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Atmospheric Sciences

Atmospheric Science

A brighter future for the Arctic

A brighter future for the Arctic

This is a follow-up from a previous publication. Recently, a new analysis of the impact of Black Carbon in the Arctic was conducted within a European Union Action.

“Difficulty in evaluating, or even discerning, a particular landscape is related to the distance a culture has traveled from its own ancestral landscape. As temperate-zone people, we have long been ill-disposed toward deserts and expanses of tundra and ice. They have been wastelands for us; historically we have not cared at all what happened in them or to them. I am inclined to think, however, that this landscape is able to expose in startling ways the complacency of our thoughts about land in general. Its unfamiliar rhythms point up the narrow impetuosity of Western schedules, by simply changing the basis of the length of the day. And the periodically frozen Arctic Ocean is at present an insurmountable impediment to timely shipping. This land, for some, is irritatingly and uncharacteristically uncooperative.”

            -Barry Lopez, Arctic Dreams, 1986


Study

Back in the 1980s the Arctic was a different place. It is one of the fastest changing regions of our planet and since then, Arctic sea ice volume has more than halved (Figure 1). Our study took place in the 2010s, when the Arctic moved into a new regime and sea ice volume showed unprecedented lows. In the last 3 years since our study ended this decline has just continued.

Figure 1: Satellite era (1979-2018) Arctic ice data. LEFT: Arctic sea ice volume, in 1000 km3 RIGHT: Normalized arctic sea ice extent. (Credit: Zachary Labe, Department of Earth System Science, The University of California, Irvine @ZLabe)

During 4 years, we collected small airborne particles at 5 different sites around the Arctic; 1 to 2 years per site. Later, we measured  the concentrations and isotopic sources of black carbon (BC) aerosols, a product of incomplete combustion of biomass and fossil fuels, and a subfraction of the total collected aerosol.

All living organisms have more or less the same relative amount of radiocarbon atoms. We call it a similar ‘isotopic fingerprint’. Through photosynthesis plants take up CO2. About 1 in 1012 CO2 molecules contains the naturally occurring (but unstable) radiocarbon atom (14C), which is formed high up in the atmosphere through solar radiation. Black carbon from biomass burning thereby has a contemporary radiocarbon fingerprint. When plants die, the radiocarbon atoms are left to decay, and no new radiocarbon is being built into the plant. Radiocarbon’s half-life is 5730 years, which means that fossils and consequentially soot from fossil fuels is completely depleted of radiocarbon.

For the same periods and sites of our observations (see Figure 2), we also simulated black carbon concentration and sources.

Figure 2: Observational sites of our study. Clockwise from top: Utqiaġvik (formerly known as Barrow, Alaska), Tiksi Observatory (Siberia), Zeppelin Observatory (Svalbard), Abisko (Sweden), and Alert (Canada).

This was done with an atmospheric transport model (FLEXPART), using emission inventory data for fossil and biofuels (ECLIPSE), and biomass burning (GFED) (see Figure 3). Emission inventories like ECLIPSE calculate emissions of air pollutants and greenhouse gases in a consistent framework. They rely on international and national statistics of the  amount of consumed energy sources for e.g., energy use, industrial production, and agricultural activities. GFED uses MODIS satellite measurements of daily burnt area. This is used – together with ’emission factors’ (i.e. amount of emitted species per consumed energy source unit) – to calculated emissions of several different gas and particle species. The details and methodologies have also been described in a previous EGU ASxCR blogpost.

Figure 3: Model setup used in our study. Anthropogenic emissions of BC are from IIASA’s ECLIPSE emission inventory and biomass burning (wild fire and agricultural fires) are from the Global Fire Emission Database (GFED). The atmospheric transport model itself is FLEXPART, developed by NILU in Norway.

Black carbon, a short live climate pollutant (SLCP), is the second or more likely third largest warming agent in the atmosphere after the greenhouse gases carbon dioxide and methane. Unlike the two gases, it is less clear how big the net warming effect of BC is. There are several open questions, that lead to the current uncertainty: 1. How much BC is exactly put into the atmosphere? 2. How long does it stay in the air and where is it located? 3. Where from and where to is it transported, and where and when is it deposited? 4. How does it affect the earths radiative balance by darkening snow and ice, and most importantly of all: how does it interact with clouds. We have a fair understanding of all these processes, but still, relatively large uncertainties remain to be resolved. Depending on how much BC is in the air and where it is located in the atmosphere, it can have different effects (e.g., strong warming, warming, or even cooling). And all these things need to be measured, and simulated correctly by computer models.

Current multi-model best estimates by the Arctic Monitoring and Assessment Programme say that BC leads to increases of Arctic surface temperature of 0.6°C (0.4°C from BC in the atmosphere and 0.2°C from BC in snow) based on their radiative forcing (see Figure 4).

Figure 3: Radiative forcing for all greenhouse gases (GHG), carbon dioxide (CO2), methane (CH4), and black carbon (BC). All numbers are for global estimates, except the last bar to the right, which is for the Arctic only. Data according to the IPCC 5th Assessment Report (2013), an extensive review on black carbon (Bond et al. 2013), and best estimates by the Arctic Monitoring Assessment Programme (AMAP 2015). Range of uncertainties (if available) are shown as white vertical line.

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. And reduction in these sources means reduction in soot as well, since soot is also a combustion product. Reduction that targets soot specifically can be achieved by installation of particulate filters (retrofitting of old engines and stringent standard for new vehicles), shifting to cleaner fuels, burning techniques, or introduction and enforcement of inspection and maintenance programs to assure compliance with already existing legislation.

It is recognized internationally that for effective implementation of the Paris Agreement (mitigation effort to hold the average global temperature well below 2°C relative to the preindustrial levels), mitigation measures of short live climate pollutants (such as BC and methane) need to be considered. As the Arctic environment is more sensitive to climate change, knowing exactly which origins (source types and regions) are contributing to black carbon in this part of the world is important for effective mitigation measures.

Source attributions of black carbon depend on the altitude where the aerosol is located at the time of measurement or modelling. Wildfires are known to contribute more at higher elevations during the fire seasons (Paris et al., 2009) than at the Arctic surface. Several of the global chemical models have already approximately predicted the proportion of source influence but their accuracy depends on the emissions input and performance of the model. Part of this problem is, that these models get input from emission inventories. These inventories tell the model where, when and how much black carbon is emitted, kind of like instructions from a cookbook.

But the different cook books don’t agree on the amount of black carbon that goes into our annual black carbon cake. Additionally, all the different cookbooks have different recipes for different years. If we take a best estimate of global black carbon emissions, our annual cake  has about the size (and weight; because of similar densities of limestone/granite and soot) of the great pyramid of Giza (7500 gigagrams). But the range of estimates vary immensely (2000-29000 gigagrams) (see Figure 5). And these numbers are only for man-made emissions (fossil fuels and biofuels) i.e. excluding wildfires and natural biomass burning. A recent multi-model analysis puts global annual BC fire emissions between 1000 and 6000 gigagrams. To correct these models and the emission inventories we rely on observational data to validate the model results.

Figure 5: Uncertainty in global annual BC emissions ranges from 2000 to 29000 Gg (according to Bond et al. 2013

The model set-up we used did really well in simulating soot concentrations. A bit less well in simulating fuel types (sources) – better for fossil fuels than biofuels and biomass burning. The model simulated that 90% of BC emissions (by mass) – reaching surface level – in the Arctic originated form countries north of 42°N.

In our isotope measurements, we found that black carbon sources had a strong seasonality, with high contributions of fossil fuels to black carbon in the winter (75%) and moderate (60%) in the summer. Black carbon concentrations where roughly four times higher in winter than in summer. Concentrations of black carbon at the different stations were also relatively different from each other. These surface level (<500m above sea level) Pan-Arctic results, based on our 14C method, were not very surprising. Few individual locations, as used in our latest study, have previously been published and had similar sources(e.g., Barrett et al., 2015. Winiger, et al, 2015, 2016). However, the sources in our study were relatively uniform for all stations and almost in seasonal sync with each other (high fossil winter, low fossil summer). This could have important implications for policy related questions.

Uniform sources could mean that mitigation measures could have a stronger impact, if the right sources are tackled at the right time, to keep the Arctic from becoming a small ice floe, not large enough to stand on. There could be brighter days ahead of us.

Edited by Dasaraden Mauree


Patrik Winiger is Research Manager at the ETH Zürich and guest researcher at the Department of Earth Sciences, Vrije Universiteit Amsterdam. His research interest focuses on sources and impact of natural and anthropogenic Short Lived Climate Pollutants and Greenhouse Gases. He tweets as @PatrikWiniger.

 

 

Water vapor isotopes: a never ending story!

Water vapor isotopes: a never ending story!

Water stables isotopes are commonly exploited in various types of archives for their information on past climate evolutions. Ice cores retrieved from polar ice sheets or high-altitude glaciers are probably the most famous type of climate archives. In ice cores, the message about past temperature variations is conserved in the ice, formed from the snow falls whose isotopic composition vary with the temperatures governing the snow crystals formation. However, deciphering the temperature variations from water isotopes is not always straightforward, as the temperature is not the only parameter which can have an imprint on the isotopic composition of the ice, but other variations like changes in origin of the moisture can also play a role. Water isotopic observations are useful tools to understand the water cycle, as the water masses keep in their isotopic composition a signal of the phase changes they have undergone. Many studies use complex atmospheric models representing the water isotopes to refine the analysis of paleoclimatic data. The same models are also used for future climate projections, a domain where large uncertainties are still linked to the prediction of the water cycle and the changes in precipitations. Water isotopes can be useful to benchmark such models and contribute to their improvement.

To better understand the processes affecting the water isotopic composition in the atmosphere, our group at the Alfred Wegener Institut in Germany has been focusing on the first step of the atmospheric water cycle: the evaporation at the oceanic surface. For this purpose, we have been continuously measuring the water vapour isotopic composition since summer 2015 directly above the ocean surface, on-board the german research ice breaker Polarstern (Figure 1).

Figure 1: The Polarstern ice breaker in the bay of Longyearbyen, Svalbard, in July 2015.

We measured humidity level, δ18O and δ2H (representing the variations of the amount of water isotopes, H218O and H2H16O, compared to the most abundant isotope H216O) and calculated the second order parameter deuterium excess, defined as d-excess = δ2H – 8.δ18O. Our observations, newly published in Nature Communications, extend over all latitudes in the Atlantic sector, from the North Pole up to the coast of Antarctica (Figure 2), and could therefore also be exploited for many projects involving water isotopes at any latitude around the whole Atlantic basin. They allowed us to experimentally explore the interactions between the atmospheric moisture and the open sea as well as the sea ice.

Figure 2: Location of water vapour isotopic observations recorded on board Polarstern, from 2015-06-29 to 2017-07-01

According to a commonly accepted theory proposed about 40 years ago (Merlivat and Jouzel, 1979), the meteorological conditions under which the oceanic evaporation takes place leave their fingerprint in the isotopic composition of the vapour. We have been able to test this theory on the field for the first time under such a large range of climatic conditions. Our observations indeed confirm the expected role of relative humidity and sea surface temperature in the isotopic composition of the evaporated flux. However, contrary to what was expected from this theory, our records reveal that the wind speed at which the evaporation takes place does not leaves its mark in the vapour isotopic composition above the oceans (Figure 3).

Figure 3: Theoretical effect of wind speed on the vapour isotopic signal d-excess, considering the Merlivat and Jouzel 1979 theory (left panel) compared to observations (right panel). Distinct distributions of d-excess against relative humidity at the sea surface are expected from the theory between low and high wind speeds (below or above 7 m/s, respectively orange and blue), but no difference is observed on the field.

In the sea ice covered areas of the polar oceans, the observations were showing highly different signals than above the open ocean. We have shown that an atmospheric model simulating the isotopic composition of water (ECHAM5-wiso) could at first not reproduce the intensity of these variations. We managed to identify the cause of this discrepancy, by adding a new source of humidity in the model. This model was already considering the sublimation of sea ice as a source of humidity. But so far, it was assuming that the sea ice was formed only from frozen oceanic water and therefore had the same isotopic composition as this oceanic water. However, the surface of the sea ice is also affected by snow falling on top of already formed sea ice. These snow falls having a totally different isotopic composition than the oceanic water, once integrated in the model as a new potential source of sublimation, they drastically changed the simulations of vapour isotopes in polar regions and the model now resolves our observations in these sectors much better (Figure 4).

Figure 4: Improvement of the simulated vapour isotopic signal (d-excess) by the isotope-enable atmospheric general circulation model ECHAM5-wiso in sea ice covered areas while considering the deposited snow as a sublimation source (ECHAMfinal, dark blue) compared to bare sea ice created from oceanic water only (ECHAMexp, orange).

Our observations have shown their ability to benchmark atmospheric models of atmospheric water cycle. They highlight different processes having significant consequences on the simulation of water isotopic composition in vapour and precipitation at the global scale which should be considered in all atmospheric water cycle modelling experiments. They contribute to better understanding the creation of the first water isotopic signal during oceanic evaporation. This is particularly important as the oceanic evaporation will later determine the isotopic signal found in subsequent precipitation. The interpretation of past climate archives originally formed from precipitation can therefore be significantly affected by these results.

Edited by Dasaraden Mauree

Jean-Louis Bonne is an atmospheric scientist at the Alfred Wegener Institut, Bremerhaven in Germany. He prepaed his PhD at the LSCE, Gif-sur-Yvette, France. His research aims at understanding the contributions of local and remote sources to locally observed atmospheric composition by their combination with atmospheric simulations. He has been working on the atmospheric components of the water and carbon cycles, exploiting present-day observations of greenhouse gases and water vapour isotopic compositions. His current project, ISOARC, is focusing on the identification of the moisture sources of the eastern-Arctic. His personal blog can be reached here.

The puzzle of high Arctic aerosols

The puzzle of high Arctic aerosols

Current Position: 86°24’ N, 13°29’E (17th September 2018)

The Arctic Ocean 2018 Expedition drifted for 33 days in the high Arctic and is now heading back south to Tromsø, Norway. With continuous aerosol observations, we hope to be able to add new pieces to the high Arctic aerosol puzzle to create a more complete picture that can help us to improve our understanding of the surface energy budget in the region.

Cruise track to the high Arctic with the 33 day drift period. (Credits: Ian Brooks)

In recent years, considerable efforts have been undertaken to study Arctic aerosol. However, there are many facets to Arctic aerosol so that different kinds of study designs are necessary to capture the full picture. Just to name a few efforts, during the International Polar Year in 2008, flight campaigns over the North American and western European Arctic studied the northward transport of pollution plumes in spring and summer time [1,2,3]. More survey-oriented flights (PAMARCMIP) have been carried out over several years and seasons [4] around the western Arctic coasts. The NETCARE campaigns [5] have studied summertime Canadian Arctic aerosol in the marginal ice zone. And the Arctic Monitoring and Assessment Programme (AMAP) has issued reports on the radiative forcing of anthropogenic aerosol in the Arctic [6,7].

These and many other studies have advanced our understanding of Arctic aerosol substantially. Since the 1950s we are aware of the Arctic Haze phenomenon that describes the accumulation of air pollution in the Arctic emitted from high latitude sources during winter and early spring. In these seasons, the Arctic atmosphere is very stratified, air masses are trapped under the so-called polar dome and atmospheric cleansing processes are minimal. In springtime, with sunlight, when the Arctic atmosphere becomes more dynamic, the Arctic Haze dissolves with air mass movement and precipitation. Then, long-range transport from the mid-latitudes can be a source of Arctic aerosol. This includes anthropogenic as well as forest fire emissions. The latest AMAP assessment report [6] has estimated that the direct radiative forcing of current global black and organic carbon as well as sulfur emissions leads to a total Arctic equilibrium surface temperature response of 0.35 °C. While black carbon has a warming effect, organic carbon and particulate sulfate cool. Hence, over the past decades the reductions in sulfur emissions from Europe and North America have led to less cooling from air pollution in the Arctic [8]. Currently, much effort is invested in understanding new Arctic emission sources that might contribute to the black carbon burden in the future, for example from oil and gas facilities or shipping [9, 10, 11].

These studies contribute to a more thorough understanding of direct radiative effects from anthropogenic aerosol and fire emissions transported to the Arctic. However, neither long-range transported aerosol nor emissions within the lower Arctic contribute substantially to the aerosol found in the boundary layer of the high Arctic [12]. These particles are emitted in locations with warmer temperatures and these air masses travel north along isentropes that rise in altitude the further north they go. The high Arctic boundary layer aerosol, however, is important because it modulates the radiative properties of the persistent Arctic low-level clouds that are decisive for the surface energy budget (see first Arctic Ocean blog in August 2018).

Currently, knowledge about sources and properties of high Arctic aerosol as well as their interactions with clouds is very limited, mainly because observations in the high Arctic are very rare. In principle, there are four main processes that shape the aerosol population in the high north: a) primary sea spray aerosol production from open water areas including open leads in the pack ice area, b) new particle formation, c) horizontal and vertical transport of natural and anthropogenic particles, and d) resuspension of particles from the snow and ice surface (snowflakes, frost flowers etc.). From previous studies, especially in the marginal ice zone and land-based Arctic observatories, we know that microbial emissions of dimethyl sulfide and volatile organic compounds are an important source of secondary aerosol species such as particulate sulfate or organics [13]. The marginal ice zone has also been identified as potential source region for new particle formation [14]. What is not known is to which degree these particles are transported further north. Several scavenging processes can occur during transport. These include coagulation of smaller particles to form larger particles, loss of smaller particles during cloud processing, precipitation of particles that acted as cloud condensation nuclei or ice nucleating particles, or sedimentation of large particles to the surface.

Further north in the pack ice, the biological activity is thought to be different compared to the marginal ice zone, because it is limited by the availability of nutrients and light under the ice. Hence, local natural emissions in the high Arctic are expected to be lower. Similarly, since open water areas are smaller, the contribution of primary marine aerosol is expected to be lower. In addition, the sources of compounds for new particle formation that far north are not very well researched.

To understand some of these sources and their relevance to cloud properties, an international team is currently measuring the aerosol chemical and microphysical properties in detail during the Arctic Ocean 2018 expedition on board the Swedish icebreaker Oden. It is the fifth expedition in a series of high Arctic field campaigns on the same icebreaker. Previous campaigns took place in 1991, 1996, 2001 and 2008 (see refs [15, 16, 17, 18] and references therein).

The picture below describes the various types of air inlets and cloud probes that are used to sample ambient aerosol particles and cloud droplets or ice crystals. A large suite of instrumentation is used to determine in high detail the particle number concentrations and size distribution of particles in the diameter range between 2 nm and 20 µm. Several aerosol mass spectrometers help us to identify the chemical composition of particles between 15 nm and 1 µm as well as the clusters and ions that contribute to new particle formation. Filter samples of particles smaller than 10 µm will allow a detailed determination of chemical components of coarse particles. They will also give a visual impression of the nature of particles through electron microscopy. Filter samples are also used for the determination of ice nucleation particles at different temperatures. Cloud condensation nuclei counters provide information on the ability of particles to form cloud droplets. A multi-parameter bioaerosol spectrometer measures the number, shape and fluorescence of particles. Further instruments such as black carbon and gas monitors help us to distinguish pristine air masses from long-range pollution transport as well as from the influence of the ship exhaust. We can distinguish and characterize the particle populations that do or do not influence low-level Arctic clouds and fogs in detail by using three different inlets: i) a total inlet, which samples all aerosol particles and cloud droplets/ice crystals, ii) an interstitial inlet, which selectively samples particles that do not form droplets when we are situated inside fog or clouds, and iii) a counterflow virtual impactor inlet (CVI), which samples only cloud droplets or ice crystals (neglecting non-activated aerosol particles). The cloud droplets or ice crystals sampled by the CVI inlet are then dried and thus only the cloud residuals (or cloud condensation nuclei) are characterized in the laboratory situated below.

Inlet and cloud probe set-up for aerosol and droplet measurements installed on the 4th deck on board the icebreaker Oden. From left to right: Inlets for particulate matter smaller 1 µm (PM1) and smaller 10 µm (PM10); forward scattering spectrometer probe (FSSP) for droplet size distribution measurements; counterflow virtual impactor inlet (CVI) for sampling cloud droplets and ice crystals; total inlet for sampling of all aerosol particles and cloud droplets/ice crystals; interstitial inlet for sampling non-activated particles; particle volume monitor (PVM) for the determination of cloud liquid water content and effective droplet radius. Newly formed , very small, particles are sampled with a different inlet (not shown in the picture) specifically designed to minimize diffusion losses. (Picture credit: Paul Zieger)

To gain more knowledge about the chemical composition and ice nucleating activity of particles in clouds, we also collect cloud and fog water on the uppermost deck of the ship and from clouds further aloft by using tethered balloon systems. When doing vertical profiles with two tethered balloons, also particle number concentration and size distribution information are obtained to understand in how far the boundary layer aerosol is mixed with the cloud level aerosol. Furthermore, a floating aerosol chamber is operated at an open lead near the ship to measure the fluxes of particles from the water to the atmosphere. It is still unknown whether open leads are a significant source of particles. For more details on the general set-up of the expedition see the first two blogs of the Arctic Ocean Expedition (here and here).

After 33 days of continuous measurements while drifting with the ice floe and after having experienced the partial freeze-up of the melt ponds and open water areas, it is now time for the expedition to head back south. We will use two stations in the marginal ice zone during the transit into and out of the pack ice as benchmarks for Arctic aerosol characteristics south of our 5-week ice floe station.

As Oden is working her way back through the ice and the expedition comes to an end, we recapitulate what we have measured in the past weeks. What was striking, especially for those who have spent already several summers in the pack ice, is that this time the weather was very variable. There were hardly two days in row with stable conditions. Instead, one low pressure system after the other passed over us, skies changed from bright blue to pale grey, calm winds to storms… On average, we have experienced the same number of days with fog, clouds and sunshine as previous expeditions, but the rhythm was clearly different. From an aerosol perspective these conditions meant that we were able to sample a wide variety characteristics including new particle formation, absence of cloud condensation nuclei with total number concentrations as low as 2 particles per cubic centimeter, coarse mode particles, and size distributions with a Hoppel-minimum that is typical for cloud processed particles.

Coming back home, we can hardly await to fully exploit our recorded datasets. Stay tuned!

Do not hesitate to contact us for any question regarding the expedition and measurements. Check out this blog for more details of life during the expedition and our project website which is part of the Arctic Ocean 2018 expedition.

Changing Arctic landscapes. From top to bottom: Upon arrival at the drift station there were many open leads. Storms pushed the floes together and partially closed leads. Mild and misty weather. Cold days and sunshine lead to freeze-up. (Credit: Julia Schmale)

Edited by Dasaraden Mauree


The authors from left to right: Andrea Baccarini, Julia Schmale, Paul Zieger

Julia Schmale is a scientist in the Laboratory of Atmospheric Chemistry at the Paul Scherrer Institute, Switzerland. She has been involved in Arctic aerosol research for the past 10 years.

Andrea Baccarini, is doing his PhD in the Laboratory of Atmospheric Chemistry at the Paul Scherrer Institute, Switzerland. He specializes in new particle formation in polar regions.

Paul Zieger, is an Assistant Professor in Atmospheric Sciences at the University of Stockholm, Sweden. He is specialized in experimental techniques for studying atmospheric aerosols and clouds at high latitudes.

The perfect ice floe

The perfect ice floe

Current position: 89°31.85 N, 62°0.45 E, drifting with a multi-year ice floe (24th August 2018)

With a little more than three weeks into the Arctic Ocean 2018 Expedition, the team has found the right ice floe and settled down to routine operations.

Finding the perfect ice floe for an interdisciplinary science cruise is not an easy task. The Arctic Ocean 2018 Expedition aims to understand the linkages between the sea, microbial life, the chemical composition of the lower atmosphere and clouds (see previous blog entry) in the high Arctic. This means that the “perfect floe” needs to serve a multitude of scientific activities that involve sampling from open water, drilling ice cores, setting up a meteorological tower, installing balloons, driving a remotely operated vehicle, measuring fluxes from open leads and sampling air uncontaminated from the expedition activities. The floe hence needs to be composed of multi-year ice, be thick enough to carry all installations but not too thick to allow for drilling through it. There should also be an open lead large enough for floating platforms and the shape of the floe needs to be such that the icebreaker can be moored against it on the port or starboard side facing all for cardinal directions depending on where the wind is coming from.

The search for the ice floe actually turned out to be more challenging than expected. The tricky task was not only to find a floe that would satisfy all scientific needs, but getting to it north of 89°N proved exceptionally difficult this year. After passing the marginal ice zone north of Svalbard, see blue line on the track (Figure 2), progress through the first year ice was relatively easy. Advancing with roughly 6 knots, that is about 12 km/h, we advanced quickly. After a couple of days however, the ice became unexpectedly thick with up to three meters. This made progress difficult and slow, even for Oden with her 24,500 horse powers. In such conditions the strategy is to send a helicopter ahead to scout for a convenient route through cracks and thinner ice. However, persistent fog kept the pilot from taking off which meant for the expedition to sit and wait in the same spot. For us aerosol scientists looking at aerosol-cloud interactions this was a welcome occasion to get hand on the first exciting data. In the meantime, strong winds from the east pushed the pack ice together even harder, producing ridges that are hard to overcome with the ship. But with a bit of patience and improved weather conditions, we progressed northwards keeping our eyes open for the floe.

Figure 2: Cruise track with drift. The light red line indicates the track to the ice floe, the dark red line indicates the drift with the floe. The thin blue line is the marginal ice zone from the beginning of August.

As it happened, we met unsurmountable ice conditions at 89°54’ N, 38°32’ E, just about 12 km from the North Pole – reason enough to celebrate the farthest North.

Figure 3: Expedition picture at the North Pole. (Credit: SPRS)

Going back South from there it just took a bit more than a day with helicopter flights and good visibility until we finally found ice conditions featuring multiple floes.

And here we are. After a week of intense mobilization on the floe, the four sites on the ice and the instrumentation on the ship are now in full operation and routine, if you stretch the meaning of the term a bit, has taken over. A normal day looks approximately like this:

7:45:  breakfast, meteorological briefing, information about plan of the day; 8:30 – 9:00: heavy lifting of material from the ship to the ice floe with the crane; 9:00 (or later): weather permitting, teams go to the their sites, CTDs are casted from the ship if the aft is not covered by ice; 11:45: lunch for all on board and pick-nick on the floe; 17:30: end of day activities on the ice, lifting of the gangway to prevent polar bear visits on the ship; 17:45: dinner; evening: science meetings, data crunching, lab work or recreation.

Figure 4: Sites on the floe, nearby the ship. (Credit: Mario Hoppmann)

At the balloon site, about 200 m from the ship, one balloon and one heli-kite are lifted alternately to take profiles of radiation, basic meteorological variables and aerosol concentrations. Other instruments are lifted up to sit over hours in and above clouds to sample cloud water and ice nucleating particles, respectively. At the met alley, a 15 m tall mast carries radiation and flux instrumentation to characterize heat fluxes in the boundary layer. The red tent at the remotely operated vehicle (ROV) site houses a pool through which the ROV dives under the flow to measure physical properties of the water. The longest walk, about 20 minutes, is to the open lead site, where a catamaran takes sea surface micro layer samples, a floating platform observes aerosol production and cameras image underwater bubbles. The ice core drilling team visits different sites on the floe to take samples for microbial and halogen analyses.

Open Lead site. (Credit: Julia Schmale)

Importantly, all activities on the ice need to be accompanied by bear guards. Everybody carries a radio and needs to report when they go off the ship and come back. If the visibility decreases, all need to come in for safety reasons. Lab work and continuous measurements on the ship happen throughout the day and night. More details on the ship-based aerosol laboratory follow in the next contribution.

Edited by Dasaraden Mauree


Julia Schmale is an atmospheric scientist at the Paul Scherrer Institute in Switzerland. Her research focuses on aerosol-cloud interactions in extreme environments. She is a member of the Atmosphere Working Group of the International Arctic Science Committee and a member of the Arctic Monitoring and Assessment Programme Expert Group on Short-lived Climate Forcers .

Into the mist of studying the mystery of Arctic low level clouds

Into the mist of studying the mystery of Arctic low level clouds

This post is the first of a “live-series of blog post” that will be written by Julia Schmale while she is participating in the Arctic Ocean 2018 expedition.

Low level Arctic clouds are still a mystery to the atmospheric science community. To understand their role the present and future Arctic climate, the Arctic Ocean 2018 Expedition is currently under way with an international group of scientists to study the ocean, lower atmosphere, clouds and aerosols.

Low level clouds in the high Arctic influence the energy budget of the region and they hence play an important role for the Arctic climate. The Arctic is warming about twice as fast as the global average, a phenomenon called Arctic amplification. The role of clouds for climate is linked to their interaction with solar radiation. They reflect short-wave radiation, thereby sending energy back to space and cooling the surface. In the case of longwave radiation, clouds reflect it back to the surface which causes a greenhouse effect that is warming the surface. The top of the clouds cools during this process, which makes air parcels surrounding the top cool as well and sink to the surface. These air masses are replaced by warmer surface air which rises. This can cause a well-mixed Arctic boundary layer. Most of the time, however, the cloud level is decoupled from the surface due to temperature inversions. This is possible when clouds are thin. In this case, clouds cannot feed on the water vapor from the surface and they might dissipate. Interaction of clouds with short-wave radiation in the summer is most of the time less important than their interaction with long-wave radiation. This is because the cloud albedo is similar to the sea ice albedo. Hence clouds do not have a strong cooling effect. However, as summer sea ice retreats and the surface gets darker, clouds may contribute to surface cooling in the future.

The overall radiative properties of clouds are further influenced by the phase of the clouds. Arctic summer clouds are normally mixed-phased, that is liquid droplets co-exist with ice crystals. Usually, ice and liquid water do not co-exist, because the ice crystals grow at the expense of liquid droplets that evaporate (because the saturation water vapor pressure is higher of liquid droplets than ice crystals). However, in simple words, in the summertime Arctic, when mixing of air masses occurs, liquid droplets form in rising air parcels that sustain the liquid layer at the bottom of the cloud which in turn feeds the ice crystal growth.

As cloud droplets and ice crystals only form on cloud condensation nuclei (CCN) and ice nucleating particles (INP), the whole complexity described above, depends on the presence of aerosol particles. But the central Arctic Ocean has an extremely limited supply of CCN and INP. Potential sources include locally produced or long-range transported particles. Long-range transport of particles – or precursor gases that form particles – to the high Arctic in the free troposphere can contribute to the number of CCN and INP. However, in the summer Arctic atmosphere precipitation is frequent and particles can be washed out along their way north. Regional transport of trace gases such as dimethyl sulfide (DMS), which is emitted from phytoplankton blooms in the marginal ice zone, can contribute to the CCN after atmospheric oxidation. Local sources in the high Arctic are however, extremely limited. Open leads, those are areas of open water which form as the sea ice is moving, can produce particles through bubble bursting. These bursting bubbles expel material such as sea salt and organic particles contained in the surface water into the air from where they might be transported to the cloud level. Another conceivable source of particles is new particle formation. This means that particles are freshly formed purely from gases. This process and the chemical nature and sources of the gases are however poorly understood.

To shed light on how cloud formation works in the summer time high Arctic and how this might change in the future with changing climatic conditions the Arctic Ocean 2018 Expedition is designed to investigate physical, chemical and biological processes from the water column to the free troposphere. The graphic below provides a schematic of the planned activities.

Arctic ocean setup by Paul Zieger

 

On 1 August, we left Longyearbyen. After a 24 hour station in the marginal ice zone, we are now heading towards the North Pole area where we look for a stable multi-year ice floe against which the ship will be moored for several weeks to drift along. This strategy will give us the opportunity for detailed process studies. In the upcoming blog contributions, several of these process studies will be featured.

Further links:
Expedition website:
https://polarforskningsportalen.se/en/arctic/expeditions/arctic-ocean-2018
Arctic ocean blog of the Paul Scherrer Institute:
https://www.psi.ch/lac/arctic-ocean-blog
Stockholm University Expedition Webpage:
https://www.aces.su.se/research/projects/microbiology-ocean-cloud-coupling-in-the-high-arctic-moccha/

Edited by Dasaraden Mauree


Julia Schmale is an atmospheric scientist at the Paul Scherrer Institute in Switzerland. Her research focuses on aerosol-cloud interactions in extreme environments. She is a member of the Atmosphere Working Group of the International Arctic Science Committee and a member of the Arctic Monitoring and Assessment Programme Expert Group on Short-lived Climate Forcers .

Buckle up! Its about to get bumpy on the plane.

Buckle up! Its about to get bumpy on the plane.

Clear-Air Turbulence (CAT) is a major hazard to the aviation industry. If you have ever been on a plane you have probably heard the pilots warn that clear-air turbulence could occur at any time so always wear your seatbelt. Most people will have experienced it for themselves and wanted to grip their seat. However, severe turbulence capable of causing serious passengers injuries is rare. It is defined as the vertical motion of the aircraft being strong enough to force anyone not seat belted to leave the chair or floor if they are standing. In the United States alone, it costs over 200 million US dollars in compensation for injuries, with people being hospitalised with broken bones and head injuries. Besides passengers suffering serious injuries, the cabin crew are most vulnerable as they spend most of the time on their feet serving customers. This results in an additional cost if they are injured and unable to work.

Clear-air turbulence is defined as high altitude inflight bumpiness away from thunderstorm activity. It can appear out of nowhere at any time and is particularly dangerous because pilots can’t see or detect it using on-board instruments.  Usually the first time a pilot is aware of the turbulence is when they are already flying through it. Because it is a major hazard, we need to know how it might change in the future, so that the industry can prepare if necessary. This could be done by trying to improve forecasts so that pilots can avoid regions likely to contain severe turbulence or making sure the aircraft can withstand more frequent and severe turbulence.

Our new paper published in Geophysical Research Letters named ‘Global Response of Clear-Air Turbulence to Climate Change’ aims at understanding how clear-air turbulence will change in the future around the world and throughout the year. What our study found was that, the busiest flight routes around the world would see the largest increase in turbulence. For example, the North Atlantic, North America, North Pacific and Europe (see Figure 1) will see a significant increase in severe turbulence which could cause more problems in the future. These regions see the largest increase because of the Jet Stream. The Jet Stream is a fast flowing river of air that is found in the mid-latitudes. Clear-air turbulence is predominantly caused by the wind traveling at different speeds around the Jet Stream. Climate change is expected to increase the Jet Stream speed and therefore increase the vertical wind shear, causing more turbulence.

To put these findings in context, severe turbulence in the future will be as frequent as moderate turbulence historically. Anyone who is a frequent flyer will have likely experienced moderate turbulence at some point, but fewer people have experienced severe turbulence. Therefore, this study suggests this will change in the future with most frequent flyers experiencing severe turbulence on some flight routes as well as even more moderate turbulence. Our study also found moderate turbulence will become as frequent in the summer as it has done historically in winter. This is significant because although clear-air turbulence is more likely in winter, it will however now become much more of a year round phenomenon (see Figure 2).

Figure 2: Seasonal variation in turbulence intensity.

 

This increase in clear-air turbulence highlights the importance for improving turbulence forecasting. Current research has shown that using ensemble forecasts (many forecasts of the same event) and also using more turbulence diagnostics than the one we used in this study can improve the forecast skill. By improving the forecasts, we could consistently avoid the areas of severe turbulence or make sure passengers and crew are seat-belted before the turbulence event occurs. Unfortunately, as these improvements are not yet fully operational, you can still reduce your own risk of injury by making sure you wear your seat belt as much as possible so that, if the aircraft does hit unexpected turbulence, you would avoid serious injuries.


This blog has been prepared by Luke Storer (@LukeNStorer), Department of Meteorology, University of Reading, Reading, UK and edited by Dasaraden Mauree (@D_Mauree). 

Volcanic Ash Particles Hold Clues to Their History and Effects

Volcanic Ash Particles Hold Clues to Their History and Effects
Volcanic Ash as an Active Agent in the Earth System (VA3): Combining Models and Experiments; Hamburg, Germany, 12–13 September 2016

Volcanic ash is a spectacular companion of volcanic activity that carries valuable information about the subsurface processes. It also poses a range of severe hazards to public health, infrastructure, aviation, and agriculture, and it plays a significant role in biogeochemical cycles.

Scientists can examine ash particles from volcanic eruptions for clues to the history of their journey from the lithosphere (Earth’s crust and upper mantle) to atmosphere, hydrosphere, and biosphere (Figure 1). These tephra particles are less than 2 millimeters in diameter, and they record most of the history on or near their surfaces. Understanding the physicochemical properties of the ash particle surfaces is essential to deciphering the underlying volcanic and atmospheric processes and to predicting the widespread effects and hazards posed by these small particles. This has been extensively investigated recently but several fundamental questions remain open.

Figure 1: Particle surface properties strongly affect the life cycle and effects of volcanic ash particles within the Earth system (Credit: G. Hoshyaripour).

For example, ash surface generation and alteration through processes occurring during eruption (e.g., fragmentation and recycling) and after eruption (e.g., aggregation, cloud chemistry, and microphysics) are not yet quantitatively well understood and thus are not fully implemented in the models. Therefore, gaps remain in our understanding of the volcanic and atmospheric life cycle of the ash and how this life cycle is linked to the ash’s surface properties and environmental effects. This limitation hinders the reliable estimation of far-field airborne ash concentrations, a central factor in assessing the ash hazard for aviation.

Addressing the challenges in volcanic ash surface characterization requires close collaboration of experts in laboratory experiments, in situ measurements, space-based observations, and numerical modeling to co-develop reliable assessment tools for both fundamental research and operational purposes. These actions should involve specialists from geochemistry, geology, volcanology, and atmospheric sciences to combine the advanced experimental and observational data on rate parameters of physicochemical processes and ash surface characteristics with state-of-the-art atmospheric models that incorporate aerosol chemistry, microphysics, and interactions among ash particles, clouds, and solar radiation in local to global scales.

As the first step in this direction, a joint European Geophysical Union (EGU) and American Geophysical Union (AGU) session on volcanic ash is organized in the upcoming general assembly and fall meeting entitled: Volcanic Ash—Generation, Transport, Impacts, and Applications. The next steps should include 1) initiation a collaborative network with two working groups on the physical and geochemical life cycles of volcanic ash; 2) development an integrated modeling, observational, and experimental data compilation on mid- to large-intensity eruptions to assist with benchmark modeling.

These actions should be linked to the existing activities within the International Association of Volcanology and Chemistry of the Earth’s Interior, EGU, and AGU.

The workshop was supported by the excellence cluster CliSAP (DFG EXE 177).

This blog post has been originally prepared as a meeting report referring to a workshop in Hamburg, Germany, sponsored by the excellence cluster CliSAP (DFG EXE 177).


This blog has been prepared by Ali Hoshyaripour (@Hoshyaripour – email: ali.hoshyaripour@kit.edu), Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Germany and edited by Dasaraden Mauree (@D_Mauree). 

How can we use meteorological models to improve building energy simulations?

How can we use meteorological models to improve building energy simulations?

Climate change is calling for various and multiple approaches in the adaptation of cities and mitigation of the coming changes. Because buildings (residential and commercial) are responsible of about 40% of energy consumption, it is necessary to build more energy efficient ones, to decrease their contribution to greenhouse gas emissions.

But what is the relation with the atmosphere. It is two folds: firstly, in a previous post, I have already described what is the impact of the buildings / obstacles on the air flow and on the air temperature. Secondly, the fact that the climate or surrounding environment is influenced, there will be a significant change in the energy consumption of these buildings.  Currently, building energy simulation tool are using data usually gathered outside of the city and hence not representative of the local context. Thus it is crucial to be able to have necessary tools that capture both the dynamics of the atmosphere and also those of a building to design better and more sustainable urban areas.

In the present work, we have brought these two disciplines together by developing a multi-scale model. On the one side, a meteorological model, the Canopy Interface Model (CIM), was developed to obtain high resolution vertical profile of wind speed, direction and air temperature. On the other hand, an energy modelling tool, CitySim, is used to evaluate the energy use of the buildings as well as the irradiation reaching the buildings.

With this coupling methodology setup we have applied it on the EPFL campus, in Switzerland.  We have compared the modelling results with data collected on the EPFL campus for the year 2015. The results show that the coupling lead to a computation of the meteorological variables that are in very good agreement. However, we noted that for the wind speed at 2m, there is still some underestimation of the wind speed. One of the reason for this is that the wind speed close to the ground is very low and there is a higher variability at this height.

Comparison of the wind speed (left) and air temperature (right) at 2m (top) and 12m (bottom).

We intend to improve this by developing new parameterization in the future for the wind speed in an urban context by using data currently being acquired in the framework of the MoTUS project. One surprising result from this part of the study, is the appearance inside of an urban setup of a phenomena call Cold Air Pools which is very typical of valleys. The reason for this is the lack of irradiation reaching the surface inside of dense urban parts.

Furthermore, we have seen some interesting behaviour in the campus for some particular buildings such as the Rolex Learning Center. Buildings with different forms and configuration, reacted very differently with the local and standard dataset. We designed a series of additional simulation using multiple building configuration and conducted a sensitivity analysis in order to define which parameters between the wind speed and the air temperature had a more significant impact on the heating demand (see Figure 1). We showed that the impact of a reduction of 1°C was more important than a reduction of 1m s-1.

Figure 1. Heating demand of the five selected urban configurations (black dots), as function of the variation by +1°C (red dots) and -1°C (blue dots) of the air temperature, and by +1.5 m s-1 (violet dots) and -1.5 m s-1 (orange dots).

Finally, we also analysed the energy consumption of the whole EPFL campus. When using standard data, the difference between the simulated and measured demand was around 15%. If localized weather data was used, the difference was decreased to 8%. We have thus been able to reduce the uncertainty of the data by 2. The use of local data can hence improve the estimation of building energy use and will hence be quite important when building become more and more efficient.

Reference / datasets

The paper (Mauree et al., Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale, PLOS One, 2017) can be accessed here and data needed to reproduce the experiment are also available on Zenodo.

The art of turning climate change science to a crochet blanket

The art of turning climate change science to a crochet blanket

We welcome a new guest post from Prof. Ellie Highwood on why she made a global warming blanket and how you could the same!

What do you get when you cross crochet and climate science?
A lot of attention on Twitter.
At the weekend I like to crochet. Last weekend I finished my latest project and posted the picture on Twitter. And then had to turn the notifications off because it all went a bit noisy. The picture of my “global warming blanket” rapidly became my top tweet ever, with more retweets and likes than anything else. Apparently I had found a creative way to visualise trends in global mean temperature. I particularly liked the “this is the most frightening knitwear I have seen all year” comment. Given the interest on Twitter I thought I had better answer a few of the questions in a blog post. Also, it would be great if global warming blankets appeared all over the world.

How did you get the idea?
The global warming blanket was based on “temperature” blankets made by crocheters around the world. Their blankets consist of one row, or square, of crochet each day, coloured according to the temperature at their location. They look amazing and show both the annual cycle and day-to-day variability. Other people make “sky” blankets where the colours are based on the sky colour of the day – this results in a more muted grey-blue-white colour palette.
I wondered what the global temperature series would look like as a blanket. Also, global warming is often explained as greenhouse gases acting like a blanket, trapping infrared radiation and keeping the Earth warm. So that seemed like an interesting link. I also had done several rainbow themed blankets in the past and had a lot of yarn left that needed using.

Where did the data come from?

I used the annual and global mean temperature anomaly compared to 1900-2000 mean as a reference period as available from NOAA. This is what the data looks like shown more conventionally.

Global temperature anomalies (source: NOAA)

I then devised a colour scale using 15 different colours each representing a 0.1 °C data interval. So everything between 0 and 0.099 was in one colour for example. Making a code for these colours, the time series can be rewritten as in the table below. It is up to the creator to then choose the colours to match this scale, and indeed which years to include. I was making a baby sized blanket so chose the last 100 years, 1916-2016.

Because of these choices, and the long reference period, much of the blanket has relatively muted colour differences that tend to emphasise the last 20 years or so. There are other data sets available, and other reference periods and it would be interesting to see what they looked like. Also the colours I used were determined mainly by what I had available; if I were to do another one, I might change a few around (dark pink looks too much like red in the photograph and needed a darker blue instead of purple for the coldest colour), or even use a completely different colour palette – especially as rainbow colour scales aren’t great as they can distort data and render it meaningless if you are colour blind. Ed Hawkins kindly provided me with a more user friendly colour scale which I love and may well turn into a scarf for myself (much quicker than a blanket!).

#endrainbow colour scale (from E. Hawkins)

How can I recreate this?
If you want to create something similar, you will need 15 different colours if you want to do the whole 1850-2016 period. You will need relatively more yarn in colours 3-7 than other colours (if, like me you are using your stash). You can use any stitch or pattern but since you want the colour changes to be the focus of the blanket, I would choose something relatively simple. I used rows of treble crochet (UK terms) and my 100 years ended up being about 90 cm by 110 cm. You can of course choose any width you like for your blanket, or make a scarf by doing a much shorter foundation row. It goes without saying that it could also be knitted. Or painted. Or woven. Or, whatever your particular craft is.

If you look closely (check out arrows on the figure at the top) you can see the 1997-1998 El Nino (relatively warm yellow stripe amongst the pink – in this photo the dark pink looks red – I might change this colour if I did it again), 1991/92 Pinatubo eruption (relatively cool pink year) as well as cool periods 1929, and 1954-56 and the relatively warm 1940-46. Remember that these are global temperature anomalies and may not match your own personal experience at a given location!

Table with the colour codes used to make the global warming blanket

How long did it take?
I used a very simple stitch, so for a blanket this size, it was a couple of months (note I only crochet in the evenings 2 or 3 evenings a week for a couple of hours with more at some weekends). It helped that the Champions League was on during this time as other members of the household were happy to sit around watching football whilst I crocheted. Weave the ends in as you go. There are a lot of them, and I had to do them all at the end. The time flies because….

Why do I crochet?
I like crochet because you can do simple projects whilst thinking about other things, watching TV or listening to podcasts, or, you can do more complicated things which require your full attention and divert your brain from all other things. There is also something meditative about crochet, as has been discussed here. I find it a good way to destress. Additionally, a lot of what I make is for gifts or for charities and that is a really good feeling.

What’s next?
Suggestions have come in for other time series blankets e.g. greys for aerosol optical depth punctuated by red for volcanic eruptions, oranges and yellows punctuated by black for solar cycle (black being high sun spot years), a central England temperature record. Blankets take time, but scarves could be quicker so I might test a few of these ideas out over the next few months. Would love to hear and see more ideas, or perhaps we could organise a mass “global warming blanket” make-athon around the world and then donate them to communities in need.

And finally.
More seriously, whilst lots of the initial comments on Twitter were from climate scientists, there are also a lot from a far more diverse set of folks. I think this is a good example of how if we want to reach out, we need to explore different ways of doing so. There are only so many people who respond to graphs and charts. And if we can find something we are passionate about as a way of doing it, then all the better.

This post has also been published here.

Edited by Dasaraden Mauree


Ellie Highwood is Professor of Climate Physics in the Department of Meteorology at the University of Reading. She did a Bsc in Physics at the University of Manchester before studying for a PhD at Reading, where she has been ever since! Her research interests concern the role of atmospheric particulates (aerosol) in climate and climate change. She has led two international aircraft campaigns to measure the properties of aerosol and has been involved in many others. Research projects have considered Saharan dust, volcanoes, and aerosols from human activities. She has over 40 publications in the peer reviewed literature and a few media appearances. She also teaches introductory meteorology and climate change to undergraduates, and project management to PhD students. Previously she has been a member of RMetS Council and Education Committee, and Editor of Society News. She also writes a regular “climate scientist” column for the Weather magazine. She tweets as @EllieHighwood.

What? Ice lollies falling from the sky?

What? Ice lollies falling from the sky?

You have more than probably eaten many lollipops as a kid (and you might still enjoy them. The good thing is that you do not necessarily need to go to the candy shop to get them but you can simply wait for them to fall from the sky and eat them for free. Disclaimer: this kind of lollies might be slightly different from what you expect…


Are lollies really falling from the sky?

Eight years ago (in January 2009), a low-pressure weather system coming from the North Atlantic Ocean reached the UK and brought several rain events to the country. Nothing is really special about this phenomenon in Western Europe in the winter. However, a research flight started sampling the clouds in the warm front (transition zone where warm air replaces cold air) ahead of the low-pressure system and discovered hydrometeors (precipitation products, such as rain and snow) of an unusual kind. Researchers named them ‘ice lollies’ due to their characteristic shape and maybe due to their gluttony. The microphysical probes onboard the aircraft, combined with a radar system located in Southern England, allowed them to measure a wide range of hydrometeors, including these ice lollies that were observed for the first time with such concentration levels.

How do ice lollies form?

A recent study (Keppas et al, 2017) explains that ice lollies form when water droplets (size of 0.1 to 0.7 mm) collide with ice crystals with the form of a column (size of 0.25 to 1.4 mm) and freeze on top of them (see Fig. 2).

Fig 2: Formation of an ice lolly: water droplet (the circle) collides with an ice crystal (the column) [Credit: Fig. 1a from Keppas et al., (2017)].

Such ice lollies form in ‘mixed-phase clouds’, i.e. clouds made of water droplets and ice crystals and whose temperature is below the freezing point (0°C). At these temperatures, water droplets can be supercooled, meaning that they stay liquid below the freezing point.

Figure 3 below shows the processes and particles involved in the formation of ice lollies. Ice lollies are mainly found at temperatures between 0 and -6°C, in the vicinity of the warm conveyor belt, which represents the main source of warm moist air that feeds the low-pressure system. This warm conveyor belt brings water vapour that participates in the formation and growth of supercooled water droplets. Ice crystals formed near the cloud tops fall through the warm conveyor belt and collide with the water droplets to form ice lollies.

Fig 3: Processes involved with the formation of ice lollies, which mainly form under the warm conveyor belt [Credit: Fig 4 from Keppas et al., (2017)].

Are these ice lollies important?

Ice lollies were observed more recently (September 2016) during another aircraft mission over the northeast Atlantic Ocean but no radar coverage supported the observations. At the moment of writing this article, the lack of observations prevent us from determining the importance of these ice lollies in the climate system. However, future missions would provide more insight. In the meantime, we suggest you to enjoy a lollipop such as the one shown in the image of this week 🙂

This is a joint post, published together with the Cryospheric division blog, given the interdisciplinarity of the topic.

Edited by Sophie Berger and Dasaraden Mauree

Reference/Further reading

Keppas, S. Ch., J. Crosier, T. W. Choularton, and K. N. Bower (2017), Ice lollies: An ice particle generated in supercooled conveyor belts, Geophys. Res. Lett., 44, doi:10.1002/2017GL073441

 


DavidDavid Docquier is a post-doctoral researcher at the Earth and Life Institute of Université catholique de Louvain (UCL) in Belgium. He works on the development of processed-based sea-ice metrics in order to improve the evaluation of global climate models (GCMs). His study is embedded within the EU Horizon 2020 PRIMAVERA project, which aims at developing a new generation of high-resolution GCMs to better represent the climate.