Category Archives: Computing

Exploring Greenland’s Coastal Currents: A Journey of Discovery with Icebreaker Polarstern

Posted on November 8, 2025 by | Leave a comment

Icebreaker Polarstern reached its home port of Bremerhaven in Germany just before Orkan “Joshua” hit northern Germany hard. The ship returned after 3 month at sea with 48 crew and 46 scientists working on ocean biology, chemistry, and physics. The 7-week expedition from Svalbard to Greenland and back to Germany culminated 3 years of planing and preparations led by the Alfred Wegener Institute (AWI). As one of 46 scientists I stepped onto the ship almost two months ago in Longyearbyen. We planned to explore what moves ice and fresh Arctic water into the Atlantic Ocean with sensors to probe the coastal circulation.  Analyzing these data, I will now live in Bremerhaven for a few months.

The map above shows where we went to the north of Greenland. I am coloring the coastal ocean shallower than 1000 m in light blue and the deeper ocean in dark blue. Our 2025 Polarstern data are the red symbols while yellow and blue symbols show data locations from 1964 ice island, 2007 icebreaker,  and 2013 helicopter surveys. This area contains the last and thickest sea ice of the Arctic Ocean and prior ocean observations originate from floating ice islands that both the Soviet Union and the U.S.A. used during the Cold War 1947-91 such as the Arlis-1964 track (yellow line). Helicopter surveys collected a few data in 2013 (blue symbols) while the Swedish icebreaker Oden collected data along two lines farther offshore (yellow symbols).

Now how does Greenland look from the ship? Well, there is always ice and it is always cold. The coldest days we had near the coast when the skies were clear. The coldest day we had -20 C, that is -4 F for my American friends, but most of the time we had clouds and storms with temperatures warmer at -12 C (10 F) with clouds and little visibility. It snowed alot and shoveling the ship’s deck was an almost daily chore. A relaxing “cruise” it was not. We worked sensors systems in the windy cold outside during all hours of the day and night. Pictures like the above were almost always taken during my 8 hours “off” that for me was from 08:00 to 16:00, because my shift was from 16:00 to 24:00. After a phone call to my wife after midnight and a peppermint tea to warm up, I slept from 01:00 to breakfast at 07:30. As almost all scientists aboard I shared my cabin with others, so there is not too much privacy. The photos below show my bunk bed (I slept atop), shared work spaces, and the rarely empty dining room. We often ate in shifts, too, because not all 50 people would fit the dining room in one sitting. So we often had 2 sittings. A comfortable living room was next door for desert, tea, coffee, games, and conversations.

Now what about science, you may ask. Here we made a major discovery, I felt. A mathematician used her craft to predict a coastal current to the north of Greenland that, I admit, made no sense to me as it contradicted 30+ years of training and intuition in which direction such currents would flow, that is, the coast should be on the right hand side looking in the direction of the flow. The curious thing was that to the north of Greenland it should go in the opposite direction, that is, with the coast on the left. In Claudia’s numerical computer model run for months on super computers, this current-in-the-wrong-direction was a both prominent and persistent feature. I always discarded it as an unrealistic feature of some computer code run amok. And yet, when we actually reach the coast of northern Greenland and I measure ocean currents from a ship sensor that runs 24/7 to tell me current speed and direction, here this weired or “wrong” current was. It screamed at me from the screen the moment I plotted the data and shared it with Claudia who was aboard with the comment: “Your model is right and my intuition was wrong. Your current is at the same location, the same speed, and in the same direction as your model said it would.” Furthermore, a distinct and separate way to estimate ocean currents from ocean temperature and salinity observations showed the exact same thing. That’s now two good complementary confirmation of the current that nobody has ever seen or measured … until now that we aboard Polarstern did so on Sept.-23, 2025:

The map on the left shows our study area to the north of North Greenland. On it in red are sticks whose length indicate the speed or strength of the ocean current (at 56 meters below the surface) while its orientation gives the direction of the current. The light blue is shallow and dark blue is deep water as before. The current is sluggish offshore with a weak component to the south. In contrast, closest to the coast of North Greenland we find long sticks that point to towards the left (west by north-west). This is Claudia’s Coastal Current.

The two plots on the left provide more detail, as it shows how the current varies with depth and distance from the coast along a line from the coast towards offshore. The bottom of the shallow ocean is the black line from 100-m to 350-m meter at a distance of 20-40 km from the coast. The top-left panel shows the current (in colors) across the section where blue colors indicate currents flow into the page while red colors indicate currents that flow out of the page towards us viewing it with the coast on the left. The bottom-left panel shows the velocity component along the section with a flow that is mostly onshore near the surface.

There is so much more to this story as well as additional stories, notice the red dots in the top-left panel between 150-m and 300-m depth that indicate a strong flow to the south and east, but I save this for later. I also do not wish to tell you about the two ocean sensors we quickly deployed at this location to stay there until we, perhaps, recover them with new data next year or the year there after. I do wish to close this essay, however, with the view of Greenland that we had where we discovered Claudia’s coastal current. Science is fun, exciting, and always surprises.

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Posted in Computing, Germany, Greenland, Ice Cover, Ice Island, Oceanography, Polar Exploration, Polarstern

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Greenland Ocean Expeditions, Science, and Fun

Posted on April 9, 2025 by | Leave a comment

Science and Greenland both combine discovery, adventure, and diverse people. I do this work free of academic constraints, responsibilities, and pay, because I retired from my university three months ago drawing on savings that accumulated since 1992 with my first job in San Diego, California. It was there and then, that my interest in polar physics started, but my first glimpse of Greenland had to wait until 1997 when a Canadian icebreaker got me to the edge of the ice in northern Baffin Bay between Canada and Greenland. It was a cold and foggy summer day as these pre-digital photos show:

Almost 25 years later I visited the area again with Her Danish Majesty Ship HDMS Lauge Koch, a Danish Navy vessel, which surveyed the coastal waters between Disko Bay in the south and Thule Air Base (now Pituffik Space Base) in the north. Two Danish goverment agencies led this expedition: the Geological Survey of Denmark and Greenland (Dr. Sofia Ribeirio, GEUS) and the Danish Metorological Institute (Dr. Steffen Olsen, DMI). Our small team of 11 scientists and 12 soldiers surveyed the seafloor with fancy acoustics, drilled into the bottom with piston corers, fished for plankton with towed nets, and collected water properties with both electronics and bottle samples. As this was during the Covid-19 pandemic, all scientists had to be both vaccinated and tested prior to boarding the flight from Copenhagen to Greenland. We also quarantined for 3 days in Aasiaat, Greenland prior to boarding the ship.

Now in retirement, I thoroughly enjoy the time to just just revisit the places and people via photos that finally get organized. More importantly, I finally feel free to explore the data fully that we collected both on 14 separate expeditions to Greenland between 1997 and 2021. For example, only in retirement did I discover that Baffin Bay was visited in 2021 by both a Canadian and an American in addition to our Danish ship. Data from these separate Baffin Bay experiments are all online and can be downloaded by anyone. I did so and processed them for my own purposes. Furthermore, NASA scientists of the Ocean Melts Greenland program flew airplanes all over Greenland to drop ocean sensors to profile and map the coastal ocean with fjords and glaciers hard to reach by ships. All these are highly complementary data that describe how icy glaciers, deep fjords, coastal oceans, and deep basins connect with each other and the forces that winds, sea ice, and abundant icebergs impose on them.

It requires a bit of skill and computer code, however, to process data from different ships, countries, and sensors into a common format to place onto a common map for different years, but here is one such attempt to organize:

There is one map for each of 9 years, i.e., station locations are shown in a top (2014, 2015, 2016), center (2017, 2018, 2019), and bottom row (2020, 2021, 1968). Land is gray with Canada on the left (west) and Greenland on the right (east) while the solid contour lines represent the 500-m and 1000-m water depth. Each colored symbol represents one station where the ship stopped to deploy a sensor package to measure temperature, depth, and salinity of the ocean water from the surface to the bottom of the ocean adjacent to the ship. The different colors represent data from Canada in red, Denmark in green, and USA in blue. The light blue color represents historical data from a study that investigated the waters after a nuclear armed B-52 bomber crashed into the ocean near Thule/Pituffik on 17 Jan. 1968 with one nuclear war head still missing. A Wikipedia story called 1968 Thule Air Base B-52 Crash provides details, references, and Cold War context, but lets return to the data and ocean physics:

Notice a single red dot near the bottom center of some maps such as 2015, 2017, or 2021. For this single dot I show the actual temperature and salinity data and how it varies with depth (labeled pressure, at 100-m depth the pressure is about 100 dbar) and from year to year:

The two bottom panels show how temperature (left) and salinity (right) change with depth (or pressure). Notice that the coldest water near freezing temperature of -1.8 degrees Celsius (29 Fahrenheit) occurs between 30-m and 200-m depth (30 to 200 dbar in pressure). Below this depth the ocean water actually becomes warmer to a depth of about 500-600 m to then become cooler again. The effects of pressure on temperature are removed, this is why I call this potential temperature and label it “Pot. Temp.” The warmest waters at 600-m depth are also the most salty (about 34.5 grams of salt per 1000 grams of water). This saltiness makes this water heavier and denser than the colder waters above. This is a common feature that one finds almost anywhere in polar regions. The top panel shows the same data without reference to depth (or pressure), but contours of density show how this property changes with temperature and salinity. It takes a little mental gymnastic to “see” how density always increases as pressure increases, but the main thing here is that both salinity and temperature can change the density of seawater.

Sketch of ocean current systems off Greenland and eastern Canada. Colors represent topography of ocean, land, and Greenland ice sheet.

U.S. Coast Guard, International Ice Patrol

The origin of the warmer (and saltier) waters is the Atlantic Ocean to the south. Currents move heat along the coast of Greenland to the north. Icebergs in Baffin Bay extend into this Atlantic Layer and thus move first north along the coast of Greenland before turning west in the north and then south along the coast of Canada. This deep ocean heat does reach coastal tidewater glaciers which are melted by this warm ocean water. So the year-to-year changes of temperature and salinity determine in part how much the coastal glaciers of Greenland melt. The temperature and salinity maxima change from year to year being warmest in 2015 and 2017 and coldest in 2019 and 2021. No “global warming” here, but notice what happens closer to the bottom at 1500-m, say. These waters are separated from the Atlantic and Arctic Oceans to the south and north by water depths that do not exceed 600-m in the south and 400-m in the north. These almost stagnant waters increase their temperatures steadily from 2003 to 2015 to 2017 to 2019 to 2021. This is the global warming signal.

My former student Melissa Zweng published a more thorough and formal study in 2006 using all then available data from Baffin Bay between 1916 and 2003. Her Figure-7 shows the results for those parts of Baffin Bay that are deeper than 2000-m for two different depth ranges. Notice that the year to year variations (up and down) is small, but a steady increase in temperature is apparent from perhaps -0.3 Celsius in 1940 to -0.05 in 2003 for the 1400-1600 m depth range. We also did a very formal error analysis on the straight line we fitted to the data and find that deep temperatures increase by +0.03 C/decade. We are 95% sure, that the error or uncertainty on this warming is +/- 0.015 C/decade. So there is a 1 in 20 chance, that our deep warming trend is below +0.005 C/decade and an equal 1 in 20 chance, that our warming trend exceed +0.045 C/decade. In 19 out of 20 cases the (unknown) true warming value is between 0.005 and 0.045 C/decade.

So, more than 20 years have passed since Melissa’s work. The data I here showed between 2003 and 2021 thus gives us a chance to test our statistical predictions that we made 20 years ago. So, deep temperatures should be between 0.01 and 0.09 degrees Celsius warmer than they were in 2003. I have not done this test yet, but science is fun even if the data are old.

After getting off the ship at Thule Air Base (now called Pituffik Space Base) in 2021, us scientists climbed Dundas Mountain to stretch our legs, take in the varied landscape, and view our ship and home for a week from a distance. Notice how small HDMS Lauge Koch at the pier appears. All photos below were taken by geophysicist Dr. Katrine Juul Andresen of Aarhus University, Denmark:

References:

Münchow, A., Falkner, K.K. and Melling, H.: Baffin Island and West Greenland Current Systems in northern Baffin Bay. Progr. Oceanogr., 132, 305-317, 2015.

Ribeiro, S., Olsen, S. M., Münchow, A., Andresen, K. J., Pearce, C., Harðardóttir, S., Zimmermann, H. H., & Stuart-Lee, A.: ICAROS 2021 Cruise Report. Ice-ocean interactions and marine ecosystem dynamics in Northwest Greenland. GEUS, Danmarks og Grønlands Geologiske Undersøgelse Rapport, 70, 2021.

Zweng, M.M. and Münchow, A.: Warming and Freshening of Baffin Bay, 1916-2003. J. GEOPHYS. RES., 111, C07016, doi:10.1029/2005JC003093, 2006.

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Posted in Computing, Global Warming, Greenland, History, Oceanography, Polar Exploration, sea ice, Thule

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Data Obsessions while in Self-Quarantine

Posted on April 2, 2020 by | 1 comment

I sit in my home office looking into a garden which explodes in yellow from the forsythia with splashes of pink from the camellias. Both flourish after a large shading cherry tree fell down a few years ago. The tree stump is covered by moss and provides a natural border. My native American Flame azaleas (Rhododendron calendulaceum) now stand 8 feet tall in front after I planted them in 2001 as 3 inch sticks. They are the pride of my garden along with Piedmont, Sweet, Okonee, and Plum azaleas all purchased from Callaway Gardens in Georgia. They grow well, because I correctly predicted that the warmer climate zones of Georgia would move northward towards Delaware. Here are the azaleas in blooms in early May or four weeks from now:

American native azaleas blooming in my garden in April and May.

These are distractions, because I need to process and analyze ocean velocity data off Greenland. My student from South Korea rightfully expects numbers that she can work with for her Masters degree. We plan to meet via Zoom video call every Friday and Wednesday. She is ordered to stay at home in Maryland while I am ordered to stay at home in Delaware. We also meet Monday and Wednesday evenings when I teach “Waves” via Zoom to eight University of Delaware graduate students from China, South Korea, Thailand, and the USA. Our topic yesterday was the waves in the wakes of a ship or a duck or an island. To me physics are as beautiful as are the flowers in my garden:

Now these are the things that I should work on during my self-quarantine, but I am obsessed and distracted with new data. The Johns Hopkins University in Baltimore, MD distributes data on the number of people who were diagnosed with Covid-19, who died of it, and who have recovered. While it is easy to access their excellent data displays as global health authorities report them, the actual raw digital data files are accessible at

https://github.com/CSSEGISandData/COVID-19

These data require computer programming and data handling skills that a well trained physical ocean, climate, or data scientist masters. The raw data, however, do not tell a story, because it just looks like gibberish,

but there is a most orderly system to this madness. With 143 lines of computer code (one C-shell and two awk scripts) I convert these data into a single graph to tell a story:

First, I focus only on the number of people who have died, because I consider this the most reliable (albeit morbid and depressing) estimate of how the virus is spreading.

Second, I present the number of people who died relative to the population. It hardly seems fair to compare the numbers from the USA with 327 million people to those of Malta with only 0.5 million people. The technical term is “normalization,” that is, all numbers are relative to 1 Million people. So, 5 dead in Malta give 10 dead per million. The same 10 dead per million correspond to 3270 dead Americans. This way I am comparing apples to apples as opposed to Americans to Maltese.

Third, I want to compare the spread of the pandemic over time on different continents, different countries, different states, and different cities. This requires to time-shift countries hit by the virus earlier than others. In the above graph, for example, I moved the curve for Italy 14-days forward and that of Spain 6-days forward relative to all other places listed.

Fourth, I am most interested in New York State (population 20 million), because it contains New York City (population 8 million) and, I believe, it gives Americans a good idea what is coming. Furthermore, I believe, that the Government of New York State is a little more efficient, smart, and forward-thinking than many other government entities. It also has resources not necessarily available to less affluent communities.

The curve for New York State initially (until Mar.-25) followed the trajectory of Italy 14 days earlier, but then it switched over to the steeper trajectory of Spain 6 days earlier. Notice that Italy’s curve has a flatter trajectory than the steep curve of Spain and New York State. From Mar.-28 to Mar.-31 the New York curve was almost exactly that of Spain 6 days ago, but yesterday, the number of people dying in New York grew even faster than those in Spain or Italy ever did. This is scary stuff.

Yesterday, New York State had about 111 dead per million people. While this is still less than the 180 dead per million people that both Italy and Spain had yesterday, it may take only 4-5 additional days for New York State to reach those numbers also, but I still do not know what these numbers mean. I do not “feel” them. So I try to compare them to other causes of death such as people getting killed every month in (a) car accidents (9 per million) or (b) gun violence (8 per million) or (c) cancer (126 per million). These references help me to visualize the scale and impact of this pandemic.

So, while Covid-19 has killed about as many people in the US the last 4 weeks as people died in car accidents, in New York State the number of Covid-19 dead is about to exceed those who died of cancer in this same period. The hardest hit place in the US, however, is not New York City (160 dead per million), but New Orleans (295 dead per million). The County or Parish of New Orleans, Louisiana has about 400,000 people or a little less than New Castle County in Delaware where I live, but New Orleans has 115 dead compared to 5 in New Castle County (9 dead per million).

There are a few bright spots and I want to close on those. Los Angeles (7 dead per million) and California (5 dead per million) are doing remarkable well as does Germany (11 dead per million). Despite physical separations from others, I feel closer to friends, family, and neighbors both overseas and across the street. With more than 10 feet distance we have impromptu get-togethers between the door and the end of the driveway of 4 different households. I am happy to know that my neighbor Joyce from Kenya is safe back home living quarantined across the street with her African friends from Mali. She runs Water for Life which is a small non-profit that provides clean drinking water for rural communities in Kenya. It makes me happy to know her as a neighbor across the street.

And then there are the true warriors who fight this virus while endangering themselves to help others. Here is a nurse from Spain whose photo at work I took from her Twitter feed. We are all surrounded by wonderful and beautiful people.

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Posted in Computing, health, Uncertainty

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Sea Ice from Satellite at 20-m Resolution

Posted on February 7, 2017 by | Leave a comment

I am a self-taught amateur on remote sensing, but it tickled my pride when a friend at NASA asked me, if I could tell a friend of his at NOAA on how I got my hands on data to produce maps of radar backscatter to describe how the sea ice near Thule Air Base, Greenland changes in time and space.

Wolstenholme Fjord, Greenland Feb.-5, 2017 from Sentinel-1 radar. The data are at 20-m resolution

Wolstenholme Fjord, Greenland Feb.-5, 2017 from Sentinel-1 radar. The data are at 20-m resolution

In about 4 weeks from today I will be working along a line near the red dots A, B, and C which are tentative locations to place ocean sensors below the sea ice after drilling through it with ice fishing gear. The colored line is the bottom depth as it was measured by the USCG Healy in 2003 when I was in Thule for the first time. Faint bottom contours are shown in gray.

I discovered the 20-m Sentinel-1 SAR-C data only 3 weeks ago. They are accessible to me (after making an account) via

https://scihub.copernicus.eu/dhus/#/home

where I then search for a specific geographic area and time frame using the following “product”

Product Type: GRD
Sensor Mode: IW
Polarization: HH

Screenshot on how I search for the Sentinel-1 SAR-C DATA.

Screenshot on how I search for the Sentinel-1 SAR-C DATA.

The more technical detail can be found at

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar

where one also finds wonderful instructional videos on how to work the software.

The data file(s) for a typical scene are usually ~800 MB, however, for processing I use the free SNAP software (provided by European Space Agency) via a sequence of steps that result in a geotiff file of about 7 MB.

Screenshot of SNAP software and processing with [1] input and [2] output of the Feb.-5, 2017 data from Wolstenholme Fjord.

Screenshot of SNAP software and processing with [1] input and [2] output of the Feb.-5, 2017 data from Wolstenholme Fjord.

This .tiff file I then read with Fortran codes to tailor my own (quantitative or analyses) purposes.

Start of Fortran code to covert the SNAP output geotiff file into an ascii file with latitude, longitude, and backscatter as columns. The code has 143 lines plus 80 lines of comment.

Start of Fortran code to covert the SNAP output geotiff file into an ascii file with latitude, longitude, and backscatter as columns. The code has 143lines plus 80 lines of comment.

The final mapping is done with GMT – General Mapping Tools which I use for almost all my scientific graphing, mapping, and publications.

Please note that I am neither a remote sensing nor a sea-ice expert, but consider myself an observational physical oceanographer who loves his Unix on a MacBook Pro.

Working the Night shift aboard CCGS Henry Larsen in the CTD van in Aug.-2012. [Photo Credit: Renske Gelderloos]

Working the Night shift aboard CCGS Henry Larsen in the CTD van in Aug.-2012. [Photo Credit: Renske Gelderloos]

If only my next problem, working in polar bear country with guns for protection, had as easy a solution.

Polar bear as seen in Kennedy Channel on Aug.-12, 2012. [Photo Credit: Kirk McNeil, Labrador from aboard the Canadian Coast Guard Ship Henry Larsen]

Polar bear as seen in Kennedy Channel on Aug.-12, 2012. [Photo Credit: Kirk McNeil, Labrador from aboard the Canadian Coast Guard Ship Henry Larsen]

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Posted in Computing, Greenland, Ice Cover, sea ice, Thule

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Sea ice and 2016 Arctic field work

Posted on June 15, 2016 by | 2 comments

The sea ice in the Arctic Ocean is quickly disappearing from coastal areas as we are entering the summer melt season. This year I follow this seasonal event with nervous anticipation, because in October and November we will be out at sea working north of northern Alaska. We plan to deploy a large number of ocean sensors to investigate how sound propagates from the deep Arctic Ocean on to the shallow Chukchi Sea. This figure shows our study area with the ice cover as it was reported yesterday from space:

Ice concentration for June 14, 2016 from SSM/I imagery. Insert show study area to the north of Alaska and planned mooring locations (red box).

Ice concentration for June 14, 2016 from SSM/I imagery. Insert show study area to the north of Alaska and planned mooring locations (red box).

Zooming in a little further, I show the coast of Alaska along with 100 and 1000 meter contour of bottom depth over a color map of ice concentrations:

Ice concentrations from SSM/I to the north of norther Alaska with planned mooring locations across the sloping bottom. The 100 and 1000 meter contours are shown in gray with blue and red symbols representing locations of ocean and acoustic sensors, respectively.

Ice concentrations from SSM/I to the north of norther Alaska with planned mooring locations across the sloping bottom. The 100 and 1000 meter contours are shown in gray with blue and red symbols representing locations of ocean and acoustic sensors, respectively.

My responsibilities in this US Navy-funded project are the seven densely packed blue triangles. They indicate locations where I hope to measure continuously for a year ocean temperature, salinity, and pressure from which to construct sections of speed of sound and how it varies in time and space. I will also measure ice draft as well ice and ocean currents from which to estimate the roughness of the sea ice over time. Sea ice and ocean properties both impact sound propagation from deep to shallow water and vice versa.

A first question: What will the ice be like when we get there? This is the question that has the 40 or so people all working on this project anxiously preparing for the worst, but how can we expect what challenges are to come our way?

Doing my homework, I downloaded from the National Snow and Ice Data Center all gridded maps of ice concentrations that microwave satellites measured almost daily since 1978. Then I crunch the numbers on my laptop with a set of kitchen-sink Unix tools and code snippets such as

set ftp = 'ftp://sidads.colorado.edu'
set dir = 'pub/DATASETS/nsidc0081_nrt_nasateam_seaice/north'
...
wget -r -nd -l1 --no-check-certificate $ftp/$dir/$year/$file

along with fancy and free Fortran and General Mapping Tools to make the maps shown above. With these tools and data I can then calculate how much sea ice covers any area at any time. The result for custom-made mooring area at almost daily resolution gives a quick visual that I use to prepare for our fall 2016 expedition. The dotted lines in the top panel indicate the dates we are in the area.

Time series of daily ice concentration in the study area for different decades from January-1 through Dec.-31 for each year from 1980 through 2015. Panels are sorted by decade. The red curve is for 2015 and is shown for comparison in all panels.

Time series of daily ice concentration in the study area for different decades from January-1 through Dec.-31 for each year from 1980 through 2015. Panels are sorted by decade. The red curve is for 2015 and is shown for comparison in all panels.

The story here is well-known to anyone interested in Arctic sea ice and climate change, but here it applies to a tiny spec of ocean between the 100 and 1000 meter isobath where we plan to deployed ocean sensors for a year in the fall of 2016. For the two decades of the last century, the ice cover looks like a crap shoot with 80% ice cover possible any month of the year and ice-free conditions unlikely but possible here or there for a week or two at most. The situation changed dramatically since about 2000. During the last six years our study area has always been free of ice from late August to early October, however, our 2016 expedition is during the transition from ice-free October to generally ice-covered early November, but, I feel, our saving grace is that the sea ice will be thin and mobile. I thus feel that we probably can work comfortable on account of ice for the entire period, but the winds and waves will blow us away …

Weather will be most uncomfortable, because fall is the Pacific storm season. And with little or only thin ice, there will be lots and lots of waves with the ship pitching and rolling and seeking shelter that will challenge us from getting all the work done even with 7 days for bad weather built into our schedule.

I worked in this area on larger ships in 1993, 2003, and in 2004. Here is a photo that Chris Linder of Woods Hole Oceanographic Institution took during a massive storm in the general vicinity in October of 2004. The storm halted all outside work on the 420 feet long USCGC Healy heading into the waves for 42 long and miserable hours:

Icebreaker taking on waves on the stern during a fall storm in the Beaufort Sea in October 2004. [Photo Credit: Chris Linder, Woods Hole Oceanographic Institution]

Icebreaker taking on waves on the bow during a fall storm in the Beaufort Sea in October 2004. [Photo Credit: Chris Linder, Woods Hole Oceanographic Institution]

Oh, I now also recall that during this four-week expedition we never saw land or the sun. It was always a drizzly gray ocean on a gray horizon. The Arctic Ocean in the fall is an often cruel and inhospitable place with driving freezing rain and fog.

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Posted in Chukchi Sea, Computing, Global Warming, Ice Cover, Oceanography

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