A dataset of direct observations of sea ice drift and waves in ice

Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the phenomena and mechanisms that govern sea ice growth, drift, and breakup. To this end, we have gathered a dataset of in-situ observations of sea ice drift and waves in ice. A total of 15 deployments were performed over a period of 5 years in both the Arctic and Antarctic, involving 72 instruments. These provide both GPS drift tracks, and measurements of waves in ice. The data can, in turn, be used for tuning sea ice drift models, investigating waves damping by sea ice, and helping calibrate other sea ice measurement techniques, such as satellite based observations.


Background & Summary
Sea ice is a major component of the global Earth ecosystem: it covers around 7% of the global oceans, averaged over a year 1 , and strongly modulates the coupling between the ocean and the atmosphere, as well as the global energy balance of the polar regions 2,3 .For example, a strong nonlinear coupling exists between ocean conditions and sea ice extent in the Arctic, due to the effect of ocean waves 4 .Indeed, as sea ice extent decreases in the Arctic basin, a new area of open ocean emerges between the polar ice cap and the surrounding continental landmasses.This, in turn, creates a new region of fetch where waves can grow larger before interacting with the sea ice.As a consequence of these larger waves, more sea ice gets broken which also

Methods
In the course of the data collection, several instrument models have been used.These are, the instrument "v2018" 46 , the instrument "v2021" 47,48 , the Sofar Spotter buoy 49 , commercial Global Positioning System (GPS) drifters with Iridium communication ability, and the Ice Wave Rider (IWR) 50 .All instruments use GPS to measure geographical location.The instrument v2018, v2021, and IWR, use acceleration measurements from inertial measurement units to measure wave motion.By contrast, the Sofar Spotter uses GPS to measure the wave motion.
In the following, we describe how measurements of drift and waves are performed, and we pinpoint differences between the instruments when relevant.The methodology used by the Sofar Spotter buoy is only partially known, as this is a close source, black box instrument.By contrast, the firmware and post processing code for the v2018, v2021 are fully open source, while the IWR is simply performing logging of an inertial measurement unit, with known configuration 50 .Therefore, and in addition to the detailed self-contained methodology description we provide here, the open source codes (available Github at 51 and 52 , respectively) can also be used as a source for technical details around the methodology used by the instruments v2018 and v2021.

Drift measurements using the Global Positioning System
Drift tracks are measured using a GPS receiver.No processing of any form is applied on the output produced by the GPS module.The GPS module has built-in hardware and software that ensure that only valid GPS positions are produced.
• In the case of the v2018, the full GPS National Marine Electronics Association (NMEA) output string is transmitted through Iridium.In addition, all the data collected by the instrument v2018 are stored on an internal SD card, so that, if the instrument v2018 is collected at the end of the deployment, the same GPS data are available there.The GPS measurements are performed with a period of approximately 3 hours.
• In the case of the v2021, only the UTC date and time as well as the latitude and longitude are transmitted.Other information is not transmitted, to save memory and cut satellite transmission costs.However, a higher GPS position sampling rate is applied, typically every 30 minutes.
• Similarly, the Sofar Spotter transmits GPS UTC time, latitude and longitude as a part of its iridium communications.
• The IWRs log GPS UTC time and geographic coordinates hourly to the internal SD card, without performing satellite transmission.Such routine is possible since IWRs deployments are either in ice camps or on shore-fast ice, and the data are retrieved together with the instruments at the end of the deployments.
• Commercial drifters also transmit GPS UTC time, latitude, and longitude.

Wave measurements using GPS
The Sofar Spotter uses GPS data in order to directly measure 2D wave surface displacement at 2.5Hz in the North-South and East-West directions, from which to compute the wave properties assuming that the underlying signal corresponds to the circular wave orbital velocity 49 .According to the datasheet delivered by Sofar, the typical resolution for significant wave height measurements is +/-2cm, depending on the conditions and sky view.The details of the implementation regarding how the raw data are filtered and how the wave spectrum is computed are, as far as the authors know, not available for this commercial close source instrument.The produced outputs include both wave statistics (significant wave height, and various wave period estimates), full wave spectra, and directional information (some of these outputs can be switched on and off individually of each other).The Sofar Spotter is considered a well-tested instrument, with several thousands units deployed according to the manufacturer, and it has been used in a number of peer reviewed measurement campaigns in the sea ice 36,[53][54][55] .

Wave measurements using Inertial Measurement Unit data
The instruments v2018, v2021, and IWR, use Inertial Measurement Units (IMUs) to measure the wave motion.In the following paragraphs, we outline the main lines of the data acquisition and the wave processing algorithms, though the reader curious of the exact, in-depth technical details regarding the open source instruments, is referred to the technical papers 46,47,50 that go deeper into the exact implementation, or to the code implementing the data processing (see the previous Github links).

Measurement of the wave vertical acceleration
The first step in measuring waves is to record the wave signal, i.e acceleration due to the wave motion.A duration of 20 minutes is used as the default time segment used to produce one wave spectrum and its associated statistics, and we used a wave acceleration sample frequency of 10Hz unless specified otherwise.In order to gather this wave signal: • In the case of the v2018 46 , all the data collection and Kalman filtering process is implemented by the thermally calibrated Vectornav VN100 Inertial Measurement Unit (IMU) that is used in the instrument [56][57][58] .The VN100 is an industry-grade IMU, and the details of the Kalman filter and signal processing algorithms running on it are proprietary and close source.The VN100 IMU outputs a number of variables, including accelerations measured in the Earth frame of reference (North, East, Down directions, referred further as NED).The Down (D) component of the acceleration, acc D , is obtained from the VN100 at a frequency of 10Hz and used for evaluating waves statistics.This 10Hz value is obtained by applying a Kalman filter to the raw sensor output (that is obtained at several kHZ), which translates into a 800Hz processed output.After that, a running average over 80 samples is performed to obtain the final 10Hz value.In the case when instruments are collected at the end of deployment, the full time series of the VN100 output at 10Hz, is available on the internal SD card.This includes both raw sensor measurements, Kalman filter state, heading and orientation output, and acceleration in the Earth frame of reference.
• In the case of the v2021 47 , the temperature-compensated 9-degree-of-freedom (9dof) sensor measures the accelerations, angular rates, and the local magnetic field, each over 3 axis (the X, Y, and Z axis of the 9dof sensor, in its own frame of reference attached to the microchip itself).These raw measurements are performed at 800Hz.Averaging and n-sigma filtering over 8 raw samples is used to downsample the signal from 800Hz to 100Hz, reject possible outliers, and reduce noise.An open source Kalman filter implementation is then used to fuse the data at 100Hz update frequency.The Kalman filter produces a unit quaternion estimate q of the absolute orientation of the sensor relative to the Earth frame of reference.This information, combined with the acceleration measurements acc re f Sensor = [acc X , acc Y , acc Z ] in the sensor frame of reference, allows to retrieve the acceleration of the sensor in the Earth frame of reference acc re f Earth = [acc N , acc E , acc D ], by applying the rotation described by the quaternion q on acc re f Sensor .At present, magnetometer calibration is not performed carefully enough to trust directional information relative to the magnetic North direction (this is ongoing work for further deployments).Therefore, the only data used at the moment are the vertical accelerations.These are averaged from the 100Hz acc D output into a 10Hz wave acceleration signal.
• Similar to the v2018 instrument, the IWR uses the Vectornav VN100 IMU.Processing and settings similar to the ones used with the instrument "v2018" are used by the IWR.However, the IWR records wave acceleration continuously, and stores it on-the-fly on an attached SD card, so that the time series of the wave displacement are available.Initial deployments were storing every 80 th value at the rate of 10 Hz.Later, to improve data quality, the sensors were reprogrammed to average sequences of 80 values, which were then saved at 10 Hz.Data output differed between the deployments, but always included [acc N , acc E , acc D ] along with yaw pitch roll angles of the IWR.The accelerations were output with constant vertical gravity acceleration removed.
At this stage, the vertical acceleration, which is the superposition of the gravity and wave acceleration (except for the IWR, where gravity is removed), is available at 10Hz for further processing in the case of either the v2018 or the v2021 (the IWR is a pure logger that is not equipped with iridium transmissions and does not perform in-situ processing of the data).

Estimation of the wave spectrum
The 10Hz wave acceleration component alongside the Down (D) direction in the Earth frame of reference is then used to compute the wave spectrum and its statistics.For this, two variants of the same core methodology are applied in the case of the instrument v2018 and v2021.
• In the case of the instrument v2018, details of the methodology are presented in the technical paper describing the instrument 46 .We reproduce the main lines of the processing here.First, the vertical acceleration is integrated twice in time using the methodology of previously developed instruments 59 , which is done in Fourier space by using the frequency response weights of 1/ω 2 and a half-cosine taper for the lower frequencies to avoid an abrupt cut-off 60 , corresponding to: where Re indicates the real part of the signal, IFFT stands for the Inverse Fast Fourier Transform, FFT the Fast Fourier Transform, and H( f ) is the half-cosine taper function: where f is the frequency, f c is the Nyquist frequency, and f 1 = 0.02Hz and f 2 = 0.03Hz are the half-cosine taper corner frequencies, similar to 59 .
Following the calculation of the time series for the wave elevation η(t) at 10Hz, the wave elevation spectrum S( f ) is estimated using the Welch method on 12000 samples (20 minutes at 10Hz), using a Hanning window of length 1024 samples per segment, and 50% overlap.In addition, the spectral moments m 0 , m 1 , m 2 , m 4 of the wave spectrum are computed, following: This allows to compute the usual wave statistics, i.e. the significant wave height calculated from the time series, H St = 4std(η), the significant wave height calculated from the spectral moment H S0 = 4 √ m 0 , the spectra peak period T p corresponding to the maximum of the spectrum, the zero-upcrossing period T z = m 2 /m 0 , and the average crest period In addition to these data, some directional spread estimates are computed, though these are not as carefully validated and their accuracy may be lower.The reader who wants to use these is invited to read about the technical details in the technical paper 46 , and to implement their own quality checks if they want to use directional information.
• In the case of the instrument v2021 47 , a slightly simpler methodology is used.The Power Spectral Density (PSD) for the vertical wave acceleration PSD accD is directly calculated from the vertical wave acceleration data at 10Hz, by applying the Welch method on 20.48 minutes of data (so that the exact number of samples is a multiple of 2 11 , which makes the calculation of the FFTs and the splitting into segments simpler and faster).Each segment for the Welch method has a length of 2048 samples, 75% overlap is used between the segments, and an energy-preserving Hanning window is used.
From there, the spectrum for the wave vertical elevation S( f ) can be retrieved as: At this stage, the spectral moments, as well as Hs, T z , and T c , can be calculated in the same way as for the instrument v2018.

Data transmission and decoding
Data are transmitted from the sea ice by the instruments v2018, v2021, and the Sofar Spotter, using the Iridium communication network and the Short Burst Data (SBD) protocol, which allows messages of size up to 340 bytes.
• In the case of the instrument v2018, the wave spectrum S(F) is downsampled into 25 logarithmically equally spaced bins between 0.05Hz and 0.25Hz, and transmitted together with the wave statistical parameters.
• In the case of the instrument v2021, the full PSD of the wave vertical acceleration PSD accD ( f ) between 0.05Hz and 0.3Hz is transmitted, alongside with the wave statistical parameters, though these are merely a cross validation of the spectrum, in the sense that they can be derived directly from the transmitted full spectrum.A simple script, which performs no further processing of the data, is then used to decode the binary SBD messages and apply the translation from PSD accD ( f ) to S( f ) following Eqn. 4.
• In the case of the Sofar Spotter, a variety of modes are available, in which either the full spectrum, or only integrated quantities, are transmitted.The data are available as JSON files, which are provided directly by Sofar by unpacking the binary data.
Commercial iridium trackers provide the track information data through a web-based API that abstract the details of the data transmission and processing protocol.

Data Records
All our high level, processed data are provided as netCDF4-CF files on the THREDDS data server of the Norwegian Meteorological Institute through the Arctic Data Center (ADC) database, at the following address, and in the folder structure therein: https://adc.met.no/datasets/10.21343/azky-0x44 61.Extensive metadata are provided, so that the different data fields are self documenting, following the FAIR data principle 62 .In addition, all the raw iridium data transmissions (hex-string binary data), raw SD card files (binary data, available only when the instruments were recovered), and scripts for reading these raw data files and processing them into netCDF files, as well as example scripts of how the netCDF datasets can be read, are available on Github in the folder structure of the following repository: https://github.com/jerabaul29/data_release_sea_ice_drift_waves_in_ice_marginal_ice_zone_2022 63 .
In the following, we provide a detailed overview of the different deployments, what kinds of instruments and how many of them were used in each of these, and some background information about the sea ice conditions and the data of interest.The time series obtained are of variable duration and some of them have holes in the data.This is due, to the best of our knowledge, to the harsh conditions found on sea ice, rather than technical issues with the instruments.Factors such as heavy snowfalls, polar bear destroying equipment, sea ice breakup, ridging and rafting, are all susceptible to interrupt iridium communications or destroy prematurely the instruments altogether.
The deployments in the Arctic are, in chronological order: • 2017-04: Arctic deployment in the MIZ that contains drift data in the Barents Sea. 8 GPS ice trackers were deployed on 6 ice floes in the Barents Sea South of Svalbard.The trackers send GPS data every 30 minutes, and were deployed during April 24-26 2017 from the Research Vessel Polarsyssel.Trackers 4610 and 8650 were deployed on the same ice floe, and trackers 5630 and 2470 were deployed on the same ice floe, different from the previous one.The other trackers were deployed each on their respective ice floe.An overview of the deployment time for the different trackers is provided in Table 1.The trackers could float and, therefore, the internal temperature records were used to determine the date and time when they entered water, as the temperature transitioned from a larger diurnal cycle when exposed to air on top of the ice, to a significantly more muted diurnal temperature variation when floating in open water.An analysis of the trackers' internal temperature records and the Svalbard regional daily ice maps from the Norwegian Meteorological Institute Ice Service led to the determination that the beacons most likely began falling into open water sometime on May 2, 2017 64 .The dispersion of the ice floes was dominated by strong shearing within the local ice pack, coinciding with a rapid increase in the speeds of the local tidal currents, which was soon followed by a rapid increase in the wave energy.Each of the six tracked ice floes increased their observed drift speeds in sync with the increase in the local tidal current speeds at different times for each floe, but at approximately the same decrease in water depth as they reached the northern edge of Spitsbergen Bank.The rapid increase in the tidal currents was linked to the topographic enhancement of tidal motion near Hopen Island in the shallower waters of Spitsbergen Bank.The last transmission from the trackers was received 2017-07-15.
• 2018-03a: Arctic deployment in the MIZ, in the East Greenland Sea.The primary aim of the cruise was to monitor the production of seal pups.For that, 5 GPS and iridium trackers were deployed on large ice floes in the dense MIZ and drifter Southwestwards, following the East Greenland Current.GPS data sampling rate was 30 minutes.The trackers were deployed around March 20th, 2018, and the last tracker stopped transmitting on April 25th, 2018, though communications were unreliable after April 6th, 2018, possibly indicating that the trackers were covered by snow and ice.The trackers were not equipped with floatability equipment, so that the trackers are guaranteed to be on an ice floe for all the trajectory duration.More information is available in 65,66 .
• 2018-03b: Arctic deployment on pack ice in the Beaufort Sea during ICEX2018, U.S. Navy exercises.Two IWRs were deployed for 4 days near an ice camp on 2018-03-17.One instrument was located on level ice near the air strip.It recorded numerous events characterized by strong, high-frequency oscillations produced by planes landing and taking off.The events matched the camp's logbook.The second instrument was placed in an ice rubble field nearby.It also measured several cases of strong accelerations, not coinciding with the first instrument observations.Their origin is unclear.The instruments were recovered on 2018-03-21.More information are available in 67 .
• 2018-04: Arctic deployment in the MIZ and drift ice in the Barents Sea.An ice tracker by Oceanetic Measurements Ltd was deployed on an ice floe to monitor the floe drift.GPS location was sent with an interval of 10 minutes.The tracker was deployed on April 27th, 2018 and transmitted until February 27th, 2019.The tracker drifted in the region of the Spitsbergen Bank for approximately 6 months, though it was on an ice floe only until around May 3rd, 2018 according to ice charts from cryo.met.no, and after this date, the tracker was floating in ice-free waters.More information are available in 68 .
• 2018-09: Arctic deployment in the MIZ in the Barents Sea, in the context of the Nansen Legacy project, Physical Process Cruise 2018.In this deployment, a total of 4 instruments v2018 were deployed while the icebreaker R/V Kronprins Haakon was traveling into the ice.The first instrument was deployed on a lone ice floe in the outer MIZ, while sea ice concentration (SIC) was about 1/10.The second instrument was deployed on an ice floe in dense drift ice, SIC about 5/10.The third instrument was deployed at the very start of the close pack ice, SIC about 9/10.The fourth instrument was deployed in the close pack ice, SIC about 10/10.All instruments were deployed on 2018-09-19.The cruise report is available if more details are needed 69 .The instruments worked for around 2 weeks.However, a strong storm took place around 2018-09-24, and after this time, the spectra reported by the v2018 are very noisy with a lot of high frequency wave energy.This indicates that the supporting ice floes got broken into small pieces and started to drift in very open water, which is confirmed by SIC from models (see, for example, the discussions in manuscripts using the data 18 ).Therefore, the GPS drift tracks can be trusted over the whole duration of the dataset, but spectra dominated by high frequency signal correspond to small, broken ice floes drifting in very open water and experiencing erratic oscillations, rather than more classical waves in ice.
• 2020-03a: Arctic deployment on landfast ice in Grønfjorden, Svalbard.Three v2018 were deployed along the main axis of the fjord on continuous landfast ice between 10 and 13 March 2020.The first instrument was deployed at a distance of approximately 500 m from the unbroken ice edge, the second and third were deployed 600 and 700 m apart.At the time of deployment, the unbroken sea ice covered approximately half the length of the fjord.The other half was covered by broken ice and extended up to the entrance of the fjord.Ice thickness was measured at various locations near the instruments between 30 and 40 cm.Instruments were recovered after approximately two weeks on the 28th of March, 2020.At the time of retrieval all instruments were still deployed on unbroken ice and recording data.These data were used in some previous works 36,70 , and some additional information are available there.
• 2020-03b: Arctic deployment on pack ice in the Beaufort Sea during ICEX2020.The deployment strategy was similar to the ICEX2018 campaign (see 2018-04).Deployment took place on 2020-03-08, and the instruments were collected on 2020-03-18.Similarly, the instrument close to the air strip measured short-living, high-frequency events.No logging of arriving and leaving planes was made.Both IWRs recorded two events of propagating flexural-gravity waves presumably forced by strong winds during passing storms.More can information be found in 67 .
• 2020-07: Arctic deployment in the MIZ in the Barents Sea over the Yermak Plateau, in the context of the Fram-2020 hovercraft expedition.The cruise report is available at 71 In this deployment, a total of 6 instruments v2018 were deployed over the summer 2020 on drift ice, SIC ranging from approximately 3/10 to 10/10.One instrument was deployed 2020-07-15, and transmitted until 2020-07-31.One instrument was deployed 2020-07-21, and transmitted until 2020-09-03.However, the energy content in the high frequency part of the spectrum of this instrument indicates that it likely drifted on a small, isolated, broken ice floe from around 2020-08-19.One instrument was deployed 2020-08-14, and transmitted until 2020-09-08.Finally, 3 instruments were deployed around 2020-08-26, and transmitted until around 2020-09-24.Several wave events were consistently observed across the array of instruments deployed simultaneously, and clear wave damping is visible.
• 2021-02: Arctic deployment in the MIZ in the Barents Sea, East of Svalbard, in the context of the Nansen Legacy project, PC-2 Winter Process Cruise 2021.In this deployment, a total of 6 instruments v2018, and 11 prototypes of the instrument v2021 (of which 6 were equipped with wave measurements) were deployed from the icebreaker R/V Kronprins Haakon on its way up and down the East coast of Svalbard, in close drift ice.The details of the deployment are reported in the cruise report 72 .3 instruments v2018 were deployed on the way into the ice, for SIC increasing from around 5/10, 9/10 and 10/10.All the other instruments were deployed in close pack ice, for SIC of 10/10.The instruments gradually stopped transmitting as ice broke up, with the last transmission on ice taking place in late April.
• 2021-03: Arctic deployment on broken pack ice in the Beaufort Sea to accompany measurements during Sea Ice Dynamic Experiment (SIDEx2021).The instruments were deployed on 2021-03-06.In total six IWR instruments were installed surrounding the ice camp, but only three were recovered.Due to battery problems, the amount of collected data varied.The shortest observational interval was 2 weeks and the longest one and a half month (it was collected on 2021-04-22).More information is available in 67 .
• 2021-04: Arctic deployment on landfast ice near Utqiagvik, Alaska as a part of Integrated System for Operations in Polar Seas project.Six buoys were placed in different locations on thick landfast sea ice, and deployment took place on the 2021-05-07.Ice conditions varied between jumble ice and level ice of a refrozen lead.Some instruments were located closer to the landfast ice edge.The measurements did not exhibit any clear sign of waves.However, a wave event was detected via ground-based radar interferometry.Respective vertical accelerations above IMU's noise level were also found in the IWRs.The instruments were collected on the 2021-06-02.More on the deployment and results can be found in 73 .
• 2021-09: Arctic deployment in the MIZ in the Laptev Sea, in the context of the NABOS campaign.Two buoys, one Sofar Spotter and one instrument v2021 packed in a Zeni floating enclosure, were deployed adjacent to the ice edge on 2021-09-15.The Sofar Spotter battery life at these latitudes and without solar input is only around 10 days, but by contrast, the v2021 instrument functioned for over 2 weeks.Several swell events were measured during the deployment, and the distance between the buoys allows to observe clear attenuation of the incoming swells by sea ice.The data are used in 74 , and the reader is referred to the corresponding work for further details about the deployment and the data collected.The last transmission included in the dataset took place on 2021-09-29.
• 2022-03: Arctic deployment in the MIZ in the East Greenland Sea, in the context of the seal pup monitoring cruise 2022.In this deployment, 2 instruments v2021 were installed on 2 separate, neighboring medium size drifting ice floes (typical floe size: 25m; typical floe thickness: 1.5m) from the icebreaker R/V Kronprins Haakon on March 27th, 2022.In addition, 5 commercial gps and iridium drifters that only measured sea ice drift were deployed on large ice floes in the dense MIZ.The instruments drifted following the East Greenland current.The trajectories of the 2 instruments v2021 remained close (less than typically 2km apart) for around 2 weeks, before drifting slightly further apart from each other but heading in the same general direction.As a consequence, tracks and wave spectra are initially very similar, before clear differences in the wave spectra due to being at different depths in the MIZ get visible after around 2 weeks of drift.
One of the instrument started to transmit data unreliably after around 4 weeks of activity, likely due to being covered by a layer of snow and ice that blocked iridium communications (since occasional transmissions were still recorded after messages started to come in unreliably, which did not indicate any technical issue with the instrument other than bad communications).The second instrument worked uninterrupted for over 4.5 weeks.The trajectories of the 5 commercial gps and iridium drifters remained close for most of the deployment.The last transmission was received on 2022-05-22.
More information is available in the cruise report 75 .
The deployments in the Antarctic are, in chronological order: • 2020-01: Antarctic deployment on landfast ice on the eastern rim of the Amery Ice Shelf.Four instruments, two v2018 and two Sofar Spotter, were deployed along a transect perpendicular to the unbroken ice edge on 7 December 2019.The first Spotter was deployed 100-200 m from the unbroken ice edge, while a v2018 and the second Sofar Spotter (40 m apart from each other) were deployed at a distance of about 3.7 km from the edge, and one more v2018 was deployed about 9.3 km from the unbroken ice edge.At the time of deployment, the ice was measured between 1 and 1.2 m thick.No wave events or drift was recorded until the 2nd of January 2020 when a large section of the fast ice broke and started drifting northward.The first v2018 stopped transmitting on 22 January 2020, while the two Sofar Spotters stopped transmitting on 1 February 2020 (although one reconnected for half a day on 3 March 2020).The last message successfully transmitted by the final v2018 was on 10 March 2020.These data were used in papers 36,55 , and some additional information are available there.
• 2020-11: Antarctic deployment on landfast ice north of Casey Station.Deployment consisted of two v2018, deployed 1.9 km apart in October 2020.Instruments were recovered after about 3-4 weeks.Ice thickness was measured 1.1 m thick during the deployment and 1.3 m during retrieval.As the deployment site was separated from the Southern Ocean open water by roughly 300 km of broken sea ice, only limited wave energy was observed.The sea ice at the deployment site remained unbroken throughout the deployment.More information is available in 33 .
A summary of the deployments is provided in Table 2, and in Fig. 2.

Technical Validation
There is no need for validation regarding GPS position measurements, as these are well established sensors with a well known accuracy (typically +-5m).
Regarding wave data, we are only using well established, longstanding methodologies.The sensors used are thermally calibrated over a range that typically exceeds the range of conditions found in the field in the MIZ (the Vectornav VN100 used in the v2018, is thermally calibrated over the full temperature range from -40 to +85 C, while the ST-Microelectronics ISM330DHCX used in the v2021 is calibrated from -40 to +105 C, according to their respective datasheets).Therefore, we consider that the data acquisition for the wave acceleration by itself does not need additional validation, and users should refer to the datasheets of the corresponding sensors for further information.As a side note, validation of the accelerometer data was performed, either directly (see Fig. 1 of 56 for the test and validation performed for the VN100), or indirectly (by validating the accuracy of wave spectra, see next paragraph).In practice, however, raw data from the instrument are only available for a couple of deployment of the instruments v2018 (when the SD card could be recovered), and for the IWR deployments, for which the data provided are always the timeseries of the IMU output.
Results that come from in-situ processing of IMU or GPS data, such as the wave spectra and statistics reported by the Sofar Spotter and the instruments v2018 and v2021, have been previously validated in details, and the reports and validation details are available in the literature: the Sofar Spotter is a commercial instrument that was validated before being released for sale 49 , the v2018 has been validated and used in scientific papers multiple times 36,46,70 , and the v2021 has been recently validated against both commercial buoys and satellite data 47 .Validation campaigns for both the v2018 and the v2021 indicated agreement to either within 5%, or within one standard deviation, of commercial instrument or other measurement methodology.While more details are available in the corresponding papers, we reproduce the main validation figures against established commercial instruments in Figs.3,4 (v2018) and Figs. 5, 6 (v2021), for the sake of completeness.In addition, since the v2018 and the v2021 have much higher levels of sensitivity compared with GPS-based buoys or satellite measurements against which we validated them, tests were performed in the laboratory, in controlled conditions, in order to estimate the noise background of the whole system (i.e., including the noise of the IMU itself, and the effect of the processing algorithms used, as described in the Methodology section).As visible in these tests, which main findings are reproduced in Fig. 7 (v2018), and Fig. 8 (v2021), the instruments are able to measure waves with amplitude down to typically a few millimeters.Test results are in agreement with the accelerometer datasheet (which describe the expected noise background intensity), and the formula for conversion from acceleration to elevation spectrum (Eqn.4, which describes the expected spectral shape of the noise), where the noise backgrounds of the v2018 and the v2021 follow the expected decay curve as frequency increases (i.e., accelerometer-based instruments are more sensitive for wave amplitude as wave frequency increases).The typical noise threshold for a single data bin for the instrument v2018 is about 10mm for 20s waves, and 0.3mm for 4s waves, as visible in Fig. 3 of 46 , reproduced here as Fig. 7.The typical noise threshold for the v2021 is even lower, as visible in the Fig. 5 of 47 , reproduced here as Fig. 8, as a 16s wave of amplitude 5mm corresponds to a signal to noise ratio (SNR) of around 10.
These validations, both against other field instruments, against satellite measurements, and in controlled laboratory conditions, give us confidence in the accuracy and reliability of our instruments.

Usage Notes
Two kinds of data processing levels are provided to the user: • High-level data that are ready-for-use are provided as netCDF-CF files, following the best practices in use in the geoscience community and the FAIR principles 62 .These are available on a specific folder of the THREDDS server of the Norwegian Meteorological Institute as part of the Arctic Data Center repository https://doi.org/10.21343/AZKY-0X44 61 .Any netCDF package, in python or other language, can be used to access the data.The use of NetCDF4-CF files ensures long time compatibility, as this is the standard used for archiving meteorological data all over the world, and the tooling is mature and stable.
• In addition, the full raw data, either SD card records when the instruments could be recovered, or raw iridium transmissions, are available at the Github repository that supports the data release https://github.com/jerabaul29/data_release_sea_ice_drift_waves_in_ice_marginal_ice_zone_2022 63 .Custom software is provided (either on the same repository, or on the repositories where the source code of the instruments and post processing scripts are available) to decode these raw data.The fact that both the firmware of the instruments (hence, the binary protocol used), and the binary decoders, are open source, guarantees long term accessibility of the data, as well as full insight into the technical details associated.
No additional processing is needed to use either the GPS or the wave data, and the data are ready to use as-is in Python or similar.
A proper use of the presented data for the analysis of wave damping will also critically depend on the availability of high-quality sea-ice concentration, thickness, and floe size distribution maps, as well as the wave frequency spectra in the open ocean adjacent to the sea-ice edge.While providing these data is, in general, outside of our scope, as there are a number of concurrent, different possible sources and models that produce such data, and these data are generated independently of the field measurements and rely on entirely different techniques, codes, and operational products, we highlight a few different sources that could be of interest to the reader.
Sea-ice concentration products are available from passive microwave sensors with a footprint of around O(20km) 76 .New multi-sensor products are becoming available, combining sensor information of passive and active microwave and Synthetic Aperture Radar (SAR) sensors [77][78][79] .These products reach resolutions of O(1 to 10km).In addition, manual sea-ice charts can be used which cover scales down to O(100m) and are available on a daily basis from the national ice services (for example, the Norwegian Meteorological Institute Ice Service charts, https://cryo.met.no/en/latest-ice-charts, or the similar Danish Meteorological Institute Icecharts, http://ocean.dmi.dk/arctic/icecharts.uk.php).Various pan Arctic sea-ice thickness satellite products are available with resolutions of O(25km) and are considered reliable in the thickness range from 0.5 to 4 m 80 .Approaches to produce satellite based information on the sea-ice floe size distribution are emerging but to our knowledge no operational products are available yet 81 .Some national ice services (e.g. the Danish Sea Ice Service) include information on floe sizes as part of the manual ice charts 82 .In addition to the sea-ice information, wave information on the wave properties adjacent to the sea-ice edge are needed.A number of wave hindcasts and reanalysis are available, however, often the energy frequency spectra are not disseminated (e.g. 83); we are currently providing this feedback to the modeling community, and hope that more detailed information from numerical models will be available in the future.   .The instruments were deployed close to each other, but drifted significantly with time.Agreement within typically 5% is obtained on most of the spectrum.The increasing, spurious noise at low frequencies observed in the Zeni-v2021, is a well known phenomena for IMU-based measurements of waves in ice in the open ocean 90 , which can be filtered out.This phenomenon is not expected to be present when performing measurements of waves in the sea ice.   .This characterizes the typical noise level resulting from the combination of raw data measurements by the accelerometer and gyroscope, and the processing algorithms used.

Figure 1 .
Figure1.Sea ice can come in many forms, from fields of small broken floes (top left picture), to continuous pack ice, to landfast ice (top right picture).This has a strong, complex influence on wave damping and sea ice drift.To illustrate the effect of sea ice on wave damping, we show the map presenting Sea Ice Concentration (SIC, bottom left) around 3 drifters corresponding to the 2020-07 deployment on 2020-09-16, and the corresponding drifter trajectories.The drifters are at different depth into the Marginal Ice Zone (MIZ), which implies different degrees of frequency-dependent significant wave heigth damping and associated peak frequency shift (bottom right).The field data released in this manuscript features many similar events, that can be used to tune numerical models.

Figure 2 .
Figure 2. Overview of the deployments present in the dataset.The SIC map show the averaged SIC over the local winter month in the Arctic and Antarctic.

Figure 3 . 21 Figure 4 .
Figure 3. Validation of the instrument v2018 IMU measurement and processing (IMU curves) against co-located pressure-sensor-based measurements of waves using a Seabird pressure sensor (SBE curves), reproduced from 46 .Shaded areas indicate the 5-sigma confidence intervals.Agreement within the confidence intervals is observed.

Figure 5 .
Figure 5. Validation of the instrument v2021 (Zeni-v2021 processed) against the Sofar Spotter (SPOT-1386), in open water, reproduced from47 .The instruments were deployed close to each other, but drifted significantly with time.Agreement within typically 5% is obtained on most of the spectrum.The increasing, spurious noise at low frequencies observed in the Zeni-v2021, is a well known phenomena for IMU-based measurements of waves in ice in the open ocean90 , which can be filtered out.This phenomenon is not expected to be present when performing measurements of waves in the sea ice.

Figure 6 .
Figure 6.Validation of the instrument v2021 against satellite measurements, reproduced from 47 .Top: drift trajectory of a freely drifting, open water version of the instrument v2021 (black), and illustration of satellite swaths intersecting the trajectory over the drift period (colored point clouds).Bottom: comparison of the significant wave height (SWH) reported from the v2021(nicknamed "floatenstein"), with satellite measurements from a variety of satellites.SWH comparison between the v2021 and the satellite measurements are in agreement, with the measurements from the v2021 always falling within the spread for each satellite measurement swath.While this is obtained from a deployment performed in the Caribbeans, this is a validation of the correct functioning of the wave measurement routines.

Figure 7 .
Figure 7. Illustration of the noise threshold at rest for the instrument v2018, reproduced from46 .This characterizes the typical noise level of the combination of the VN100 IMU and the wave processing algorithm used to generate the spectra transmitted over Iridium.

Figure 8 .
Figure 8. Illustration of the noise threshold at rest and under a variety of wave motions produced artificially in the laboratory for the instrument v2021, reproduced from47 .This characterizes the typical noise level resulting from the combination of raw data measurements by the accelerometer and gyroscope, and the processing algorithms used.

Table 1 .
Details around the deployment conditions for the 8 ice trackers, Svalbard Banks, 2017-04.