Sea ice is difficult, expensive, and potentially dangerous to observe in nature. The remoteness of the Arctic Ocean and Southern Ocean complicates sampling logistics, while the heterogeneous nature of sea ice and rapidly changing environmental conditions present challenges for conducting process studies. Here, we describe the Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC), a laboratory facility designed to reproduce polar processes and overcome some of these challenges. The RvG-ASIC is an open-topped 3.5 m
To characterise some of the technical capabilities of our facility, we have quantified the timescale over which our chamber exchanges gas with the outside,
We also present results characterising our experimental sea ice. The extinction coefficient for PAR varies from 3.7 to 6.1 m
Sea ice lies at the ocean–atmosphere interface. As such, sea ice mediates the exchange of energy
The remoteness and extremeness typical of the polar oceans make observing sea ice in situ difficult, expensive, and potentially dangerous – both for personnel and equipment. Such logistical challenges are heightened during the initial growth and final melt of sea ice, which are particularly interesting study periods. Also, the heterogeneous nature of sea ice, with important parameters varying over sub-metre scales
Existing laboratory facilities vary widely, tending to be designed with specific observations in mind and circumventing specific constraints. The lengths of sea-ice tanks vary from tens of metres
There are several examples of sea-ice tanks having proved effective in generating and testing hypotheses. As an example, much of our understanding of gravity drainage was produced or refined using sea-ice tank experiments. Laboratory studies traced brine
Here, we describe and characterise the Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC) to aid future users when planning experiments. We first describe the facility, the instrumentation available, and typical protocols used to grow artificial sea ice (Sect.
Our artificial ocean is contained in a cuboid, open-topped, glass tank (Fig.
The tank just after installation
A lighting rack sits at 1.3 m above the tank base (Fig.
Spectral irradiance,
The tank and lights are housed in a cold room with a temperature range of
Scaled schematic diagram of the cold room. The three panels show orthogonal views from different vantage points. Crosses and dots indicate air flow away from and towards the viewer, respectively. The lights, shown in grey, are made up of eight sets of visible, UV-A, and UV-B triplets. The main and side tanks are pale green.
The cold room is located in an external laboratory. The control boxes for instrumentation, heating, pumps, cameras, and valves are all situated adjacent to the cold room. Instruments log to an Envidas Ultimate acquisition system software for continuous monitoring of the data. Mains or 18.2 M
We use “chamber” to describe the experimental system. When the tank is exposed to the entire cold room, as for all the experiments presented here, the cold room is the chamber.
The RvG-ASIC has a suite of instruments for carrying out measurements of the experimental ocean, sea ice, and atmosphere (Table
Instruments that are generally available in the RvG-ASIC.
The ocean temperature,
Temperature,
Our version of the wireharps use two alternating current frequencies, 2 kHz (as used in
The temperature, wind speed, and relative humidity of our atmosphere are measured using a weather station (WS600-UMB). Two Los Gatos Research (LGR) greenhouse gas analysers measure CO
Protocols vary widely between experiments. Here, we provide a typical protocol to help future users visualise the facility and plan experiments.
We set up instrumentation in a dry, clean tank. Sea-ice instrumentation is attached to poles that are free to rise in the vertical as sea ice grows and floats. Ocean and atmosphere instrumentation and sample lines are mounted in a fixed position. The nature of the experiment will determine the state of the tank sides and base. For optical experiments (Sect.
To fill the tank, we add 100 kg of salt and mix this with tap or 18.2 M
The water circulation rate and the atmospheric temperature determine the nature of the sea ice
Grease ice
A view of a supercooled ocean. Frazil ice crystals are floating upwards in the water column (white flecks) and have nucleated on wireharps well ahead of the advancing sea-ice–ocean interface.
Underlying water may be sampled throughout, providing the volume is replaced. We sample sea ice either by taking cores using a 7.5 cm diameter Kovacs ice corer or using the procedures outlined by
We now turn to a characterisation of our experimental system. First, in Sect.
For most experiments, it is desirable to have the sea-ice–atmosphere interface exposed to the bulk air within the cold room. Leaving the atmosphere of the tank uncapped ensures that the temperature of the atmosphere overlying the sea ice is responsive to the cold room atmosphere. When the atmosphere is contained by some headspace, the temperature tends to be much warmer than the cold room
Data from experiments to determine the chamber air exchange rate. Panels
To do so, we sealed the cold room and left the tank dry. We then diluted the chamber air by filling it with N
For some experiments, it may be necessary to spike the ocean with a chemical. We may, in such cases, want to know when the water will be well mixed with respect to our spike. Similar to the air exchange rate (Sect.
Experiments to determine the mixing time constant of our tank,
Producing a homogeneous light field in a laboratory environment can be difficult, because shading and reflection can cause heterogeneities. The intensity of our lights is also temperature dependent, which is particularly important in the RvG-ASIC given the wide range of experimental temperatures. In this section, we aim to characterise our light field, both in terms of lateral heterogeneity and with changes in temperature.
To assess the spatial variability, we measured PAR (photosynthetically active radiation,
Normalised PAR (
We measured spectra for UV (UV-A lighting, 320 to 380 nm) and PAR (LED lighting, 400 to 700 nm) at
Sensitivity of lights to variations in temperature. Panels
The importance of understanding the sea-ice light field is critical as thinner, fresher, and more transient sea ice becomes more common. Even thin sea ice without snow cover impacts the transmission of PAR to the ocean and has been seen to accumulate algal biomass rapidly within the sea ice
The rationale for UV–Vis illumination experiments in a controlled sea-ice facility is twofold: first, to allow for experiments investigating the optical properties of sea ice (and potentially other mediums such as snow); second, to allow simple experimental simulations of photochemistry or biology occurring in the sea ice, atmosphere, or ocean. The extinction coefficient,
To quantify
Overview of experiments used to calculate with
PAR extinction coefficients.
Comparison of PAR extinction coefficients (
Irradiance profiles
Measured light profiles taken at the end of four experiments are shown in Fig.
Using method A, our calculated
Bulk salinity is a sea-ice state variable that, when measured alongside temperature, can allow for estimation of the sea-ice liquid fraction. Growing sea ice desalinates rapidly by gravity drainage
We performed two sea-ice growth experiments in the RvG-ASIC and estimated the sea-ice salinity by (1) constructing a salt and mass budget, (2) taking sea-ice cores, (3) taking sea-ice slabs
Vertical temperature (
The mass balance was constructed by conservation of mass and salt from the start of each run (
We first turn to the vertical profiles of
The mass balance produces
The underestimation of
Results for the mean bulk salinity,
The growth rate of sea ice depends on the balance of fluxes at the sea-ice–ocean interface, the thermal conductivity of the sea ice (
Thickness measured from temperature profiles during the experiments presented in Sect.
Over the four experiments, measured growth rates range from 2 cm d
Modelling thickness in this way is useful for planning experiments but – considering temperature profiles are measured during each experiment – measuring temperature and thickness gives better precision. Growth rates in the RvG-ASIC are within the range of those measured in the field and are in agreement with thermodynamic modelling
We have described the Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC) and the suite of instruments supporting it, and we have given an overview of the protocols used to run experiments in the facility. We presented technical results from experiments in the facility showing (1) the time constant for air exchanging between our sealed chamber and the outside is (
The RvG-ASIC is a powerful and versatile tool for studying sea ice and has potential to investigate physics, chemistry, and biology. It is best suited to process studies, bridging the gap between numerical models and reality. The facility was named in honour of its founder, who won funding for the facility, led its design and construction, but sadly died in September 2015 before it could be put into full use.
All data, plot scripts, and model code used to produce this article are provided as supplementary information accessible at
MTh prepared the article with JF, JK, and DN. All authors were involved in some of the experimental work. MTh did the modelling. JF managed the facility from 2015 to 2018, and OC managed the facility from 2018 to 2020, both under the supervision of JK.
The authors declare that they have no conflict of interest.
This article is part of the special issue “Simulation chambers as tools in atmospheric research (AMT/ACP/GMD inter-journal SI)”. It is not associated with a conference.
Roland von Glasow was instrumental in the design, construction, and scientific vision of the facility. Thanks to Bill Sturges, Dorothee Bakker, Martin Vancoppenolle, and Finlo Cottier for their time and scientific input to the RvG-ASIC. Jeremey Wilkinson and Martin King provided much useful advice and loaned us equipment. Thanks also to the technical support at UEA: Andy Macdonald, Stuart Rix, Dave Blomfield, Nick Griffin, Gareth Flowerdue, Ben McLeod, and Nick Garrard. This work received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7-2007-2013, grant agreement no. 616938) and the Horizon 2020 research and innovation programme through the EUROCHAMP-2020 Infrastructure Activity under grant agreement no. 730997, as well as the University of East Anglia. Oliver Tooth, and Mathilde Tranter were supported by an internship granted by the Environmental Sciences department at UEA.
This research has been supported by the European Research Council, Seventh Framework Programme (FP7 Ideas (grant no. 616938)) and the H2020 Research Infrastructure EUROCHAMP-2020 (grant no. 730997).
This paper was edited by Hartmut Herrmann and reviewed by Brice Loose and one anonymous referee.