2008 mean and annual
cycle of temperature, salinity, and steric height in the global ocean from the Argo Program. Progress in Oceanography, 82, 81100.

The temperature of the global oceans down to 1900 m
depth has been increasing since about 2011, but with apossible peak around 2020. The global increase since 2013is mainly due to changes occurring near the Equator,
between 30oN and 30oS. In contrast, for the circum-Arctic

oceans north of 55oN, depth-integrated ocean
temperatures have been decreasing since 2011, but with apossible low around 2019. Near the Antarctic, south of
55oS, temperatures have essentially been stable. At mostlatitudes, a clear annual rhythm is evident.

Global ocean net temperature change since 2004 at different depths, updated to December 2020

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Net temperature change since 2004 from surface to 1900 m depth in different parts of the global oceans, using Argo-data.
Source: Global Marine Argo Atlas. Additional information can be found in: Roemmich, D. and J. Gilson, 2009. The 2004-2008
mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program. Progress in
Oceanography, 82, 81-100. Please note that due to the spherical form of Earth, northern and southern latitudes represent only
small ocean volumes, compared to latitudes near the Equator.

La Niña and El Niño episodes, Oceanic Niño Index (ONI), updated to June 2024

25
Warm (>+0.5oC) and cold (<0.5oC) episodes for the Oceanic Niño Index (ONI), defined as 3 month running mean of ERSSTv4 SST
anomalies in the Niño 3.4 region (5oN-5oS, 120o-170oW)]. For historical purposes cold and warm episodes are defined when thethreshold is met for a minimum of 5 consecutive over-lapping seasons. Anomalies are centred on 30-yr base periods updated
every 5 years.

In the Pacific Ocean, trade winds usually blow west
along the equator, pushing warm water from SouthAmerica towards Asia. To replace that warm water,
cold water rises from the depths near South America.
During El Niño episodes, trade winds weaken, andwarm water is spreading back east, toward SouthAmerica. In contrast, during La Niña episodes, tradewinds are stronger than usual, pushing more warm
water than usual toward Asia, and upwelling of cold
water near South America therefore increases.

The 2015-16 El Niño episode is among the strongest
since the beginning of the record in 1950. Considering
the entire record, however, recent variations
between El Niño and La Niña episodes do not appear
abnormal in any way.
A Fourier frequency analysis (not shown here) shows
the ONI record to be influenced by a significant 3.6year cycle, and feasibly also by a longer 5.6-year
cycle.

Zonal lower troposphere temperatures from satellites, updated to June 2024

26

Global monthly average lower troposphere temperature since 1979 for the tropics and the northern and southern extratropics,
according to University of Alabama at Huntsville, USA. Thin lines show the monthly temperature. Thick lines represent thesimple running 37-month average, nearly corresponding to a running 3-year average. Reference period 1981-2010.
The overall warming since 1980 has dominantly been anorthern hemisphere phenomenon, and mainly played out
as a marked change between 1994 and 1999. However, thisrather rapid temperature change is probably influenced by
the Mt. Pinatubo eruption 1992-93 and the subsequent
1997 El Niño episode. The diagram also shows thetemperature effects of the strong Equatorial El Niño’s in
1997 and 2015-16, as well as the moderate El Niño in 2019.
Apparently, these effects were spreading to higher
latitudes in both hemispheres with some delay. Recently, a
new El Niño was playing out in the Pacific Ocean (p.25), as
is clearly shown by tropics surface air temperatures.

Arctic and Antarctic lower troposphere temperature, updated to June 2024

27

Global monthly average lower troposphere temperature since 1979 for the North Pole and South Pole regions, based on satellite
observations (University of Alabama at Huntsville, USA). Thin lines show the monthly temperature. The thick line is the simple
running 37-month average, nearly corresponding to a running 3-year average. Reference period 1991-2020.

In the Arctic region, warming mainly took place 1994-96,
and less so subsequently. In 2016, however, temperatures
peaked for several months, presumably because of oceanic
heat given off to the atmosphere during the 2015-15 El
Niño (see also diagram on page 25) and subsequently
advected to higher latitudes.
This underscores how Arctic air temperatures may beaffected not only by variations in local conditions but also
by variations playing out in geographically remote regions.

A slight temperature decrease has characterised the Arctic
since the marked 2016 El Niño peak. In contrast, thepresent (2023-24) El Niño episode is recorded by Arctic
temperatures in a less pronounced way.
In the Antarctic region, temperatures have basicallyremained stable since the onset of the satellite record in
1979. In 2016-17 a small temperature peak visible in themonthly record may be interpreted as the subdued effectof the recent El Niño episode.

Arctic and Antarctic surface air temperature, updated to December 2021

Diagram showing area weighted Arctic (70-90oN) monthly surface air temperature anomalies (HadCRUT4) since January 2000,
in relation to the WMO normal period 1961-1990. The thin line shows the monthly temperature anomaly, while the thicker line
shows the running 37-month (c. 3 year) average.

28

Diagram showing area weighted Antarctic (70-90oS) monthly surface air temperature anomalies (HadCRUT4) since January
2000, in relation to the WMO normal period 1961-1990. The thin line shows the monthly temperature anomaly, while thethicker line shows the running 37-month (c. 3 year) average.

Diagram showing area weighted Arctic (70-90oN) monthly surface air temperature anomalies (HadCRUT4) since January 1957,
in relation to the WMO normal period 1961-1990. The thin line shows the monthly temperature anomaly, while the thicker line
shows the running 37-month (c. 3 year) average.

29

Diagram showing area weighted Antarctic (70-90oS) monthly surface air temperature anomalies (HadCRUT4) since January
1957, in relation to the WMO normal period 1961-1990. The thin line shows the monthly temperature anomaly, while thethicker line shows the running 37-month (c. 3 year) average.

Diagram showing area-weighted Arctic (70-90oN) monthly surface air temperature anomalies (HadCRUT4) since January 1920,
in relation to the WMO normal period 1961-1990. The thin line shows the monthly temperature anomaly, while the thicker line
shows the running 37-month (c. 3 year) average.

30

Because of the relatively small number of Arctic
stations before 1930, month-to-month variations in
the early part of the Arctic temperature record 19202018 are higher than later (diagram above).
The period from about 1930 saw the establishment ofmany new Arctic meteorological stations, first in
Russia and Siberia, and following the 2nd World War,also in North America, explaining the above
difference.
The period since 2005 is warm, about as warm as theperiod 1930-1940.
As the HadCRUT4 data series has improved highlatitude coverage data coverage (compared to the
HadCRUT3 series), the individual 5ox5o grid cells havebeen weighted according to their surface area. This
area correction is especially important for polar

regions, where longitudes converge rapidly. Thisapproach differs from the approach used by Gillet etal. 2008, which calculated a simple average, with nocorrection for the substantial latitudinal surface area
effect in polar regions.
The area weighted Arctic HadCRUT4 surface airtemperature anomalies (p.28-30) correspond rather
well to the lower troposphere temperature anomalies
recorded by satellites (p.27).

Literature:
Gillett, N.P., Stone, D.A., Stott, P.A., Nozawa, T.,
Karpechko, A.Y.U., Hegerl, G.C., Wehner, M.F. andJones, P.D. 2008. Attribution of polar warming tohuman influence. Nature Geoscience 1, 750-754.

Long Arctic annual surface air temperature series, updated to year 2023

31

Arctic annual surface air temperature series, selected because of their length of observation time. The thin blue line
represents the mean annual air temperature, and the thick blue line is the running 5-year average. Annual values
were calculated from monthly average temperatures. More info on Climate4you.

Long Antarctic annual surface air temperature series, updated to year 2023

32

Antarctic annual surface air temperature series, selected because of their length of observation time. The thin blueline represents the mean annual air temperature, and the thick blue line is the running 5-year average. Annual
values were calculated from monthly average temperatures. More info on Climate4you.

Temperature over land versus over oceans, updated to June 2024

33

Global monthly average lower troposphere temperature since 1979 measured over land and oceans, respectively, according toUniversity of Alabama at Huntsville, USA. Thick lines are the simple running 37-month average, nearly corresponding to arunning 3-year average. Reference period 1991-2020.

Since 1979, the lower troposphere over land has
warmed much more than over oceans, suggestingthat the overall warming is derived mainly fromincoming solar radiation. In addition, there may besupplementary reasons for this divergence, such as,e.g., variations in cloud cover and changes in land use.
Compare also with cloud cover diagram on page 60.
The present (2023) El Niño episode is recorded more
pronounced over land regions, compared to ocean
regions.

Troposphere and stratosphere temperatures from satellites, updated to June 2024

34

Global monthly average temperature in different according to University of Alabama at Huntsville, USA. The thin lines
represent the monthly average, and the thick line the simple running 37-month average, nearly corresponding to a running 3year average. Reference period 1991-2020.

Arctic and Antarctic sea ice, updated to June 2024

35

Sea ice extent 29 June 2024. The median limit of sea ice (orange line) is defined as 15% sea ice cover, according to the average of satellite
observations 1981-2010 (both years included). Sea ice may therefore well be encountered outside and open water areas inside the limit shownin the diagrams above. Map source: National Snow and Ice Data Center (NSIDC).

Diagrams showing Arctic sea ice extent and concentration 29 June 2023 (left) and 2024 (right), according to the Japan Aerospace Exploration
Agency (JAXA).

36

Graphs showing monthly Antarctic, Arctic, and global sea ice extent since November 1978, according to the National Snow and Ice data Center(NSIDC).

Diagram showing daily Arctic sea ice extent since June 2002, to 29 June 2024, data courtesy of Japan Aerospace Exploration Agency (JAXA).

37

Diagrams showing Arctic sea ice extent and thickness 30 June 2023 (left) and 2024 (right and above) and the seasonal cycles of
the calculated total arctic sea ice volume, according to The Danish Meteorological Institute (DMI). The mean sea ice volume
and standard deviation for the period 2004-2013 are shown by grey shading. Please note that DMI on 7 December 2021
changed their sea ice calculation model. DMI’s description of the model version change can be read here:
http://polarportal.dk/en/sea-ice-and-icebergs/sea-ice-thickness-and-volume/38

12 month running average sea ice extension, global and in both hemispheres since 1979, the satellite-era. The October 1979 value
represents the monthly 12-month average of November 1978 - October 1979, the November 1979 value represents the average of December
1978 - November 1979, etc. The stippled lines represent a 61-month (ca. 5 years) average. Data source: National Snow and Ice Data Center(NSIDC).

Sea level in general
Global (or eustatic) sea-level change is measured relative to an
idealised reference level, the geoid, which is a mathematicalmodel of planet Earth’s surface (Carter et al. 2014). Global sealevel is a function of the volume of the ocean basins and thevolume of water they contain. Changes in global sea-level arecaused by – but not limited to - four main mechanisms:
1.
2.
3.
4.

Changes in local and regional air pressure and wind, andtidal changes introduced by the Moon.
Changes in ocean basin volume by tectonic (geological)
forces.
Changes in ocean water density caused by variations incurrents, water temperature and salinity.
Changes in the volume of water caused by changes in
the mass balance of terrestrial glaciers.

In addition to these there are other mechanisms influencing sealevel, such as storage of ground water, storage in lakes and rivers,
evaporation, etc.

39

Mechanism 1 is controlling sea-level at many sites on a time scalefrom months to several years. As an example, many coastal
stations show a pronounced annual variation reflecting seasonalchanges in air pressures and wind speed. Longer-term climaticchanges playing out over decades or centuries will also affectmeasurements of sea-level changes. Hansen et al. (2011, 2015)
provide excellent analyses of sea-level changes caused byrecurrent changes of the orbit of the Moon and otherphenomena.
Mechanism 2 – with the important exception of earthquakes andtsunamis - typically operates over long (geological) time scales
and is not significant on human time scales. It may relate tovariations in the seafloor spreading rate, causing volume changes
in mid-ocean mountain ridges, and to the slowly changing
configuration of land and oceans. Another effect may be the slow
rise of basins due to isostatic offloading by deglaciation after an
ice age. The floor of the Baltic Sea and the Hudson Bay arepresently rising, causing a slow net transfer of water from thesebasins into the adjoining oceans. Slow changes of excessively big
glaciers (ice sheets) and movements in the mantle will affect thegravity field and thereby the vertical position of the ocean surface.
Any increase of the total water mass as well as sedimentdeposition into oceans increase the load on their bottom,
generating sinking by viscoelastic flow in the mantle below. The
mantle flow is directed towards the surrounding land areas, which
will rise, thereby partly compensating for the initial sea level
increase induced by the increased water mass in the ocean.
Mechanism 3 (temperature-driven expansion) only affects theuppermost part of the oceans on human time scales. Usually,
temperature-driven changes in density are more important thansalinity-driven changes. Seawater is characterised by a relatively
small coefficient of expansion, but the effect should however not
be overlooked, especially when interpreting satellite altimetrydata. Temperature-driven expansion of a column of seawater will
not affect the total mass of water within the column considered
and will therefore not affect the potential at the top of the watercolumn. Temperature-driven ocean water expansion will
therefore not in itself lead to any lateral displacement of water,
but only locally lift the ocean surface. Near the coast, where
people are living, the depth of water approaches zero, so no
measurable temperature-driven expansion will take place here
(Mörner 2015). Mechanism 3 is for that reason not important forcoastal regions.
Mechanism 4 (changes in glacier mass balance) is an importantdriver for global sea-level changes along coasts, for human timescales. Volume changes of floating glaciers – ice shelves – has noinfluence on the global sea-level, just like volume changes offloating sea ice has no influence. Only the mass-balance ofgrounded or land-based glaciers is important for the global sealevel along coasts.
Summing up: Presumably, mechanism 1 and 4 are the mostimportant for understanding sea-level changes along coasts.

References:
Carter R.M., de Lange W., Hansen, J.M., Humlum O., Idso C., Kear, D., Legates, D., Mörner, N.A., Ollier C., Singer F. & Soon W. 2014.
Commentary and Analysis on the Whitehead& Associates 2014 NSW Sea-Level Report. Policy Brief, NIPCC, 24. September 2014, 44 pp.
http://climatechangereconsidered.org/wp-content/uploads/2014/09/NIPCC-Report-on-NSW-Coastal-SL-9z-corrected.pdf
Hansen, J.-M., Aagaard, T. and Binderup, M. 2011. Absolute sea levels and isostatic changes of the eastern North Sea to central Baltic region
during the last 900 years. Boreas, 10.1111/j.1502-3885.2011.00229.x. ISSN 0300–9483.
Hansen, J.-M., Aagaard, T. and Huijpers, A. 2015. Sea-Level Forcing by Synchronization of 56- and 74-YearOscillations with the Moon’s Nodal
Tide on the Northwest European Shelf (Eastern North Sea to Central Baltic Sea). Journ. Coastal Research, 16 pp.
Mörner, Nils-Axel 2015. Sea Level Changes as recorded in nature itself. Journal of Engineering Research and Applications, Vol.5, 1, 124-129.

Global sea level from satellite altimetry, updated to September 2023

40

Global sea level since December 1992 according to the Colorado Center for Astrodynamics Research at University of Colorado at Boulder. The
blue dots are the individual observations, and the purple line represents the running 121-month (ca. 10 year) average. The two lower panels
show the annual sea level change, calculated for 1 and 10-year time windows, respectively. These values are plotted at the end of the interval
considered. Compare with tide-gauge diagram on page 41.

Ground truth is a term used in various fields to refer toinformation provided by direct observation as opposed to
information provided by inference, such as, e.g., by satellite
observations.

aids in the interpretation and analysis of what is being
sensed or recorded by satellites. Ground truth sites allow
the remote sensor operator to correct and improve theinterpretation of satellite data.

In remote sensing using satellite observations, ground truth
data refers to information collected on location. Groundtruth allows the satellite data to be related to real features
observed on the planet surface. The collection of groundtruth data enables calibration of remote-sensing data, andFor satellite observations on sea level ground true data areprovided by the classical tide gauges (example diagram onnext page), that directly measures the local sea level many
places distributed along the coastlines on the surface of theplanet.

Global sea level from tide-gauges, extended Holgate-9, updated to December 2022

41

Extended Holgate-9 monthly tide-gauge data from PSMSL Data Explorer. Holgate (2007) suggested 9 stations to capture the global variability
found in a larger number of stations over the last half century studied previously. However, some of the stations suggested by Holgate has notreported values for several years, leading to the southern hemisphere now being seriously underrepresented in his original data set. Therefore,
in the above diagram several other long tide-gauge series have been included, to provide a more balanced representation of both hemispheres(15 stations in total). The blue dots are the individual average monthly observations, and the purple line represents the running 121-month(ca. 10 year) average. The two lower panels show the average annual sea level change, calculated for moving 1 and 10-year windows,
respectively. These values are plotted at the end of the time window considered, month by month.

Data from tide-gauges all over the world suggest an
average global sea-level rise of 1-2 mm/year, while themodern satellite-derived record (since 1992, page 40)
suggest a rise of about 3.4 mm/year, or more. The
difference between the two data sets is remarkable. It is
however known that satellite observations are facing

several complications in areas near the coast. Vignudelli etal. (2019) provide an updated overview of the current
limitations of classical satellite altimetry in coastal regions.
Since 2015 a sea level increase rate may be suggested by
the above composite record.

References:
Holgate, S.J. 2007. On the decadal rates of sea level change during the twentieth century. Geophys. Res. Letters, 34, L01602,
doi:10.1029/2006GL028492
Vignudelli et al. 2019. Satellite Altimetry Measurements of Sea Level in the Coastal Zone. Surveys in Geophysics, Vol. 40, p. 1319–1349.
https://link.springer.com/article/10.1007/s10712-019-09569-1

This month’s selected sea level station (tide-gauge): Port Louis, Republic of Mauritius, Southern Indian
Ocean

42

Port Louis monthly tide gauge data from PSMSL Data Explorer. The blue dots are the individual monthly observations, and the
purple line represents the running 121-month (ca. 10 yr) average. The two lower panels show the annual sea level change,
calculated for 1 and 10 yr time windows, respectively. These values are plotted at the end of the interval considered.

Port Louis is the capital of Mauritius (Republic of
Mauritius). Mauritius is an island nation in the Indian
Ocean, about 950 km east of Madagascar. Along withthe other Mascarene Islands, Mauritius is known for
its many species endemic to the island. The island was
the only known home of the flightless dodo bird –famous from ‘Alice's Adventures in Wonderland’ which was made extinct by human activities relatively
shortly after the island's settlement in the late 16th

century. If the observed relative sea level rise since1986 at Port Louis continues, relative sea level will
have increased about 40 cm by year 2100.
The Indian Ocean is the third-largest of theworld's oceanic divisions, covering 70,560,000 km2 or
almost 20% of the water on Earth's surface. In
contrast to the Atlantic and Pacific, the Indian Ocean
is enclosed by major landmasses and an archipelago

on three sides and does not stretch from pole to pole.
In fact, it can be likened to an embayed ocean, andseveral other features make the Indian Ocean unique.
It constitutes the core of the large-scale Tropical
Warm Pool which, when interacting with theatmosphere, affects the climate both regionally andglobally. Asia blocks heat export in the ocean towards
north, and the Indian Ocean is the warmest ocean in
the world.
The Indian Ocean contains several islands, some ofwhich is known from the ongoing sea-level change
debate, mainly because of a claimed rapid relative sea
level rise. Many of these islands are volcanic in origin,and due to their high bedrock density, they will43

inevitably sink slowly because of crustal deformation.
Several of these volcanic islands were eroded down to
the former 120-130 m long-lasting lower sea level
during the Quaternary glaciations. The position andoutline of several of these eroded and drowned
volcanoes are today indicated at the ocean surface byfringing coral reefs, where colonies of reef building
corals have been able to accommodate the about 120
m sea level rise since the maximum of the last glacial
period, keeping pace with rising sea level by vertical
growth and accretion. In the Indian Ocean, coral reefs
are widespread north of 30oS.

Northern Hemisphere weekly and seasonal snow cover, updated to June 2024

Northern hemisphere snow cover (white) and sea ice (yellow) 29 June 2023 (left) and 2024 (right). Map source: National Ice
Center (NIC).

44

Northern hemisphere weekly snow cover since January 2000 according to Rutgers University Global Snow Laboratory. The thin blue line is
the weekly data, and the thick blue line is the running 53-week average (approximately 1 year). The horizontal red line is the 1972-2023
average.

Northern hemisphere weekly snow cover since January 1972 according to Rutgers University Global Snow Laboratory. The thin blue line is
the weekly data, and the thick blue line is the running 53-week average (approximately 1 year). The horizontal red line is the 1972-2023
average.

45

Northern hemisphere seasonal snow cover since January 1972 according to Rutgers University Global Snow Laboratory.

Greenland Ice Sheet net surface mass balance, updated to June 2024

46

Left: Surface mass balance 29 June 2024. Right: Net surface mass balance anomaly since September 1, 2023. Courtesy of Danish
Meteorological Institute (DMI).

Atmospheric relative and specific humidity, updated to June 2024

47

Relative atmospheric humidity (g/kg) at three different altitudes in the lower part of the atmosphere (the Troposphere) since January 1948
(Kalnay et al. 1996). The thin blue lines show monthly values, while the thick blue lines show the running 37-month average (about 3 years).
Data source: Earth System Research Laboratory (NOAA).

48

Specific atmospheric humidity (g/kg) at three different altitudes in the lower part of the atmosphere (the Troposphere) since January 1948
(Kalnay et al. 1996). The thin blue lines show monthly values, while the thick blue lines show the running 37-month average (about 3 years).
Data source: Earth System Research Laboratory (NOAA).

Water vapor is the most important greenhouse gas in the
Troposphere. The highest concentration is found within alatitudinal range from 50oN to 60oS. The two polar regionsof the Troposphere are comparatively dry.

A Fourier frequency analysis (not shown here) suggests
these changes are influenced, not only by the significant
annual variation, but feasibly also by a longer variation of
about 35-years’ duration.

The diagram above shows the specific atmospherichumidity to be stable or slightly increasing up to about 4-5
km altitude. At higher levels in the Troposphere (about 9km), the specific humidity has been decreasing for theduration of the record (since 1948), but with shorter
variations superimposed on the falling trend.

The persistent decrease in specific humidity at about 9 km
altitude is particularly noteworthy, as this altitude roughly
corresponds to the level where the theoreticaltemperature effect of increased atmospheric CO2 is
expected initially to play out.

Atmospheric CO2, updated to June 2024

49

Monthly amount of atmospheric CO2 (upper diagram) and annual growth rate (lower diagram); average last 12 months minus average
preceding 12 months, thin line) of atmospheric CO2 since 1959, according to data provided by the Mauna Loa Observatory, Hawaii, USA. The
thick, stippled line is the simple running 37-observation average, nearly corresponding to a running 3-year average. A Fourier frequency
analysis (not shown here) shows the 12-month change of Tropospheric CO2 to be influenced especially by periodic variations of 2.5- and 3.8years’ duration.

The relation between annual change of atmospheric CO 2 and La Niña and El Niño episodes, updated toJune 2024

50

Visual association between annual growth rate of atmospheric CO2 (upper panel) and Oceanic Niño Index (lower panel). See also diagrams
on page 47 and 25, respectively.

Changes in the global atmospheric CO2 is seen to varyroughly in concert with changes in the Oceanic Niño Index.
The typical sequence of events is that changes in the global
atmospheric CO2 to a certain degree follows changes in the
Oceanic Niño Index, but clearly not in all details. Many
processes, natural as well as anthropogenic, controls theamount of atmospheric CO2, but oceanographic processes
are clearly particularly important (see also diagram on nextpage).
Atmospheric CO2 and the recent coronavirus pandemic
Modern political initiatives usually assume the human
influence (mainly the burning of fossil fuels) to represent

the core reason for the observed increase in atmospheric
CO2 since 1958 (diagrams on page 47).
The coronavirus pandemic since January 2020 resulted in amarked reduction in the global consumption of fossil fuels.
It is therefore enlightening to follow the effect of thisreduction on the amount of atmospheric CO2.
However, there is still no clear effect to be seen of theabove reduction in release of CO2 from fossil fuels.
Presumably, the main explanation for this is that thehuman contribution is too small compared to thenumerous natural sources and sinks for atmospheric CO2 toappear in diagrams showing the amount of atmospheric
CO2.

The phase relation between atmospheric CO2 and global temperature, updated to May 2024

51

12month change of global atmospheric CO2 concentration (Mauna Loa; green), global sea surface temperature (HadSST4; blue) and global
surface air temperature (HadCRUT5; red dotted). Entire data series since 1958 in upper figure, and last 15 years in lower figure, to enhancemodern dynamics. All graphs are showing monthly values of DIFF12, the difference between the average of the last 12 month and theaverage for the previous 12 months for each data series.

The typical sequence of events is seen to be that changes
in the global atmospheric CO2 follow changes in global
surface air temperature, which again follow changes in
global ocean surface temperatures. Thus, changes in global

atmospheric CO2 usually are lagging 9.5–10 months behindchanges in global air surface temperature, and 11–12
months behind changes in global sea surface temperature.

Reference: Humlum, O., Stordahl, K. and Solheim, J-E. 2012. The phase relation between atmospheric carbon dioxide andglobal temperature. Global and Planetary Change, August 30, 2012.
http://www.sciencedirect.com/science/article/pii/S0921818112001658?v=s5

Global air temperature and atmospheric CO2, updated to June 2024

52

53

54

Diagrams showing UAH, RSS, HadCRUT5, NCDC and GISS monthly global air temperature estimates (blue) and the monthly
atmospheric CO2 content (red) according to the Mauna Loa Observatory, Hawaii. Purple line (running along red CO2 curve) showstheoretical temperature change due to changing atmospheric CO2. The Mauna Loa data series begins in March 1958, and 1958
was therefore chosen as starting year for all diagrams above. Reconstructions of past atmospheric CO2 concentrations (before1958) are not incorporated in this diagram, as such past CO 2 values are derived by other means (ice cores, stomata, or older
measurements using different methodology), and therefore are not directly comparable with direct atmospheric measurements.

From a theoretical point of view, it is generally agreed thatthe atmospheric temperature effect ∆T of increasing
atmospheric CO2 may be expressed as (see, e.g. Myhre etal. 1998 and IPCC Third Assessment Report, section 6.1):∆T = ∆F * 
where ∆F = 5,35ln(C1/Co) W/m2, and where Co and C1
indicates the concentration of atmospheric CO2 at the
beginning and end of the time interval considered. The
factor  is a so-called climate sensitivity parameter(expressing the global mean surface temperature responseto the imposed radiative CO2 forcing). This factor has been
determined to about 0,26oCW-1m2. The relation shows thatas the concentration of atmospheric CO2 increases, its

theoretical greenhouse effect increases in a logarithmic
fashion, not linear. Therefore, for each increase in CO2
concentration, the effect on temperature is smaller andsmaller.
If all other effects in the real world are ignored, the above
relation shows that any doubling of atmospheric CO2
concentration produces a temperature increase of nearly
1oC (0.96oC), no matter how high the initial concentrationof CO2.
The purple line in the above diagrams (p.50-52) iscalculated using the observed concentration of
atmospheric CO2 since March 1958. The axis for CO2 isadjusted to show overlap between CO2 (red) and thecalculated accumulated temperature effect (purple). In allgraphs, the temperature anomality axis has been adjusted
to position the initial calculated effect of CO2 roughly at the
average for the beginning of the observed temperaturegraph (blue). This is done to make it possible to compare
the theoretical CO2 temperature development (purple)
with the observed development (blue).
All these diagrams show the observed temperaturedevelopment to be much more complicated than thetheoretical development from atmospheric CO 2 alone.
With exception of the UAH diagram, the overall observed
temperature increases since 1958 is much larger thancalculated from CO2 alone. In addition, the observed
temperature development is characterised by recurrent
intervals characterised by increasing and decreasing
temperatures, respectively, a development extremely
different from the calculated temperature (purple graph).
Clearly many other factors than only CO2 is in control of thereal-world atmospheric temperature.

55

In contrast to this real-world observation, climate models
are programmed to give the greenhouse gas carbon dioxide
CO2 a leading role on control on the global air temperature.

The fact that the observed real-world temperature has
been changing much more than expected just from CO2, isusually ascribed to an added greenhouse effect of
atmospheric water vapour in the upper Troposphere, theconcentration of which by the models is expected toincrease along with CO2 (see, e.g. Schneider et. al. 1999).
However, measurements of water vapour in the upper
Troposphere apparently show this assumption to be
mistaken (see, e.g., diagram on p.46). Therefore, the quite
substantial difference between modelled and observed
atmospheric temperature must be caused by other factors(see, e.g., Koutsoyiannis and Vournas 2023). In addition,
the very dynamic change pattern displayed by the observed
temperature also needs to be explained before a soundunderstanding of global climate dynamics can be claimed.
All temperature-CO2 diagrams (p.50-52) shows both
atmospheric temperature and atmospheric CO2 to be
increasing since 1959. However, this fact does notdemonstrate that temperature is controlled by CO2. In fact,
it might just as well demonstrate the opposite relation(temperature controlling CO2), or, that both temperature
and CO2 is controlled by a third factor.

Litterature:
Demetris Koutsoyiannis & Christos Vournas 2023. Revisiting the greenhouse effect – a hydrological perspective. Hydrological
Sciences Journal, doi: 10.1080/02626667.2023.2287047
Myhre, G., E. Highwood, K. Shine, and F. Stordal 1998. New estimates of radiative forcing due to well mixed greenhouse gases,
Geophys. Res. Lett., 25(14), 2715–2718, doi:10.1029/98GL0190
Schneider, E.K., Kirtman, B.P., and Lindzen, R.S. 1999. Tropospheric Water Vapor and Climate Sensitivity. Journal of the
Atmospheric Sciences, 56, 1649-1658.

Latest 20-year QC1 global monthly air temperature changes, updated to May 2024

56
Last 20 years’ global monthly average air temperature according to Quality Class 1 (UAH and RSS; see p.6 and 9) global monthly
temperature estimates. The thin blue line represents the monthly values. The thick black line is the linear fit, with 95% confidence
intervals indicated by the two thin black lines. The thick green line represents a 5-degree polynomial fit, with 95% confidence
intervals indicated by the two thin green lines. A few key statistics are given in the lower part of the diagram (please note thatthe linear trend is the monthly trend).

In the enduring scientific climate debate, the following
question is often put forward: Is the surface airtemperature still increasing or has it basically remained
without significant changes during the last 15-16 years?
The diagram above may be useful in this context anddemonstrates the differences between two often usedstatistical approaches to determine recent temperature
trends. Please also note that such fits only attempt todescribe the past, and usually have small, if any, predictive
power.
In addition, before using any linear trend (or other) analysisof time series a proper statistical model should be chosen,
based on statistical justification.

For global temperature time series, there is no a priori
physical reason why the long-term trend should be linear intime. In fact, climatic time series often have trends forwhich a straight line is not a good approximation, as isclearly demonstrated by several of the diagrams shown in
the present report.
For an commendable description of problems often
encountered by analyses of temperature time series
analyses, please see Keenan, D.J. 2014: Statistical Analysesof Surface Temperatures in the IPCC Fifth Assessment
Report.

Sunspot activity (SIDC) and QC1 average satellite global air temperature, updated to May 2024

57

Variation of global monthly air temperature according to Quality Class 1 (UAH and RSS; see p.4) and observed sunspot number
as provided by the Solar Influences Data Analysis Center (SIDC), since 1979. The thin lines represent the monthly values, while
the thick line is the simple running 37-month average, nearly corresponding to a running 3-year average. The asymmetricaltemperature 'bump' around 1998 is influenced by the oceanographic El Niño phenomenon in 1998, as is the case also for 201516. Temperatures in year 2019-20 was influenced by a moderate El Niño. In summer 2023 a new El Niño episode has begun(see diagram on p.25).

Monthly sunspot activity (SIDC) and average neutron counts (Oulu, Finland), updated to June 2024

58

Observed monthly sunspot number (Solar Influences Data Analysis Center (SIDC) since April 1964, and (lower panel) monthly
average counts of the Oulu (Finland) neutron monitor, adjusted for barometric pressure and efficiency.

Monthly sunspot activity (SIDC), Oceanic Niño Index (ONI), and change rates of atmospheric CO 2 andspecific humidity, updated to June 2024

59

Visual association since 1958 between (from bottom to top) Sunspot Number, Oceanic Niño Index (ONI) and annual change
rate of atmospheric CO2. and specific humidity at 300 mb (ca. 9 km altitude). Upper two panels: Annual (12 month) change
rate of atmospheric CO2 and specific humidity at 300 mb since 1959, calculated as the average amount of atmospheric
CO2/humidity during the last 12 months, minus the average for the preceding 12 months (see also diagrams on page
43+44). Niño index panel: Warm (>+0.5oC) and cold (<0.5oC) episodes for the Oceanic Niño Index (ONI), defined as 3 monthrunning mean of ERSSTv4 SST anomalies in the Niño 3.4 region (5 oN-5oS, 120o-170oW)]. For historical purposes cold andwarm episodes are defined when the threshold is met for a minimum of 5 consecutive over-lapping seasons. Anomalies arecentred on 30-yr base periods updated every 5 years. Thin vertical stippled lines indicate the visually estimated timing ofsunspot minima. The typically sequence following a sunspot minimum appears to be a warm El Niño episode followed by acold La Niña episode. Effects on change rates of atmospheric CO2 and atmospheric specific humidity are visually apparent,with ONI variations being followed by changes in first humidity, and then (last) by CO2.

The above diagram is inspired by the Leamon et al. 2021 publication: Robert J. Leamon, Scott W. McIntosh,
Daniel R. Marsh. Termination of Solar Cycles and Correlated Tropospheric Variability. Earth and Space Science,
2021; 8 (4) DOI: 10.1029/2020EA001223

Monthly lower troposphere temperature (UAH) and global cloud cover, updated to April 2021

60

Lower tropospheric air temperature and global cloud cover. Upper panel: Global cloud cover according to Satellite Application Facility on
Climate Monitoring. Lower panel: Global monthly average lower troposphere temperature (thin line) since 1979 according to University of
Alabama at Huntsville, USA. The thick lines represent the simple running 37-month average. Reference period for UAH is 1991-2020.

Cloud cover data citation: Karlsson, Karl-Göran; Anttila, Kati; Trentmann, Jörg; Stengel, Martin; Solodovnik, Irina; Meirink, Jan
Fokke; Devasthale, Abhay; Kothe, Steffen; Jääskeläinen, Emmihenna; Sedlar, Joseph; Benas, Nikos; van Zadelhoff, Gerd-Jan;
Stein, Diana; Finkensieper, Stephan; Håkansson, Nina; Hollmann, Rainer; Kaiser, Johannes; Werscheck, Martin (2020): CLARAA2.1: CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - Edition 2.1, Satellite Application Facility on
ClimateMonitoring,
DOI:10.5676/EUM_SAF_CM/CLARA_AVHRR/V002_01, https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V002_01.

Climate and history; one example among many
384-322 BC; Aristotle's views on weather and climate

61

Marble bust of Aristotle (left). Roman copy after a Greek bronze original by Lysippus c. 330 BC. Geocentric celestial
spheres (center); Peter Apian's Cosmographia (Antwerp, 1539). Right picture: Plato (left) and Aristotle (right), a
detail of The School of Athens, a fresco by Raphael. Aristotle gestures to the earth, representing his belief inknowledge through empirical observation and experience, while holding a copy of his Nicomachean Ethics in his
hand, whilst Plato gestures to the heavens, representing his belief in The Forms.

Aristotle (384-322 BC) was a Greek philosopher, astudent of Plato and later teacher of Alexander theGreat. Aristotle is one of the most important
founding figures in Western philosophy, and his
views on the physical sciences profoundly shaped
medieval scholarship, and their influence extended
well into the Renaissance, although they were
ultimately replaced by Newtonian physics. Much of
the summary below is adopted from different
sources in Wikepedia and from Rasmussen 2010,
from where additional information is available.

BC Aristotle was invited by Philip II of Macedon to
become the tutor to his son Alexander the Great.
Aristotle was appointed as the head of the royalacademy of Macedon and gave lessons not only toAlexander, but also to two other future kings:
Ptolemy and Cassander. By 335 BC he had returned
to Athens, establishing his own school there known
as the Lyceum, where he conducted courses at for
the next twelve years. It is during this period in
Athens from 335 to 323 BC when Aristotle is believed
to have composed many of his works.

Aristotle was born in Stageira in 384 BC, about 55 km
east of the modern-day city Thessalonika. His father
Nicomachus was the personal physician to King
Amyntas of Macedon. Aristotle was trained andeducated as a member of the aristocracy. At about
the age of eighteen, he went to Athens to continue
his education at Plato's Academy. Aristotle remainedat the academy for nearly twenty years before
quitting Athens in 348/47 BC, and traveling to Asia
Minor, where he studied botany and zoology. In 343

Aristotle studied almost every subject possible at thetime, and made significant contributions to most ofthem. In physical science, Aristotle studied anatomy,
astronomy, embryology, geography, geology,
meteorology, physics and zoology. In philosophy, hewrote on aesthetics, ethics, government,
metaphysics, politics, economics, psychology,
rhetoric and theology. He also studied education,
foreign customs, literature and poetry. His combined
works constitute a virtual encyclopedia of Greekknowledge. It has been suggested that Aristotle wasprobably the last person to know everything there
was to be known in his own time. Like his teacher
Plato, Aristotle's philosophy was aiming at theuniversal. Aristotle, however, found the universal inparticular things, which he called the essence ofthings. Aristotle's method is both inductive anddeductive, while Plato's is essentially deductive froma priori principles.
In 350 BC Aristotle wrote a treatise entitled'Meteorologica', which probably is the first attempt
ever to make a comprehensive about the earthsciences, including meteorology. 'Meteorologica'consists of four books, including early accounts ofwater evaporation, weather phenomena, andearthquakes, and was considered a benchmark
publication for more than 2000 years. Interestingenough, Aristotle expected clouds to consist ofwater. In chapter (part) nine in his first book, hedirectly states that 'air condensing into water iscloud'.

62•

Clouds and rain••

In 'Meteorologica' Aristotle presents a number ofinteresting interpretations concerning different
phenomena related to the Earth, atmosphere, clouds
weather, climate and climate change effects:
Earth, Sun and atmosphere
•

•
•

•

•

The earth is surrounded by water, just as thatis by the sphere of air, and that again by thesphere called that of fire.
...four bodies are fire, air, water, earth.
Fire occupies the highest place among themall, earth the lowest, and two elements
correspond to these in their relation to one
another, air being nearest to fire, water toearth.
...the motion of these latter bodies [of four]
being of two kinds: either from the centre orto the centre.
Fire, air, water, earth, we assert, originate
from one another, and each of them exists
potentially in each, as all things do that canbe resolved into a common and ultimate
substrate.

The efficient and chief and first cause is thecircle in which the sun moves. For the sun as
it approaches or recedes, obviously causes
dissipation and condensation and so gives
rise to generation and destruction.

•

Now the earth remains but the moisturesurrounding it is made to evaporate by the
sun's rays and the other heat from above,and rises. But when the heat which was
raising it leaves it, in part dispersing to thehigher region, in part quenched throughrising so far into the upper air, then thevapour cools because its heat is gone andbecause the place is cold, and condenses
again and turns from air into water. And
after the water has formed it falls down
again to the earth.
Since water is generated from air, and air
from water, why are clouds not formed in theupper air? They ought to form there themore, the further from the earth and thecolder that region is. For it is neither
appreciably near to the heat of the stars, nor
to the rays reflected from the earth. It isthese that dissolve any formation by theirheat and so prevent clouds from forming
near the earth. For clouds gather at the point
where the reflected rays disperse in theinfinity of space and are lost. To explain this
we must suppose either that it is not all air
which water is generated, or, if it is produced
from all air alike, that what immediately
surrounds the earth is not mere air, but a sortof vapour, and that its vaporous nature is thereason why it condenses back to water
again.
However, it may well be that the formationof clouds in that upper region is also
prevented by the circular motion. For the airround the earth is necessarily all of it inmotion, except that which is cut off inside thecircumference which makes the earth acomplete sphere. In the case of winds it isactually observable that they originate in

•

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•

marshy districts of the earth; and they do notseem to blow above the level of the highest
mountains. It is the revolution of the heaven
which carries the air with it and causes its
circular motion, fire being continuous withthe upper element and air with fire. Thus its
motion is a second reason why that air is notcondensed into water.
The exhalation of water is vapour: aircondensing into water is cloud. Mist is what
is left over when a cloud condenses into
water, and is therefore rather a sign of fineweather than of rain; for mist might be calleda barren cloud. So we get a circular processthat follows the course of the sun. For
according as the sun moves to this side orthat, the moisture in this process rises orfalls. We must think of it as a river flowing up
and down in a circle and made up partly of
air, partly of water. When the sun is near, thestream of vapour flows upwards; when it
recedes, the stream of water flows down:
and the order of sequence, at all events, inthis process always remains the same. So if'Oceanus' had some secret meaning in early
writers, perhaps they may have meant thisriver that flows in a circle about the earth.
So the moisture is always raised by the heatand descends to the earth again when it getscold. These processes and, in some cases,
their varieties are distinguished by specialnames. When the water falls in small drops it
is called a drizzle; when the drops are larger
it is rain.

Water vapour, dew and hoar-frost••

Some of the vapour that is formed by day
does not rise high because the ratio of thefire that is raising it to the water that is being
raised is small
Both dew and hoar-frost are found when thesky is clear and there is no wind. For thevapour could not be raised unless the sky
were clear, and if a wind were blowing it
could not condense.

•...hoar-frost is not found on mountains
contributes to prove that these phenomena
occur because the vapour does not rise high.
One reason for this is that it rises from hollow
and watery places, so that the heat that is
raising it, bearing as it were too heavy aburden cannot lift it to a great height but
soon lets it fall again.

Weather••

When there is a great quantity of exhalationand it is rare and is squeezed out in the clouditself we get a thunderbolt.
So the whirlwind originates in the failure of
an incipient hurricane to escape from its
cloud: it is due to the resistance which
generates the eddy, and it consists in the
spiral which descends to the earth and dragswith it the cloud which it cannot shake off. It
moves things by its wind in the direction inwhich it is blowing in a straight line, andwhirls round by its circular motion andforcibly snatches up whatever it meets.

Climate change effects:•

So it is clear, since there will be no end to time
and the world is eternal, that neither theTanais nor the Nile has always been flowing,
but that the region whence they flow wasonce dry: for their effect may be fulfilled, buttime cannot. And this will be equally true ofall other rivers. But if rivers come into
existence and perish and the same parts ofthe earth were not always moist, the sea
must needs change correspondingly. And if
the sea is always advancing in one place andreceding in another it is clear that the same
parts of the whole earth are not always
either sea or land, but that all this changes incourse of time.

Aristotle's writings were never to influence directlyon practical meteorology. For many centuries people
relied instead on a few weather rules of thumb,sometimes blended with the assumption of a certaindegree of divine interference. One of Aristotle's
students, Theophrastus (371-287 BC) succeeded him
as a director of the Lyceum in Athens. He took overthe philosophy of Aristotle in parts reshaping,commenting, and developing it in an original way. His
thinking leads to empiricism by means ofobservation, collection, and classification.

he also continued Aristotle's work on meteorology,
formulating about 80 weather rules, based entirelyon observations. This indicates that empiricalmeteorology already at this time had reached anadvanced stage in Greek science (Rasmussen 2010).
Later, much of the scientific knowledge acquired andformulated by Aristotle and his students was sadly
ignored and forgotten in Europe, and it was not
before 1000-1100 AD that it was rediscovered by
European scientist, after surviving among Arabianscientists. By this, with a delay of at least 1300 years,
the theories and explanations set forth by Aristotle
were to gain huge impact on the later European
scientific development.

Theophrastus was years the director of the Lyceum
around 35 years and he was a teacher of up to 2000
students. Today he is often considered the "father ofbotany". In addition, he probably was the first in
Europe to discover Sunspots (although observed also
independently and much earlier in China). However,

References:
Rasmussen, E.A. 2010. Vejret gennem 5000 år (Weather through 5000 years). Meteorologiens historie. Aarhus
Universitetsforlag, Århus, Denmark, 367 pp, ISBN 978 87 7934 300 9.

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All diagrams in this report, along with any supplementary information, including links to data sources
and previous issues of this newsletter, are freely available for download on www.climate4you.com

Yours sincerely,
Ole Humlum (Ole.Humlum@gmail.com)
Arctic Historical Evaluation and Research Organisation, Longyearbyen, Svalbard
20 July 2024.
Planned publication of next newsletter: around 24 August 2024.