Contents:

1

Page 2: June 2014 global surface air temperature overview
Page 3: Comments to the June 2014 global surface air temperature overview
Page 4: Lower troposphere temperature from satellites
Page 5: Global surface air temperature
Page 8: Global air temperature linear trends
Page 9: Global temperatures: All in one
Page 10: Global sea surface temperature
Page 13: Ocean heat content uppermost 100 and 700 m
Page 16: North Atlantic heat content uppermost 700 m
Page 17: Zonal lower troposphere temperatures from satellites
Page 18: Arctic and Antarctic lower troposphere temperatures from satellites
Page 19: Arctic and Antarctic surface air temperatures
Page 22: Arctic and Antarctic sea ice
Page 25: Global sea level
Page 26: Northern Hemisphere weekly snow cover
Page 27: Atmospheric specific humidity
Page 28: Atmospheric CO2
Page 29: The phase relation between atmospheric CO2 and global temperature
Page 30: Global surface air temperature and atmospheric CO2
Page 33: Last 20 year monthly surface air temperature change
Page 34: Climate and history; one example among many:
1805: The Battle at Trafalgar – the less well-known stormy aftermath

All diagrams in this newsletter as well as links to the original data are available on www.climate4you.com

June 2014 global surface air temperature overview

2

June 2014 surface air temperature compared to the June average 1998-2006. Green-yellow-red colours indicate areas with higher
temperature than the 1998-2006 average, while blue colours indicate lower than average temperatures. Data source: Goddard Institutefor Space Studies (GISS).

Comments to the June 2014 global surface air temperature overview
General: This newsletter contains graphs showing
a selection of key meteorological variables for the
past month. All temperatures are given in degrees
Celsius.
In the above maps showing the geographicalpattern of surface air temperatures, the period
1998-2006 is used as reference period. The reason
for comparing with this recent period instead of
the official WMO ‘normal’ period 1961-1990, is thatthe latter period is affected by the cold period
1945-1980. Most comparisons with such a low
average value will therefore appear as warm, and it
will be difficult to decide if modern surface airtemperatures are increasing or decreasing.
Comparing with a more recent period overcomes
this problem.

and the thick line indicate a simple runningaverage, in most cases a simple moving 37-monthaverage, nearly corresponding to a three year
average. The 37-month average is calculated fromvalues covering a range from 18 month before to
18 months after, with equal weight for every
month.
The year 1979 has been chosen as starting point inmany diagrams, as this roughly corresponds toboth the beginning of satellite observations and theonset of the late 20th century warming period.
However, several of the records have a much
longer record length, which may be inspected ingreater detail on www.Climate4you.com.

June 2014 global surface air temperatures

3

In addition to the above consideration, the recent
temperature development suggests that the time
window 1998-2006 may roughly represent a global
temperature peak (see, e.g., p. 4-6). However, it
might be argued that the time interval 1999-2006
or 2000-2006 would better represent a possible
temperature peak period. However, by starting in1999 (or 2000) the cold La Niña period 1999-2000
would result in a unrealistic low reference
temperature by excluding the previous warm El
Niño in 1998. These two opposite phenomena must
be considered together to obtain a representativereference average, and this why the year 1998 isincluded in the adopted reference period.
Finally, the GISS temperature data used for
preparing the above diagrams show a pronounced
temporal instability for data before 1998 (see p. 7).
Any comparison with the WMO ‘normal’ period
1961-1990 is therefore influenced by monthly
changing values for the so-called ‘normal’ period,
which is therefore not suited as reference.
In the other diagrams in this newsletter the thinline represents the monthly global average value,

General: In general, the global air temperature wasnear the 1998-2006 average.
The Northern Hemisphere was characterised byregional air temperature contrasts, althoughsmaller than during NH-winter. Western North
America experienced below average temperatures,
while eastern North America had above averagetemperatures. Most of Europe and western Siberia
had below 1998-2006 average temperatures, whilecentral Siberia had above average temperatures.
Eastern Siberia had below average temperatures.
Most of the Arctic had below averagetemperatures, the only major exception being thesouthern part of Greenland.
Near the Equator temperatures conditions weregenerally somewhat above the 1998-2006 average.
The Southern Hemisphere temperatures weremainly near average 1998-2006 conditions. The
only major exception from this was extensive partsof the Antarctic continent.

Lower troposphere temperature from satellites, updated to June 2014

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

4

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.

Global surface air temperature, updated to June 2014

5

Global monthly average surface air temperature (thin line) since 1979 according to according to the Hadley Centre for Climate Prediction
and Research and the University of East Anglia's Climatic Research Unit (CRU), UK. The thick line is the simple running 37 month average.
Version HadCRUT4 (blue) is now replacing HadCRUT3 (red). Please note that this diagram is not yet updated beyond May 2013.

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. The thick line is the simple running 37 month average.

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.

6
A note on data record stability:
All the above temperature estimates display
changes when one compare with previous monthly
data sets, not only for the most recent months as aresult of supplementary data being added, but
actually for all months back to the very beginningof the records, more than 100 years ago.
Presumably this reflects recognition of errors,changes in the averaging procedure, and theinfluence of other unknown phenomena.

None of the temperature records are stable overtime (since 2008). The two surface air temperaturerecords, NCDC and GISS, show apparent systematicchanges over time. This is exemplified the diagramon the following page showing the changes since
May 2008 in the NCDC global surface temperaturerecord for January 1915 and January 2000,
illustrating how the difference between the earlyand late part of the temperature records graduallyis growing by administrative adjustments.
You can find more on the issue of lack of temporalstability on www.climate4you (go to: Global
Temperature, followed by Temporal Stability).

7

Diagram showing the adjustment made since May 2008 by the National Climatic Data Center (NCDC) in theanomaly values for the two months January 1915 and January 2000.

Note: The administrative upsurge of the temperature increase between January 1915 and January 2000 has
grown from 0.39 (in May 2008) to 0.52 oC (in June 2014), representing an about 33% administrative
temperature increase over this period.

Global air temperature linear trends updated to May 2014

Diagram showing the latest 5, 10, 20 and 30 yr linear annual global temperature trend, calculated as the slopeof the linear regression line through the data points, for two satellite-based temperature estimates (UAH MSU
and RSS MSU). Last month included in analysis: April 2014.

8

Diagram showing the latest 5, 10, 20, 30, 50, 70 and 100 year linear annual global temperature trend,
calculated as the slope of the linear regression line through the data points, for three surface-based
temperature estimates (GISS, NCDC and HadCRUT4). Last month included in all analyses: April 2014.

All in one, updated to May 2014

9

Superimposed plot of all five 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 (10 years) from January 1979 to December 1988. 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 rightcorner represent the temperature anomaly relative to the individual 1979-1988 averages.

It should be kept in mind that satellite- and surfacebased temperature estimates are derived fromdifferent types of measurements, and thatcomparing them directly as done in the diagram
above therefore may be somewhat problematical.
However, as both types of estimate often are
discussed together, the above diagram maynevertheless be of some interest. In fact, thedifferent types of temperature estimates appear toagree quite well as to the overall temperature
variations on a 2-3 year scale, although on ashorter time scale there are often considerable
differences between the individual records.

All five global temperature estimates presently
show an overall stagnation, at least since 2002.
There has been no increase in global air
temperature since 1998, which however wasaffected by the oceanographic El Niño event. This
stagnation does not exclude the possibility that
global temperatures will begin to increase again
later. On the other hand, it also remain a possibility
that Earth just now is passing a temperature peak,
and that global temperatures will begin to decreaseduring the coming years. Time will show which ofthese two possibilities is correct.

Global sea surface temperature, updated to late June 201410

Sea surface temperature anomaly on 23 June 2014. Map source: National Centers for Environmental Prediction(NOAA).

Because of the large surface areas near Equator,
the temperature of the surface water in theseregions is especially important for the global
atmospheric temperature (p.4-6).

major heat exchanges takes place between the
Pacific Ocean and the atmosphere above,
eventually showing up in estimates of the global air
temperature.

Relatively warm water is dominating the Pacific
Ocean and Indian Ocean near the Equator, and is
influencing global air temperatures now and in themonths to come.

However, this does not reflect similar changes inthe total heat content of the atmosphere-oceansystem. In fact, global net changes can be small andsuch heat exchanges may mainly reflect
redistribution of energy between ocean andatmosphere. What matters is the overalltemperature development when seen over anumber of years.

The significance of any such short-term cooling or
warming reflected in air temperatures should not
be over stated. Whenever Earth experiences cold
La Niña or warm El Niño episodes (Pacific Ocean)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.

11

Global monthly average sea surface temperature since 1979 according to University of East Anglia's Climatic Research Unit (CRU), UK.
Base period: 1961-1990. The thick line is the simple running 37 month average. Please note that this diagram is not yet updated beyond
May 2014.

Global monthly average sea surface temperature since 1979 according to the National Climatic Data Center (NCDC), USA. Base period:
1901-2000. The thick line is the simple running 37 month average.

12

Ocean heat content uppermost 100 and 700 m, updated to March 201413

Global monthly heat content anomaly (GJ/m2) in the uppermost 700 m of the oceans since January 1955. Data source: National
Oceanographic Data Center(NODC).

World Oceans vertical average temperature 0-100 m depth since 1955. The thin line indicate 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). Baseperiod 1955-2010.

Pacific Ocean vertical average temperature 0-100 m depth since 1955. The thin line indicate 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). Baseperiod 1955-2010.

14

Atlantic Ocean vertical average temperature 0-100 m depth since 1955. The thin line indicate 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). Baseperiod 1955-2010.

Indian Ocean vertical average temperature 0-100 m depth since 1955. The thin line indicate 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). Baseperiod 1955-2010.

15

North Atlantic heat content uppermost 700 m, updated to March 201416

Global monthly heat content anomaly (GJ/m2) 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).

Zonal lower troposphere temperatures from satellites, updated to June 201417

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 the simple running 37 monthaverage, nearly corresponding to a running 3 yr average. Reference period 1981-2010.

Arctic and Antarctic lower troposphere temperature, updated to June 201418

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 yr average.

Arctic and Antarctic surface air temperature, updated to May 201419

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 blue line shows the monthly temperature anomaly, while
the thicker red line shows the running 37 month (c.3 yr) average.

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

20

Diagram showing area weighted Antarctic (70-90oN) monthly surface air temperature anomalies (HadCRUT4) since
January 1957, in relation to the WMO normal period 1961-1990. The thin blue line shows the monthly temperature
anomaly, while the thicker red line shows the running 37 month (c.3 yr) 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 blue line shows the monthly temperature anomaly, while
the thicker red line shows the running 37 month (c.3 yr) average. Because of the relatively small number of Arctic stations
before 1930, month-to-month variations in the early part of the temperature record are larger than later. The period fromabout 1930 saw the establishment of many new Arctic meteorological stations, first in Russia and Siberia, and following
the 2nd World War, also in North America. The period since 2000 is warm, about as warm as the period 1930-1940.

21

As the HadCRUT4 data series has improved highlatitude coverage data coverage (compared to the
HadCRUT3 series) the individual 5ox5o grid cells has
been weighted according to their surface area. This
is in contrast to Gillet et al. 2008 which calculated asimple average, with no consideration to thesurface area represented by the individual 5ox5ogrid cells.

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.

Arctic and Antarctic sea ice, updated to June 201422

Sea ice extent 26 June 2014. The 'normal' or average limit of sea ice (orange line) is defined as 15% sea ice cover, according to theaverage of satellite observations 1981-2010 (both years inclusive). Sea ice may therefore well be encountered outside and open water
areas inside the limit shown in the diagrams above. Map source: National Snow and Ice Data Center (NSIDC).

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

Graph showing daily Arctic sea ice extent since June 2002, to 27 June 2014, by courtesy of Japan Aerospace Exploration Agency (JAXA).

23

Northern hemisphere sea ice extension and thickness on 28 June 2014 according to the Arctic Cap Nowcast/Forecast System (ACNFS), US
Naval Research Laboratory. Thickness scale (m) is shown to the right.

24

12 month running average sea ice extension in both hemispheres since 1979, the satellite-era. The October 1979 value represents themonthly average of November 1978 - October 1979, the November 1979 value represents the average of December 1978 - November
1979, etc. Last month included in the 12-month calculations: June 2014. Data source: National Snow and Ice Data Center (NSIDC).

Global sea level, updated to March 2014

Globa lmonthly sea level since late 1992 according to the Colorado Center for Astrodynamics Research at University of Colorado at
Boulder, USA. The thick line is the simple running 37 observation average, nearly corresponding to a running 3 yr average.

25

Forecasted change of global sea level until year 2100, based on simple extrapolation of measurements done by the Colorado Center for
Astrodynamics Research at University of Colorado at Boulder, USA. The thick line is the simple running 3 yr average forecast for sea levelchange until year 2100. Based on this (thick line), the present simple empirical forecast of sea level change until 2100 is about +34 cm.

Northern Hemisphere weekly snow cover, updated to late June 2014

Northern hemisphere weekly snow cover since January 2000 according to Rutgers University Global Snow Laboratory. The thin blue lineis the weekly data, and the thick blue line is the running 53 week average (approximately 1 year). The horizontal red line is the 19722013 average.

26

Northern hemisphere weekly snow cover since January 1972 according to Rutgers University Global Snow Laboratory. The thin blue lineis the weekly data, and the thick blue line is the running 53 week average (approximately 1 year). The horizontal red line is the 19722013 average.

Atmospheric specific humidity, updated to June 201427

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 shows monthly values, while the thick blue lines show the running 37 month average (about
3 years). Data source: Earth System Research Laboratory (NOAA).

Atmospheric CO2, updated to June 2014

28

Monthly amount of atmospheric CO2 (upper diagram) and annual growth rate (lower diagram); average last 12 months minus average
preceding 12 months, blue line) of atmospheric CO2 since 1959, according to data provided by the Mauna Loa Observatory, Hawaii, USA.
The red line is the simple running 37 observation average, nearly corresponding to a running 3 yr average.

The phase relation between atmospheric CO2 and global temperature, updated to June 201412-month change of global atmospheric CO2 concentration (Mauna Loa; green), global sea surface temperature (HadSST3; blue) andglobal surface air temperature (HadCRUT4; red dotted). All graphs are showing monthly values of DIFF12, the difference between the
average of the last 12 month and the average for the previous 12 months for each data series.

29

References:
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 surface air temperature and atmospheric CO2, updated to June 2014

30

31

Diagrams showing HadCRUT3, GISS, and NCDC monthly global surface air temperature estimates (blue) and the monthly
atmospheric CO2 content (red) according to the Mauna Loa Observatory, Hawaii. The Mauna Loa data series begins inMarch 1958, and 1958 has therefore been chosen as starting year for the diagrams. Reconstructions of past atmospheric
CO2 concentrations (before 1958) are not incorporated in this diagram, as such past CO2 values are derived by other means(ice cores, stomata, or older measurements using different methodology), and therefore are not directly comparable withdirect atmospheric measurements. The dotted grey line indicates the approximate linear temperature trend, and the boxesin the lower part of the diagram indicate the relation between atmospheric CO 2 and global surface air temperature,negative or positive. Please note that the HadCRUT4 diagram is not yet updated beyond May 2014.

Most climate models assume the greenhouse gas
carbon dioxide CO2 to influence significantly upon
global temperature. It is therefore relevant tocompare different temperature records withmeasurements of atmospheric CO2, as shown in the
diagrams above. Any comparison, however, should
not be made on a monthly or annual basis, but fora longer time period, as other effects(oceanographic, etc.) may well override thepotential influence of CO2 on short time scales suchas just a few years. It is of cause equally
inappropriate to present new meteorologicalrecord values, whether daily, monthly or annual, as
support for the hypothesis ascribing highimportance of atmospheric CO2 for global

temperatures. Any such meteorological record
value may well be the result of other phenomena.
What exactly defines the critical length of a
relevant time period to consider for evaluating thealleged importance of CO2 remains elusive, and is
still a topic for discussion. However, the critical
period length must be inversely proportional to thetemperature sensitivity of CO2, including feedback
effects. If the net temperature effect of
atmospheric CO2 is strong, the critical time period
will be short, and vice versa.
However, past climate research history provides
some clues as to what has traditionally been
considered the relevant length of period over

which to compare temperature and atmosphericCO2. After about 10 years of concurrent global
temperature- and CO2-increase, IPCC wasestablished in 1988. For obtaining public andpolitical support for the CO2-hyphotesis the 10 year
warming period leading up to 1988 in all likelihood
was important. Had the global temperature instead
been decreasing, politic support for the hypothesis
would have been difficult to obtain.
Based on the previous 10 years of concurrent
temperature- and CO2-increase, many climate
scientists in 1988 presumably felt that their32

understanding of climate dynamics was sufficient
to conclude about the importance of CO2 for global
temperature changes. From this it may safely beconcluded that 10 years was considered a period
long enough to demonstrate the effect ofincreasing
atmosphericCO2
onglobaltemperatures.
Adopting this approach as to critical time length (atleast 10 years), the varying relation (positive or
negative) between global temperature andatmospheric CO2 has been indicated in the lower
panels of the diagrams above.

Last 20 year monthly surface air temperature changes, updated to May 201433

Last 20 years global monthly average surface air temperature according to Hadley CRUT, a cooperative effort between the
Hadley Centre for Climate Prediction and Research and the University of East Anglia's Climatic Research Unit (CRU), UK.
The thin blue line represents the monthly values. The thick red line is the linear fit, with 95% confidence intervals indicatedby the two thin red lines. The thick green line represents a 5-degree polynomial fit, with 95% confidence intervals indicatedby the two thin green lines. A few key statistics is given in the lower part of the diagram (note that the linear trend is themonthly trend). Please note that the linear regression is done by month, not year.

It is quite often debated if the global surface airtemperature still increases, or if the temperature
has levelled out during the last 15-18 years. The
above diagram may be useful in this context, anddemonstrates the differences between two often
used statistical approaches to determine recent
temperature trends. Please also note that such fits
only attempt to describe the past, and usually have
limited predictive power. In addition, before using
any linear trend (or other) analysis of time series aproper statistical model should be chosen, basedon statistical justification.

For temperature time series there is no a priori
physical reason why the long-term trend should be
linear in time. In fact, climatic time series often
have trends for which a straight line is not a good
approximation, as can clearly be seen from severalof the diagrams in the present report.
For an excellent description of problems often
encountered by analyses of temperature timeseries analyses please see Keenan, D.J. 2014:
Statistical Analyses of Surface Temperatures in the
IPCC Fifth Assessment Report.

Climate and history; one example among many

1805: The Battle at Trafalgar – the less well-known stormy aftermath

Battleorder at the onset of the Battle at Trafalgar, southern Spain (left). Horatio Nelson's flagshipVictory breaking through the French battle line at 1.00pm 21st October 1805. Painting by Robert Taylor(centre). Horatio Nelson (right).

34

On the morning of Monday 21 October 1805 theFrench Admiral Villeneuve to his horror saw a
British fleet with 27 ships approaching his own
combined Franco-Spanish fleet consisting of 35
ships. The weather was pleasant, with a soft
breeze, so both fleets were moving slowly on thesea beyond Trafalgar on the south coast of Spain,
north-west of Gibraltar.

Nelson’s seamanship and prescience, however,remained to the last. While lying in his bed after
being treated for his wound he noticed a growing
swell, in spite of the fine weather. This alerted himthat bad weather was on the way, threatening all
ships by driving them by the wind on to the nearby
lee shore. His last order was therefore to anchor
the British ships to avoid this coming disaster.

The result of the following battle is well known. The
British fleet under Admiral Horatio Nelson defeatedthe Franco-Spanish fleet, in the process taking noless that 16 battleships as prizes. By this feat, theFrench treat of invasion in Britain was removed, atleast for some time.

Nelson’s second in command, Collingwood,
however decided to ignore Nelson’s orders toanchor, partly because some of the anchors aboard
British ships had been lost during the battle, andpartly to sail as far as possible from the dangerous
lee shore of Spain, with its treacherous shoals at
Trafalgar.

When crossing the French line in his flagshipVictory, Nelson was shot by the French Mariner
Guillemend, placed as sharpshoter in one of themasts of the nearby battleship Redoutable (seepicture above). Later in the afternoon, Nelson diedof his wound. He traveled back to Britain in thehold of Victory, preserved in a huge cask filled withbrandy (Harvey 2007).

It the following night the British fleet with all prizes
sailed straight into a fateful storm. Colossal waves
battered the ships, many of them already crippled,rolling about helplessly with their gaping holes
from the battle. Many of the captured French ships
sank behind the ships towing her, or had to be cut

adrift and then stranded on the shoals near thecoast.

All British ships managed to limp back home
(Harvey 2007).

At dawn, the storm continued unabated and more
French prizes went aground, sank or had to be
destroyed. The captured French Admiral Villeneuve
presumably saw with considerable relief that his
ships now would not be part of the British fleet.
The storm continued for three days, and no lessthan 12 of the original French 16 prizes were lost.

The Battle of Trafalgar was a great British naval
victory. But it would have been even moresignificant, had these 12 French battleships notbeen lost during the following storm, but instead
successfully incorporated into the already large
British navy. This would even more significantly
have changed the naval balance between the
Britain and France at this critical time.

References:
Harvey, R. 2007. The Wars of Wars. The epic struggle between Britain and France 1789-1815. Constable &Robinson Ltd., London, 962 pp.

*****

35

All the above diagrams with supplementary information, including links to data sources and previous
issues of this newsletter, are available on www.climate4you.com

Yours sincerely,
Ole Humlum (Ole.Humlum@geo.uio.no)
July 22, 2014.