CR
Cryospheric Sciences

# snow

## An interview with… Marie Dumont

Snow! Here, Marie is spreading mineral dust on natural snow to investigate how this will change snow evolution (Col du Lautaret, France) [Credit : Maxim Lamare]

This week, we are interviewing Dr Marie Dumont. At the European Geosciences Union (EGU) general assembly in 2019, Marie was awarded the Arne Richter Award for Outstanding Early Career Scientist. Marie is currently a research team leader and deputy scientific director for the Snow Research Centre (part of Centre National de Recherches Meteorologiques, Météo-France & Le Centre national de la Recherche Scientifique [CNRS]) in France. Here, we ask her questions to find out a little more about the snow scientist.

Let’s start off with an easy question: what is it that you work on?

My researches are about the optical properties of snow, aka as the color of snow for the visible wavelengths. The “color” of snow is both cause and an effect of the snow cover evolution, it controls a large part of the melt rate and triggers potent climate feedbacks. I am working on how to measure and model the optical properties of snow at differences length scales and how to use this knowledge to better predict the evolution of the snow cover, in the past, now and in the future.

Did you always know you wanted to be a scientist?

Tricky question! Maybe, I knew deep down inside of me. It popped up quite naturally in my career. I hesitated for a while between mountain sports and science, and for some reason (maybe education, maybe something else) I ended up with one being my job and the other being my hobby, so I am quite lucky!

What is it about snow that has inspired you (and prompted four uses of ‘snow’ in your twitter handle)?

Snow snow snow …
Snow is beauty and fairy-like, snow is complex and simple at the same time. To me, it makes everything look great and perfect. As far as I remember, I have always been fascinated by snow. It calms me down and makes me feel incredibly good and peaceful. Maybe, it has also something to do with the fact that snow is ephemeral and somehow bound to melt and disappear and also that it’s changing/evolving continuously, it’s never the same, never boring.

Jon Snow or actual snow?

Jon Snow cause “I know nuthin’”
Jon Snow, except in season 8 …**spoiler alert**.
Kidding … both. I was really happy to see that a worldwide success like Game of Thrones was using snow and winter as part of the (scary) story.  In Game of Thrones, everyone is worrying that the world would end with winter coming. In reality, it was more the contrary. Naively, it made me happy to live in the fiction whilst winter was coming: it somehow distracted me from my sad thoughts on climate change and snow disappearance.

What worries you more: giving an award lecture at EGU, or panicking that you’ve left your tap running once you’ve left for fieldwork?

Giving an award lecture at EGU and knowing that I left the tap running when I left home for the conference… just kidding…. I think I am at bit of a scatterbrain, so I am quite used to leaving home with the tap running, losing my keys, my visa card and my passport. I don’t worry too much about that kind of thing anymore, it’s part of me and I am used to it.
On the contrary, I am not used to giving award lectures at all, so it worried me a lot, really a lot! I thought about it for quite a long time before EGU this year and the thing that worries me the most besides being in the limelight is the fact that I could possibly disappoint people that pushed me to get there and thus put their trust in me.

Marie received her award at the EGU2019 General Assembly in April 2019 [Credit: Olaf Eisen].

You’ve been very successful in both grant funding and winning awards, but what about times of less success? Do you have advice for any Early Career Scientists who’ve recently been rejected?

Usually only success is publicly reported. As anyone, I had, have and will have time of less success: rejected papers, rejected proposals, bad meetings, fully unsuccessful ideas, errors and conflicts with colleagues. I think I learnt, at least equally if not more, from errors and rejection than from success.
Advice? I’m not sure I am the right person to be giving any. This is a bit cliché but: keep trying, be passionate, be open to others, listen to them, listen to their comments and even when they are criticisms.

What do you crave/miss most when in remote locations?

My kids, friends and family, and after a few weeks a hot shower.

Do your kids have an interest in following in your footsteps (Marie is a mother of twins)?

Don’t know 😉 they are five years old! I brought them to one of my favourite field sites when they were two and taught them how to do a snow pit profile. For a while, they thought my job was about tasting snow J I am not really interested in the fact that they follow my footsteps or not. I just want, if I am able to do it, to show them how nature, wild places, and snow are beautiful and I think (ask me again in 10 years) that I would be happy if they are able to find their own passion about something and live it.

They could be the youngest early career scientists in the field of snow research! Do you think science has made advances in supporting women and parents in science? Are there still more things we can work on?

I am always a bit “torn” by this kind of question. On one hand, I think there has been a lot of advances in supporting parents and women in science, and I benefited from that a really a lot and it’s great!
On the other hand, in the push to promote male/female equality, I am always a bit puzzled by the emphasis that is put on supporting women only. There is something contradictory in this.
I think maybe it would make sense not to underline the differences too much. Getting funding, awards, sitting on committees is not all about quota, it should be mainly about skills. I am not at all saying that women, parents and other minorities should not be encouraged and offered new possibilities, as this is happening and is really great. However, there is a weight from history (more men than women in some science topics) that can’t disappear immediately and to some extent, I think pushing women only for quotas is harming the gender equality. Some women (I am part of them) may think they are successful only because of a quota. For example, I have encountered this argument:
XX : “Can you be part of this committee? Can you chair this or that?”
Me : “Why are you asking me ?”
XX: “Because you are a woman …”
Situations like this are frequent and in fact, it can make me quite angry.

You regularly participate and organise summer schools. Do you enjoy teaching? Do you have any advice for someone who might want to start teaching?

Not summer schools, winter schools of course!
I enjoy teaching but it’s also not a large part of my working time and I don’t have a huge experience in teaching. I enjoy teaching because I like sharing with students, learning about them, about their opinion … Advice? Same as above: listen to the students: as kids they teach you as much as you teach them, try to be funny and convincing!

As you spend lots of time in cold places for your work, do you prefer hot/beach holidays or do you still holiday in colder places?

Before having kids, it was really only about cold/mountain places. Now that I am getting older, I do also appreciate hot/beach holidays as long as I can climb or do some sports and that the places are wild and beautiful.

Day to day, what does being a scientist look like?

Coffee, taking kids to school, cycling to work, meetings (I need another coffee), emails, reviews, proposal writing, abstract writing (promising work that I know I will never be able to do before the conference), debugging some programs, discussing ideas with colleagues and students, ticking 2 things on my to-do list and adding 7 new items, trying to fit in two hours of pure science, asking for deadline extensions, meetings again, cycling back home… something like that.

She might look happy but digging snow pits is hard work! Snow pits are often dug to allow scientists to look at the change in snow properties with depth (Col du Lautaret, France) [Credit: François Tuzet].

That sounds busy! And on really cool, awesome-science days, what does being a scientist look like?

Top 10 awesome-science days/moments (with no preference):

• Field days (even the unsuccessful days and during bad weather)
• Sharing ideas and debating with colleagues/students when the understanding is beyond words
• Passionate science/equation discussions in weird places (carparks, planes, trains, …)
• Exciting new lab measurements that we still don’t know what they are useful for
• Friday beers when the discussion oscillates between what happened during the past week and what the plans for the weekend are
• Making at least one person laugh or smile in a conference talk with a nerdy joke
• Finally getting the figure that demonstrates the hypothesis we were convinced about for a while and realizing a few hours after that there was a bug in the plot routine.
• Finally finding the bug I was looking for after two weeks
• Working as a team
• Making nice figures with nice colours

Fieldwork is a regular part of Marie’s scientific career. Here she is doing spectral albedo measurements with her PhD student, François Tuzet in Col du Lautaret, France. This instrument was developped by Laurent Arnaud and Ghislain Picard (IGE, Grenoble, France) [Credit: Mark Flanner].

We always love a nerdy science joke! What might be the next big break-through in your field? (E.g higher resolution satellite data or a new model or method of observing etc).

The next paper from my student 😉 kidding of course!
I think it’s a combination of the 3 points you mentioned.  On one hand, temporal and spatial resolution of satellite data are getting better and better. For instance, the Sentinel satellites provide us unprecedented means to monitor the state of the snow cover. On the other hand, new observing methods (such as new instruments enabling observations of the snow properties at the microns/millimiters scales) provide new insights on snow evolution (in the lab and in the field) and snow physics that could be implemented in new snow models. So my vision, probably quite biased by what I currently plan to develop, is that a big break-through in snow science can probably be reached by developing modelling-assimilation systems that combine the most advanced knowledge of snow physics and the wealth of high resolution satellite data.

Model, satellite data or in-situ observations, you can only do one for the rest of time… which one?

Sorry, I can’t choose!

Ooo, we will let you off then. Afterall, science is about using the best techniques and data available. Thank you so much for chatting with us Marie!

Interviewed and edited by Jenny Turton

Dr Marie Dumont is a snow scientist at the Snow Research Centre in the Centre National de Recherches Meteorologiques (Météo-France & CNRS). This unit is also associated to the  Observatoire des Sciences de l’Univers de Grenoble – OSUG and  to Univ. Grenoble Alpes in France. Her research focuses on remote sensing and observations of optical snow properties, and uses a range of methods including data assimilation of observations into models and laboratory work. She tweets from @mpneige.

## Image of the Week – Life in blooming melting snow

Melting snowfields in a forested catchment of glacial lake in Šumava (mid-April), the Czech Republic [Credit: Lenka Procházková]

The new snow melting season has just started in the mountains of Europe and will last, in many alpine places, until the end of June. Weather in the middle of April is changeable. In the last few days sub-zero air temperatures have prevailed in the mountains during the day. In a frame of an international research project, me (Charles University) and Daniel Remias (Applied University Upper Austria), are both packing warm winter clothes as well as all the research equipment necessary for a new field mission: the aims are to find blooming spots of snow algae and to collect it for analyses. Upon our arrival in Šumava, a surprising but wonderful sunny day welcomes the expedition and we regret not taking the sun cream with us. While we are walking on still-compact partly frozen snowfields, our heads feel that they are exposed to hot summer.

## Snow blooms – what do they look like?

Red snow colouration at nearly all ice-covered parts of a high-alpine glacial lake (mid-June), High Tatras (Slovakia). Detailed view of red snow after harvest [Credit: Daniel Remias and Lenka Procházková, see study Procházková et al. 2018a]

Snow blooms – see the figure above – can be found in polar and alpine regions worldwide. Availability of liquid water is a key factor for the development of a snow algae population. In our experience, only wet and slowly melting snowfields are suitable.  This colourful phenomenon can appear in different colour shades, as green, yellow, pink, orange or blood-red (Procházková et al., 2018a). Snow blooms are currently a focus of an increasing number of studies because of their significant effects on albedo reduction and subsequent acceleration of snow and ice melting.

## Why are they colourful?

A few representatives of microalgae forming blooming snow – a coloured frame of each of these species corresponds with a colour of blooming snowfields [Credit: Lenka Procházková and Daniel Remias]

The macroscopic blooms are caused by microalgae of a cell size ranging from ~5 µm up to ~100 µm. During the melting season, cells live in a water film microhabitat surrounding large snow grains. The main genera that form these blooms are Chloromonas, Sanguina and Chlainomonas, each associated with a specific bloom color (see the figure above).  A massive population development of golden algae can also occur.

## When in the season do blooms occur?

Typical seasonal life cycle of a snow alga (Chloromonas nivalis), based on observation over many seasons in European Alps [Figure modified with permission from Sattler et al. 2010]

I would like to reveal a few secrets of snow algae.
The first strategy represents their seasonal life cycle. At the beginning the season in late April, one can hardly see any snow colouration. Snow algae from the previous seasons are lying at the interface between snow and soil in a resistant stage (called cyst). Snow is starting to melt slowly, and the cysts recognize the availability of liquid water and germinate. Flagellates are released and migrate upwards to the sub-surface layers, where they mate. With proceeding melting the cysts are accumulated and exposed at the snow surface. After total snowmelt these resistant stages should survive over summer in soil or at bare rock, where they can be subject to long-distance transport by wind.

## The red colour of snow is caused by astaxanthin

A cross-section of a typical snow algal cyst, Chloromonas nivalis-like species, with abundant lipid bodies (“L”) with astaxanthin and plastids (“P”) [transmission electron microscope, credit: Lenka Procházková]

The next strategy of snow algae is an accumulation of the red pigment astaxanthin during their maturation, which has many benefits to life of these microorganisms. For example, astaxanthin is a powerful antioxidant, and its synthesis is not limited by the supply of nitrogen.
Another big advantage of astaxanthin is its protective action against excessive visible and harmful ultraviolet irradiation which are characteristic for snow surfaces in alpine and polar regions. This “sunscreen” effect of astaxanthin – which has maximum absorbance in the visible light region and also a significant capability of UV protection – is supported by the algae’s clever intracellular arrangement (shown in the figure above), namely that sensitive compartments of the algae, like chloroplast or nucleus, are located in the central part, whereas lipid bodies, which accumulate the astaxanthin, are in the periphery.

## Our mission

Sequence-related sampling in Lower Tauern, Austria. Checking of a qualitative composition of a sampled spot using light microscope already in field. [Credit: Linda Nedbalová]

Do you wonder why we explore the physiology and biodiversity of snow algae? Because these extremophilic organisms cope with high ultraviolet radiation, repeated freeze-thaw cycles, desiccation, mechanical abrasion, limited nutrients and short season and are well adapted to it! Because of their ability to adapt to these extreme conditions, pigments of snow algae (as the astaxanthin presented above) are even used as biomarkers to detect life on Mars! Moreover, these microalgae are essential primary producers in such an extreme ecosystem, where phototrophic life is restricted to a few specialised organisms. For instance, they provide a basic ecosystem for snow bacteria, fungi and insects. Snow algae communities play an important role in supraglacial and periglacial snow food webs and supply nutrients that will be delivered throughout the glacial ecosystem.

## Further reading

Edited by Jenny Turton

Lenka Procházková is a PhD Student at the Charles University, Prague, the Czech Republic. She investigates biodiversity and ecophysiology of snow algae. Her favourite algal group is in her focus in a lab as well as in field samplings in the European Alps, High Tatras, Krkonoše, Šumava and Svalbard. Contact Email:  lenkacerven@gmail.com

## Image of the Week — Orange is the new white

Figure 1. True color composite of a Sentinel-2 image showing the dust plume off the coast of Libya on 22-Mar-2018 (see also on the ESA website) [Credit: processed by S. Gascoin]

On 22 March 2018, large amounts of Saharan dust were blown off the Libyan coast to be further deposited in the Mediterranean, turning the usually white snow-capped Mountains of Turkey, Romania and even Caucasus into Martian landscapes.  As many people were struck by this peculiar color of the snow, they started documenting this event on social media using the “#orangesnow hashtag”. Instagram and twitter are fun, but satellite remote sensing is more convenient to use to track the orange snow across mountain ranges. In this new image of the week, we explore dusty snow with the Sentinel-2 satellites…

A post shared by Alina Smurygina (@sinyaya_ptiza) on

## Sentinel-2: a great tool for observing dust deposition

Sentinel-2 is a satellite mission of the Copernicus programme and consists of two twin satellites (Sentinel-2A and 2B). Although the main application of Sentinel-2 is crop monitoring, it is also particularly well suited for characterizing the effect of dust deposition on the snowy mountains because:

1. Sentinel-2A and 2B satellites provide high-resolution images with a pixel size of 10 m to 20 m (depending on the spectral band), which enables to detect dust on snow at the scale of hillslopes.
2. Sentinel-2 has a high revisit capacity of 5 days which increases the probability to capture cloud-free  images shortly after the dust deposition.
3. Sentinel-2 has many spectral bands in the visible and near infrared region of the light spectrum, making easy to separate the effect of dust on snow reflectance — i.e. the proportion of light reflected by snow — from other effects due to snow evolution. The dust particles mostly reduce snow reflectance in the visible, while coarsening of the snow by metamorphism (i.e. the change of microstructure due to transport of vapor at the micrometer scale) tends to reduce snow reflectance in the near infrared (Fig. 2).
4. Sentinel-2 radiometric observations have high dynamic range and are accurate and well calibrated (in contrast to some trendy miniature satellites), hence they can be used to retrieve accurate surface dust concentration, provided that the influence of the atmosphere and the topography on surface reflectance are removed.

Figure 2: Diffuse reflectance for different types of snowpack. These spectra were computed with 10 nm resolution using the TARTES model (Libois et al, 2013) using the following parameters: snowpack density: 300 kg/m3, thickness: 2 m, fine snow specific surface area (SSA): 40 m2/kg, coarse snow SSA: 20 m2/kg, dust content: 100 μg/g. The optical properties of the dust are those of a sample of fine dust particles from Libya with a diameter of 2.5 μm or less (PM2.5) (Caponi et al, 2017). The Sentinel-2 spectral bands are indicated in grey. [Credit: S. Gascoin]

## Dust on snow from Turkey to Spain

The region of Mount Artos in the Armenian Highlands (Turkey) was one of the first mountains to be imaged by Sentinel-2 after the dust event. Actually Sentinel-2 even captured the dust aloft on March 23, before its deposition (Fig. 3)

Figure 3: Time series of three Sentinel-2 images near Mount Artos in Turkey (true color composites of level 1C images, i.e. orthorectified products, without atmospheric correction). [Credit: Contains modified Copernicus Sentinel data, processed by S. Gascoin]

Later in April another storm from the Sahara brought large amounts of dust in southwestern Europe.

Figure 4: Sentinel-2 images of the Sierra Nevada in Spain (true color composites of level 1C images). [Credit: Contains modified Copernicus Sentinel data, processed by S. Gascoin]

This example in the spanish Sierra Nevada nicely illustrates the value of the Sentinel-2 mission since both images were captured only 5 days apart. The high resolution of Sentinel-2 is also important given the topographic variability of this mountain range. This is how it looks in MODIS images, having a 250 m resolution.

Figure 5: MODIS Terra (19) and Aqua (24) images of the Sierra Nevada in Spain. True Color composites of MODIS corrected reflectance. [Credit: NASA, processed by S. Gascoin]

Sentinel-2 satellites enable to track the small-scale variability of the dust concentration in surface snow, even at the scale of the ski runs as shown in Fig. 6.

Figure 6: Comparison of a true color Sentinel-2 image and a photograph of the Pradollano ski resort, Sierra Nevada. [Credit: photograph taken by J. Herrero / Contains modified Copernicus Sentinel data, processed by S. Gascoin]

A current limitation of Sentinel-2, however, is the relative shortness of the observation time series. Sentinel-2A was only launched in 2015 and Sentinel-2B in 2017. With three entire snow seasons, we can just start looking at interannual variability. An example in the Prokletije mountains in Albania is shown in Fig. 7.

Figure 7. Sentinel-2 images of the Prokletije mountains in Albania (true color composites of level 1C images) [Credit: Contains modified Copernicus Sentinel data, processed by S. Gascoin]

These images suggest that the dust event of March 2018 was not exceptional in this region, as 2016 also highlights a similar event. The Sentinel-2 archive will keep growing for many years since the EU Commission seems determined to support the continuity and development of Copernicus programme in the next decades. In the meantime to study the interannual variability the best option is to exploit the long-term records from other satellites like MODIS or Landsat.

## Beyond the color of snow, the water resource

Dust on snow is important for water resource management since dust increases the amount of solar energy absorbed by the snowpack, thereby accelerating the melt. A recent study showed that dust controls springtime river flow in the Western USA (Painter et al, 2018).

“It almost doesn’t matter how warm the spring is, it really just matters how dark the snow is.”

said snow hydrologist Jeff Deems in an interview about this study in Science Magazine. Little is known about how this applies to Europe…

## Further reading

Edited by Sophie Berger

Simon Gascoin is a CNRS researcher at Centre d’Etudes Spatiales de la Biosphère (CESBIO), in Toulouse. He obtained a PhD in hydrology from Sorbonne University in Paris and did a postdoc on snow and glacier hydrology at the Centro de Estudios Avanzados en Zonas Áridas (CEAZA) in Chile. His research is now focusing on the application of satellite remote sensing to snow hydrology. He tweets here and blog here.

Marie Dumont is a researcher, leading the snow processes, observations and modelling research team at the snow study centre (CNRM/CEN, Grenoble, France). Her research focuses on snow evolution mostly in alpine region using numerical modelling and optical remote sensing.

Ghislain Picard is a lecturer working at the Institute of Geosciences and Environment at the University Grenoble Alpes, in the climate and ice-sheets research group. His research focuses on snow evolution in polar regions in the context of climate change. Optical and microwave remote sensing is one of its main tools.

## Image of the week – Skiing, a myth for our grandchildren?

Ski or water ski? Carnival season is typically when many drive straight to the mountains to indulge in their favorite winter sport. However, by the end of the century, models seem to predict a very different future for Carnival, with a drastic reduction in the number of snow days we get per year. This could render winter skiing something of the past, a bedtime story we tell our grandchildren at night…

Christoph Marty and colleagues investigated two Swiss regions reputed for their great skiing resorts and show that the number of snow days (defined as a day with at least 5 cm of snow on the ground) could go down to zero by 2100, if fuel emissions and economic growth continue at present-day levels, and this scenario is less dramatic than the IPCC’s most pessimistic climate change scenario (Marty et al., 2017). They show that temperature change will have the strongest influence on snow cover. Using snow depth as representative for snow volume, they predict that snow depth maxima will all be lower than today’s except for snow at elevations of 3000 m and higher. This implies that even industrially-sized stations like Avoriaz in the French Alps, with a top elevation of 2466 m, will soon suffer from very short ski seasons.

Marty et al. (2017) predict a 70% reduction in total snow volume by 2100 for the two Swiss regions, with no snow left for elevations below 500 m and only 50% snow volume left above 3000 m. Only in an intervention-type scenario where global temperatures are restricted to a warming of 2ºC since the pre-industrial period, can we expect snow reduction to be limited to 30% after the middle of the century.

Recent work by Raftery et al (2017) shows that a 2ºC warming threshold is likely beyond our reach, however limiting global temperature rise, even above the 2ºC target, could help stabilize snow volume loss over the next century. We hold our future in our hands!

Further reading/references

• Marty, C., Schlögl, S., Bavay, M. and Lehning, M., 2017. How much can we save? Impact of different emission scenarios on future snow cover in the Alps. The Cryosphere, 11(1), p.517.
• Raftery, A.E., Zimmer, A., Frierson, D.M., Startz, R. and Liu, P., 2017. Less than 2 C warming by 2100 unlikely. Nature Climate Change, 7(9), p.637.
• Less snow and a shorter ski season in the Alps | EGU Press release

Edited by Sophie Berger

Marie Cavitte just finished her PhD at the University of Texas at Austin, Institute for Geophysics (USA) where she studied the paleo history of East Antarctica’s interior using airborne radar isochrone data. She is involved in the Beyond EPICA Oldest Ice European project to recover 1.5 million-year-old ice. She tweets as @mariecavitte.

## Image of the week – How hard can it be to melt a pile of ice?!

Snow, sub-zero temperatures for several days, and then back to long grey days of near-constant rain. A normal winter week in Gothenburg, south-west Sweden. Yet as I walk home in the evening, I can’t help but notice that piles of ice have survived. Using the equations that I normally need to investigate the demise of Greenland glaciers, I want to know: how hard can it be to melt this pile of ice by my door? In the image of this week, we will do the simplified maths to calculate this.

## Why should the ice melt faster when it rains?

The icy piles of snow are made of frozen freshwater. They will melt if they are in contact with a medium that is above their freezing temperature (0°C); in this case either the ambient air or the liquid rainwater.

How fast they will melt depends on the heat content of this medium. Bear with me now – maths is coming! The heat content of the medium per area of ice, $Q$, is a function of the density $\rho$ and specific heat capacity $c$ of the medium. Put it simply, the heat capacity is a measure of by how much something will warm when a certain amount of energy is added to it. $Q$ also depends on the temperature $T$ of the medium over the thickness $H$ of the boundary layer i.e. the thickness of the rain or air layer that directly impacts the ice.

Assuming that I have not scared you away yet, here comes the equation:

$Q = \rho c \int_{ice}^{H} T dz$

For liquid water (in this article, the rain): $\rho_{rain} \approx 1000 \: kg \: m^{-3}$, $c_{rain} \approx 3.9 \: kJ \: kg^{-1} \: K^{-1}$. For the ambient air: $\rho_{air} \approx 1.2 \: kg \: m^{-3}$, $c_{air} \approx 1.0 \: kJ \: kg^{-1} \: K^{-1}$. So we can plug those values into our equation to obtain the heat content $Q$ of the rain and of the air. We can consider the same temperature over the same $H$ (e.g. Byers et al., 1949), and hence we get $Q_{rain} \approx 3250 Q_{air}$.

Stepping away from the maths for a moment, this result means that the heat contained in the rain is more than 3000 times that of the ambient air. Reformulating, on a rainy day, the ice is exposed to 3000 times more heat than on a dry day!

The calculations have obviously been simplified. The thickness $H$ of the boundary layer is larger for the atmosphere than for the rain, i.e. larger than just a rain drop. At the same time, the rain does not act on the ice solely by bringing heat to it (this is the thermic energy), but also acts mechanically (kinematic energy): the rain falls on the ice and digs through it. For the sake of this blogpost however, we will keep it simple and concentrate on the thermic energy of the rain.

## How long will it take for the rain to melt this pile of ice then?

Promise, this will be the last equation of this blogpost! Reformulating the question, what is the melt rate of that ice? Be it for a high latitude glacier or a sad pile of snow on the side of a road, the melt rate $F_{melt}$ is the ratio of the heat flux from the rain $F_{Qrain}$ (or any other medium) over the heat needed to melt the ice. It indicates whether the rain brings enough heat to the ice surface to melt it, or whether the ice hardly feels it:

$F_{melt} = \frac{F_{Qrain}}{\rho_{ice}(L+c_{ice}\Delta T)}$

More parameters are involved

• $\rho_{ice} = 917 \: kg \: m^{-3}$ the density of the ice;
• $L = 335 \: kJ \: kg^{-1}$ the latent heat of fusion, defined as how much energy is needed to turn one kilogram of solid water into liquid water;
• $c_{ice} = 2.0 \: kJ \: kg^{-1} \: K^{-1}$ the heat capacity of the ice (see previous paragraph);
• $\Delta T$ the difference between the freezing temperature (0°C) and that of the interior of the ice (usually taken as -20°C).

But what is $F_{Qrain}$ I am glad you ask! This heat flux , i.e. $Q_{rain}/time$, is crucial: it not only indicates how much heat your medium has, but also how fast it brings it to the ice. After all, it does not matter whether you are really hot if you stay away from your target. I actually lied to you, here comes the final equation, defining the heat flux:

$F_{Qrain} = \rho_{rain}c_{rain}T_{rain}P$

We can consider that $T_{rain} \approx T_{air}$. We already gave $\rho_{rain}$ and $c_{rain}$ earlier. As for $P$, this is our precipitation, or how much water is falling on a surface over a certain time (given in mm/hour usually during weather bulletins). On 24th January 2018, as I was pondering why the ice had still not melted, my favourite weather forecast website indicated that $T_{air} = 5^{\circ}C$ (278.15 K) and $P = 1 \: mm/hour$.

Eventually putting all the numbers together, we obtain $F_{melt} \approx 3 \: mm/hour$. So that big pile on the picture that is about 1 m high will require constant rain for nearly 14 days – assuming that the temperature and precipitation do not change, and neglecting a lot of effects as already explained above. Or it would take just over one hour of the Wikipedia record rainfall of 300 mm/hour – but then ice would be the least of my worries.

The exact same equations apply to this small icy island, melted by the air and ocean [Credit: Monika Dragosics (distributed via imaggeo.egu.eu)]

In conclusion, liquid water contains a lot more heat than the air, but ice is very resilient. The mechanisms involved in melting ice are more complex than this simple calculation from only three equations, yet they are the same whether you are on fieldwork on an Antarctic ice shelf or just daydreaming on your way home.

### Other blogposts where ice melts…

Edited by Adam Bateson and Clara Burgard

## 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]

## 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

## Image of the Week – Let it snow, let it snow, let it snow…

Christmas is coming to town and in the Northern Hemisphere many of us are still dreaming of a white Christmas, “just like the ones we used to know”. But how likely is it that our dreams will come true?

## What is the definition of a White Christmas ?

Usually Christmas can be defined as a “White Christmas” if the ground is covered by snow on either Christmas Eve or Christmas Day depending on local traditions. If you believe Christmas movies, it seems like Christmas was accompanied by snow much more often in the past than today! But is this really the case, or is it just the “Hollywood” version of Christmas? According to the UK Met Office White Christmases were more likely in the past. Due to climate change, average global temperatures are higher, which in many places reduces the chance of a White Christmas. However, the chances of a White Christmas also depend strongly on where you live…

## Living in Western or Southern Europe, the Southern US or the Pacific coast of the US? Unlucky you!

Not too surprisingly, most of the inhabitants of Portugal, Southern Spain, and Southern Italy have probably never experienced White Christmas in their hometown. Maybe more counter intuitively the probability of a White Christmas is also low in most of France, the Netherlands, Ireland, and the Southern UK! In the US, the probability of a White Christmas increases from South to North, except on the Pacific Coast, which has a very low probability of a White Christmas.

Probability of a White Christmas in Europe (snow on the ground on 25th of December), inferred from reanalysis data (ERA Interim from 1979-2015). Probability [in %] increases from white to blue [Credit : Clara Burgard, Maciej Miernecki. We thank the ECMWF for making the data available]

## What influences the probability of snowfall on Christmas?

The mean air temperature decreases with altitude and latitude, meaning that chances of a white Christmas increase the further North and at the higher you travel. However, coastal regions represent an exception. The air often has traveled over the ocean before reaching land. As the ocean is often warmer than the land surface in winter, the air in coastal regions is often too warm for snow to form. Additionally, in the Northern Hemisphere, ocean currents on the Western coast of the continents tend to carry warm water to high latitudes, while ocean currents on the Eastern coast tend to carry cold water to low latitudes. The probability of snowfall is therefore even lower in Western coastal regions (e.g. Pacific coast of the US, Atlantic coast of Europe).

## Don’t despair !

If you want to increase your chances of experiencing a White Christmas, you have three solutions:

1. You already live in an area with high probability of White Christmas (lucky you!) – Sit tight and do a “snow dance”, here is one suggestion that we have heard works well:

2. Travel or move to one of these 10 suggested destinations (e.g. St. Moritz, Swizerland)

Frozen Lake St. Moritz in Winter 2013 [Credit: Wikimedia Commons]

3. Build your own snow with this simple recipe!

We hope that you find a satisfactory solution that makes you happy this Christmas. Otherwise, remember that snow is not the only thing that defines Christmas. Enjoy the relaxed time with family and friends and prepare yourself for the coming new year! If you find yourself at a loose end, then there is always the back catalogue of EGU Cryosphere Blog posts to read – and we guarantee a healthy dose of snow and ice can be found here.

So, this is it from the EGU Cryosphere blog team for 2016. See you in 2017 – after all, the snow must go on…

Further reading:

•  MetOffice website with interesting facts around White Christmas!

Edited by Emma Smith