CL
Climate: Past, Present & Future

Climate: Past, Present & Future

What is in the (European) air?

What is in the (European) air?

You thought that Mauna Loa was the only observatory to provide continuous measurements of atmospheric carbon dioxide concentration and were disappointed because Hawaii is way too far from your study area or because you wanted to know how bad  the air is in your hometown? The US have been monitoring the composition of the atmosphere since 1972, but what about Europe? Since 2008, Europe has its own measurement network that is managed by a research infrastructure called ICOS (Integrated Carbon Observation System).

Context

Since the beginning of the industrial era (around 1750), atmospheric concentrations of greenhouse gases such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) have increased, mostly because of human activities. As a consequence, the climate is getting warmer, which could have dramatic impacts on our daily life. The evolution of the atmospheric composition should therefore be closely monitored.

To improve our understanding of the climate system and achieve good climate predictions, high-precision measurements of greenhouse gas sources and sinks are needed. A large amount of datasets already exists, but the problem is that these data are often too difficult to access, too scattered, not consistent or not reliable.

ICOS main objectives

This is why the main goal of ICOS is to provide scientists, citizens and decision makers with harmonized and high-quality measurements of greenhouse gases in Europe. But the scope of ICOS mission is wider because these data can further be used to:

  • quantify greenhouse gas budgets
  • improve climate predictions
  • check how well/badly European countries are doing in reducing their greenhouse gas emissions
  • adapt policies

ICOS also encompasses an educational dimension by training young scientists through summer schools, workshops and conferences and by spreading knowledge about the carbon cycle to the general public.

Network

ICOS is subdivided in national networks managed by research institutes. Twelve countries are currently members of ICOS: Belgium, Czech Republic, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Sweden, United Kingdom and Switzerland. The regional dynamics of greenhouse gases is monitored thanks to a network of 126 measurement stations implemented across these countries. Among these stations, 71 are ecosystem stations, 34 are atmospheric stations and 21 are ocean stations (Figure 1). ICOS grows rapidly and 8 other countries are expected to become members soon: Poland, Ireland, Estonia, Portugal, Spain, Hungary, Greece and South Africa.

To be part of the ICOS standardized network, candidate sites have to follow strict specifications regarding equipment, measurement protocols and data processing in order to ensure a homogeneous dataset. Periodic measurements are also carried out across the network with independent instruments to limit systematic errors. Moreover, ICOS is planning to render its data products compatible with outputs from other international measurement networks by taking part in an intercomparison program.

Atmosphere stations (Figure 2)

Atmospheric CO2, CO and CH4 concentrations are continuously measured in atmosphere stations, together with a range of usual meteorological variables such as air temperature, atmospheric pressure, relative humidity, wind direction and speed.

Figure 2: Cabauw atmosphere station in the Netherlands (ICOS ERIC, https://meta.icos-cp.eu/labeling/)

Ecosystem stations (Figure 3)

Flux towers measure the exchange of water vapour, greenhouse gases and energy between the different types of ecosystems and the atmosphere. The list of variables collected at ecosystem stations is available here.

Figure 3: Brasschaat ecosystem station in Belgium (ICOS ERIC, http://www.icos-belgium.be/inf_ecosystem.html)

Ocean stations (Figure 4)

Ocean stations include ships, fixed buoys and flux towers. Carbon fluxes are measured at the ocean-atmosphere interface together with other marine variables such as pH, temperature, or salinity. You can have a look at the exhaustive list of measurements here.

Figure 4: VLIZ data buoy ocean station (ICOS ERIC, https://www.icos-ri.eu/sites/default/files/2017-07/ICOS_Belgium_Media_Kit_EN_0.pdf)

Data products

Data collected by national network stations are gathered, processed and stored by central facilities called Thematic Centers (TC): the Atmosphere Thematic Center (ATC), the Ocean Thematic Center (OTC) and the Ecosystem Thematic Center (ETC).

You can access all these precious data for free here on the carbon portal. Among many examples, you can find ecosystem fluxes time series, atmospheric methane observations or global carbon budget. It is easy to handle as you can apply filters to refine your search, click on the “eye” icon to preview the data, or just select the dataset to obtain its description.

These data are protected by a Creative Commons Attribution 4.0 international licence, which means you can share and even modify them provided that you document any change, mention the original data source and give a link to the licence text (https://data.icos-cp.eu/licence). It is of course necessary to cite  ICOS when you use the data. To make this as easy as possible, the citation is provided when you download the data set.

On the website of the Atmosphere Thematic Center, you can also find near real time data that are computed from all ICOS atmospheric stations every day in the morning. For example, Figures 5 and 6 show time series of the fraction of CO2 (top plot) and CH4 (bottom plot) in the air mass coming from the European continent measured at Mace Head station (MHD). Depending on the wind direction, this atmospheric station, located on the west coast of Ireland, is exposed to either the North Atlantic Ocean air mass and or the European continental air mass, offering a unique way to study these very different air masses. Time series for the period 2011-2017 show a clear upward trend for both greenhouse gases in the continental air mass. These increases are mainly caused by growing emissions associated to human activities.

Figure 5: CO2 molar fraction in continental air mass between 2011 and 2017 at Mace Head atmospheric station (ICOS ERIC, https://icos-atc.lsce.ipsl.fr/P0031.1)

Figure 6: CH4 molar fraction in continental air mass between 2011 and 2017 at Mace Head atmospheric station (ICOS ERIC, https://icos-atc.lsce.ipsl.fr/P0031.1)

 

Hopefully, this post helped you to get to know ICOS better. Do not hesitate to use this great tool in the future!

Find out more about ICOS

https://www.icos-ri.eu/

For those interested, the 3rd ICOS Science Conference will take place between the 11th and the 13th of September 2018 in Prague, Czech Republic.

Edited by Gabriele Messori and Célia Sapart

 

Forams, the sea thermometers of the past!

Forams, the sea thermometers of the past!
Name of proxy

Mg/Ca-SST on planktonic foraminifera shell

Type of record

Sea Surface Temperature (SST)

Paleoenvironment

Marine environments

Period of time investigated

55 Million years ago to recent times

How does it work ?

Foraminifera (or Forams) are single-celled organisms varying from less than 1 mm to several cm in size. They are very abundant in the ocean floor (benthic species) or floating amongst the marine plankton (planktonic species) where they produce their shells mostly using calcite (CaCO3). The oldest fossils of benthic foraminifera date back to the Cambrian period (older than 485 million year ago (Ma)) (Armstrong and Brasier, 2005). Planktonic species are younger than the benthic group. For instance, the species Globigerina bulloides (Figure 1) range from Middle Jurassic (180 Ma) to recent times (Sen Gupta, 1999).

A large spectrum of information can be provided by the analysis of foraminifera shells, based on the chemical composition and morphology of their shells as well as the species abundance patterns. One type of proxy is the ratio between the abundance of magnesium (Mg) and calcium (Ca) (Mg/Ca ratio) present in the calcite shell. During the formation of the shell, Mg is incorporated and may weaken the shells. In some cases, it seems that foraminifera expend energy to control the incorporation of Mg (Toler et al., 2001). The substitution of Mg into calcite depends on the temperature of the seawater, so that the amount of Mg in the shell exponentially increases from cold to warm water (Lea, 1999). This means that the Mg/Ca ratio of the shells is expected to rise with increasing temperature (Rosenthal, 2007). Measuring the Mg/Ca ratio of foraminifera shells therefore allows reconstructing the sea surface temperature (SST) of the past.

What are the key findings that have been done using Mg/Ca-SST?

Past SST determination is essential for understanding past changes in climate. An advantage of the Mg/Ca ratio measured on the shells of planktonic foraminifera is that the same sample can be used for different types of analyses in order to obtain a large set of information on the past sea conditions (Elderfield and Ganssen, 2000; Barker et al., 2005). Another advantage of this Mg/Ca proxy is the possibility to reconstruct changes of temperature within the water column using multiple species living at different depths and/or coming from different seasonal habitats (Barker et al., 2005). This can give us, for example, valuable information for describing seasons in the past.

Planktonic foraminifera can survive in a wide range of environments, from polar to tropical areas, thus the analysis of their shells allows reconstructing the ocean conditions all around the world. Moreover, foraminifera are very sensitive to temperature and environmental changes therefore it is possible to reconstruct climate changes of various amplitudes and timescales, e.g. the Paleocene-Eocene Thermal Maximum (55 Ma) or the more recent climate oscillations (Zachos et al., 2003; Cisneros et al., 2016). For instance, Figure 2 shows that Mg/Ca ratio allows reconstructing the ~2ºC warming observed from the Roman Period onset to higher frequency thermal variability like those observed in the Little Ice Age (LIA).

Figure 2: Sea Surface Temperature (SST) record stack for the last 2700 years reconstructed by means of Mg/Ca analysed on the shell of the planktonic foraminifera Globigerina bulloides in the central-western Mediterranean Sea. The different historical/climate periods are indicated: TP=Talaiotic Period, RP=Roman Period, DMA=Dark Middle Ages, MCA=Medieval Climate Anomaly, LIA=Little Ice Age, IE=Industrial Era. Years are expressed as Before Common Era (BCE) and Common Era (CE). The grey shaded area integrates uncertainties of average values and represents 1 sigma of the absolute values. This uncertainty includes analytical precision and reproducibility and the uncertainties derived from the G. bulloides core-top calibration developed in the original reference. (Modified from Cisneros et al., 2016).

 

This article has been edited by Célia Sapart and Carole Nehme
References
  • Armstrong, H. and Brasier, M., Foraminifera. In: Microfossils, Blackwell Publishing, pp. 142-187.
  • Barker, S., Cacho, I., Benway, H. and Tachikawa, K., 2005. Planktonic foraminiferal Mg/Ca as a proxy for past oceanic temperatures: A methodological overview and data compilation for the Last Glacial Maximum, Quat. Sci. Rev., 24, 821–
  • Cisneros, M., Cacho, I., Frigola, J., Canals, M., Masqué, P., Martrat, B., Casado, M., Grimalt, J. O., Pena, L. D., Margaritelli, G., and Lirer, F., 2016. Sea surface temperature variability in the central-western Mediterranean Sea during the last 2700 years: a multi-proxy and multi-record approach. Climate of the Past, 12, 849-869. https://www.clim-past.net/12/849/2016/
  • Elderfield, H. and Ganssen, G., 2000. Past temperature and δ18O of surface ocean waters inferred from foraminiferal Mg / Ca ratios, Nature, 405, 442–
  • Lea, D.W., 1999. Trace elements in foraminiferal calcite. In: Sen Gupta, B.K., (), Modern Foraminifera, Great Britain, Kluwer Academic Publishers, pp. 259-277.
  • Rosenthal, Y., 2007. Elemental proxies for reconstructing Cenozoic seawater paleotemperatures from calcareous fossils. In: Hillaire-Marcel, C. and de Vernal, A. (), Developments in Marine Gelology, Elsevier, pp. 765-797.
  • Sen Gupta, B.K., 1999. Introduction to modern Foraminifera. In: Sen Gupta, B.K., (), Modern Foraminifera, Great Britain, Kluwer Academic Publishers, pp. 3-6.
  • Toler, S.K., Hallock, P., and Schijf, J., 2001. Mg/Ca ratios in stressed foraminifera, Amphistergina gibbosa, from the Florida Keys, Marine Micropalentology, 43, 199-206.
  • Zachos, J. C., Wara, M. W., Bohaty, S., Delaney, M. L., Petrizzo, M. R., Brill, A., Bralower, T. J., and Premoli-Silva, I., 2003. A transient rise in tropical sea surface temperature during the Paleocene–Eocene thermal maximum, Science, 302, 1551–1554.

Decomposing algae have not said their last word yet!

Decomposing algae have not said their last word yet!
Name of proxy

Phytane, a compound resulting from the degradation of Chlorophyll-a (Chl a), a green pigment in plants and algae that is involved in photosynthesis

Type of record

Atmospheric carbon dioxide concentrations

Paleoenvironment

Marine sediments and oils

Period of time investigated

Phanerozoic (last 540 million years)

How it works

Before we can start predicting the potential impact of human activities on climate change, we first need to study the behavior of atmospheric CO2 concentration (pCO2) in the past. This represents a challenge given that continuous atmospheric measurements started only about 60 years ago.

To reconstruct past pCO2, a single well-constrained, ubiquitous proxy would be ideal. Unfortunately, it does not exist and we have to combine the estimates from many different types of proxies, each with their own advantages and weaknesses.

Different potential compounds that can give information on the pCO2 over the last hundreds of millions of years have been explored. The idea is based on the fact that algae consume CO2 and use that carbon to build organic compounds. But carbon atoms are not all the same. They can have different masses depending on the composition of their nucleus. We therefore differentiate between heavy carbon (13C) and light carbon (12C). Algae rather use the lighter, more common carbon (12C), but when less CO2 is available, they must use both 12C and 13C– or go hungry.

Therefore, it is considered that the more abundant is the CO2, the smaller is the 13C/12C ratio of the algae. Likewise, when CO2 is lower, the 13C/12C ratio in algae is higher. Long after an algae died, the 13C/12C ratio of its organic compounds will remain preserved in ancient sediments and oils and reflect the environment in which they were first produced.

Consequently, this ratio is compared to the ratio in CO2 consumed by the algae in order to calculate the fractionation factor (Ɛp) due to CO2-fixation. The fractionation factor is a measure of the discrimination occurring between heavy and light carbon. It can therefore be used to estimate the abundance of CO2 at the time the organic compounds were first produced.

Key Findings

This pCO2 estimation method via Ɛp is generally applied to organic compounds that come from specific species of algae. However, this has limitations – a single species is limited by its evolutionary history and its global abundance.

Here instead, we decided to explore the possibilities of using a general biomarker – an organic compound that all algae have and that contributes to the ocean record. We have explored naturally occurring CO2 vents, pockets of bubbling CO2 caused by volcanic activity, to test several different general biomarkers using this Ɛp method.

Collecting water samples, plankton nets, and sediment at a CO2 vent in Japan

One of the biomarkers that seems to work well are phytol and phytane, which are byproducts of Chl – a green pigment in plants and algae involved in photosynthesis. Phytane was used in specific case studies (e.g. Bice et al., 2006; Damste et al., 2008) but has not been tested extensively. We are now calibrating this potential proxy, by comparing it with other well-established pCO2 proxies over different timescales, and forming a compilation that extends the entire Phanerozoic (the past 540 million years!).

This proxy could significantly increase how far we can reconstruct pCO2 – Chl a and its products have been found in samples over 2 billion years old and is found everywhere (both spatially and temporally) throughout the geologic record.

Edited by Caroline Jacques and Célia Sapart

Further readings

Bice, K. L., Birgel, D., Meyers, P. A., Dahl, K. A., Hinrichs, K. U., & Norris, R. D. (2006). A multiple proxy and model study of Cretaceous upper ocean temperatures and atmospheric CO2 concentrations. Paleoceanography21(2).

Damsté, J. S. S., Kuypers, M. M., Pancost, R. D., & Schouten, S. (2008). The carbon isotopic response of algae,(cyano) bacteria, archaea and higher plants to the late Cenomanian perturbation of the global carbon cycle: Insights from biomarkers in black shales from the Cape Verde Basin (DSDP Site 367). Organic Geochemistry39(12), 1703-1718.

What speleothems can tell about the past climates !

What speleothems can tell about the past climates !
Name of the proxy:

Stable isotope ratios of carbonates in speleothems

Type of proxy:

Precipitation, atmospheric circulation, CO2 availability in soil, soil productivity

Paleoenvironment:

Continental environments

Period of time investigated:

Present day to 10 million years

Figure 1: Cut face of the Jeita cave stalagmite covering the last 12,000 years and showing  how the stratigraphy of a speleothem can be determined (Lebanon, central-Levant) (Modified after Verheyden et al., 2008)

How does it work?

Speleothems are inorganic carbonate deposits growing in caves that form from super-saturated cave waters (with respect to CaCO3) (Figure 1). Their analysis allows recovering aspects of past changes of the cave drip water geochemical composition, which provides information on climate and environmental variations above the cave (Fairchild and Baker, 2012). Different types of speleothems (e.g. flowstone, stalagmites) are widespread in karstic cave environments, but stalagmites as well as flowstones are used mainly to reconstruct past climates, because of a well-defined stratigraphic order. The major strengths of speleothems include their suitability for accurate age determinations (U/Th for ages up to c. 500,000 years; U/Pb for ages older than 500,000 years). Moreover, the preservation of multiple quasi-independent climate and environmental proxies enables the investigation of past climate changes on orbital to seasonal scale worldwide. Some of the most used proxies of speleothem carbonates are the ratios between oxygen-18 and oxygen-16 (δ18O) and carbon-13 and carbon-12 (δ13C), which are stated as a relative deviation to the Vienna Pee Dee Belemnite (VPDB) standard.

 

Figure 2: A diagram illustrating the primary processes related to δ18O variations relevant to paleoclimatology using speleothem records. Variations in temperature and relative humidity affect δ18O values through various processes in the atmosphere, in in the hydrosphere, in the soil and epikarst zones, and finally in the speleothem CaCO3. Modified after Lachniet, 2009.

 

The δ18O values of speleothem carbonates are determined mostly by two variables: the δ18O value of the cave drip water, which in turn is related to the δ18O value of the precipitation and in-cave fractionation processes (Lachniet, 2009). The δ18O value of the precipitation is determined by the atmospheric circulation, the trajectory of the precipitation, the amount effect (describing the negative relationship between precipitation δ18O and precipitation amount) and/or the seasons. The δ13C values of speleothem carbonates are locally controlled by biogenic soil productivity associated with the vegetation type (C4- or C3-type) and density, which regulates the soil CO2 content. Furthermore, it can reflect the availability of CO2 in the soil during the dissolution of limestone, which is a function of the water level in the karst and thus of the local precipitation amounts.

 

Figure 3: Different types of speleothem laminas. (A) Fluorescent laminas excited by UV light. (B) Visible laminas observed under reflected-light microscopy. (C) Calcite (C) and aragonite (A) couplets, observed under transmitted-light microscopy (Modified from Tan et al. (2006) and Johnson et al. (2006)) and (D) δ18O and δ13C variations measured in different laminas, reported in permil VPDB, from the Proserpine stalagmite (Han-sur-Lesse cave, Belgium). Note that dark and compacted layers become whiter due to the translucent light of the scan while the white and porous layers become dark. Modified from Van Rambelbergh et al. (2013).

What are the key findings that have been done using speleothems?

Speleothems are growing in caves worldwide and complement marine and polar climate archives, revealing unique views onto past climates. Speleothem δ18O records were employed to study the timing and climate of glacial/interglacial transitions (Lachniet et al., 2014; Winograd et al., 1992) as well as Heinrich events of the late Pleistocene. Several speleothem δ18O records from Western Europe (Genty et al., 2003) and the Eastern Mediterranean (Unal-Imer et al., 2015) revealed Dansgaard-Oeschger (rapid climate fluctuations) oscillations and were used to precisely date these climate events (Fleitmann et al., 2009). Furthermore, speleothem δ18O records allow studying past changes of global Monsoon systems (Cruz et al., 2005; Partin et al., 2007; Wang et al., 2005) as far back as 640 thousand years (Cheng et al., 2016). Lately new efforts are undertaken by the speleothem community to map the speleothem landscape in space and time to identify the current status of speleothem-based paleoclimate reconstructions globally.

You can learn more here: http://www.pages-igbp.org/ini/wg/sisal/intro

Edited by Célia Sapart

References
 • Cheng et al., 2016, Nature 534, 640-646.
 • Cruz et al., 2005, Nature 434, 63-66.
 • Fairchild & Baker, 2012,  John Wiley & Sons, Ltd, Chichester, UK.
 • Fleitmann et al., 2009, Geophysical Research Letters 36.
 • Lachniet et al., 2009, Quaternary Science Reviews, 28(5), 412-432.
 • Lachniet et al., 2014, Nature Communications 5, 8.
 • Genty et al., 2003, Nature, 421(6925), 833.
 • Partin et al., 2014, Pages Magazine, 22(1), 22-23.
 • Ünal-İmer et al., 2015, Scientific Reports, 5, 13560.
 • Wang et al, 2005, Science 308, 854-857.
 • Winograd et al., 1992, Science (New York, N.Y.) 258, 255-260.