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Cryospheric Sciences

albedo

Image of the Week – Bioalbedo: algae darken the Greenland Ice Sheet

Image of the Week – Bioalbedo: algae darken the Greenland Ice Sheet

Most of the energy that drives glacier melting comes directly from sunlight, with the amount of melting critically dependent on the amount of solar energy absorbed compared to that reflected back into the atmosphere. The amount of solar energy that is reflected by a surface without being absorbed is called the albedo. A low albedo surface absorbs more of the energy that hits it compared to a high albedo surface. Our Image of the Week shows patches of dark grey-brown algal blooms on the Greenland Ice Sheet, giving the surface a surprisingly low albedo.


The colour of ice

Clean ice and snow are among the most reflective natural materials on Earth’s surface making them important ‘coolers’ in Earth’s climate system. The term ‘albedo’ describes how effectively a material absorbs or reflects incoming solar energy – it is the ratio of downwelling light arriving at a surface to the amount of upwelling light leaving it. The albedo of fresh, clean snow can be as high as 90%, meaning that out of all the solar energy reaching the surface only 10% is absorbed. However, the albedo of ice and snow can vary widely. This is important because the albedo determines how much of the incoming solar energy is retained within the snow or ice and used to raise the temperature or drive melting. It therefore controls snow and ice energy balance to a large extent.

There are several reasons why the albedo of snow and ice can vary. First, once ice crystals begin to melt they lose their delicate structures that efficiently scatter light and develop rounded granular shapes. Meltwater generated by snow or ice melt fills the gaps between the grains, promoting forward scattering of light deeper into the ice, rather than scattering back towards the surface. This increases the distance travelled through media where absorption can occur, and therefore lowers the albedo as the light is less likely to escape the material after it enters. The more melt, the greater this effect. Second, other materials such as dust or rock debris can enter the snow or ice. These ‘impurities’ generally absorb light more effectively than the ice crystals themselves and therefore reduce the albedo. However, this depends upon their concentration, optical properties and proximity to the surface. Additionally, whether the impurities are inside or outside the ice crystals, where on the planet the material is and the time of day are also important.

Any impurity that darkens a mass of ice or snow increases the amount of solar energy absorbed compared to when the material is impurity-free. This means that impurities promote melting, which is in itself an albedo reducing process. Therefore, the impact of impurities on albedo is non-linear and greater than the direct effect of their absorption alone. There are many different impurities that commonly lower the albedo of ice and snow, including mineral dusts and black carbon (e.g. from fossil fuel combustion). However, there is also a growing literature on another form of impurity that darkens ice and snow on glaciers and ice sheets on both hemispheres: biological growth (also see this previous post). Algae are the primary biological albedo-reducers on ice and snow. Photosynthetic microalgae bloom on the surface where light is abundant, which provides them with energy that they use to turn carbon dioxide and water into sugars. This in turn provides food for other microorganisms. In doing so, they darken the ice surface simply because the algal cells are more effective absorbers than the ice crystals. However, as the algae become exposed to increasing light intensities, they produce pigments that act as sun shields, protecting their cellular machinery from the damaging effects of too much light. This effect enhances the biological darkening and increases the energy absorbed within the snow or ice.

Biological darkening

There are several distinct microbial habitats on glaciers and ice sheets. Snow algae are a feature of melting snowpacks that colour snow surfaces green early in the year and red later because prolonged exposure to sunlight causes them to produce red ‘sunscreen’ pigments (see this previous post). Their influence on snow albedo has yet to be determined, although they have been shown to change the amount of visible light reflected from the surface (Lutz et al., 2014) and in Antarctica they have been shown to influence light absorption at depth within the snowpack (Hodson et al., 2017). Some bacteria have been identified feeding upon the algae, and the algal blooms also provide food for red coloured ice worms. This is probably why, in ‘The History of Animals’, Aristotle wrongly attributed the red discoloration of patches of snow to red worms rather than pigmented algae!

Fig. 2: (a) Albedo for clean snow, bare ice and ice with an algal bloom measured on the Greenland Ice Sheet in July 2017. (b) Microscope image of melted surface ice from the Greenland ice sheet. The red oval shaped particles are ice algae and the angular, clear particles are mineral dust fragments. [Credit: A: J. Cook, B: C. Williamson]

On ice, a different species of algae exists in a thin liquid water film on the upper surface of melting ice crystals. These algae are also photosynthetic but are not bright green or red, but rather grey, brown or purple. They produce a purple pigment that acts as a UV shield that protects their delicate intracellular machinery from excessive light energy. The side effect of this is that the algae become very dark and have an albedo-lowering effect on the ice surface (see our Image of the Week). Ice with algae has a lower albedo than clean ice (Fig 2a) but, up to now, the magnitude of the biological darkening effect has not been quantified because of difficulties isolating algal darkening from that of mineral dusts, soot and the changing optical properties of the ice itself. This also limits our capability to map these algae using remote sensing. Samples of dark coloured ice examined under the microscope clearly show the presence of an algal community darkening the ice (Fig 2b).

In addition to surface-dwelling ice algae, microbial life exists in small pits known as cryoconite holes (see also this previous post). At the bottom of these holes exists a thin layer of granules comprising living microbial cells, dead cells, biogenic molecules, mineral fragments and soot. The organic matter in these granules is very dark, so they warm up when illuminated by the sun and melt into the ice. The relationship between cryoconite and ice surface albedo is complex because, although the cryoconite is dark, the hole geometry hides the granules beneath the ice surface.

Implications for the future of glaciers and ice sheets

The challenge facing scientists now is to quantify the bioalbedo effect by determining the optical properties of individual algal cells and remotely assessing their spatial coverage at the scale of entire glaciers and ice sheets. This will require new methods to be developed for detecting living cells from the air or space. Then, we must understand the factors controlling their growth, so we can predict biological darkening of ice in future climate scenarios. It is possible that algal coverage will increase as glaciers and ice sheets waste away because algae bloom where there is liquid melt water. Because of the darkening effect, an increasingly widespread algal ecosystem in a warming climate will accelerate the demise of its own habitat by enhancing glacier and ice sheet retreat.

Further reading

Edited by Scott Watson and Clara Burgard


Joseph Cook is a Postdoctoral Research Associate on NERC’s Black and Bloom project based at the University of Sheffield, UK where his remit is the measurement and modelling of surface albedo on the Greenland Ice Sheet. His background is in biotic-abiotic interactions on ice. He tweets as @tothepoles and blogs at http://tothepoles.wordpress.com. Contact Email: joe.cook@sheffield.ac.uk

Image of the Week – Fifty shades of snow

Image of the Week – Fifty shades of snow

When I think of snow, I tend to either think about the bright white ski slopes in the mountains or the large white areas in the Arctic. However, natural phenomena can lead to colorful snow. Our Image of the Week shows snow can be green! Snow can also turn orange, pinkish, grey and even yellow… But where do these different shades of snow come from?


White

The most common color of snow is white (see Fig. 2). Snow generally appears white when it is pure snow, which means that it is only an aggregate of ice and snow crystals. When sunlight meets the snow surface, all frequencies of the sunlight are reflected several times in different directions by the crystals, leading to a white color of the snowpack.

 

Fig. 2: Fresh powder snow, snow crystals [Credit: Introvert, Wikimedia Commons]

 

 

If other particles or organisms are present in the snow though, they can alter the color of the snow’s surface…

Green

Snow can obtain a green color if it is host to an algal bloom (see our Image of the Week). Depending on the wetness of the snow, sunlight conditions and nutrient availability, unicellular snow algae can develop and thrive on the snow. Although it is not clear exactly how fast snow algae grow, algae populations from temperate regions have been found to grow sixteen-fold in one day! As the algae population increases, the snow turns green as the algae reflect the green light back.

 

Red/Pink

The pink-red-colored snow, commonly called “watermelon snow”, can also be caused by snow algae (see Fig. 3). The snow algae responsible for the pink color are similar to the ones responsible for green color. However, these algae use pigments of red color to protect their cells from high sunlight and UV radiation damage during the summer. Just like how we use sunscreen to protect our skin! The red pigments come either from iron tannin compounds or, more commonly, from orange to red-pigmented lipids.

There is also another origin for pink snow: Penguin poo! Indeed, the krill they eat contain a lot of carotenoids that give their poo a red color.

Fig. 3: Watermelon snow streaks [Credit: Wikimedia Commons].

 

Yellow

Yellow snow is the result of a different process (and no, it is not from Penguin pee!). Fig. 4 shows the Sierra Nevada in Spain before and after dust transported from the Sahara settled down on the snow-covered mountain tops. The dust was lifted up from the Sahara desert and blown north before ending its trip in Spain.

Fig. 4: Snow-covered Sierra Nevadas (Spain) before and after a dust deposition event [Credit: modified from NASA’s Earth Observatory]

 

Do these colors have an influence on snow cover?

In all cases of colored snow, the snow surface is darker than before. The darker surface absorbs more sunlight than a white surface, which causes the snow to melt faster… Therefore, although it looks artistic, colored snow is not necessarily healthy for the snow itself…

 

So, if you don’t like winter because everything is boring and white, just think about the variety of snow colors and try to look out for these special types! 🙂

 

Further reading

Edited by David Rounce

Black Carbon: the dark side of warming in the Arctic

Black Carbon: the dark side of warming in the Arctic

When it comes to global warming, greenhouse gases – and more specifically CO2 – are the most often pointed out. Fewer people know however that tiny atmospheric particles called ‘black carbon’ also contribute to the current warming. This post presents a paper my colleague and I recently published in nature communications. Our study sheds more light into the chemical make-up of black carbon, passing through the Arctic.


Black Carbon warms the climate

 Figure 1: Global radiative forcing of CO2 (green) compared to black carbon (blue). The colored bars show the mean change in radiative forcing due to the concentration of CO2 and BC in the atmosphere. The estimated range for the expected radiative forcing is everything between the white lines, which show the 90% confidence interval. (Data according to Boucher et al. 2013 (IPCC 5th AR) and Bond et al. 2013). [Credit: Patrik Winiger]

Figure 1: Global radiative forcing of CO2 (green) compared to black carbon (blue). The colored bars show the mean change in radiative forcing due to the concentration of CO2 and BC in the atmosphere. The estimated range for the expected radiative forcing is everything between the white lines, which show the 90% confidence interval. (Data according to Boucher et al. 2013 (IPCC 5th AR) and Bond et al. 2013). [Credit: Patrik Winiger]

Black Carbon (BC) originates from incomplete combustion caused by either natural (e.g., wild fires) or human (e.g., diesel car emissions) activities. As the name suggests, BC is a dark particle which absorbs sunlight very efficiently. In scientific terms we call this a strong positive radiative forcing, which means that the presence of BC in the atmosphere is helping to heat the planet. Some estimates put its radiative forcing in second place, only after CO2 (Figure 1). The significant thing about BC is that it has a short atmospheric lifetime (days to weeks), meaning we could quickly avoid some climate warming by getting rid of its emissions. Currently global emissions are increasing year by year and on snow and ice, the dark particles have a longer lasting effect due to the freeze and thaw cycle, where BC can re-surface, before it is washed away. It is important however to note, that our main focus on emission reduction should target (fossil-fuel) CO2 emissions, because they will affect the climate long after (several centuries) they have been emitted.

Arctic amplification: strongest warming in the North Pole

The Arctic is warming faster than the rest of our planet. Back in 1896, the Swede Arrhenius, (better known for his works: in chemistry), calculated, that a change in atmospheric CO2 – which at that time was a good 100 ppm lower than today – would change the temperature at higher latitudes (towards the poles) more than at lower latitudes.

Figure 2: Observation based global surface temperature anomalies for Jan-Mar (2016) in °C with respect to a 1961-1990 base year. Credit: GISTEMP Team, 2016: GISS Surface Temperature Analysis (GISTEMP). NASA Goddard Institute for Space Studies. Dataset accessed 2016-10-15 at http://data.giss.nasa.gov/gistemp/ [Hansen et al., 2010].

Figure 2: Surface temperature anomalies (in °C) for Jan-Mar (2016) with respect to a 1961-1990 baseline. [ Credit: NASA — GISTEMP (accessed 2016-10-15) and Hansen et al., 2010].

The problem with his calculations – as accurate and impressive they might have been – was, that he ignored the earth’s geography and seemed unaware of the big heat capacity of the oceans. On the southern half of our planet there is a lot more water, which can take up more heat, as compared to the northern half with more land surface. Thus, in reality the latitudes on the southern hemisphere have not heated as much as their northern counterparts and this effect came to be known as Arctic amplification.

Dark particles on bright snow and ice

Figure 3: Welcome to the Greenland Ice Sheet everybody. Probably an extreme case of ice covered in cryoconite, captured in August 2014 [Credit: Jason Box, (LINK: http://darksnow.org/)].

Figure 3: Ice covered in cryoconite, Greenland Ice Sheet, in August 2014 [Credit: Jason Box — Dark Snow project].

Greenhouse gases and BC are not the only reasons for the increase in temperature change and earlier onset of the melting season in the Arctic. Besides BC, there are other ‘light absorbing impurities’ such as dust, microorganisms, or a mixture of all of the above, better known as cryoconite. They all absorb solar radiation and thus decrease the albedo – the amount of solar energy reflected back to space – of the underlying white surface. This starts a vicious cycle by which these impurities melt the snow or ice and eventually uncover the usually much darker surface (e.g., rock or open sea water), leading to more solar absorption and the cycle continues. The effect and composition of these impurities are currently intensively studied on the Greenland ice sheet (check out the Black and Bloom, as well as the Dark Snow projects).

 Black Carbon effect on climate is highly uncertain

One of the reasons for the high uncertainty of BC’s climate effects is the big range in effects it has (see white line on Figure 1), when it interacts with snow and ice (or clouds and the atmosphere).

Another source of uncertainty is probably the big estimated range in the global, and especially in the regional emissions of BC in the Arctic. For example, the emission inventory we work with (ECLIPSE), is based on international and national statistics that indicate how much of a certain fuel (diesel, coal, gas, wood, etc.) is used, and in which way it is used (vehicle sizes, machine type and age, operating conditions, etc.). These numbers can vary a lot. If we, for example, line up different emission inventories of man-made emissions (Figure 4), by comparing the two different fractions of BC (fossil fuels vs. biomass burning) at different latitudes, then we see that the closer we get to the North pole, the more these emission inventories disagree. And this is still ignoring atmospheric transport or emissions of natural sources, such as wildfires.

Computer models, necessary to calculate global climate change, are partly based on input from these emission inventories. Models used for the calculation of the transport of these tiny particles have vastly improved in recent years, but still struggle at accurately mimicking the seasonality or extent of the observed BC concentrations. To some extent this is also due to the range of parametrization in the model, mainly the lifetime of BC, including its removal from the atmosphere by wet scavenging (e.g., rain). So to better understand black carbon effects on climate, more model calculations are necessary, for which the emission inventory estimates need to be verified by observations.

Figure 4: Fraction biomass burning of BC (fbb) at different latitudes North, estimated by three different emission inventories. The green line shows the GAINS emission inventory, which was the precursor to the ECLIPSE inventory (Klimont et al. 2016) [Credit: Patrik Winiger]

Figure 4: Fraction biomass burning of BC (fbb) at different latitudes North, from three different emission inventories. The green line shows the GAINS emission inventory, which was the precursor to the ECLIPSE inventory (Klimont et al. 2016) [Credit: Patrik Winiger]

How do we trace the origin of black carbon?

This is where the science of my colleagues and me comes in. By looking at BC’s isotopic ratio of stable-carbon (12C/13C) and its radiocarbon (14C) content we were able to deduce information about the combustion sources (Figure 5).

Plants (trees) take up contemporary radiocarbon, naturally present in the atmosphere, by photosynthesis of atmospheric CO2. All living organisms have thus more or less the same relative amount of radiocarbon atoms, we talk of a similar isotopic fingerprint. BC from biomass (wood) burning thereby has a contemporary radiocarbon fingerprint.

When they die, organisms stop incorporating contemporary carbon and the radiocarbon atoms are left to decay. Radiocarbon atoms have a relative short (at least on geological time-scales) half-life of 5730 years, which means that fossils and consequentially BC from fossil fuels are completely depleted of radiocarbon. This is how the measured radiocarbon content of a BC sample gives us information on the relative contributions of fossil fuels vs. biomass burning.

The stable carbon isotopic ratio gives information on the type of combustion sources (liquid fossil fuels, coal, gas flaring or biomass burning). Depending on how a certain material is formed (e.g., geological formation of coal), it has a specific isotopic ratio (of 12C/13C), like a fingerprint. Sometimes isotopic fingerprints can be altered during transport (because of chemical reactions or physical processes like condensation and evaporation). However, BC particles are very resistant to reactions and change only very little. Hence, we expect to see the same fingerprints at the observation site and at the source, only that the isotopic signal at the observation site will be a mixture of different source fingerprints.

Figure 5/ Carbon isotopic signatures of different BC sources, summarized by E.N. Kirillova (2013).

Figure 5: Carbon isotopic signatures of different BC sources, summarized by E.N. Kirillova (2013). To give information about the isotopic fingerprint, the delta-notation is used (small delta for 12C/13C, and big delta for 12C/14C). The isotopic values show how much a certain sample is different, on a per mil scale, from an international agreed isotopic standard value (or ratio) for carbon isotopes. [Credit: fig 1 from  Kirillova (2013)]

Where does the black carbon in European Arctic come from?

In our study (Winiger et al, 2016), we observed the concentrations and isotopic sources of tiny particles in airborne BC for over a year, in the European Arctic (Abisko, Sweden), and eventually compared these observations to model results, using the freely available atmospheric transport model FLEXPART and emission inventories for natural and man-made BC emissions.

Seeing our results we were first of all surprised at how well the model agreed with our observations. We saw a clear seasonality of the BC concentrations, like it has been reported in the literature before, and the model was able to reproduce this. Elevated concentrations were found in the winter, which is sometimes referred to as Arctic haze. The combustion sources showed a strong seasonality as well. The radiocarbon data showed, that fossil fuel combustion dominated in the winter and (wood) biomass burning during the low BC-burden periods in the summer. With a combination of the stable isotope fingerprints and Bayesian statistics we further concluded, that the major fossil fuel emissions came from liquid fossil fuels (most likely diesel). The model predicted a vast majority of all these BC emissions to be of European origin. Hence, we concluded, that the European emissions in the model had to be well constrained and the model parametrization of BC lifetime and wet-scavenging had to be fairly accurate for the observed region and period. Our hope is now that our work will be implemented in future models of BC effects and taken into account for future BC mitigation scenarios.

Figure 6: This is an example from the model calculations, showing where the (man-made) BC came from in January 2012. Abisko's position is marked as a blue star. The darker (red) spots show sources of higher BC contribution. This winter example was among the three highest observed (in terms of BC concentration) and the sources were ~50% wood burning, ~20% liquid fossil fuels (diesel) and ~30% coal. Some of the darkest spots can clearly be attributed to European cities.

Figure 6: Example from the model calculations, showing where the (man-made) BC came from in January 2012. Abisko’s position is marked as a blue star. The darker (red) spots show sources of higher BC contribution. This winter example was among the three highest observed (in terms of BC concentration) and the sources were ~50% wood burning, ~20% liquid fossil fuels (diesel) and ~30% coal. Some of the darkest spots can clearly be attributed to European cities. [Credit: fig4b from Winiger et al (2016)]

References

  • Anderson, T. R., E. Hawkins, and P. D. Jones (2016), CO2, the greenhouse effect and global warming: from the pioneering work of Arrhenius and Callendar to today’s Earth System Models, Endeavour, in press, doi:10.1016/j.endeavour.2016.07.002.
  • Arrhenius, S. (1896), On the influence of carbonic acid in the air upon the temperature of the ground., Philos. Mag. J. Sci., 41(August), 239–276, doi:10.1080/14786449608620846.
  • Hansen, J., R. Ruedy, M. Sato, and K. Lo (2010), Global surface temperature change, Rev. Geophys., 48(4), RG4004, doi:10.1029/2010RG000345.
  • Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-880, in review, 2016.
  • Kirillova, Elena N. “Dual isotope (13C-14C) Studies of Water-Soluble Organic Carbon (WSOC) Aerosols in South and East Asia.” (2013). ISBN 978-91-7447-696-5 pp. 1-37
  • Winiger, P., Andersson, A., Eckhardt, S., Stohl, A., & Gustafsson, Ö. (2016). The sources of atmospheric black carbon at a European gateway to the Arctic. Nature Communications, 7.

Edited by Sophie Berger, Dasaraden Mauree and  Emma Smith
This is joint post with the Atmospheric Division , given the interdisciplinarity of the topic featured.


portraitPatrik Winiger is a PhD student at the Department of Environmental Science and Analytical Chemistry and the Bolin Centre for Climate Research, at Stockholm University. His research interest focuses on impact and mitigation of Short Lived Climate Pollutants and anthropogenic CO2 emissions. Currently he investigates the sources of black carbon aerosols in the Arctic. He tweets as @PatrikWiniger

 

Image of the week — The warming effect of the decline of Arctic Sea Ice

Image of the week — The warming effect of the decline of Arctic Sea Ice

One of the most dramatic signals of Earth’s recent warming has been the precipitous decline of the Arctic sea ice. While the sea-ice decline is in response to warming ocean and atmosphere, it also has an important feed-back on the climate itself.

Solar radiation and albedo

Earth’s main energy source is solar radiation. This solar radiation is either absorbed in the atmosphere or at the surface of the planet, or it is reflected back into space. The measure of how reflective a surface is is called its albedo. Sea ice, being white, has an extremely high albedo, compared to the ocean. Therefore when the sea ice declines, more solar radiation is absorbed by the planet, leading to more warming.

Shrinking sea ice decreases the albedo of the Arctic

Our image of the week shows a figure based on data presented in Pistone et al (2014), produced by the NASA/GSFC Scientific Visualization Studio. It shows how the declining Arctic sea ice has decreased the average albedo in the Arctic, with darker colors indicating a declining albedo and therefore warming of the Arctic Ocean. Based on satellite estimates of the sea-ice extent since 1979, the authors were able to constrain that the impact of the sea-ice retreat alone has led to an amount of global warming that is more than 1/4 as strong as the effect due to increased C02 in the atmosphere. 

An animation of the annual Arctic sea ice minimum with a graph overlay showing the area of the minimum sea ice in millions of square kilometres.(Credit: NASA/GSFC Scientific Visualization Studio)

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