The Hiatus in Global-Mean Surface Warming during the last 15 years is only a proof of internal decadal climate variability

Figure 1 Maps of Arctic ice concentration trends (1979–2012) in summer (left) and autumn (right) (updated from Comiso, 2010 and IPCC AR5)

In the fifth IPCC assessment report (AR5) dated Sep. 2013, the observed global-mean surface temperature (GMST) is showing a much smaller increasing trend over the last 15 years than over the past 30 to 60 years.

The reduction in observed GMST trend is most marked in Northern hemisphere during winter time. 

This had been highlighted by the climate warming denier's community as a proof that the Global Warming issues were biased by Climate scientists.

The decade of the 2000s had nevertheless been the warmest in the record of GMST. As analysed by NOAA, the top five warmest years since record began in 1880 were 2010 (0.66°C above the 20^th century average), 2005 (0.65°C),1998  (0.63°C),  followed by 2013 tied with 2003 as the fourth warmest year  globally (0.62°C) .

Summer time Artic sea-ice volume- which trends are spoted in Figure 1 above- had a dramatic 75% decrease since 1979 particularly during the last 2 decades (Chapter 4- Figure 4.2 AR5 report).  

Additionally, during this 15-year hiatus there is a discrepancy between the observed data and the forward model applied to past and observational data, which needs to be assessed.

Temperature anomalies are increasing by step and rise

Contrary to "climate sceptics", we believe that this is evidence that climate statistics are properly grounded and that some stakeholders like to fiddle with the fundamental distinction to be done between long-term trends (Global warming) and short-term trends (variability).

The GMST trend over 1998–2012 is estimated to be around one-third to one-half of the trend over 1951–2012. For example, in HadCRUT4 the trend is 0.04°C per decade over 1998–2012, compared to 0.11°C per decade over 1951–2012.

Temperature anomalies are increasing by steps with moderate evolutions followed by deep rise, while other indicators as Sea level, Arctic sea-ice extent or Glacier mass balance have more steady trends. 

As concerns GMST, during the last 1860-2012 period, we find successively: 1860-1909 (50yrs) ~flat; 1910-1944 (35yrs) ~rise; 1945-1974 (30yrs) ~flat; 1975-1997 (23yrs)~ rise; 1998-2012 (15 yrs) ~ flat.

Climate model projections, performed by the Coupled Model Intercomparison Project (CMIP5) indicate that hiatus are relatively common and could appear in the 21st century when decadal periods are considered. 

Climate models simulations link these hiatus decades to La Niña-like cool conditions in the equatorial Pacific. The hiatus or cooling periods are less likely when 20 or 30 years periods are considered.

Figure 2: Global mean surface temperature (black lines) from HadCRUT4, GISTEMP, and MLOST, compared to model simulations (CMIP3 models – thin blue lines and CMIP5 models – thin yellow lines) with all anthropogenic and natural forcings.  Global average anomalies are shown with respect to mean surface temperature  ~1900+/-20.

So the question is to examine whether these surface temperature developments are acceptable as a part of natural internal variability of the climate system or is-it that the anthropogenic external forcing long term trends resulting from GHG accumulation are either weaker than currently estimated or dampened by other external trends such as Solar variation  or Aerosol accumulation   ?

The climate system

Global warming discussions are centered on GMST for long and no doubt it is a good metric since surface temperature record is available for most land areas since pre-industrial period. 

Communication of global warming to the public using temperature metric is also easy. 

However, it has one major limitation, this quantity is reflecting the heat content of only a thin layer (depth ~ 50-100 meters) on the land and ocean surface and not the true heat content of the climate system. 

This  thin layer is the place of important exchange with the deep ocean and the troposphere and hence is permeated by heat as well as other quantities such as salt and CO2.

The climate system is huge including the troposphere to an altitude of around 17 km containing 80% of its total atmospheric mass and 99% of its water vapor and aerosols, land masses culminating in average up to 840m  above sea level and ocean covering about 71% of the earth's surface with an average depth approximately 3500m.

As explained by IPCC AR5 report: “Ocean warming dominates the increase in energy stored in the climate system, accounting for more than 90% of the energy accumulated between 1971 and 2010 (high confidence). It is virtually certain that the upper ocean (0−700 m) warmed from 1971 to 2010”.

While GMST and Sea level are both critical for human and animal habitat, Sea level rise is probably a more adapted metric than GMST. It  integrates both the thermal expansion of the oceans and the waters received from  glaciers and ice sheets melting. 

Global mean sea level has risen monotonically by about 20 cm since 1900 and the rate has increased: “It is very likely that the mean rate of global averaged sea level rise was 1.7 mm/yr between 1901 and 2010, 2.0 mm/yr between 1971 and 2010 and 3.2 mm/yr  between 1993 and 2010”.

Note: In IPCC report: "virtually certain" means: 99–100% probability; "very likely": 90–100%; "likely": 66–100%; "about as likely as not" 33–66%; "unlikely" 0–33% probability...A level of confidence is expressed using five qualifiers: very high, high, medium, low and very low.

All indicators of the climate system are pointing to the same direction

It is clear that we are mostly concerned by Global mean surface temperature of land and sea, but it is necessary to take into account all exchanges within the climate system.

If we look at the wider picture with all the extent of the Global climate system over the last 160 years, then we see that ultimately all indicators are pointing in the same direction! 

Don’t forget that during the same industrialization period world population had increase by 5, world GDP per capita by 100 (Wikipedia) and fossil energy consumption (coal, oil and gas)  ramped fom zero to 3000 Mil MWh (see ideas21.co.za )

Figure 3: Multiple complementary indicators of a changing global climate. Each line representing an independently derived estimate of change in the climate element.

The drivers of climate internal variability

One method to assess internal climate variability is to use temperature estimates derived from climate models. This was done in the IPCC last report. 

The curves in the following Figure 4 show for the concerned periods, the probability density function (PDF) or frequency distribution of the two random variables that are global mean surface temperature (GMST) and effective radiative forcing (ERF) .

This allows - using normalized density curves - to accurately measure the distance between climate model's best estimate and temperatures actually observed. 

Figure 4 :  Top: Observed and simulated GMST trends in ºC per decade, over the periods 1998–2012 (a),1984–1998 (b), and 1951–2012 (c).  For the observations, 100 realisations of the HadCRUT4 ensemble are shown (red, hatched). Bottom: Trends in effective radiative forcing (ERF, in W m–2 per decade) over the periods 1998–2011 (d), 1984–1998 (e), and 1951–2011 (f).  The figure shows the best estimates for the models, all CMIP5 simulation in RCP4.5 scenario: top GMST (grey, shaded).and bottom ERF (grey, shaded).

During the 15-year period beginning in 1998, HadCRUT4 GMST trends lies below almost all model-simulated trends, whereas during the 15-year period ending in 1998, they lie above 93 out of 114 modeled trends.

Over the 62-year period 1951–2012, observed and CMIP5 ensemble-mean trend agree to within 0.02°C per decade.

Due to natural variability, trends based on short records are very sensitive to the beginning and end dates and do not in general reflect long-term climate trends: for example, the rate of warming over the past 15 years, which begins with a strong El Niño.

Models do not reproduce this slowdown in warming because the timing of events related to internal variability (e.g. El Nino and Pacific Decadal Oscillation) probably could be different in models and observations and hence the way these internal oscillations combine with those associated with anthropogenic forcing is likely to be different.

Due to internal climate variability in any given 15-year period, the observed GMST trend sometimes lies near one end of the PDF, an effect that had been pronounced since GMST was influenced by a very strong El Niño event in 1998.

Natural internal climate variability

Hiatus periods of 10–15 years can arise as a manifestation of internal decadal climate variability, which sometimes enhances and sometimes counteracts the long-term externally forced trends.

It is very likely that the climate system, including the ocean below 700 m depth, has continued to accumulate energy over the period 1998–2010, global-mean sea level having continued to rise during 1998–2012, at a rate only slightly and insignificantly lower than during 1993–2012.

Over the 62-year period 1951–2012, observed and CMIP5 agree to within 0.02°C per decade. There is hence very high confidence that the CMIP5 models show long-term GMST trends consistent with observations, despite the disagreement over the most recent 15-year period.

Overall, there is medium confidence only that initialization – a very strong El Niño event in 1998 for instance- could lead to simulations of GMST during 1998– 2012 that are more consistent with the observed trend hiatus than are the uninitialized CMIP5 historical simulations, and that the hiatus is in part a consequence of internal variability that is predictable on the multiyear timescale.

Radiative external forced variability

Dampening of ERF could arise naturally from strong volcanic eruption or downwards trend of Solar phase.

The AR5 best-estimate ERF forcing trend difference between 1998–2011 and 1951–2011 thus might explain about one-half (0.04 ºC per decade) of the observed GMST trend difference between these periods (0.06 to 0.08 ºC per decade, depending on observational data set):

Figure 4 :  Forced GSTM response from the ERF forcing trend

The forcing trend reduction is primarily due to a negative forcing trend from both volcanic eruptions and the downward phase of the solar cycle. However, there is low confidence in quantifying the role of forcing trend in causing the hiatus, because of uncertainty in the magnitude of the volcanic forcing trend and low confidence in the aerosol forcing trend.

Main conclusions

Even with this “hiatus” in GMST trend, the decade of the 2000s has been the warmest in the instrumental record of GMST, the highest temperature record being either 1998 (HadCUT4) or 2005 (NOAA).

The main trouble with GSMT is that it reflects the heat content of only a thin layer (depth ~ 50-100 meters) above the land and ocean surface and not the true heat content of the climate system: thus it is prone to huge natural variability.

Global mean sea level has risen monotonically by about 20 cm since 1900 and the rate has increased as assessed by IPCC and Sea level rise is probably a more pertinent metric integrating both the ocean heat content as well as the melt water in the cryosphere.

Trends based on decadal year records are very sensitive to the beginning and end dates:  an example is the past 15 years beginning with a strong El Niño.  Hiatus can arise as a manifestation of internal decadal climate variability, which sometimes enhances and sometimes counteracts the long-term externally forced trend.

The forcing reduction due to a negative forcing trend from both volcanic eruptions and the downward phase of the solar cycle could explain about one-half of the observed GMST trend difference.