[1] Uncertainty in the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) Arctic sea ice volume record is characterized. A range of observations and approaches, including in situ ice thickness measurements, ICESat retrieved ice thickness, and model sensitivity studies, yields a conservative estimate for October Arctic ice volume uncertainty of 1.35 × 103 km3 and an uncertainty of the ice volume trend over the 1979–2010 period of 1.0 × 103 km3 decade–1. A conservative estimate of the trend over this period is −2.8 × 103 km3 decade–1. PIOMAS ice thickness estimates agree well with ICESat ice thickness retrievals (<0.1 m mean difference) for the area for which submarine data are available, while difference outside this area are larger. PIOMAS spatial thickness patterns agree well with ICESat thickness estimates with pattern correlations of above 0.8. PIOMAS appears to overestimate thin ice thickness and underestimate thick ice, yielding a smaller downward trend than apparent in reconstructions from observations. PIOMAS ice volume uncertainties and trends are examined in the context of climate change attribution and the declaration of record minima. The distribution of 32 year trends in a preindustrial coupled model simulation shows no trends comparable to those seen in the PIOMAS retrospective, even when the trend uncertainty is accounted for. Attempts to label September minima as new record lows are sensitive to modeling error. However, the September 2010 ice volume anomaly did in fact exceed the previous 2007 minimum by a large enough margin to establish a statistically significant new record.

/pdf/uncertainty-in-modeled-arctic-sea-ice-volume-1pbx9p75m9.pdf

Uncertainty in modeled Arctic sea ice volume

. Sea ice thickness is a fundamental climate state variable that provides an integrated measure of changes in the high-latitude energy balance. However, observations of mean ice thickness have been sparse in time and space, making the construction of observation-based time series difficult. Moreover, different groups use a variety of methods and processing procedures to measure ice thickness, and each observational source likely has different and poorly characterized measurement and sampling errors. Observational sources used in this study include upward-looking sonars mounted on submarines or moorings, electromagnetic sensors on helicopters or aircraft, and lidar or radar altimeters on airplanes or satellites. Here we use a curve-fitting approach to determine the large-scale spatial and temporal variability of the ice thickness as well as the mean differences between the observation systems, using over 3000 estimates of the ice thickness. The thickness estimates are measured over spatial scales of approximately 50 km or time scales of 1 month, and the primary time period analyzed is 2000–2012 when the modern mix of observations is available. Good agreement is found between five of the systems, within 0.15 m, while systematic differences of up to 0.5 m are found for three others compared to the five. The trend in annual mean ice thickness over the Arctic Basin is −0.58 ± 0.07 m decade−1 over the period 2000–2012. Applying our method to the period 1975–2012 for the central Arctic Basin where we have sufficient data (the SCICEX box), we find that the annual mean ice thickness has decreased from 3.59 m in 1975 to 1.25 m in 2012, a 65% reduction. This is nearly double the 36% decline reported by an earlier study. These results provide additional direct observational evidence of substantial sea ice losses found in model analyses.

/pdf/arctic-sea-ice-thickness-loss-determined-using-subsurface-1wqnoablv7.pdf

Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations

Estimating Arctic sea ice thickness and volume using CryoSat-2 radar altimeter data

. Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness ranges. Satellite altimeters, such as CryoSat-2 (CS2), sense the height of the ice surface above the sea level, which can be converted into sea-ice thickness. Relative uncertainties associated with this method are large over thin ice regimes. Another retrieval method is based on the evaluation of surface brightness temperature (TB) in L-band microwave frequencies (1.4 GHz) with a thickness-dependent emission model, as measured by the Soil Moisture and Ocean Salinity (SMOS) satellite. While the radiometer-based method looses sensitivity for thick sea ice (> 1 m), relative uncertainties over thin ice are significantly smaller than for the altimetry-based retrievals. In addition, the SMOS product provides global sea-ice coverage on a daily basis unlike the altimeter data. This study presents the first merged product of complementary weekly Arctic sea-ice thickness data records from the CS2 altimeter and SMOS radiometer. We use two merging approaches: a weighted mean (WM) and an optimal interpolation (OI) scheme. While the weighted mean leaves gaps between CS2 orbits, OI is used to produce weekly Arctic-wide sea-ice thickness fields. The benefit of the data merging is shown by a comparison with airborne electromagnetic (AEM) induction sounding measurements. When compared to airborne thickness data in the Barents Sea, the merged product has a root mean square deviation (RMSD) of about 0.7 m less than the CS2 product and therefore demonstrates the capability to enhance the CS2 product in thin ice regimes. However, in mixed first-year (FYI) and multiyear (MYI) ice regimes as in the Beaufort Sea, the CS2 retrieval shows the lowest bias.

/pdf/a-weekly-arctic-sea-ice-thickness-data-record-from-merged-wu8rxsl12v.pdf

A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

Overview of the MOSAiC expedition

Helicopter-borne measurements of sea ice thickness, using a small and lightweight, digital EM system

A new, extremely small helicopter-borne frequency-domain electromagnetic induction sensor (HEM bird) has been developed by Alfred-Wegener-Institute (AWI), Aerodata Systems GmbH, Ferra Dynamics Inc., and K.-P. Sengpiel for extensive surveys of sea-ice thickness. In the summer of 2001 it has been successfully operated for the first time from the German research icebreaker Polarstern over sea ice in the central Arctic. This paper describes the system and shows some results of the first deployment.

First operation of AWI HEM-bird for sea-ice thickness sounding

https://epic.awi.de/25581/1/Rabensteinetal_Polar2_JAG2011.pdf

Noise characteristics of an electromagnetic sea-ice thickness sounder on a fixed wing aircraft

Sea ice remote sensing, thickness profiling, and ice and snow analyses during Polarstern cruise Ark 19/1 / CryoVex2003 in the Barents Sea and Fram Strait, February 28 April 24, 2003: Cruise report

With five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements the Alfred Wegener Institute (AWI) decided to construct an EM platform on a fixed wing aircraft in an attempt to overcome the helicopter flight range restrictions. The system operates in the frequency domain with 1990 Hz and a vertical coplanar coil configuration. The primary field voltage is electrically attenuated on the receiver coil which allows for increased amplification and resolution of the much smaller amplitude secondary field voltage. Before data are converted to ice thickness a correction for electronic drift and orientation effects is applied. First test flights show that the ice thickness accuracy of the fixed-wing system lies only between 1 m and 2.5 m in comparison to 0.1 m for the HEM systems. The lower accuracy is probably caused by electrical noise of the airplane engines and coil motion. Introduction Airborne frequency domain electromagnetic systems are a suitable tool for measuring sea ice thickness. Airborne electromagnetics (AEM) was first applied to sea ice in the 1980s by the US Army’s Cold Regions Research and Engineering Laboratory (Kovacs et al., 1987). From 1991 to 1994 Multala et.al. (1996) used a fixed wing system for sea ice thickness mapping in the Baltic Sea. With the recent rapidly changing global climate, sea ice observations become more important. Therefore, in the 1990’s, the Alfred Wegener Institut (AWI) started extensive EM sea ice thickness mapping in the Arctic, Antarctic and Baltic Sea. For this purpose, in 2001, two lightweight helicopter EM Birds were constructed, especially designed for ice breaker based operations (Haas et al., 2008[a]). Since then a couple of successful EM ice thickness campaigns were done using the two AWI ‘mini’ EM Birds (Haas et al., 2006, Haas et al. 2007, Haas et al., 2008[b], Pfaffling et al., 2007). Sea ice thickness is an important parameter to understand and model processes driving the climate and oceanography of the polar regions. It influences the heat exchange between ocean and atmosphere, the drift of the sea ice, the light penetration into the ocean, the trafficability of the sea ice and last but not least it’s interannual and decadal variability is an indicator for climate change. Therefore regular and wide area observations of regional sea ice thickness distribution are necessary. To overcome the limited range of helicopter measurements, the AWI constructed a new airplane based fixed wing EM system. Its’ development status and results from first test flights will be presented on the AEM2008 conference. EM ice thickness measurements differ from conventional exploration targets. Basically the EM signal measures the distance between instrument and ocean, which is the underside of the sea ice, while a laser altimeter measures the distance between instrument and surface of the sea ice. The difference of both altitudes is the ice thickness. It is a highly quantitative measurement which AEM2008 – 5 th International Conference on Airborne Electromagnetics Haikko Manor, Finland, 28 – 30 May 2008 requires a vertical resolution of 0.1 m. This level of accuracy can be achieved due to the strong conductivity contrast between sea ice and ocean (~0.01 to ~3 S/m). The AWI EM Birds achieve this accuracy over level ice, a 1D situation. Since the sea ice thickness problem is not a multi layer problem, sea ice thickness measurements can be achieved with only one frequency. The sea ice layer is almost invisible for the EM signal. Furthermore noise and drift of a sea ice thickness system have to be very low. Technical Parameters The fixed wing system was constructed in order to mount it easily on the Dornier 228 polar airplane of the AWI. Two pylons, one under each wing, already existed on the airplane for installation of several other geophysical instruments, e.g. a ground penetrating radar. The most cost saving realization with respect to air certification and aerodynamics was a pair of vertical coplanar coils mounted below each of the pylons, starboard the receiver coil and port the transmitter coil. The technical parameters are listed in Table 1. The system is shown in Figure 1. The fixed wing system uses an electrical compensation method to attenuate the primary field on the receiver coil. Calibration is done during high altitude flights in free space, by actively transmitting electric pulses of well known phase (quadrature pulses) and amplitude. These pulses can be used to determine the correct phase and amplitude of the signal in a post flight processing step. Totally four EM signals are recorded: The transmitter reference voltage, the compensation voltage, the primary plus secondary field voltage on the receiver coil and the amplified residual secondary field voltage (post compensation). A laser altimeter records the altitude of the airplane with an accuracy of 0.02 m. To correct for orientation effects, pitch, roll and yaw of the airplane is recorded. In addition basic meteorological data are routinely recorded during flight.

Development and Test of a Fixed Wing AEM Sea Ice Thickness Sounder

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