Alfred Wegener Institute and University of Alberta

Airborne EM ice thickness

Airborne Electromagnetic Induction Estimates of Ice plus Snow Thickness

Alfred Wegener Institute for Polar and Marine Research
and York University
Dr. Christian Haas and Dr. Stefan Hendricks
Principal contacts

Dr Christian Haas, email: Christian.Haas at

Dr. Stefan Hendricks, email: stefan.hendricks at


Airborne electromagnetic induction measures snow+ice thickness

EM sounding is a classical geophysical method to detect the distance between an EM instrument and the boundary between the resistive sea ice and the conductive sea water, i.e. its altitude above the ice/water-interface. The method is based on measurements of the amplitude and phase of a secondary EM field induced in the seawater by a primary field transmitted by the EM instrument. Surveys are usually performed with a towed sensor package, which is operated some tens of meters below the aircraft and 20 m above the ice. The Bird’s altitude above the snow or ice surface is measured with a laser altimeter. Ice-plus-snow thickness results from the difference between the altitude above the ice/water-interface and above the snow or ice surface [Haas et al., 2009]. The accuracy of EM measurements is ±0.1 m over level ice [Pfaffling et al., 2007; Haas et al., 2009]. However, the maximum thickness of pressure ridges is generally underestimated due to their porosity and the EM footprint diameter of up to 3.7 times the instrument altitude [Reid et al., 2006]. The measured thickness of unconsolidated ridges can be less than 50% of the “true” thickness [e.g., Haas and Jochmann, 2003]. Therefore, the measured thickness distributions are most accurate with respect to their modal thickness, while mean ice thickness can still be used for relative comparisons between regions and campaigns.

Arctic Ocean and Fram Strait
Time interval
Data processing notes
Data were processed and calibrated by Dr. Haas. Statistical summaries and PDFs for 50-km clusters were computed and by R. Lindsay and Axel Schweiger, PSC, from the point data. Where the tracks overlap or bend, more than 50 km of track is included in many clusters. When flights spaned a few days in a small region, the flights were combined when the clusters were formed.
Number of samples
5123374 point measurements, 455 cluster averages, 24 campaigns
  V20160513: added PAM-ARCMIP 2015, 47 clusters

Point data

Some of the point data were reformated so that the formats are uniform for the different files and missing values are removed. There are 11 columns of data, the variables are ['year','mth','dom','yday','hour','lat','lon', 'fid', 'dist', 'alt','thick'], and the format is '(4i5,3f11.5,i7, f9.1, 2f9.3 )'. Some variables are set to constants in some of the files.

year = year of observation
month = month
dom = day of month
yday = year day
hour = GMT hour
lat = degrees north
lon = degrees east
fid = sequential observation identifier
dist = dist from the start of each flight leg (km)
alt = instrument altitude (m)
thick = sea ice thickness (m)


Method (use this one as a general reference if you use the data):
Haas, C., Lobach, J., Hendricks, S., Rabenstein, L., Pfaffling, A. (2009). Helicopter-borne measurements of sea ice thickness, using a small and lightweight, digital EM system, Journal of Applied Geophysics, 67(3), 234-241.

Other citations:
Pfaffling, A., Haas, C., Reid, J. E. (2007). A direct helicopter EM sea ice thickness inversion, assessed with synthetic and field data, Geophysics, 72, F127-F137.

Ark 17, 20, 22, NP_07:
Haas, C., Pfaffling, A., Hendricks, S., Rabenstein, L., Etienne, J.-L., Rigor, I. (2008). Reduced ice thickness in Arctic Transpolar Drift favors rapid ice retreat, Geophys. Res. Lett., 35, L17501.

GreenICE 2004 2005:
Haas, C., Hendricks, S., Doble, M. (2006). Comparison of the sea ice thickness distribution in the Lincoln Sea and adjacent Arctic Ocean in 2004 and 2005, Annals of glaciology,44, 247-252.

Ark 19:
Haas, C., J. Lieser, J. Lobach, T. Martin, A. Pfaffling, S. Willmes, V. Alexandrov, and S. Kern (2004), Sea ice remote sensing, thickness profiling, and ice and snow analyses, In U. Schauer and G. Kattner with contributions of the participants (Eds.), The Expedition ARKTIS XIXl1 a, b and XIW2 of the Research Vessel POLARSTERN in 2003, Rep. Pol. Mar. Res., 481, pp 13-46, ISSN 1618 - 3193.

SEDNA: The Sea Ice Experiment: Dynamic Nature of the Arctic
Jennifer K. Hutchings, The Sea Ice Experiment: Dynamic Nature of the Arctic(SEDNA) Applied Physics Laboratory Ice Station (APLIS) 2007, Field Report pdf file
Funding Agency: NSF

BREA: Beaufort Region Environmental Assessment
(data provided by Christian Haas)

SIZONet & PAM-ARCMIP: 2007-2015
(Seasonal Ice Zone Observing Network, Pan-Arctic Measurements and Arctic Regional climate model simulations), Netcare (AWI)
PAM-ARCMIP report, Funding Agency (SIZONet): NSF
Haas, C., S. Hendricks, H. Eicken, and A. Herber (2010), Synoptic airborne thickness surveys reveal state of Arctic sea ice cover, Geophys. Res. Lett., 37, L09501, doi:10.1029/2010GL042652.

Russian-German Cooperation: The Transdrift l Expedition to the Laptev Sea
Field report
Please contact Thomas Krumpen (
Funding Agency: BMBF (German Federal Ministry of Education and Research)


German Federal Ministry of Education and Research

National Science Foundation


Diagram of airborne electromagnetic induction measurement system

airboren em diagram


Map of the location of each cluster from each campaign

Campaigns mapped individually (click to enlarge)

Date of each campaign


Boxplots of ice thickness for each cluster for each campaign

ARF17 box plots
Ark 19 box plots
Ark 20 box plots
Ark 22 box plots
GreenICE 04 box plots
GreenICE 05 box plots
CryoVex 06 box plots
NP 04 box plots

Box plots show the median (black) and the 5th, 25th, 75th, and 95th percentile values for each cluster of each campaign. The star marks the mode. Click on an image to see an enlarged view.