Global Temperature Measurement
Reported
Temperature Measurements
Average global temperature anomalies
(AGT) since temperatures have been measured world wide and with increasing
accuracy are reported 1,2,3,4 on the web by three
agencies. These reported data are graphed in Figure 1.
Figure 1. Differences in reported
average global temperature anomalies are due primarily to differences in
reference temperatures. All exhibit trends with similar periodicities.
These all use essentially the same
raw temperature measurement database. Each group processes the data slightly
differently from the others. Each believes their method is most accurate. To
avoid bias, each anomaly trajectory is shifted (reference-temperature change
only) so its average is the same as the average for HadCRUT4 over the time period
for which both are given and then the average from the available values
(as-shifted if not HadCRUT4) for each year is calculated. This normalizes the
set to an unbiased single trajectory which is shown in Figure 2.
Examination of
Figure 2 discloses four approximately linear trends: downtrend 1877-1909,
uptrend 1909-1941, downtrend 1941-1973 and uptrend 1973-2005. Although the
trend has been flat since 2001, a continuation of history portends a downtrend
2005-2037.
It has been
demonstrated 5 that, since AGT have been accurately measured world
wide (approximately 1895), the AGT trends are explained (R2=0.9) by
the net average natural ocean surface temperature oscillations combined with a
proxy factor times the sunspot number time-integral.
Effective
Thermal Capacitance
Some ocean surface
temperature oscillations have been named according to the particular area of
the oceans where they occur. Names such as PDO (Pacific Decadal Oscillation),
ENSO (el Nino Southern Oscillation), and AMO (Atlantic Multidecadal
Oscillation) may be familiar. They report the temperature of the water surface
while the average temperature of the bulk water that is participating in the
oscillation (approximate equivalent depth of 110 meters) can not significantly
change so quickly because of its high thermal capacitance 6.
A simple check on
the 110 meter equivalent depth assessment can be made using only temperature
vs. distance-below-the-surface profiles. The rationale uses the realization
that the energy increase of a unit of water is equal to the thermal capacitance
of the unit times its temperature change. Because the thermal capacitance of a
unit is essentially constant, the equivalent depth (the depth that, if all is
at the surface temperature, would have the same thermal capacitance as the
actual effective thermal capacitance) is equal to the integral of the
temperature vs. distance-below-the-surface profile divided by the surface
temperature. The temperature typically declines for approximately 1 km below
the surface, a bit further for another km and then remains nearly constant at approximately 3 °C on down to the
bottom. Thus the temperatures in the profile should be reduced by this constant
amount. Actual effective thermal capacitance cannot be greater than this method
calculates.
Two temperature
profiles were found on line. Applying this method resulted in a calculated
effective thermal capacitance equivalent to a depth of 196 meters for one and
225 meters for the other. Given that the effective depth cannot be greater than
the actual depth and that much of the ocean is less than 2 km deep, the
effective depth of 110 meters for calculating effective thermal capacitance
appears reasonable.
Temperature
Measurement Uncertainty
The huge effective
thermal capacitance absolutely prohibits the reported rapid (year-to-year) AGT
fluctuations, such as shown in Figure 2, as a result of any credible forcing.
According to one assessment 6, the time constant (time to change
63.2% of the total temperature change that would result from a step change in
forcing) is about five years. A possible explanation for the impossibly rapid
fluctuations is that the reported rapid fluctuations might be stochastic
artifacts of the process that has been used to determine measured AGT. Animations
7,8,9,10 illustrate the continuous fluctuation of local surface
temperatures which are measured at discreet points. The uncertainty occurs as a
result of the location and timing of the discreet measurements of the continuing
fluctuation. Spencer explains similar rapid fluctuations of surface temperature
data obtained using meteorological satellites 11.
For the period
1895-2012, the standard deviation (σ) of the reported annual average measurements
is approximately ±0.09 K with respect to the trend. The temperature
fluctuations of the bulk volume near the surface of the planet are more closely
represented by the fluctuations in the trend. The trend is a better indicator
of the change in global energy; which is the difference between energy received
that is above or below break-even and energy radiated above or below
break-even.
Figure 3 shows the
approximately Gaussian (normal) distribution of the difference of reported
measurements with respect to the calculated trend 5. The average,
which is zero as it should be, and standard deviation are also shown. A bin
width of 0.025 K was used in generating this distribution of reported measured
data. The ordinate is the number of measurements that fell within each of the
21 bins.
Figure 3:
Distribution of reported measurements with respect to the trend.
Influence
of Natural Ocean Oscillations on Average Global Temperature
There is some
average ocean surface temperature oscillation that accounts for all of the
oceans considered together of which the named oscillations are participants.
Studies 12,13,14,15 of the primary contributor (the PDO) to this
planet-wide oscillation have been done which identify the period of this
oscillation to be in the range of 50-70 years. One of these studies considered
data from as far back as 1000 years.
Future
Trends
Complex phase
relations between the various local ocean cycles cause the effective over-all surface
temperature oscillation to vary in magnitude and period over the centuries. In
the present assessment, the period of the planet-wide oscillation, since before
1900, has been found to be approximately 64 years with a magnitude of
approximately ± 1/5 K. The most recent calculated trend peak was in 2005.
Average global
temperature should, however, continue to correlate with the time-integral of
sunspot numbers, as it has ever since sunspots have been regularly recorded (since
1610).
Thus, the
prediction of average global temperatures depends primarily on the ability to
predict sunspot numbers and secondarily on the oscillation up to about 1/5 K that
results from the net effect of the several ocean oscillations above and below
the prediction from the time-integral of sunspot numbers. Reported measurements
for each year will continue to have an uncertainty equivalent to σ ≈ 0.09 K.
References:
- HadCRUT4, http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/time_series/HadCRUT.4.1.1.0.annual_ns_avg.txt
- HadCRUT3, http://www.metoffice.gov.uk/hadobs/hadcrut3/diagnostics/global/nh+sh/monthly
- NOAA, ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/annual.land_ocean.90S.90N.df_1901-2000mean.dat
- GISS, http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt
- http://climatechange90.blogspot.com/2013/05/natural-climate-change-has-been.html
- Schwartz, Stephen E., (2007)
Heat capacity, time constant, and sensitivity of earth’s climate system, J. Geophys. Res., vol. 113, Issue
D15102, doi:10.1029/2007JD009373
- http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_update/sstanim.shtml
- http://www.ospo.noaa.gov/Products/ocean/sst/anomaly/anim.html
- http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_update/gsstanim.shtml
- http://www.youtube.com/watch?v=1ir1w3OrR4U
- http://www.drroyspencer.com/2012/03/what-causes-the-large-swings-in-global-satellite-temperatures/
- MacDonald, Glen M. and
Roslyn A. Case (2005), Variations in the Pacific Decadal Oscillation over
the past millennium, Geophysical
Research Letters, 32, L08703
- Mantua, N. J., S. R. Hare,
Y. Zhang, J. M. Wallace, and R. C. Francis, A Pacific interdecadal climate
oscillation with impacts on salmon production. Bull. Am. Met. Soc. 76, 1069-1079, 1997
- Minobe, S., (1999),
Resonance in bidecadal and pentadecadal climate oscillations over the
North Pacific: Role in climatic regime shifts, Geophys. Res. Lett., 26, 855–858.
- Minobe S., (1997) A 50–70
year climatic oscillation over the North Pacific and North America. Geophs. Res. Lett., 24, 683–686.
Key words: Global
warming, effective thermal capacitance, uncertainty in reported temperature,
natural ocean oscillation