Video: Alive and Well: Microbes Add to Melting of Greenland Ice Sheet

Peter Sinclair and Yale Climate Connections have released an excellent video detailing the role of microbial life in driving Greenland Ice Sheet melt, featuring several researchers from the Dark Snow Project and Black and Bloom. We were lucky enough to have Peter with us for a couple of days at the beginning of our trip in 2016.

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Svalbard UAV: Lessons learned

 

Here are a few things I learned after ten days of field testing the UAV multispectral data acquisition in Svalbard…

Video showing take off in stabilize mode, switch to loiter mode at about 5 m, quick control test then into automatic mission. 

1. The UAV is surprisingly robust.

The aircraft was transported to the sites on a sled on the back of a snowmobile, hitting sastrugi and general lumps and bumps in the landscape, was hold baggage on three flights, launched and landed in snow, flown in winds and operated at temperatures down to -25 degrees. It is still is perfect working order and flew every mission without issue. I’m now pretty confident in the flight case and arrangement of kit inside, and trust that there won’t be significant flight issues in Greenland in summer.

2. Very low temperatures rapidly deplete the LiPo batteries

One noticeable, and unsurprising, effect of flying in these conditions was that the battry ran down very quickly. The toughest day was about -19 but with strong winds, and we only managed a 2.5 minute automated flight before the battery voltage dropped low enough for me to get twitchy and land the UAV manually.

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Taking off on a particularly cold flight, near Telbreen, Svalbard

3. A dGPS and ground control points will be essential for ground truthing the UAV imagery 

It was impossible to accurately pinpoint ground sampling locations using handheld GPS and ground feature ID. This was especially true in Svalbard because of the homogenous snow cover, but will also be an issue in Greenland in the summer. This is not really surprising, but the need for an accurate dGPS location lock has been reinforced by the test flights.

4. The workflow for geotagging multispectral images using Photoscan is not as straightforward as I originally thought. 

The red-edge camera does not output GeoTIFFs – they have to be postprocessed with ground control point data before they can be stacked and aligned. This is not a big problem, but good to know in advance of summer data collection.

5. New landing gear needed

The three-leg solution currently used on the UAV is better than I expected, but there is still the real problem that the legs sink into soft ground (e.g. snow) which risks pushing the camera lenses and the internal electronics into the snow. This could scratch the lenses or soak the electronics when the snow melts. Also, with the current model, a problem with any one of the three legs compromises the whole UAV because it becomes impossible to land flat. I’m going to develop something new before Greenland.

Video showing manual landing on a patch of compacted snow after an auto mission. It would be more stable on soft ground with a skid-type landing gear rather than the three legs. Includes heckling by Tedstone…!

6. Some a priori knowledge of image area can be useful

High resolution imagery is not available for all locations – for some of our field sites there was not sufficient google earth coverage to orient ourselves or draw a polygon by eye in Mission Planner.  It is possible to estimate using the compass and the map scale, but with some existing knowledge of the GPS coordinates of the grid perimeter would help to plan an accurate mission.

7. It’s amazing how small the UAV looks, even when flying quite close by

Even flying the UAV at 30 or 40 m elevation, it quickly becomes difficult to keep track of its orientation when it flies a hundred metres or so on a mission. This does have implications for the length of mission I’d be comfortable flying, since I want to be able to rescue it manually if there are any GPS or autopilot issues – maybe I’m soft but my comfortable range is less than the CAA ‘dronecode’ distance limits- even though these do not currently apply in Svalbard/Greenland. Of course, the conditions (esp. visibility) affect what feels comfortable.

8. The controller is awkward in gloves

At -25 C gloves were pretty essential, but it is also difficult to have fine control over the switches and sticks on the controller. I was flying in a very thin pair of gloves or gloveless, which meant my fingers quickly went numb, especially when there was any wind. This will be less of a problem in Greenland in summer, but I will still get some warmer, thinner gloves with rubber finger pads to help with the UAV control in the cold.

9. Pre-flight checklists are invaluable

It’s so easy to overlook or forget something in harsh conditions or when rushed or excited. The written checklists developed before we went out to Svalbard were extremely useful for making sure everything went smoothly. These are a condition of CAA compliant flights in the UK and our experience in Svalbard demonstrates why! I will probably add a few additional checks or reorder a few things before our Greenland deployment – site specific things like take off and landing zone preparation (in Svalbard it was often a compacted snow platform, in Greenland I intend to use plyboard to avoid melt ponds and cryoconite holes).

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One of the field sites at Reiperbreen, Svalbard

Svalbard UAV tests

Having made successful UAV test flights at home in the Peak District, we have relocated to Svalbard for a week to test the equipment in the most challenging possible conditions. We are flying in temperatures as low as -10 C, in gusty wind and after pulling the UAV to the field site in its flight case on a sled behind a snow scooter. It is taking off and landing on platforms of compacted snow.

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Day 1 field site, Svalbard, Norway

Nevertheless, so far it has performed magnificently. There has been no damage even to the delicate props during transport, suggesting the flight case is sufficient, and the autopilot seems to be deftly dealing with the gusty wind. It interfaces quickly with the laptop and it is easy to load a preprogrammed flight, even in these very cold conditions. It was quite difficult to take of and land in ‘stabilize’ mode with the wind though.

A few modifications I’d still like to make include a new landing gear design. The three legs are OK for flat, hard ground, but for ice and snow I think it would be much better to have something with skids, or possibly a circular base, as this would protect it from landing with a leg in a cryoconite hole and prevent the camera touching the snow if the legs sink. Also, at the moment any problem with a single leg compromises the UAV’s ability to land, whereas a unit that joins to the UAV in more than one place would give more redundancy.

The battery life is also significantly reduced in these temperatures. That’s to be expected, but I’m wondering if there are more mods we can make to extend the flight time for surveying big areas in Greenland.

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Day 1 Field Site, Svalbard, Norway

This performance gives me hope for a successful mapping mission in Greenland, where the UAV will be used to map the ice surface in much less demanding conditions than we are experiencing here, but will be worked on more ambitious missions (higher, further, more frequent). We are continuing to test the UAV protocol in the field for a few more days, but will now focus on our methodology for pairing UAV flights with ground sampling rather than flight tech and UAV control.

As a bonus, we were treated to a spectacular aurora on the way in…

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A picture that doesn’t do it justice…!

 

High bradfield: UAV test flights

The past few weeks have been spent working down in the robotics department at the University of Sheffield building a UAV (unmanned aerial vehicle, a.k.a drone). Ultimately, it will be used to make measurements of spectral reflectance of the ice surface in Greenland. It’s been great fun working in robotics – entering the lab is like walking onto the set of Robot Wars! UAV expert Owen McAree has been a huge help in developing the hardware and software for the drone – affectionately known as ‘albedrone’ in recognition of the albedo work it will enable – and we have now made successful test flights.

It began as an off-the-peg Steadidrone Mavrik quadcopter. However, we have made several modifications. We added a new brushless gimbal powered from the autopilot, machined a new mount that allowed us to better balance the camera and minimize the power being drawn by the gimbal, and added a GPS that can be used to trigger the image capture. We have also invested significant time into tuning the flight parameters and making it as stable and easy to fly as possible.

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Overview of the UAV and camera

Flying can still be quite challenging, so I also invested in flight simulator software that interfaces with the real UAV controller, meaning I have been able to get the hang of flying safely without endangering the UAV. Significant time and effort has also gone in to writing a flight manual and logbooks for the batteries, build modifications and flight records.

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A close up of the UAV set-up with the red-edge camera in downwards-looking position

We have been flight-testing the UAV at the University of Sheffield’s High Bradfield site and have now successfully made a pre-programmed flight and captured overlapping images in five spectral bands. Some examples are shown below. These are interesting as they were captured over an area with a thick cover of green vegetation, perfect for NDVI analysis. Next jobs are to a) keep modifying the UAV to extend the flight time and perhaps add some additional sensors, and b) test the software that will stitch the images and analyse the spectral information…

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The same area imaged in five spectral bands using the red-edge camera on the UAV. 1 = blue (475nm) 2 = green (560 nm) 3 = red (668 nm) 4 = NIR (840 nm) 5 = red-edge (717nm)

Challenges in quantifying ‘bioalbedo’

On Wednesday last week I traveled to the University of Bristol to give a seminar at the Centre for Glaciology. I presented a new physical model for the spectral albedo of ice with algal growth, along with some field data from 2016. Preparing for the talk, discussions with fellow researchers and insightful questions in the Q&A all reinforced some key issues that remain unresolved in bioalbedo studies – fundamental questions that have proven difficult to answer. First, do algae darken ice? Second, are they widespread enough to have ice sheet scale impact?

The answer to the first question is a clear yes. That dark materials contaminating an ice surface lower its albedo is not surprising. However, the crucial follow-up question is “by how much?” and this is much more challenging to answer; however, physical modelling provides a clear framework for determining the impact of an algal bloom on ice albedo. With sufficient information from empirical lab and field studies, we can quantify the bioalbedo effect and characterize its variability over space and time.

Standing in the so called ‘dark zone’ on the Greenland ice sheet, the answer to the second question also seems to be a clear ‘yes’. The ice surface is dark for as far as the eye can see in all directions, and wherever ice is sampled and examined under the microscope, it is found to be teeming with algal cells. However, what is visible from standing in the dark zone and what is important at the ice-sheet scale are two different things. To quantify algal coverage over the ice sheet we need to be able to detect blooms remotely, ideally from space using spectral data from satellites. This method of mapping is routine for terrestrial vegetation and algal blooms in the ocean; however, there are specific challenges to doing the same for algal blooms on ice.

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A field camp in the ‘dark zone’ on the Greenland ice sheet, where the surface is darkened by expansive, dense algal blooms along with other impurities.

 

The most common way to identify photosynthetic life in satellite reflectance data is to apply the ‘red-edge’ biomarker. This refers to a sharp rise in the reflectance spectrum of a surface due to vegetation because of efficient absorption by chlorophyll and very little absorption at near-infrared wavelengths (which has been suggested to be the result of evolutionary pressure to avoid overheating, or alternatively a side-effect of the evolution of cell-spacing in early aqueous plants). This has also been proposed as a spectral feature that could be used to map photosynthetic life on other planets. Amazingly, the red-edge has been detected in Earth-shine (light that has reflected multiple times between the Earth and moon and faintly illuminates the dark part of crescent moons), which provides a hemisphere-integrated reflectance signal for our planet. Since ice algae is photosynthetic, it follows that it could be mapped using the red-edge biomarker.

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The ‘red-edge’ in the reflectance spectrum for green vegetation. This diagram is from Seager and Ford (2002)

However, there are several issues that may complicate matters and increase the risk of a ‘false-positive’ result from applying the red-edge biomarker to Earth’s ice. These are

1. Carotenoids obscuring chlorophyll

Ice algae produce photoprotective carotenoid pigments that absorb over a wide range of visible wavelengths. They have a strong but broad absorption spectrum (which is why they protect the algae from ‘sunburn’). This could obscure the chlorophyll ‘bump’ near 500 nm and make interpretation of the red-edge more difficult. While the carotenoids themselves might provide a diagnostic reflectance spectrum, they too are hard to distinguish from other reflectance-reducers on ice.

2. Dust

Dust also absorbs strongly in visible wavelengths and also reflects effectively at red wavelengths, leading to a pseudo-red-edge feature in the reflectance spectrum. The precise shape of the reflectance spectrum varies for each mineral, and actually no mineral exactly replicates the vegetation red-edge signal. However, dust on ice is not composed of a single mineral, and both the dust and any biological impurities are mixed together and set in a complex ice matrix with its own reflectance spectra. It is feasible that the slope of the red-edge might be diagnostic of biological impurities, but this requires truly hyperspectral (i.e. spectral resolution of 1-2 nm) and will not be achievable using current satellite data. These issues combined lead to a high chance of a false positive result from the application of the red-edge biomarker to ice surfaces. This is especially important for explaining the ‘dark ice’ on the Greenland ice sheet since the two leading hypotheses are biological growth and outcropping dust.

3. Spatial integration reducing signal

An additional important issue is that any biomarker signal will be diluted by spatial integration over the viewing footprint of a satellite sensor. The presence of clean ice, ponded water, cryoconite, abiotic impurities or roughness elements will decrease the signal to noise ratio, probably further obscuring the red-edge signal.

These issues do not necessarily prohibit the use of the red-edge biomarker, but they do necessitate robust correction for abiotic impurities (particularly dusts) and rigorous ground truthing to validate the application of the biomarker to satellite data. There was a fascinating discussion in the planetary sciences in the early-mid twentieth century surrounding a reflectance signal detected on Mars which spread to cover wider areas each spring. This was proposed to be evidence of Martian plant life (e.g. Lowell, 1911); however, this hypothesis was discredited by further spectral analysis (Millman, 1939) and was then shown to be due to blowing dusts (Sagan and Pollack, 1969).

While physical modelling paired with ground reflectance measurements and sample analysis can answer the first fundamental question (do algae darken ice?), the second question (are they widespread enough to have an albedo-lowering effect at the ice sheet scale?) may prove challenging to answer robustly.

Refs:

Arnold, (2008) https://link.springer.com/article/10.1007%2Fs11214-007-9281-4

 

Lowell, P. (1911) The cartouches of the canals of Mars. Lowell Obs. Bull. 1(12), 59–86.

Millman, P.M. (1939) Is there vegetation on Mars? Sky 3, 10–11.

Sagan, C. and Pollack, J.B. (1969) Windblown dust on Mars. Nature 223, 791–794.

Seager and Ford (2002): https://arxiv.org/abs/astro-ph/0212550

Seager et al (2005) https://www.cfa.harvard.edu/~kchance/EPS238-2012/refdata/Seager-red-edge-2005.pdf