Tag Archives: Global temperature

Long-term climate variability ‘could fall’ as the world warms

Long-term climate variability is the range of temperatures and weather patterns experienced by the Earth over a scale of thousands of years. New research suggests it could fall as the world warms.

A study using data taken from fossils and ice cores finds that long-term temperature variability decreased four-fold from the Last Glacial Maximum (LGM) around 21,000 years ago to the start of the Holocene around 11,500 years ago. Within this period, natural processes caused the planet to warm by around 3-8C.

If future global emissions are not curbed, human-driven global warming could cause further large declines in long-term temperature variability, the lead author tells Carbon Brief, which may have far-reaching effects on the world’s seasons and weather.

However, it is still unclear how a decline in long-term variability could affect the frequency of extreme weather events, she adds. This is because the chances of an extreme event happening could be influenced by both short- and long-term climate variability, as well as global temperature rise.

Digging up the past

The new study, published in Nature, is the first to make a global assessment of how long-term temperature variability changed from the LGM to the Holocene.

During the LGM, the world’s last major ice age, snow covered much of Asia, Europe and North America. Yet, within a few thousand years, global temperatures rose by around 3-8C, causing the ice to thaw and the world to enter its current geological period, the Holocene.

The cause of this temperature rise is still disputed by scientists, but research suggests the natural release of large stores of CO2 from the world’s oceans may have played a role.

To work out how long-term climate variability changed over the period, the researchers analysed data taken from ancient ice cores, marine sediments and animal and plant fossils stretching back thousands of years.

Scientists are able to analyse some of these samples – which are known as proxy records –  by looking at the ratios between different chemical isotopes.

Combining data derived from different parts of the world and time periods allows scientists to create a picture of past temperature change, explains Dr Kira Rehfeld, a research fellow at the British Antarctic Survey and the Alfred-Wegener Institute for Polar and Marine Research (AWI) in Potsdam, Germany. She tells Carbon Brief:

“We set out and started collecting more and more records that we could use to get a more general picture of changing climate variability for temperature. It’s taken us three and a half years to find enough records and to develop the methodology to be able to analyse them.”

The researchers then compared data taken from the LGM and the Holocene to help them work out how global temperatures could have changed over large time scales. Rehfeld says:

“We don’t look at the variability in terms of just temperature rise, we look at the ratio of the variability. So we divide the variability of the LGM by the variability of the Holocene. That way we can compare records that have very different origins.”

Ancient landscape

The research finds that, from the LGM to the Holocene, long-term temperature variability fell by a factor of four.

However, some parts of the world experienced larger changes in temperature than others, the study notes.

This is shown on the chart below, where dark blues show areas that experienced a large amount of temperature change from the LGM to the Holocene, whereas light blue shows areas that experienced less change.

On the chart, symbols are used to show the location of ice cores (circle), marine sediments (diamond), lacustrine – or lake – sediment (triangle) and tree fossil data (square). Colours are used to show samples from the Holocene and LGM (red), the Holocene (orange) and the LGM (purple).

Global temperature change from the Last Glacial Maximum to the Holocene. Dark blue indicates high temperature change while light blue shows low temperature change. Symbols show the location of ice cores (circle), marine sediments (diamond), lacustrine sediment (triangle) and tree fossil data (square). Colours show samples from the Holocene and LGM (red), the Holocene (orange) and the LGM (purple). Source: Rehfeld et al. (2018)

The findings show that the world’s poles experienced a larger change in temperature than the equator over the time period. These changes led to an overall decline in long-term temperature variability, the research finds.

The difference in warming between the poles and the equator could be down to a process known as “polar amplification”, Rehfeld says.

Polar amplification is the phenomenon that any change in the impact of sunlight on the Earth tends to have a larger effect on the poles than the equator.

This is thought to be because as warming causes sea ice near the poles to melt, energy from the sun that would have been reflected away by the ice is instead absorbed by the ocean. Because of this, surface temperatures near the poles start to rise at an accelerated rate.

The findings reinforce the prediction that future climate change driven by humans will cause a larger increase in temperature at the poles than at the equator, Rehfeld says:

“The temperature difference between the poles and the equator has decreased as the Earth warms due to polar amplification. This relates to a change in overall long timescale temperature variability.

“If you take that and extrapolate that into the future, warming could be larger at the poles. The temperature difference is then further reduced, which would translate into a reduction of overall temperature variability.”

Carbon Brief previously reported on how the effect of climate change on polar amplification could cause the amount of wind available for power generation to fall in the northern hemisphere.

Future forecast

Although long-term variability is expected to fall, this does not mean that short-term variability will also be reduced, Rehfeld says:

“The question we’re asking is what would a warmer world than today look like? If we can translate our changes in the temperature gradient, then that would mean, theoretically, that long timescale variability in the future will be reduced. But that doesn’t mean that short timescale variability will be reduced.”

Short-term climate variability is a term typically used to describe the natural range of temperatures and weather patterns experienced by the Earth within shorter periods.

For example, after an extreme weather event, scientists often carry out single attribution studies to determine how the likelihood of such an event could have been influenced by climate change and short-term climate variability.

It is still not clear how a reduction in long-term variability will affect the frequency and severity of extreme weather events, Rehfeld says:

“There seems to be a correlation. This change in long timescale climate variability could have influences on extreme events and seasonal variability.

“Based on what we know about how extreme events work, if we have a broader distribution of temperatures then we should have more extreme events. However, what we perceive as extreme events, like floods or heatwaves, is not reflected in our datasets.”

In other words, scientific theory suggests that declines in long-term climate variability could lead to fewer extreme events. However, the timescale used in the study was too broad to reflect short-term events, such as floods and heatwaves.

Modelling change

The findings are “interesting”, but could hold “limited relevance” to understanding future climate change, which is occuring at a much faster rate than the warming observed from the LGM to the Holocene, says Prof Amanda Maycock, a research fellow from the University of Leeds who was not involved in the new study. She tells Carbon Brief:

“Current surface temperature changes and associated changes in climate variability and extremes are occurring much more rapidly than the multi-centennial timescales considered in the study.”

The datasets collated in the study could be used to help climate models simulate more long-term changes in climate variability, says Dr Lauren Gregorie, an academic research fellow at the University of Leeds, who was also not involved in the study. She tells Carbon Brief:

“What I find particularly interesting is that while models do simulate a reduction in variability, they tend to underestimate that change compared to the records [used in the study]. There is a great opportunity to use our knowledge of past climate change to test and improve climate models. Unfortunately, there’s currently very little funding to do this kind of work.”

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Rainforests: Scientists concerned climate change is altering the tropical life cycle

Climate change could be causing shifts to the natural cycle of life in the tropical rainforest, scientists have suggested.

A rise in global temperatures may be driving trees and plants to produce fruit and flowers earlier or later than before, researchers have found. This could have large consequences for a diverse range of animals that rely on tropical rainforests for food and shelter.

The animals most at risk include those that rely on flower nectar for survival, including bees and hummingbirds, as well as animals that feed on the fruit of tropical trees, including great apes, monkeys and parrots.

However, a lack of historical data and ongoing research in the tropics means that the scale of these changes is yet to be fully understood, scientists told Carbon Brief at a Royal Society conference held in Buckinghamshire earlier this month.

Changing seasons

In every part of the world, plants rely on cues from their environment, including changes in sunshine, temperature and rainfall, to determine when to start producing leaves, flowers or fruit. The study of this phenomenon is known as plant “phenology”.

Primary rainforest Langkawi Malaysia. Credit: David Noton Photography / Alamy Stock Photo.

In temperate regions, including the UK and North America, plants tend to time their natural cycles to the changing of the seasons. For instance, plants respond to warming temperatures and increasing daylight hours in the spring by sprouting new leaves.

However, rainforests do not have well-defined seasons, such as spring, summer, autumn, and winter, says Prof Patricia Morellato from São Paulo State University in Brazil. Morellato chaired a session on the possible future of tropical phenology research at the conference. At the sidelines of the event, she told Carbon Brief:

“In the tropics, we don’t have sharp seasons, so it’s more difficult to track changes. Instead, we have to know the cycle and, over time, see if the cycle is changing.”

Most rainforests have a wet and a dry season, which is caused by annual changes in rainfall. But many tropical plants do not time events, such as flowering, in accordance with these seasons, says Dr Joseph Wright, from the Smithsonian Tropical Research Institute in Panama. At the conference, Wright presented a talk on the environmental controls of leaf fall and flowering in tropical rainforests. He told Carbon Brief:

“I work on a 16 sq km site in Panama with 2,000 plant species. Every month of the year, there are several hundred species flowering. At the peak month, there’s probably a thousand species flowering. But even in the minimum month, there’s 200 species flowering.”

Because tropical plants do not time their life cycles according to the seasons, it is more difficult to work out what environmental cues could be causing the plants to begin flowering, Wright said:

“It could be unusually low temperature. It could be the beginning of the rainy season. Or it could be sunlight. These hypotheses are very vague.”

Data drought

Another limitation in the tropics is a lack of long-term climate and plant data, the researchers said.

In Europe and North America, scientists and nature enthusiasts alike have been recording the date of the first bud, leaf and flower for thousands of species for more than a century.

This long record has enabled researchers to track how plants are responding to global warming. Recent research (pdf) from the Met Office finds that spring is currently advancing at a rate of 2.5 days per decade across Europe.

However, in the tropics, there are very few known historical records and little funding available for research to be conducted, Wright said:

“There’s an incredible north-south divide. The northern hemisphere is rich and there’s tonnes of excellent universities and national research councils and so, as a consequence, in the northern temperate zone we have an incredible knowledge base. There’s tonnes of scientists and there’s very few species.

“You go to the tropics, we have the opposite situation. Countries are poor, each country might have one national university and the vast majority have no national research programme. But there’s thousands of species, there’s a hundred times more species and three orders of magnitude fewer scientists.”

Measuring mismatch

Despite a lack of historical knowledge, a growing number of researchers are trying to find new ways of understanding how climate change could affect the natural cycle of tropical rainforests.

One key area of this new research is to understand how shifts in forest cycles could affect the unique community of animals that live in the tropics.

It is still unclear how climate change may affect rainfall patterns in much of the tropics, but research (pdf) suggests that rainforests could experience longer dry periods by the end of the century.

A research paper published by Morellato and her colleagues in 2016 in the journal Biological Conservation attempts to evaluate how a longer dry season caused by climate change could affect the timings of key events in the rainforest.

It suggests that a longer dry season could cause plants to start flowering later on in year. This is shown in the chart below, where blue bars show the amount of monthly rainfall, while blue lines show the percentage of plants that are producing flowers. Red lines show the percentage of plants producing fruit.

On the chart, red-dashed arrows show how a longer dry season caused by climate change could lead to later plant reproduction via flowering. Later flowering could lead to less time available for plant pollination, which will result in fewer plants producing fruit the following year.

Schematic diagram showing the effects of climate change in tropical rainforests. On the top chart, blue bars show monthly rainfall, blue lines show the percentage of plants flowering and red lines show the percentage of plants producing fruit. The bottom chart shows the overlap (black) and non-overlap (striped) of the activity timing of flowers and pollinators (blue) and fruit and fruit-eating animals (red). Caption: Morellato et al. (2016)

Beneath the chart, a diagram shows how a later flowering period caused by climate change could lead to a smaller overlap between the activity time of flowers and their pollinators (shown in blue).

This “mismatch” could greatly threaten the survival of pollinators, including insects and birds, who rely on flowers for both food and shelter.

The animals most at risk are those which feed on the nectar of just a small number of plant species, such as many bees and hummingbirds, the study notes:

“The reliable and continuous availability of floral resources in the tropics has enabled strong and diverse adaptations in flower visitors, maintaining rich assemblages of highly specialised floral foragers, such as bees and hummingbirds.”

On top of this, a reduction in fruit availability in the following year as a result of climate change could cause a “mismatch” in the activity time of fruit trees and fruit-eating animals, which are known as “frugivores”. The paper reads:

“Frugivorous animals critically rely on fruits, and fundamental aspects of their ecology – including diet, population size, social behaviour reproduction, and movements – depend on fruit abundance and seasonality.”

A wild, young male orangutan climbs trees in the rainforest to find red berries to eat. Credit: Lillian Tveit / Alamy Stock Photo.

Such animals include great apes, smaller monkey species, as well as a range of tropical birds, including parrots, the paper adds.

‘Critical to every organism’

Although recent research outlines the species most at risk from shifts to the tropical cycle, it is likely that such changes will affect almost every animal found in the rainforest in some way, Morellato said:

“In the tropics, almost all species rely, at some point in their lives, on a plant in flower or in fruit. Changes in phenology will affect the animal community in forests, that’s for sure.”

Fully understanding how climate change is affecting plant phenology will be key to protecting rainforest wildlife, Wright said:

“Primary producers [plants] are critical to every organism, every animal, every consumer in the forest. The more we’re able to get some understanding on what the link between what climate and the plant response is, the more we’re going to be able to make predictions about their chances of survival.”


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State of the climate: how the world warmed in 2017

The climate data for 2017 is now in. In this article, Carbon Brief explains why last year proved to be so remarkable across the oceans, atmosphere, cryosphere and surface temperature of the planet.

A number of records for the Earth’s climate were set in 2017:

  • It was the warmest year on record for ocean heat content, which increased markedly between 2016 and 2017.
  • It was the second or third warmest year on record for surface temperature – depending on the dataset used – and the warmest year without the influence of an El Niño event.
  • It saw record lows in sea ice extent and volume in the Arctic both at the beginning and end of the year, though the minimum extent reached in September was only the eighth lowest on record.
  • It also saw record-low Antarctic sea ice for much of the year, though scientists are still working to determine the role of human activity in the region’s sea ice changes.

Warmest year on record in the oceans

More than 90% of the heat trapped by increasing greenhouse gas concentrations ends up going into the Earth’s oceans. While surface temperatures fluctuate a bit from year to year due to natural variability, ocean heat content increases much more smoothly and is, in many ways, a more reliable indicator of the warming of the Earth, albeit one with a shorter historical record.

2017 set a clear record for the highest ocean heat content since records began in 1958, according to the Institute of Atmospheric Physics of the Chinese Academy of Sciences (IAP-CAS), which maintains an up-to-date ocean heat content database.

The figures below shows ocean heat content for each year in the region of the ocean between the surface and 2,000 meters in depth (comprising the bulk of the world’s oceans), as well as a map of 2017 anomalies.

The upper figure shows changes in ocean heat content since 1958, while the lower map shows ocean heat content in 2017 relative to the average ocean heat content between 1981 and 2010, with red areas showing warmer ocean heat content than over the past few decades and blue areas showing cooler.

Change in global ocean heat content between the surface and 2000 meters of depth from 1958 to 2017 (top) and distribution of ocean heat content anomalies in 2017 (bottom). Figure from Cheng and Zhu (2018), using data from IAP-CAS.

Ocean heat content in 2017 was significantly higher than in 2015, the next warmest year. While 2016 was the warmest year on the surface, it was only the third warmest year for ocean heat content as the El Niño event that helped 2016 surface temperatures be so warm redistributed heat out of the ocean and into the atmosphere.

Warmest surface temperatures without an El Niño

Global surface temperatures in 2017 were the second or third warmest on record since 1850, when global temperatures can first be calculated with reasonable accuracy. Unlike the other warmest years – 2015 and 2016 – there was no El Niño event in 2017 (or in late 2016) contributing to increased temperatures this year (and mild El Niño conditions in early 2017 were offset by mild La Niña conditions during the later part of the year).

Records that include coverage of the full Arctic, such as those from NASA, Berkeley Earth and Copernicus/ECMWF, showed 2017 as the second warmest after 2016, while records with sparser coverage in that region showed 2017 as the third warmest behind 2016 and 2015. All surface records show quite similar results when examined over regions where they all have coverage.

The figure below shows global surface temperatures records from the principal research groups around the world since 1970. These are created by combining ship- and buoy-based measurements of ocean sea surface temperatures with temperature readings of the surface air temperature from weather stations on land. Temperatures are shown as anomalies relative to a 1970 to 2000 average. [Click the figure legend to show or hide different temperature records.]

Annual global average surface temperatures from 1970-2017. Data from NASA GISTemp, NOAA GlobalTemp, Hadley/UEA HadCRUT4, Berkeley Earth, Cowtan and Way, and Carbon Brief’s raw temperature record. 1979-2000 temperatures from Copernicus/ECMWF (as the reanalysis record starts in 1979). Anomalies plotted with respect to a 1970-2000 baseline. Chart by Carbon Brief using Highcharts.

Short-term variability in the record is mostly due to the influence of El Niño and La Niña events, which have a short-term warming or cooling impact on the climate. Other dips, such as the one in the mid-1990s, are associated with large volcanic eruptions. The longer-term warming of the climate is entirely driven by atmospheric increases in CO2 and other greenhouse gases emitted from human activity.

The record warm temperatures experienced over the past three years are not due to any adjustments made to the underlying temperature records. The figure above includes a “raw records” line calculated by Carbon Brief using data not subject to any adjustments or corrections for changes in measurement techniques. Since 1970, the raw data and the adjusted temperature records produced by different groups largely agree.

Global surface temperature records can be calculated back to 1850, though some groups choose to start their records in 1880 when more data was available. Prior to 1850, records exist for some specific regions, but are not sufficiently widespread to calculate global temperatures with any reasonable accuracy. Global temperature records since 1850 are shown in the figure below, again shown as the difference from a baseline of 1970-2000.

Same as prior figure, but with data extending back to 1850 (or as far back as each individual record is available). Chart by Carbon Brief using Highcharts.

Global surface temperatures in 2017 were 1-1.2C warmer than temperatures in late 19th century (between 1880 and 1900), depending on the temperature record chosen.

It is striking how warm 2017 was, despite the end of the massive El Niño event that pushed up 2015 and 2016 temperatures. The past three years are well above any prior years’ temperatures, by a margin of more than 0.15C,

This is shown in the figure below from Berkeley Earth. Each shaded curve represents the annual average temperature for that year, and the further that curve is to the right, the warmer it was.

The width of each year’s curve reflects the uncertainty in the annual temperature values (caused by factors such as changes in measurement techniques and the fact that some parts of the world have more sparse station coverage).

Global average surface temperatures for each year with their respective uncertainties (width of the curves) from Berkeley Earth. Note that warming is shown here relative to the temperature of the 1951-1980 period, but the relative position of the years would be the same using a 1970-2000 baseline. Figure produced by Dr Robert Rohde.

While El Niño and La Niña events have a sizable short-term impact on global temperatures, their influence tends not to extend for more than six months or so after the event has ended. With the large El Niño event of 2015 and 2016 fading by the summer of 2016, it had little direct influence on 2017 temperatures.

In the figure below, Dr Gavin Schmidt, director of the NASA Goddard Institute for Space Studies, uses a simple statistical model to estimate what the global temperature record (black line) would be like in the absence of El Niño or La Niña influences (red line).

Although El Niño bumped up the temperatures of 2015 modestly and 2016 quite a bit, it had almost zero effect on 2017 temperatures. When the influence of El Niño is removed from the record, according to Schmidt’s analysis, 2017 would be the warmest year on record.

Global average surface temperatures from NASA’s GISTemp (black) and with the influence of El Niño and La Niña (collectively referred to as ENSO) removed (red). Figure produced by Dr. Gavin Schmidt.

However, Dr Tim Osborn, director of the Climatic Research Unit at the University of East Anglia, cautions that these results are somewhat sensitive to the statistical method and El Niño index used.

He suggests that, while 2017 is probably the warmest when ENSO is taken out, it is not necessarily as clear a winner over 2016 and 2015 if different methods are used. It is clear, though, that 2017 is the warmest non-El Niño year by any measure.

A paper recently published in Geophysical Research Letters by researchers at the University of Arizona suggests that global temperatures may not return down to pre-2015 levels any time soon. They suggest that extra heat was absorbed by the tropical Pacific Ocean since the late 1990s and that the recent El Niño event acted as a trigger for that heat to be released. The cycle of extra heat uptake by the oceans may be over for at least a decade.

Near-record warmth in satellite records

In addition to surface measurements over the world’s land and oceans, satellite microwave sounding units have been providing estimates of global lower atmospheric temperatures since 1979. These measurements, while subject to some large uncertainties, also show 2017 as a near-record warm year.

The record produced by Remote Sensing Systems (RSS) shows 2017 as the second warmest year after 2016, while the record from the University of Alabama, Huntsville (UAH) shows it as the third warmest after 2016 and 1998. The two records are shown in the figure below – RSS in red and UAH in blue.

Global average lower troposphere temperatures from RSS version 4 (red) and UAH version 6 (blue) relative to a 1979-2000 baseline (as the satellite records begin in 1979). Chart by Carbon Brief using Highcharts.

These satellites measure the temperature of the lower troposphere and capture average temperature changes around 5km above the surface. This region tends to be influenced more strongly by El Niño and La Niña events than the surface and satellite records show correspondingly larger warming or cooling spikes during these events.

This is why, for example, 1998 shows up as one of the warmest years in satellites, but not in surface records.

Observations tracking close to climate modelling projections

Climate models provide projections of both long-term and shorter-term changes to the Earth’s climate. While climate models show their own El Niño- and La Niña-like behaviour, it does not necessarily occur at the same time in models as it does in the real world.

However, temperatures in recent years – both during the El Niño event and, more importantly, now that the El Niño event is over – are tracking rather close to the average projection of the climate models included in the latest report from the Intergovernmental Panel on Climate Change (the CMIP5 models).

These models used historical records of greenhouse gases and other factors through to 2005. Model estimates of temperatures prior to 2005 are a “hindcast” using known past climate influences, while temperatures projected after 2005 are a “forecast” based on a estimate of how things might change.

The figure below shows the range of individual models forecasts between 1970 and 2020 with grey shading, with the average projection across all the models shown in black. Individual observational temperature records are represented by coloured lines.

Annual global average surface temperatures from CMIP5 models and observations between 1970 and 2020. Models use RCP4.5 forcings after 2005. They include sea surface temperatures over oceans and surface air temperatures over land to match what is measured by observations. Anomalies plotted with respect to a 1970-2000 baseline. Chart by Carbon Brief using Highcharts.

While global temperatures were running a bit below climate models between 2005 and 2014, the last few years have been pretty close to the model average.

Low sea ice at both poles

In addition to near-record temperatures, 2017 also saw record-low sea ice during parts of the year, both in the Arctic and Antarctic.

The figure below shows the average Arctic sea ice extent for each week of the year for every year between 1978 and 2017. Prior to 1978, satellite measurements of sea ice extent are not available and the data is much less reliable.

Average Arctic sea ice extent by week from 1978-2017. Data from the US National Snow and Ice Data Center (NSIDC). 2017 is shown by the black line. Chart by Carbon Brief using Highcharts.

The figure shows a clear and steady decline in Arctic sea ice since the late 1970s, with lighter darker colours (earlier years) at the top and lighter colors (more recent years) much lower. A typical summer now has nearly half as much sea ice in the Arctic as it had in the 1970s and 1980s.

Arctic sea ice in 2017 had record-low extents for much of the first five months of the year, though it recovered a bit after that to show only the eight lowest summer minimum on record. However, Arctic sea ice has again seen near-record lows in the December 2017, reflecting unusual warmth in the region.

Sea ice extent only provides part of the picture, as some sea ice is much thicker or older than others. The Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) project provides estimates of sea ice volume since 1979, shown in the figure below.

Arctic sea ice volume anomalies from 1979 through 2017 from PIOMAS.

According to PIOMAS, sea ice volume was around 12,000 cubic kilometers lower than in 1979. They found that 2017 tied 2012 for the lowest measured Arctic sea ice volume on record, though 2012 remains the year with the lowest summer minimum volume.

While the long-term decline in Arctic sea ice is clear, the Antarctic is much more complicated. Weekly Antarctic sea ice extent from 1978 through to 2017 is shown in the figure below.

Average Antarctic sea ice extent by week from 1978-2017. Data from the US National Snow and Ice Data Center (NSIDC). 2017 is shown by the black line. Chart by Carbon Brief using Highcharts.

Unlike in the Arctic, the Antarctic has no clear long-term trend in sea ice extent. In the figure early years (darker lines) and recent years (lighter lines) are intermixed. In fact, 2015 and early 2016 set records for the most sea ice extent observed.

In 2017, however, Antarctic sea ice hit record lows for much of the year. Even in recent months it has been the second lowest recorded after late 2016. It is unclear what role, if any, climate change is playing in Antarctic sea ice changes, though it is an area of very active research.

Finally, both Antarctic and Arctic sea ice extent is combined to estimate global sea ice extent in the figure below.

Average global sea ice extent by week from 1978-2017. Data from the US National Snow and Ice Data Center (NSIDC). 2017 is shown by the black line. Chart by Carbon Brief using Highcharts.

Global sea ice set a clear record low in the first half of 2017, driven in large part by record low Antarctic sea ice cover. There has been a long-term downward trend in summer global sea ice extent, though the trend is less clear in the winter, reflecting the fact that the Arctic shows a clearer long-term trend than the Antarctic.


Carbon Brief produced a raw global temperature record using using unadjusted ICOADS sea surface temperature measurements gridded by the UK Hadley Centre and raw land temperature measurements assembled by NOAA in version 4 of the Global Historical Climatological Network (GHCN).

Raw land temperatures were calculated by assigning each station to a 5×5 latitude/longitude grid box, converting station temperatures into anomalies relative to a 1971-2000 baseline period, averaging all the anomalies within each grid box for each month, and averaging all grid boxes for each month weighted by the land area within each grid box.

Raw combined land/ocean temperatures were estimated by averaging raw land and ocean temperatures weighted by the percent of the globe covered by each.

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Timeline: The history of climate modelling

The climate models used by scientists today rely on some of the world’s most advanced supercomputers. It can take dozens of highly skilled people to build and then operate a modern-day climate model.

However, less than a century ago, climate models were little more than an idea; basic equations roughly sketched out on paper. After the second world war, though, the pace of development quickened dramatically, particularly in the US.

By the late 1960s, policymakers were being presented with the models’ findings, which strongly reinforced the theory that the continued rise in human-caused greenhouse gas emissions would alter the global climate in profound ways.

In the interactive timeline above, Carbon Brief charts more than 50 key moments in the history of climate modelling.

Such moments include…

  • Guy Callendar’s seminal paper published in 1938.
  • The first computerised, regional weather forecast in 1950.
  • Norman Phillips’ first general circulation model in 1956.
  • The establishment of a modelling group at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, in 1964.
  • Syukuro Manabe and Richard Wetherald’s seminal climate modelling study in 1967.
  • The Met Office’s first general circulation model in 1972.
  • The Charney Report in 1979.
  • James Hansen’s three scenarios published in 1988.
  • The first Intergovernmental Panel on Climate Change (IPCC) report published in 1990.
  • The Coupled Model Intercomparison Project (CMIP) launched in 1995.
  • The IPCC’s fifth assessment report published in 2013.

Scroll through the various slides within the interactive timeline, above, by clicking on the arrows. Or you can use the calendar above each slide to jump to a particular moment within the history.

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