ASA's Operation
IceBridge Data Brings New Twist to Sea Ice Forecasting
Dec. 19, 2012 — Shrinking Arctic sea ice grabbed
the world's attention again earlier this year with a new record low minimum.
Growing economic activity in the Arctic, such as fishing, mineral exploration
and shipping, is emphasizing the need for accurate predictions of how much of
the Arctic will be covered by sea ice. Every June, an international research
group known as the Study of Environmental Arctic Change (SEARCH) publishes a
summary of the expected September Arctic sea ice minimum known as the Sea Ice
Outlook. The initial reports and monthly updates aim to give the scientific
community and public the best available information on sea ice.
In a paper published last month in the journal Geophysical
Research Letters, Ron Lindsay, IceBridge science team member and Arctic
climatologist with the Polar Science Center at the University of Washington in
Seattle, outlined efforts to use IceBridge data to improve the accuracy of
seasonal sea ice forecasts. Lindsay and colleagues used a new quick look sea
ice data product that IceBridge scientists released before the end of the
Arctic campaign earlier this year. The quick look data, intended for use in
time-sensitive applications like seasonal forecasts, supplements the final sea
ice data product typically released roughly six months after the campaign. By
using new data processing techniques, IceBridge scientists were able to publish
the quick look measurements in a matter of weeks. "The idea was to make
the data available for anyone to use for the Sea Ice Outlook," said sea
ice scientist Nathan Kurtz of NASA's Goddard Space Flight Center in Greenbelt,
Md.
The work outlined in Lindsay's paper marks the first use of
IceBridge quick look data in an ensemble sea ice forecast (computer) model.
"An ensemble forecast is where you run a single forecast model many
different times," said Lindsay. In this case, they ran the Pan-Arctic Ice
Ocean Modeling and Assimilation System (PIOMAS) model seven times using conditions
from previous summers. PIOMAS uses sea ice extent, the area of sea containing
sea ice, and atmospheric data to simulate ice and ocean conditions.
IceBridge data and thickness measurements made by the
Seasonal Ice Zone Observing Network (SIZONet), a multidisciplinary project
aimed at observing Arctic sea ice, served as a way to correct initial sea ice
conditions. These initial measurements come from running the forecast model
with historical atmospheric conditions. Lindsay and colleagues used IceBridge
and SIZONet data to adjust these measurements and then used the PIOMAS model to
create a forecast of September's mean sea ice extent. To make sure what effect
the corrected measurements had, they also ran the model as normal, something
known as a control run.
Careful
Measurements
Before this forecasting work could begin though, the
researchers had to gather and process data, something that takes the hard work
of many people. During March and April of 2012, IceBridge gathered sea ice
thickness data using four different airborne science instruments.
First, researchers measure the surface freeboard, or the
amount of ice and snow above the sea level height, using a laser altimeter
known as the Airborne Topographic Mapper (ATM). Next, they use snow thickness
data derived from airborne snow radar and subtract that to get an accurate ice
freeboard measurement. This figure is then combined with known average density
measurements to calculate total ice thickness, of which freeboard is typically
only 10 percent. One other instrument, the KT-19 temperature sensor, was used
to detect leads, or openings, in sea ice, which are used to determine the sea
level height.
SIZONet scientists used a different method, measurements
from a helicopter-borne electromagnetic sensor that detects differences in how
well sea ice and ocean water conduct electricity, giving a distance between the
sensor and ocean water below.
Collecting measurements is only the beginning of the work.
Measurements from the ATM laser have to be combined with information from the
aircraft's GPS and inertial navigation systems and the readings have to be
filtered to remove things like false returns from low clouds and fog. Preparing
instrument data for release is a labor-intensive and time-consuming process that
normally takes six months. With the quick look product, it was done in a matter
of weeks.
Producing quality data so quickly is challenging, but the
process proved a good test of the instrument team's talents. "We gained
some valuable insights into our capabilities," said ATM senior scientist
John Sonntag. "This new confidence in the quick data may open new avenues
for us in the future."
Looking
Forward
The September mean ice extent for the corrected model were
slightly closer to the actual result than the control forecast run, but both
were fairly far off from the actual record minimum. This may have been due to
unusual weather over the summer, including a large Arctic storm in August, or
to deficiencies in the model simulation of the new very thin ice conditions of
the Arctic. Lindsay said winds have a bigger impact on the thinner ice of
recent years than on thick ice. It may be possible to redo this experiment,
using this summer's atmospheric conditions in the forecasts. "This would
tell us the impact of the observations for the weather we actually
experienced," said Lindsay.
As a step in a new direction, the study and quick look data
collection could improve sea ice forecasts in the future. Providing near
real-time sea ice data may also help in other areas, such as evaluating model
performance.
With plans to produce another quick look product in the
coming 2013 Arctic campaign, Kurtz is hopeful that IceBridge data will be
useful to sea ice forecasters and other researchers. "The question is how
will people use it," Kurtz said.
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