The largest coral reefs in the world and the most valuable for their biodiversity are located in Southeast Asia

Most worldwide coral reefs are located in the Indian & Pacific and a small portion of Atlantic oceans 

Coral reefs and old growth forests are both nature richest realms. They are deriving their primary energy from plants thriving from solar radiation. As a result their location is within 30°S & 30°N latitudes where sun activity and temperature are at their maximum. Both are extremely complex systems consisting of numerous micro habitats and huge number of species.

Coral reefs today represent a development episode of only some thousand years ago when sea level remained relatively stable, because 15,000 years ago seas were as much as 150m below the present level. As explained by Charles Darwin’s theory for Coral Reefs development they are closely related to volcano island subsidence and sea level fluctuations.

Environmental conditions exert a great influence on determining how an individual coral polyp copes with its basic needs. Optimum coral reefs are strongly correlated with very clean and relatively shallow waters (<70m depth) to obtain maximum sunlight at a warm temperature (optimum 23°-24°C).

But during periods of million years, succeeding generations of coral species became gradually modified in a manner allowing them to utilize most efficiently their environment. The end result is communities of organism that are finely tuned to their environment.

 Why should we care about coral reefs in Asia Pacific?

Southeast Asia contains the largest area of coral reefs in the world known as the Coral Triangle shared between Indonesia, Malaysia, Philippines, Timor-Leste, Papua New Guinea and the Solomon Islands, .

The biodiversity of coral reefs in Southeast Asia is unparalleled in the world according to the Global Coral Reef Monitoring Network in their 2008 report on the status of coral reefs.

More than 138 million people in Southeast Asia live on the coast within 30 km of a coral reef, which is more than in all of the other coral reef regions combined. Fish, including reef fish, form a major part of the diet even in urban populations; across the region, fish and seafood provide an average of 36% of dietary animal protein.

Among the coral triangle countries, such as Malaysia and the Solomon Islands, tourism had enabled a rapid diversification of the economy and coral reefs had become one of the most attractive destination.

Contribution of observation satellites to coral reef mapping and monitoring

Since the late 1990s, the contribution of satellites for remote sensing of coral reefs has been fundamental to improving their mapping and monitoring. 

The observation satellites – such as Landsat (USA), Spot (EU) or IRS (India) - with optical sensor resolutions ranging from 10 to 50 m and capable of recording the radiation emitted in the visible and IR by the benthic environment, make it possible to obtain after treatment very accurate mapping of coral reefs, while monitoring their health and surveying the quality of their environment (bleaching thermal stress).

Specific treatments can eliminate noise as sun glint factors of the marine environment. The study of spectral signatures help to differentiate the various components of the benthic coral habitat: type of coral, living or dead, type of coral rubble, type of green algae or red by the absorption due to the presence of specific pigments, discrimination of coral sand or silt sediments by their reflectance, correction of the light signal attenuation in the water column by bathymetric treatment etc.

The University of South Florida (USF) had provided an exhaustive worldwide inventory of coral reefs using high-resolution satellite imagery. By using a consistent dataset of high-resolution multispectral Landsat 7 images acquired between 1999 and 2002, USF characterized, mapped and estimated the extent of shallow coral reef ecosystems in the main coral reef provinces (Caribbean-Atlantic, Pacific, Indo-Pacific, Red Sea).

Similar studies were conducted in Europe (IRD) , Australia and Indonesia from the data supplied by Landsat, SPOT, satellites or IRS.

Distribution of worldwide coral reefs habitat by region

Under the project called the Millennium Coral Reef Mapping a team of international researchers compiled an updated inventory of all "marine protected areas" containing coral reefs and compared it with the most detailed and comprehensive satellite inventory of coral reefs. 

The World Reef Initiative (WRI) was founded in 1994 by eight governments: Australia, France, Japan, Jamaica, the Philippines, Sweden, UK, and the USA. It was announced at the First Conference of the Parties of the Convention on Biological Diversity in December 1994, and at the high level segment of the Intersessional Meeting of the U.N. Commission on Sustainable Development in April 1995. 

The main result concerning the distribution of worldwide coral reefs by region is summarize in the following Figures 1 & 2 (see RWI 2011 Coral Reefs revisited ).

The world’s coral reefs are covering an area of approximately 250,000 sq km which the richest concentration being in Southeast Asia (30% of all coral reef areas in the planet), then Pacific (28%) and Australia (17%), followed by Indian Ocean (13%), Atlantic (10%) and the Middle East (6%) (see Figure 1 & 2).

Figure 1: Distribution of Coral Reefs by regions (From WRI 2011)

Figure 2 : Distribution of Coral Reefs and the associated population by regions (From WRI 2011)

Coral Reefs associated human population   

As reported in WRI “Reefs at risk revisited -2011” , the coral’s reefs associated worldwide population could be featured by two values:

-          Close population within 10 km of coast and 30 km from the reef            : 275 Mil

-          Larger area population within 100 km of the reef                                   : 850 Mil

Figure 3 : Population associated with coral reefs by regions

There is a great variation of the population close to the reefs: 

-          Highly populated reef areas are: Indian Ocean 2065.5 people /km2; Southeast Asia 1,983.9, Atlantic 1,645.8 and  Middle Eas 1,322.4

-          Low populated reef areas are: Pacific 113.5,  Australia 82.9

The ratio between larger and close area populations for reefs region is more or less stable between  2.5 (for low population countries) to 3.5 (highly populated).

Are coral reefs doomed to shrink progressively? 

We must never forget that when we are seeing the coral reefs distribution around the world such as the one presented here, it is a snapshot in a development episode of some 5000 years of coral reefs life. 

Coral have disappeared or have been  greatly reduced in every part of the world. 

Over the past 50 years for example, the Great Barrier Reef in Australia has decreased by 50% due to agricultural and industrial development of the western side of Australia!

Most of this coral reef reduction is due to the extraordinary development of people living on Earth which increased by a factor of 2.3 in average over the past 50 years, due to the correlative increase or human population direct or indirect pressure on coral reefs which are  particularly heavy in the Asian Pacific region.

So our ocean and coral reefs are changing a lot and what we see today- if we don’t take the greatest care - maybe is doomed to shrink progressively! There in the contemplation of the beauty of corals a fragile and transient aspect and perhaps we must keep the memory of what will perhaps one day disappear.

Such is the aim of the Catlin Seaview Survey study  which is a unique global study, working with some of the world's leading scientific institutions, dedicated to monitoring our oceans change and communicating on it to the world.

The aim of the survey is to document a baseline record by video and pictures of the world’s coral reefs seaview, in high-resolution panoramic vision.

Our oceans are changing and coral reefs are a clear visual indicator of this change – with a 40% loss of corals around the globe in the last 30 years alone. 

The painstaking work that scientists realize could well be a kind of archive that will be quickly out of date  due to ocean acidification, bleaching of the reefs, death of species and habitat.

In addition to their aesthetic appeal, coral reefs are also natural defenses against waves and coastal erosion. Their disappearance is a double punishment face of rising sea levels, expected over the next century.

2014 Environment Performance Index (EPI) analysis is showing a 4% worldwide average reduction over 2012 which means EPI Yale experts are more pessimistic especially concerning urgent actions on water issues

Figure 1: Water scarcity has become one of our greatest challenges. In less than twenty years, nearly two billion people could face water shortages.

© Binh Thuan, Thien Anh Huynh / Vietnam / 

Yale last 2014 EnvironmentPerformance Index (EPI) is showing deterioration from the assessment made in 2012: the worldwide ranking based on population weighted index over all the ranked countries is around 45.7 in 2014 after 47.5 in 2012 which is a reduction of 4% over the last two years.

There had been modifications in the methodology and some additional countries missing in 2012 are now included in 2014’s assessment. Altogether the general situation of Environment Performance is looking bleaker than it was 2 years ago mostly because of water issues. 

Water scarcity has become one of the greatest challenge: nowadays about 1.6 Mil people, or a quarter of the world's population, live in countries that have insufficient water supplis (see Figure 1 above).  

As illustrated by the concept of “Tragedy of the Commons”, the "Commons" which include the atmosphere, oceans, rivers, forests, fish stocks and national parks are shared resource, that should be exploited in connection with sustainable development, meshing economic growth and environmental protection, as well as in the debate over global warming.  The tragedy of the commons is an example of emergent behavior, the outcome of individual interactions in a complex system which are provoking huge negative "externalities" that nobody is prepared to pay.

If we want to restore and protect the environment against pollution and seamlessly share the burden of efforts among the various stakeholders, it is necessary to define new indicators and tools. EPI ranking is essential to detect in which countries further actions are needed to avoid disastrous environmental issues.

Starting from year 2002, Yale 2014 country EPI rankings along with others ranking from OECD or Siemens (Asian Green City index) are necessary steps to discuss and address these issues.

EPI methodology adjustments in 2014

My blog dated 6 Nov 2012 has presented the EPI 2012 methodology and main results in Asia Pacific. The last EPI 2012 issue’s overall architecture is respected, with 4 levels of indexes or indicators:

(1) Global EPI;

(2) Environmental Health index EH, Environmental Vitality EV;

(3) 9 sub indexes: 3 for EH and 6 for EV 

(4) Twenty indicators with 1, 2 or 4 depending of the sub indexes

More countries are now in the scope with a total of 178 EPI ranked in 2014 against 132 in 2012. The 2014 EPI evaluates 178 countries, with 46 new additions, in large part, from Small-Island Developing States and sub-Saharan Africa.

The overall population ranked is now 6900 Mil in 2014 against 6550 Mil in 2012, which is an increase of 5% over 2012.

Most of the new countries ranked are low Income (18), lower middle income (13) or upper middle income countries (10). There are only 5 high income countries: Bahamas, Barbados, Antigua & Barbuda, Bahrain and Equatorial Guinea.     

The overall method has been adjusted (see Figure 2) in order to address some shortcoming, notably with the following sub indexes or indicators:

-     Drinking, sanitation and water resources weighting are increased from 16% to 28% (+12%) with a new wastewater treatment indicator, which is a major driver of ecosystem water quality;

-     Forest and Fisheries are more or less the same;

-    Air pollution: SO2 pollution has been deleted to use only PM2.5 particulate pollution: Air quality weighting is reduced from 16.26% to 13.32% (-2.94%);

-     Health impact (child mortality) is reduced from 15% to 13.33% (-1.67%);

-     Agriculture is reduced from 5.83% to 3% (-2.83%);

-     Biodiversity is reduced from 17% to 15% (-2%);

-     Climate and energy is also reduced from 17.52% to 15% (-2.52%) with a new index calculation that is dependant on the country's economic development level.

The water increased weighting in EPI is mirroring the water situation following a recent UN report asking urgent actions: water demand is likely to increase by 55% by 2050, with 40% of population living in areas of "severe" water stress. 

Asia will be the biggest hotspot over water extraction, where water sources straddle national borders. "Areas of conflict include the Aral Sea and the Ganges-Brahmaputra River, Indus River and Mekong River basins".

Apart from this adjustment for water, the overall architecture is more or less the same and past comparisons are still very useful.

It is true that it should be necessary – as explained by EPI Yale- to “back-cast” the new definition and weighting of indicators to know exactly the overall variation from the past.

However as explained by EPI Yale not every indicator in the 2014 EPI lends itself to back-cast or trend calculations. But more importantly we can say that the expert judgment EPI Yale is issuing now in 2014 is more pessimistic as compared to the 2012 assessment meanly because of water urgent issues to be addressed.

Figure 2 : EPI 2014 coefficients values and EPI 2012 comparison

Main results over the countries

If we compare the new EPIs and their variations over 2012-2014 – with all precautions discussed above- the following Figure 3 is showing the last two year trend over the 132 countries already ranked in 2012:

-    73 countries have increased their current EPI scores over the last two years : mostly higher income and upper middle  income;

-    59 countries have decreased their current EPI scores over the last two years: mostly lower income and lower middle income.

Large high income countries are progressing: Spain: +32%; Germany: +20%; USA: +20%; Japan: +14%; UK: +12%.

But heavily populated and low income countries are showing a strong reduction: Bangladesh: -39%;; Philippines: -23%; Indonesia: -15%; India: -14%; Brazil: -13%.

Figure 3 : EPI 2014 and trend 2012-2014 over various income-groups; note that only EPI 2012 ranked countries are presented. The above figure is showing: 32 high income OCDE countries 31 with increasing & 1 with decreasing (Taiwan) trends; 15 high-income non OCDE countries: 11 with increasing & 4 with decreasing (Croatia, Uruguay, Lithuania & Latvia) trends; 39 upper middle income countries: 24 with increasing & 15 with decreasing trends; 30 lower middle income countries: 7 with increasing & 23 with decreasing trends; 16 lower income countries all with decreasing trends

If we want to know the overall result over the planet, Yale EPI ranking does not give any clue and we have to make further assumptions as explained hereafter.

Relationship between EPI and income per capita

If we plot each country EPI against its respective income per capita with a logarithm scale for both EPI and income, we have a much better view over the small EPI countries.

We see- which is an amazing outcome- that all countries are more or less aligned in their average  line that best fits the showed income level EPI points with the method of least squares (see table 4).

Nevertheless there is a slight tendency for high income countries to be above the average line.

We see also that EPI’s volatility around the average line is increasing when income level decrease.  

Figure 4 : Curve of 2014 EPI scores plotted against GDP per capita with logarithm scales  

Another aspect is to show among a group of homogenous countries an average EPI value and which countries are doing well or bad at their income level.

For instance (see following Figures 5, 6 & 7) :

Figure 5 : Curve of High Income countries 2014 EPI scores plotted against GDP per capita with logarithm scales; in high income OCDE countries (red signs): USA, Belgium, Taiwan, South Korea and Israel have bad EPI as compared with the average line; France, Canada & Japan are a better EPI but still down the line; Switzerland, Luxembourg, Australia & Germany are much above the line; in high income non-OCDE countries(yellow signs): Equatorial Guinea; Bahamas and Barbados are far down the average line; Qatar, Bahrain & Trinidad & Tobago are not doing well also when compared with the average line; Singapore and United Arab Emirates are much above the average line

Figure 6: Curve of upper middle income countries 2014 EPI scores plotted against GDP per capita with logarithm scales; Grenada, Angola & Irak are down from the average line; China is slightly down;  Hungaria, Serbia and Belarus are well above the line

Figure 7 : Curve of lower middle income and lower income countries 2014 EPI scores plotted against GDP per capita with logarithm scales; in lower middle income countries: Mali, Sierra Leone and Afghanistan are down the average line; Zimbabwe is well above the average line; in lower middle income countries (blue signs) Lesotho & Sudan are down from the average lines; India is less down the line; Armenia and Egypt are well above the average line

Can we define 2013 EPI average value for all the ranked countries?  What is the overall evolution over 2012?

The country's EPI is an averaged value of each part or unit EPI of the country.  

When comparing relative situation of countries such as Switzerland or Singapore (5-7 Mil) with say USA (313 Mil), Indonesia (246 Mil), India (1236 Mil) or China (1350 Mil), we need to factor EPI by the population.

So there is a relationship between EPI and population. This means that to know the overall impact on the planet we need to use the EPI cumulated-weighted average (see Figure 8).

This Figure is showing that during the last two years the average value - or the worldwide EPI- was 45.7 in 2014 after 47.5 in 2012. 

This means that during the 2012-2014 period:  EPI was in average less than the middle value between 0 and 100.

We see also that in the last two years there have not been any improvement but a reduction of 3.8%:  some countries have improved- mostly small populated and high-income countries such as: Australia, Singapore or even USA- but the reduction of the highly populated middle and low income countries is showing a huge deterioration of the overall value.

Figure 8 : Population weighted 2012 and 2014 EPI monotonous curves

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.