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Mark Wensnahan

Senior Physicist





Research Interests

Science Education Outreach, Sea Ice Remote Sensing


Mark Wensnahan is currently part of a project to produce a 49-year record of arctic sea-ice draft measured by U.W. Navy submarines. Dr. Wensnahan has also conducted research on the use of passive microwave satellite data for determining sea ice extent and thickness, and the associated fluxes of heat and mass. Dr. Wensnahan joined the Laboratory in 1998.

Department Affiliation

Polar Science Center


Sc.B. Physics, University of Washington, 1988

M.S. Atmospheric Sciences, University of Washington, 1991

Ph.D. Atmospheric Sciences, University of Washington, 1995


2000-present and while at APL-UW

Evaluation of seven different atmospheric reanalysis products in the Arctic

Lindsay, R., M. Wensnahan, A. Schweiger, and J. Zhang, "Evaluation of seven different atmospheric reanalysis products in the Arctic," J. Clim., 27, 2588-2606, doi:10.1175/JCLI-D-13-00014.1, 2014.

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1 Apr 2014

Atmospheric reanalyses depend on a mix of observations and model forecasts. In data-sparse regions such as the Arctic, the reanalysis solution is more dependent on the model structure, assumptions, and data assimilation methods than in data-rich regions. Applications such as the forcing of ice%u2013ocean models are sensitive to the errors in reanalyses. Seven reanalysis datasets for the Arctic region are compared over the 30-yr period 1981–2010: National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research Reanalysis 1 (NCEP-R1) and NCEP–U.S. Department of Energy Reanalysis 2 (NCEP-R2), Climate Forecast System Reanalysis (CFSR), Twentieth-Century Reanalysis (20CR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF Interim Re-Analysis (ERA-Interim), and Japanese 25-year Reanalysis Project (JRA-25). Emphasis is placed on variables not observed directly including surface fluxes and precipitation and their trends. The monthly averaged surface temperatures, radiative fluxes, precipitation, and wind speed are compared to observed values to assess how well the reanalysis data solutions capture the seasonal cycles. Three models stand out as being more consistent with independent observations: CFSR, MERRA, and ERA-Interim. A coupled ice–ocean model is forced with four of the datasets to determine how estimates of the ice thickness compare to observed values for each forcing and how the total ice volume differs among the simulations. Significant differences in the correlation of the simulated ice thickness with submarine measurements were found, with the MERRA products giving the best correlation (R = 0.82). The trend in the total ice volume in September is greatest with MERRA (–4.1 ± 103 km3 decade-1) and least with CFSR (–2.7 ± 103 km3 decade-1).

Analysis of the Arctic system for freshwater cycle intensification: Observations and expectations

Rawlins, M.A., et al., including M. Steele, C.M. Lee, M. Wensnahan, and R. Woodgate, "Analysis of the Arctic system for freshwater cycle intensification: Observations and expectations," J. Clim., 23, 5715-5737, doi:10.1175/2010JCLI3421.1, 2010.

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1 Nov 2010

Hydrologic cycle intensification is an expected manifestation of a warming climate. Although positive trends in several global average quantities have been reported, no previous studies have documented broad intensification across elements of the Arctic freshwater cycle (FWC). In this study, the authors examine the character and quantitative significance of changes in annual precipitation, evapotranspiration, and river discharge across the terrestrial pan-Arctic over the past several decades from observations and a suite of coupled general circulation models (GCMs). Trends in freshwater flux and storage derived from observations across the Arctic Ocean and surrounding seas are also described.

Thinning and volume loss of the Arctic Ocean sea ice cover: 2003-2008

Kwok, R., G.F. Cunningham, M. Wensnahan, I. Rigor, H.J. Zwally, and D. Yi, "Thinning and volume loss of the Arctic Ocean sea ice cover: 2003-2008," J. Geophys. Res., 114, doi:10.1029/2009JC005312, 2009.

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7 Jul 2009

We present our best estimate of the thickness and volume of the Arctic Ocean ice cover from 10 Ice, Cloud, and land Elevation Satellite (ICESat) campaigns that span a 5-year period between 2003 and 2008. Derived ice drafts are consistently within 0.5 m of those from a submarine cruise in mid-November of 2005 and 4 years of ice draft profiles from moorings in the Chukchi and Beaufort seas. Along with a more than 42% decrease in multiyear (MY) ice coverage since 2005, there was a remarkable thinning of ~0.6 m in MY ice thickness over 4 years. In contrast, the average thickness of the seasonal ice in midwinter (~2 m), which covered more than two-thirds of the Arctic Ocean in 2007, exhibited a negligible trend. Average winter sea ice volume over the period, weighted by a loss of ~3000 km3 between 2007 and 2008, was ~14,000 km3. The total MY ice volume in the winter has experienced a net loss of 6300 km3 (>40%) in the 4 years since 2005, while the first-year ice cover gained volume owing to increased overall area coverage. The overall decline in volume and thickness are explained almost entirely by changes in the MY ice cover. Combined with a large decline in MY ice coverage over this short record, there is a reversal in the volumetric and areal contributions of the two ice types to the total volume and area of the Arctic Ocean ice cover. Seasonal ice, having surpassed that of MY ice in winter area coverage and volume, became the dominant ice type. It seems that the near-zero replenishment of the MY ice cover after the summers of 2005 and 2007, an imbalance in the cycle of replenishment and ice export, has played a significant role in the loss of Arctic sea ice volume over the ICESat record.

More Publications

The decline in Arctic sea-ice thickness: separating the spatial, annual, and interannual variability in a quarter century of submarine data

Rothrock, D.A., D.B. Percival, and M. Wensnahan, "The decline in Arctic sea-ice thickness: separating the spatial, annual, and interannual variability in a quarter century of submarine data," J. Geophys. Res., 113, doi:10.1029/2007JC004252, 2008.

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3 May 2008

Naval submarines have collected operational data of sea-ice draft (93% of thickness) in the Arctic Ocean since 1958. Data from 34 U.S. cruises are publicly archived. They span the years 1975 to 2000, are equally distributed in spring and autumn, and cover roughly half the Arctic Ocean. The data set is strong: we use 2203 values of mean draft, each value averaged over a nominal length of 50 km. These values range from 0 to 6 m with a standard deviation of 0.99 m. Multiple regression is used to separate the interannual change, the annual cycle, and the spatial field. The solution gives a climatology for ice draft as a function of space and time. The residuals of the regression have a standard deviation of 0.46 m, slightly more than the observational error standard deviation of 0.38 m. The overall mean of the solution is 2.97 m. Annual mean ice draft declined from a peak of 3.42 m in 1980 to a minimum of 2.29 m in 2000, a decrease of 1.13 m (1.25 m in thickness). The steepest rate of decrease is –0.08 meters per year (m/a) in 1990. The rate slows to –0.007 m/a at the end of the record. The annual cycle has a maximum on 30 April and a peak-to-trough amplitude of 1.06 m (1.12 m in thickness). The spatial contour map of the temporal mean draft varies from a minimum draft of 2.2 m near Alaska to a maximum just over 4 m at the edge of the data release area 200 miles north of Ellesmere Island.

The accuracy of sea ice drafts measured from U.S. Navy submarines

Rothrock, D.A., and M. Wensnahan, "The accuracy of sea ice drafts measured from U.S. Navy submarines," J. Atmos. Ocean. Technol., 24, 1936-1949, 2007.

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1 Nov 2007

Navy submarines in the Arctic Ocean routinely obtain observations from an upward-looking sonar of the draft of the sea ice cover overhead. Draft data are now publicly available from some 40 cruises from 1975 to 2000 covering over 120 000 km of track in roughly the central half of the Arctic Ocean. To apply these observations to geophysics, error estimates are needed. This paper assesses how well the correction of the data during normal processing accounts for the major sources of error in the draft data from U.S. Navy submarines and what errors remain in the data. The error treated is the error for the average draft over tens of kilometers. The following sources of error are considered: measurement precision error; errors in identifying open water (as ice of zero draft); sound speed error; errors caused by variable sonar footprint size, by uncontrolled gain and thresholds, and by ship's trim; and differences between data from analog charts and digitally recorded data. The bias with respect to the actual draft is 29 cm and is important both for knowing the actual ice draft and for comparing drafts from submarines with thicknesses in models and with draft, thickness, or freeboard estimated by other vehicles and technologies. The standard deviation is 25 cm. This number estimates the repeatability and comparability of draft measurements by U.S. Navy submarines and is important for examining the submarine data for regional and temporal variation. These errors are tolerable for an operational data source with a signal many meters in amplitude.

New arctic sea ice draft data from submarines

Wensnahan, M., D. Rothrock, and P. Hezel, "New arctic sea ice draft data from submarines," Eos, Trans. AGU, 88, 55, doi:10.1029/2007EO050003, 2007.

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30 Jan 2007

Arctic sea ice thickness data from 17 newly processed submarine cruises covering over 49,000 kilometers of cruise track have now been added to the archive at the National Snow and Ice Data Center (NSIDC). This addition increases the archive by 68%, to a total of over 120,000 kilometers of track from 37 U.S. Navy and 2 Royal Navy submarine cruises. The data are actually of ice draft, the submerged portion of floating sea ice, which is about 89% of ice thickness.

Declines in Arctic sea ice extent and thickness in recent decades make this an invaluable data set for research into Arctic climate variations, for testing sea ice models, and for intercomparison with measurements of thickness by other methods.

Sea-ice draft from submarine sonar: Establishing a consistent record from analog and digitally recorded data

Wensnahan, M., and D.A. Rothrock, "Sea-ice draft from submarine sonar: Establishing a consistent record from analog and digitally recorded data," Geophys. Res. Lett., 32, 10.1029/2005GL022507, 2005

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11 Jun 2005

Measurements of arctic sea-ice draft have been taken by Navy submarines for nearly five decades. The data are in two inherently different forms, analog paper charts and digitally recorded data. "Raw" analog drafts digitized from paper charts are biased toward thicker ice by over 30 cm compared with the digital drafts. This is due to the coarser temporal resolution of the paper charts compared the digital data. We examine coincident analog and digital data to determine how they can be made equivalent in mean draft and draft distribution (the histogram of draft vs. fractional frequency of observation). Image processing techniques are used to thin vertical features in the scanned chart images; this produces a "final" analog mean draft that is essentially unbiased (2 ± 6 cm) relative to the digital mean and final draft distributions that are in good agreement.

Correcting the Ice Draft Data from the SCICEX '98 Cruise

Dickinson, S., M. Wensnahan, G. Maykut, and D. Rothrock, "Correcting the Ice Draft Data from the SCICEX '98 Cruise," APL-UW TM 5-02, June 2002.

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30 Jun 2002

A solution is presented for correcting the data collected by the digital ice profiling system (DIPS) from the first half of the SCICEX '98 cruise. The ice draft measurements are intrinsi- cally related to the depth of the submarine and were corrupted by faulty measurements of depth. The ship's digital depth detector measured the gross movements of the submarine, but was unresponsive to small changes in depth associated with the natural porpoising of the boat. This porpoising, which is a periodic vertical movement of the submarine of several feet, was transferred to the ice draft data. An independent sensor package, the Icecat2, collected pressure data, which were converted to depth. The DIPS and Icecat2 systems had different clocks. To align them the depth signatures from each system were compared during large, rapid descents of the submarine. A time-dependent time offset between the two clocks was computed. By removing the DIPS depths from the ice draft measurements and replacing them with the depths measured by the Icecat2 system, the ice draft data were corrected.

Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center