Ravens dominate the Kangerlussuaq landscape. Perhaps it is their deep ebony color and solid frame, or perhaps it is the white stillness of winter with little else but humans moving about, but whatever the cause the ravens are a recognized presence. The towering black hill rising above the glacially carved fjord is aptly named Raven Hill and boasts a steady circling of the mythical black winged creatures calling out in their raspy voices. With ravens being much a part of the region, it seems only fitting that our first flight would be to Raven Camp in search of deep enough ice to test the Deep Ice Radar system or “D-Ice” as it is referred to.
The day starts out a bit hazy and the weather is forecast to deteriorate during the day. Most flights have been cancelled, but the Icepod team has been cleared for flight if we can manage a departure by noon and return to base by 2 p.m. Sensor and equipment adjustments keep the team busy until mid morning, and weather maps are continually being consulted for updates. Several times the planning team reconfigures the flight lines looking for the optimal plan to maximize the testing of the equipment with available time and weather considerations. Our NYANG partners are as anxious for the flight to go as the Icepod team, but if there are any weather concerns, caution must override enthusiasm. With the camp being at a higher elevation than Kangerlussuaq, the weather can vary considerably from the base.
Raven Camp lies at close to 2000 meters (~6800 ft.) elevation, where the glacial ice is approximately 1800 meters thick. “Noise” in the radar system drops after 1200-1500 meters of ice thickness, so although the weather is poor, we are hoping to get to this ice thickness to run a first real test of the D-Ice. Unlike our optical systems, the radar is not affected by poor visibility, so this is the right decision for the flight today. The plane is loaded with cold weather emergency gear, standard protocol when flying in the polar regions, and we take off down Sondrestrom fjord, making the noon flight departure time.
This series of flights is designed for instrument testing, so the science team is troubleshooting as they fly. Every instrument is tested in the short two-hour flight, and procedures are reviewed. The sound in the aircraft is deafening and earplugs are mandatory, which makes communicating challenging, but communicating is an essential part of the testing.
The plane reached the edge of the deep ice and the aircraft lowers to a survey elevation of 900 meters (3000 ft.) above the surface flying along the ice contour. The radar system is up and recording. In too short a time, the plane has reached Raven Camp, but the poor weather conditions limit our ability to see the camp below. The aircraft turns and we head back to base. In our post-flight debrief, reviewing data takes a top priority for tomorrow. With a limited number of flight hours available, every flight is precious, so we need to be sure that assessment and adjustment is made to the instruments as we go.
For more on this program see: http://www.ldeo.columbia.edu/icepod
Icepod joined the first large wave of science teams headed to Greenland via the NYANG LC130 transport system. Four LC130 aircraft were packed to bursting with pallets of equipment, supplies and science teams anxious to get to their designated research locations. Planes one and three were designated for cargo load, plane two would carry the bulk of the science personnel, including half the Icepod team, and plane four would carry Icepod with its skeletal engineering support team. 5:00 a.m. pick-ups for the science members set up the planes for staggered departures every 30 minutes starting at 8:00 a.m. With a flight time of seven hours from Schenectady NY to Kangerlussuaq Greenland, an early departure facilitates moving through customs and getting settled with the science support staff that awaits the group in Greenland.
All the aircraft were packed from end to end with either cargo or personnel. While we waited for the pallets of cargo to be loaded onto the planes the science teams’ discussion focused on how Greenland’s ice will be dissected and examined in the upcoming season. One group will look at ice surface processes using ground penetrating radar and shallow ice cores starting at the Dye 2 location, another will drop into the high elevation Summit camp to start an overland traverse examining the ice (although we learned that nighttime temperatures are running at -50 degrees C, a bit too low currently for set up). A third group will examine the firn layer (that section in the ice that is just starting to compress) over Jakonbshavn glacier, and the Icepod team will be doing their first set of instrument test flights in polar conditions looking at the ice from the bed up to the ice surface.
The science personnel were finally loaded into Plane two, which had been divided across the middle of the main cabin, to accommodate cargo aft and science teams foreward packed knee to knee in two sets of facing rows. With this heavy load the aircraft would need to stop to refuel in Goose Bay, in Labrador, Newfoundland, Canada. Goose Bay Air Base, affectionately known by many as “The Goose”, was once home to Strategic Air Command’s 95th Strategic Wing. The ice cream served to the visitors of the airfield has become part of the travel lore of the teams en route to Greenland, so by the time the wheels touched down, everyone’s thoughts had moved from polar ice to ice cream. Two baskets full of assorted Good Humor truck style ice cream were quickly dispensed and we were back up in the air and underway for the last half of the journey.
When the west coast of Greenland came into view the sun was just peaking through the clouds lying low along the tops of the coastal mountains. The shadowy ridgeline just visible through the mist was a welcome sight after seven hours of flight. Tomorrow will be a day of setting up base stations and reviewing some of the transit data, then the Icepod project will launch into its first set of Greenland test flights.
For more information on the IcePod project: http:www.ldeo.columbia.edu/icepod
By Ana Camila Gonzalez
“You can do math on excel?” I ask. I immediately imagine a face-palm response, but Dario, one of my advisors, is nice enough to hide it. I’ve collected tree core samples, I’ve prepared them and cross-dated them. Now what?
Oh, right. The Science.
I guess I never really understood there could be so much involved in answering a question. When I imagine the scientific method I’ve learned since the sixth grade, I somehow imagine a question that can be answered with a yes or no. If I let go of this apple, will it fall to the ground? Hypothesis: yes, it will. Experiment: yes, it does. Conclusion: yes, it will. To the credit of my high school science teachers, it’s not that they didn’t make it perfectly clear that the why and the how are just as important as the yes or the no. I just couldn’t imagine that you’d have to explain why the apple falls with four different figures: haven’t you seen an apple fall too?
Dario is helping me understand how to analyze the data from the black oak samples I have already been working with for some time now. I know these samples. Or at least I think I know these samples. I’m learning there’s more to know about them than I initially thought.
We’re analyzing the climate response, which proves to be exactly what it sounds like. We have recorded measurements of climate (precipitation records, temperature records) and a proxy for tree growth (our ring width measurements!) and by comparing those we can see how a tree population responds to a range of climactic conditions. Alright. I can do this. I’ve made graphs before.
“So we’re going to find correlations,” says Dario.
“Click on an empty cell.” I start to make a scatter plot; I think what we’re going to do is look at the slope of a line of best fit.
“So we’re going to see if the correlation is positive or negative?” I ask.
“Yes, but we also have to see if the correlations are significant.” Isn’t any correlation higher than a zero significant? They’re showing a relationship.
Dario continues, “Any correlation above a 0.2 or so is significant for the hundred years of ring width and climate that you have for this analysis.” I learn how to use the =correl function to compare the populations to temperature and I have to say I’m disappointed. I thought 0.2 sounded so low, but some of my data is showing a much lower correlation, and the data that is significant only ranges from about really close to 0.2 to 0.38 or so. I wanted to see a 0.5 correlation like I did between tree samples within a species as I was cross-dating. Comparing precipitation to ring width gives me slightly higher correlations, a few in the 0.3 range, but I’m still feeling underwhelmed.
“No, but it’s still significant! It matters!” Dario tells me to make a scatter plot comparing precipitation to ring-width measurements over time at both sites. At first it looks like a ball of yarn, but as I mask the plot out I can see why those 0.3 correlations are significant. I follow each curve, visually skateboarding up and down the peaks and valleys and noticing that I’m going up and down a lot of very similar hills as I do so. What’s most rewarding is looking for years I know are drought years (1966 and 1954 were big droughts) and seeing relatively low measures of precipitation and ring width during those years. I knew while I was cross-dating that those years were important when I saw how small the rings were, but now I can prove it. Like the apple falling, I can’t just say that because I see the rings are small those were dry years. I have to compare it to precipitation records, temperature records, and, dare I say it, the Palmer Drought Severity Index (I have to admit I don’t entirely understand the mechanics behind the index, but I understand that dryness is a composite of precipitation and temperature forcings).
Dario, over multiple days, teaches me a few more nuances of Excel and helps me understand the ARSTAN program and how we use it to make our ring-width measurements more effective as proxies for tree growth. He mentions this would all be easier if I knew how to use R. I make a mental note: learning R is the next step. If I thought that was scary, now I have to put this information on a poster. That real people will see. At a real conference.
Neil shows me a few poster examples, and the message is clear. Show your data instead of describing it in words. That also means I’ll have to explain my data by actually… talking… about it. Gulp. The North East Natural History Conference is next weekend, but I feel like I’m ready. I understand the why and how after analyzing my data. At least I understand it enough to give an answer better than yes or no.
Ana Camila Gonzalez is a first-year environmental science and creative writing student at Columbia University at the Tree Ring Laboratory of Lamont-Doherty Earth Observatory. She will be blogging on the process of tree-ring analysis, from field work to scientific presentations.