Wave buoys are a popular choice for measuring sea surface waves, and there is also an increasing interest for wave information from ice-covered water bodies. Such measurements require cost- eﬀective, easily deployable, and robust devices. We have developed LainePoiss (LP)—an ice- resistant and lightweight wave buoy. It calculates the surface elevation by double integrating the datafromtheinertialsensorsofthemicro-electromechanicalsystem(MEMS),andtransmitswave parameters and spectra in real-time over cellular or satellite networks. LP was validated through: 1) sensor tests, 2) wave tank experiments, 3) a ﬁeld validation against a Directional Waverider, 4) an inter-comparison of several buoys in the ﬁeld, and 5) ﬁeld measurements in the Baltic Sea marginal ice zone. These extensive ﬁeld and laboratory tests conﬁrmed that LP performed well (e.g., the bias of <0in the ﬁeld was 0.01 m, correlation 0.99 and scatter index of 8 %). LP was alsodeployedwithanUnmannedAerialVehicleandwepresentourexperienceofsuchoperations. One issue that requires further development is the presence of low-frequency artefacts caused by the dynamic noise of the gyroscope. For now, a correction method is presented to deal with the noise.22 23 24 25 26 27 28 29 30 31 32 33 34 35 3 Signiﬁcance statement. Operational wave buoys are large and therefore expensive and inconve- 36 nient to deploy. Many commercially available devices cannot measure short waves and are not 37 testedinice. Ourpurposewastodevelopanaﬀordablewavebuoythatislightweight,ice-resistant, 38 capableofmeasuringshortwaves,andalsohasalongeroperatinglifethanexistingresearchbuoys. 39 Thebuoyiseasilydeployedwithasmallboatorevenanindustrialdrone,thusreducingoperating 40 costs. Thebuoyisaccurate,andcaptureswavesthataretooshortforoperationalwavebuoys. This 41 is relevant for coastal planning in e.g., archipelagos and narrow fjords. We measured waves in ice 42 in the Baltic Sea, and are planning to extend these measurements to Antarctica. 43 1. Introduction 44 Wind-generated waves dominate the spectrum of ocean surface vertical variance (Munk 1950; 45 Holthuĳsen 2007). These waves are observed visually, but an objective quantiﬁcation of wave 46 heights,lengths,andpropagationdirectionsrequiresmeasurementswithin-situorremotesensing 47 technologies. This paper focuses on a newly developed wave measuring buoy. 48 In-situ instruments do not measure wave properties directly. At the sea surface, wave buoys 49 should follow the three-dimensional movement of water particles while measuring the inertial 50 data or the Doppler shift of a GPS signal (Herbers et al. 2012). Below the sea surface, pressure 51 transducers measure wave-induced pressure ﬂuctuations (Cavaleri 1980), Doppler current meters 52 measure the wave-induced orbital motions (Gordon and Lohrmann 2002), and inverted echo- 53 sounders measure acoustic travel time between the device and the sea surface (Wadhams 1978). 54 Wave gauges piercing the sea surface measure the up-and-down movement of water through 55 electrical capacitance or resistance (Donelan et al. 1985; Graber et al. 2000). The surface wave 56 spectra is then calculated from the measured physical quantity by mathematical transformations 57 and wave theory. 58 4 All the measurements techniques in the above (non-exhaustive) list are feasible, but have their 59 own limitations and peculiarities. For example, gaps in data due to salty water over washing 60 the buoy and blocking the GPS signal (Björkqvist et al. 2016), spurious data in echo-soundings 61 generated by breaking waves and diminishing of short-waves in pressure recordings (Bishop and 62 Donelan 1987). More generally, the size of the instrument, the basic measurement principle and 63 the met–ocean conditions aﬀect the measurement result. Besides inherent limitations, operational 64 and practical considerations, like ease of use and cost of the instrument, might be important. 65 Majority of operational wave measurements are done with surface-following buoys, which may 66 also include sensors for recording atmospheric and upper ocean state variables (Thomson 2012). 67 These buoys can be tethered to the sea ﬂoor or allowed to drift under the inﬂuence of wind and 68 currents. An advantage of these buoys is their long operational life (several years). However, the 69 established operational buoys are large and heavy. The National Data Buoy Center of NOAA has 70 tailored met–ocean buoys, equipped with wave measuring sensors, ranging from 1.8 m to 12 m 71 in diameter. The widely used Datawell Waverider Mk-III, TRIAXYS Directional Wave Buoy and 72 Fugro Seawatch Mini II Buoy have diameters of at least 70 cm and weights of over 100 kg. These 73 oﬀ-the-shelfoperationalbuoysmaynotbeanaﬀordablechoiceforsimultaneousdeployments,and 74 their handling requires expertise as well as vessel for deployment. These issues are somewhat 75 alleviatedwithbuoysastheDatawellDWR-G4,whichweighs17kg,hasadiameterof40cmand 76 a battery life of 30 days. 77 Recent advances in accurate and low-cost motion sensors and GPS technology have led to the 78 developmentofalow-costeasy-to-handlewavemeasurementplatformcalledSpotter(Raghukumar 79 et al. 2019; Lancaster et al. 2021). It is a sea state detector with unprecedented coverage (Smit 80 et al. 2021; Houghton et al. 2021) and thanks to its small size, it might turn out to be a practical 81 tool for estimating wind speed from wave spectra (Voermans et al. 2020). First ﬁeld experiments 82 5 of measuring waves in grease ice with Spotter show promising results in performing these types 83 of observations at a low cost (Kodaira et al. 2020). The simultaneous deployments of several 84 (tens, hundreds) drifting wave buoys is also beneﬁcial for understanding wave–current interaction 85 atcoastalandoceanicscales(Pearmanetal.2014;VerasGuimarãesetal.2018)andwavegrowth 86 in complex archipelagos (Björkqvist et al. 2019) and fjords (Christakos et al. 2021). 87 In this paper, we describe and validate a new wave buoy called LainePoiss (LP), which uses the 88 micro-electromechanical system (MEMS) inertial measurement unit to detect surface motion. LP 89 wasoriginallydesignedforwavemeasurementsinice,buthasover3yearsofresearchanddevelop- 90 mentmaturedintoavaliddevice;itisalreadyusedforreal-timewavemonitoringintheBalticSea. 91 Whendevelopingthebuoy,wehavekeptthefollowingcombinationofperformancecharacteristics 92 in focus: ice-resistant, lightweight, operational, small and aﬀordable. These characteristics allow 93 LP to be used for various research and engineering applications. For example, we are currently 94 planningtouseLPforwavemeasurementsinthemarginalice-zone,extendingmeasurementtimes 95 ofoperationalwavebuoysintheseasonallyicecoveredBalticSea,ﬁeldmeasurementsofshorter- 96 waves in archipelagos and lakes and using Unmanned Aerial Vehicles (UAV) as a rapid method 97 fordeployments. LPisalsoacoreinfrastructureforvalidatingoperationalcoastalwavemodelsin 98 Estonia. 99 The structure of the paper is as follows. In Chapter 2, we describe the wave buoy in detail and 100 introduce algorithms for converting the acceleration data into displacement data. In Chapter 3, 101 the omnidirectional and directional wave parameters are deﬁned. Chapter 4 describes diﬀerent 102 laboratory tests for sensor validation, including standstill measurements of acceleration noise and 103 benchmark tests with monochromatic motions. Thereafter, we will describe the accuracy of the 104 buoy in capturing high-frequency waves in a wave tank. Chapter 5 deals with the ﬁeld test 105 results. This includes an extensive validation campaign against a Directional Waverider and an 106 6 intercomparisonofseveralLPbuoys. Wealsodescribedriftingexperimentsresults,whereanUAV 107 was used as a deployment method. We end Chapter 5 by describing the results of waves-in-ice 108 measurements from the Baltic Sea. In Chapter 6, we discuss the limits and merits of the new 109 technology and conclude our main ﬁndings in Chapter 7. Three appendixes end the paper, with 110 the description of the denoising procedure, calculating validation statistics and describing our 111 experience of UAV deployments. 112 2. Materials and Methods 113 a. Technical description of the buoy 114 LP is a spherical wave buoy with a diameter of 32 cm, a height of 22 cm (Fig. 1) and a weight 115 of 3.5 kg. The enclosure is made of two tough glass ﬁber halves. Between the halves, there is a 116 seal that makes the hull waterproof after it has been bolted together. After the buoy is sealed, it 117 can be turned on and oﬀ by holding a magnet to the outside of the hull. Rechargeable lithium-ion 118 batteries, with a capacity of 335 Wh, can power the buoy for roughly two months. 119 Themicrocontrollerofthebuoyisconnectedtothesensors,thememoryandthecommunication 120 modems through a custom built PCB board (Fig. 2). This controller—using an ARM Cortex-M4 121 core—waschosenbecauseofitslowpowerconsumption,ﬂoatingpointsupportanddigitalsignal 122 processing functionality. 123 The inertial sensors of the buoy are a 3D accelerometer, a 3D gyroscope, and a magnetometer. 124 These sensors are part of the Xsens MTi-3 attitude and heading reference system (AHRS). The 125 internal processor of the system synchronizes the sensors, applies calibration models and runs the 126 sensor fusion algorithm. After assembling the buoy, we performed a magnetic calibration that 127 7 correctedforthedisturbanceinﬂictedtothemagneticﬁeldoftheEarthbyferromagneticmaterials. 128 The device location was logged by a GNSS (Global Navigation Satellite System) receiver. 129 We conﬁgured the output frequency of the inertial data to 50 Hz, and this data is written to an 130 SD-card. Depending on the conﬁguration set by the user, the data is also sent to a cloud server 131 in real time (e.g., every 30 minutes) using cellular LTE or satellite Iridium SBD®networks. The 132 buoycanbeconﬁguredtouseeitheroneorbothofthesecommunicationoptions;thebuoyalways 133 prioritizes the cellular network, but can automatically switch to the satellite network if no cellular 134 coverage exists. We chose the cellular network as the primary communication channel because 135 of its signiﬁcantly lower data transmission costs. The buoy can therefore also send the raw data 136 through the cellular network, although this option can be disabled to save power. 137 b. Data processing 138 Thebuoysampledtheaccelerationwitha50Hzsamplingfrequency,and(intheﬁeldtests)this 139 datawassavedinﬁlescontaining65538measurements(ca22minutes). Foreachdeployment,this 140 acceleration data was combined into one long time series from which we constructed 30-minute 141 displacement time series with starting times of :00 and :30 using the following procedure: 142 1. We constructed 32-minute time series from the continuous acceleration data (:59–:31). 143 2. Thex,y,andzaccelerationswerelow-passﬁltered(ﬁlter"biting"between1.28Hzand5.12Hz) 144 withaﬁniteimpulseresponse(FIR)ﬁlterthathad162coeﬃcientsbeforebeingdown-sampled 145 to a 5.12 Hz resolution using a nearest neighbour interpolation. Because of the original 50 146 Hz sampling frequency, this resulted in a maximum shift on 100 ms of the measurement. 147 3. The acceleration data was double integrated in Fourier space. Before integration, the white 148 noisewasremovedforfrequenciesupto0.10Hz,andtheamplitudesatthelowestfrequencies 149 8 weresettozero(seeAppendixBfordetails). Weremoved30secondsfromthestartandend 150 ofthedoubleintegratedtimeseriestocutouttransientdatacausedbytheFourierintegration. 151 4. Finally, after accounting for the data lost by FIR-ﬁltering and Fourier integration, we cut the 152 time series to start exactly at :00 or :30 to a 9216 point long block. These 30-minute block 153 coincided exactly with the displacement time series of the Waverider at Suomenlinna, which 154 we used for validation. 155 The denoising of the acceleration data was performed by estimating the mean amplitude of the 156 Fast Fourier Transform (FFT) of the signal between frequencies 1/100 Hz and 1/30 Hz. The 157 integration was performed in Fourier space, where the removing of the low-frequency energy was 158 applied gradually below 0.05 Hz using a half-cosine function, setting the amplitudes to 0 below 159 0.04Hz. ThisintegrationprocedureissimilartotheoneusedinRabaultetal.(2020). Fortheﬁeld 160 data, a correction to the energy was performed based on the amount of variance that was lost in 161 the denoising. The denoising, compensation and integration procedures are documented in detail 162 in Appendix B. 163 The 30-minute displacement time series were then used to calculate wave spectra from 100- 164 second blocks using the Welch method with a 50% overlap (35 segments), resulting in a wave 165 spectrumwitha0.01Hzresolution. EachsegmentwastaperedwithaHannwindow. Thehighest 166 frequencyusedinthespectrumwas1.28Hz,whichcorrespondstoa95cmdeepwaterwavelength 167 and approximately 3 times the buoy diameter. Higher frequencies were starting to be distorted 168 by the size of the buoy when compared to the wave gauge data (see Section 4c on the wave tank 169 experiment). 170 9 Notethatthedataprocessingproceduresinthelaboratoryexperimentsdiﬀeredslightlyfromthe 171 data collected from ﬁeld tests, since the time series were shorter. Please see Section 4c for details 172 on the exact procedure for laboratory data. 173 3. Wave parameters 174 a. Omnidirectional parameters 175 We used the following deﬁnitions of wave parameters. The spectral moments are deﬁned as 176 <==¹51 505=¹5ºd5 (1) where a lower integration frequency of 50=010Hz and an upper frequency of 51=058Hz was 177 used to match the highest frequency that was reliably captured by the Waverider. 178 Using the spectral moments we deﬁned the signiﬁcant wave height: 179 <0=4p<0 (2) The wave periods were deﬁned as 180 )<10=<1 <0(3) )<01=<0 <1(4) )<02=r<0 <2(5) )?=¹argmax¹5ºº1(6) )2=¹51 5051¹5º4d5 ¹51 50¹5º4d5 (7) 10 Here, the peak period, )?, was determined using a parabolic ﬁt. )2is the so-called characteristic 181 period,whichisofthesametypethatwasoriginallydevelopedasanalternativetopeakfrequency 182 byYoung(1995). Björkqvistetal.(2019)proposeditasamorestablealternativecharacterisation 183 of a representative wave frequency in archipelago conditions, where the peak period is often ill- 184 deﬁned. Notethatweuseaslightmodiﬁcationbyintegratingaweightedaverageoftheinverseof 185 the frequency ( 51) compared to the weighted integration of 5by Young (1995) and Björkqvist 186 et al. (2019). 187 The narrowness of the spectrum was determined by the ^2-narrowness parameter (Battjes and 188 van Vledder 1984): 189 ^2=1 <02 ¹51 50¹5ºcos¹2c5)<02ºd52 ¸¹51 50¹5ºsin¹2c5)<02ºd52! (8) ^2takesvaluesbetween1(inﬁnitelynarrowspectrum)and0(whitenoise)andhasbeenfoundto 190 capture the spectral shape better (especially in the archipelago) than width parameters depending 191 on high moments ( <2or<4) (Björkqvist et al. 2019). 192 b. Directional parameters 193 Directional parameters were calculated using the ﬁrst pair of Fourier coeﬃcients, 01¹5ºand 194 11¹5º. These coeﬃcients were calculated from the cross-spectra following Longuet-Higgins 195 (1961): 196 01¹5º=&E4¹5ºp EE¹5º¹==¹5º¸44¹5ºº(9) 11¹5º=&E=¹5ºp EE¹5º¹==¹5º¸44¹5ºº (10) 11 where&¹5ºand¹5ºare the quadrature- and co-spectra, with subscripts E,4and=referring to 197 the vertical, east and north displacements. 198 The mean direction at each frequency was calculated as 199 \<¹5º=arctan01¹5º 11¹5º ¸180 (11) with the mean and peak direction being 200 \<=arctan01 11 ¸180 (12) \?=\¹5?º=arctan01¹5?º 11¹5?º ¸180 (13) where5?is the peak frequency determined without a parabolic ﬁt. 201 The directional spread was deﬁned as 202 f¹5º=q 22< 1¹5º (14) where 203 < 1¹5º=q 02 1¹5º¸12 1¹5º (15) The mean and peak spreads were deﬁned as for the directional spread (Eq. 14) using 204 < 1=q 012¸112(16) < 1¹5?º=q 02 1¹5?º¸12 1¹5?º (17) 4. Laboratory tests 205 a. Sensor static noise 206 The manufacturer of the MEMS sensor reports a static noise density value of 0.12 <6¹p Iº1 207 for the acceleration sensor. In order to test if this represents the actual noise of a single sensor, 208 12 we conducted a standstill measurement, where, at a room temperature of 21 °C, we let the sensor 209 measure for 3 hours. We then calculated the power spectrum of the acceleration noise and 210 transformed it to noise displacement spectra by dividing the acceleration spectra with ¹2c5º4. 211 Wefoundthattheunusedsensorhasahighernoisedensitythanthemanufacturer’svalue(Fig. 3). 212 We repeated the same procedure for sensors already used in deployments and found that the noise 213 does not increase with the usage of the sensor (LP1 was used the most, 5100 hours). Therefore, 214 for the sensor noise, we will use the value 0.22 <6¹p Iº1. From a practical point of view, this 215 sensor noise level only becomes important when dealing with very low amplitude waves, e.g., 216 waves-in-ice. Fortheﬁeldmeasurementsdescribedinthispaper,thestaticnoiseofthesensorwas 217 subtracted only for the waves-in-ice measurements (Section 5d). 218 b. Benchmark test 219 The benchmark tests were conducted with a custom-made device (Fig. 4a). The amplitude was 220 keptconstantat68mm(+-1mm),whileperiodwasvariedbetween1to25sbyadjustingthespeed 221 ofthedevice. Sincethedevicedidn’treproduceaperfectsinewave,allthemeasuredacceleration 222 signals had harmonics at multiples of the dominant signal. The measured acceleration signal was 223 transferred to frequency space, the noise was removed and then double integrated and transferred 224 back to time space. Mean amplitudes of #cycles were calculated. #varied between 8 and 30, 225 depending on the cycle period. 226 The results of the benchmark test for periods 1, 5, 10, 20 and 25 s are shown in Table 1. The 227 sensor is able to measure movement in the wind-wave and swell period range. The diﬀerence 228 betweentheprescribedandmeasuredvaluedependsontheacceleration—themeasuredamplitude 229 starts to deviate with decreasing acceleration, being 6% at 0.04 Hz. 230 13 c. Wave tank 231 We tested the wave buoy’s response to irregular waves in both tethered and free-drift setups. 232 The experiments were conducted in a wave tank (Fig. 4b) owned by the Small Craft Competence 233 Centre of the Tallinn University of Technology. The aim was to validate the high-frequency part 234 of the spectrum and determine the accuracy of LP in conditions which represent wave growth at 235 short fetches. 236 The60mlong,5mwideand3mdeeptankuses6paddlestogeneratewaves,whicharerecorded 237 by a capacitance wave height gauge (developed by Akamina Technologies) in the middle of the 238 tank. The duration of wave generation varied from 210 s to 300 s. 239 For the tests, we moored one buoy 2 m from the wave gauge and let the other two drift. With 240 the JONSWAP spectrum, we made 8 tests (Table 2), in which each combination of peak period 241 and signiﬁcant wave height was repeated twice. For each test, a 3-minute-long time-series was 242 analyzed. ThetimeserieswasconvertedintoadisplacementpowerspectrausingtheWelchmethod 243 (block length 30 s, 50 % overlap). Neither data sets were decimated; LP data sampled at 50 Hz 244 and wave gauge data sampled at 200 Hz were used. 245 Signiﬁcant wave height, integrated between 0.30 Hz and 1.28 Hz, shows a satisfactory match 246 between wave gauge and wave buoys (Table 2). The diﬀerence in signiﬁcant wave height between 247 the buoys and the wave staﬀ was -1–3 cm. The wave spectra (Fig. 5) reveals a similar structure 248 between the wave gauge and buoys up to 1.28 Hz and a slight shift of frequencies of the drifting 249 buoys due to Doppler shift. 250 14 5. Field tests 251 The ﬁeld tests were conducted in the seasonally ice-covered Baltic Sea, which is an enclosed 252 basin with a maximum fetch of 700 km. The deployments were made within 5 km from the coast 253 (Fig. 6). 254 a. Comparison against a Directional Waverider 255 We deployed buoys at two locations close to the operational Directional Waverider DWR-Mk 256 III/one.sup,whichwasmooredatadepthof20moutsideofSuomenlinnaintheFinnishArchipelago(Fig. 257 6). Themeasurementareaischaracterizedbytensofislandsinvaryingsizeandbusyrecreational 258 andcommercialvesseltraﬃc,althoughthecommercialtraﬃcduringthedeploymentswasreduced 259 because of COVID-19 restrictions to travel. 260 With some short gaps, the deployments lasted from June to November 2020 (Table 3). Four 261 diﬀerentbuoyswereused,becausethebatterylifeofonedevicedidnotlastfortheentirecampaign. 262 The buoys were moored approximately 300 m north of the DWR (Fig. 6), where the water depth 263 was17m. Therecommendedmooringconsistedofananchor,asurfaceﬂoat,LP,ropesconnecting 264 theassembly,andweights(Fig. 4c). Themooringenduredstrongwindsfromallmajordirections. 265 The maximum 10 minute averages were 15 ms1(west), 16 ms1(north), 14 ms1(east) and 21 266 ms1(south), with the gusts reaching 27 ms1. The buoy was not dragged from its deployment 267 location, which shows that a 25 kg mooring anchor was suﬃcient. 268 TwobuoysweredeployedinJuneusingasmallplasticmotorboat. InAugust,oneofthesebuoys 269 was removed and the second one was replaced (using the same boat). In September, the buoy was 270 replacedagainusingamotorizedsailingvessel,anditwasﬁnallyretrievedwithapilotboatinthe 271 beginning of December. 272 /one.supThen owned by the City of Helsinki, now owned by Finnish Meteorological Institute. 15 The spectra from both LP and DWR were integrated between 0.10–0.58 Hz, and both devices 273 generally agreed on the wave statistics for the ﬁeld experiment (Table 4; see Appendix A for the 274 deﬁnition of the statistical parameters). The mean signiﬁcant wave height was 0.42 m, which is 275 0.10 m higher than the 2016–2018 measured average (Björkqvist et al. 2019). Both LP and DWR 276 measured a similar highest signiﬁcant wave height, with the diﬀerence being within the expected 277 samplingvariability. Thewaveperiodsagreedbetterthemoretheyweredeterminedbytheshorter 278 waves, with)<02showing the best agreement and )?the worst. The maximum peak period values 279 for LP are probably not realistic but stem from the low-frequency noise dominating the lowest 280 integration frequency when total energy was very low. The dominant wave direction for both 281 instrumentswassouth-southwest. Thespreadingwas,inameansense,slightlyhigherforLPthan 282 for DWR. 283 Overall,thesigniﬁcantwaveheightmeasuredbyLPandDWRmatchedwell(Figs. 7–9),witha 284 0.01mbiasand0.99correlationcoeﬃcient(Table5). Duringtwooccasionsintheﬁrstdeployment, 285 LP measured an around 0.2 m higher signiﬁcant wave height than the DWR (Fig. 7b). Both of 286 these cases took place during around 10 ms1easterly winds, but LP and DWR matched up well 287 during roughly 13 ms1easterly winds in the autumn (Fig. 9b). We have not yet determined a 288 deﬁnitive reason for the discrepancy during the summer cases. A tangling of the moorings of the 289 LPs is improbable since both LPs measured similar wave heights. 290 The wave periods determined from spectral moments compared well to those from the DWR 291 (Fig. 10b,d,f). The scatter index was 3–5%, with the biases being no more than 0.16 s (Table 5). 292 The scatter index is highest (23 %) for the peak period (Table 5). The general poor validation for 293 the peak period is explained by the archipelago environments, where the peak of the spectrum is 294 often not well deﬁned (Björkqvist 2020). The wave spectrum was more closely unimodal for the 295 strongestsoutherlywinds,andthepeakperiodthereforematchedupwellinthecaseofthehighest 296 16 signiﬁcant wave heights (Fig. 10j). The characteristic period has been proposed as an alternative 297 to the instances when the peak period is ill-deﬁned. The validation of the characteristic period 298 showed that it removed a large part of the scatter between the two devices while keeping the bias 299 at a low 0.03 s value (Fig. 10h, Table 5). 300 Similarly to the peak period, the scatter index was also high for the peak spreading (25%). One 301 majorissueincomparingthepeakwavedirectionandspreadingofdiﬀerentdevicesinarchipelagos 302 isthat,becausethespectralpeakisill-deﬁned,onemightcomparepropertiesofcompletelydiﬀerent 303 wave components. The validation of the mean direction shows that LP and DWR agree on the 304 wavedirection(Fig. 10c). Themeanspreadingalsoshowsagenerallygoodagreement(Fig. 10g), 305 but with a slight oﬀset corresponding to a bias of 3 °(Table 5). 306 An additional validation of the spectral shape was performed by using the spectral narrowness 307 parameter (^2). This parameter was proposed by Battjes and van Vledder (1984) and was found 308 to be suitable for archipelago conditions by Björkqvist et al. (2019). The agreement between 309 DWR and LP was reasonable (Fig. 10i), with a correlation of 0.92 and a bias of -0.02 (Table 310 5). The scatter index was high (23%), although we are not aware of any other cross-instrumental 311 validationforthisparticularparameter. Severalwidthparametersaredeﬁnedusinghighermoments 312 (Cartwright and Longuet-Higgins 1956) and are therefore sensitive to the high-frequency part of 313 thespectrum. Thevalidationwasthereforepartiallylimitedbythe0.58Hzupperfrequencyofthe 314 DWR. In the 0.10–0.58 Hz frequency range, LP spectra tend to be slightly wider than those from 315 the DWR, which might be caused by low-frequency artefacts during low sea states. 316 The spectral comparison shows a qualitatively good match (Fig. 11) between LP and DWR, 317 except for the low-frequency part where LP has artefacts. During the northerly wind case (Fig. 318 11a), the peak of the spectrum was roughly at 0.5 Hz, just below the cut-oﬀ frequency of the 319 DWR. Above the DWR cut-oﬀ frequency, LP spectra followed a 54tail. For the easterly and 320 17 westerly wind events, a clear peak was not deﬁned (Figs. 11b,c), which is a typical situation for 321 the archipelago-type spectrum with many diﬀerent fetches for a ﬁxed wind direction (Björkqvist 322 2020). The highest waves measured during the campaign were due to southerly winds, and both 323 the LP and the DWR spectra showed a good match even for the longer waves of a 9 s period (Fig. 324 11d). 325 Insummary,thevalidationconﬁrmstheaccuracyofLPincomplexwaveconditions. Thescatter 326 ofthepeakparametersisexplainedmorebytheill-deﬁnednatureoftheparameterthananyactual 327 diﬀerencesbetweenthedevices. Otherwise,thevalidationstatisticsaresimilartothosedetermined 328 for other small buoys when validated against established technologies (Raghukumar et al. 2019; 329 Lancaster et al. 2021). 330 b. Intercomparison of four moored devices 331 Foranintercomparisonofseveralbuoysinthesamewaveconditions,wemooredfourbuoysina 332 squarelayoutwithamaximumdistanceof140mfromeachotherinplaceswherethewaterdepth 333 was 18–19 m (deduced from nautical charts) (Fig. 6). The buoys were deployed in December and 334 retrievedtendayslaterinJanuarywithamotorboat. Thelocationwaschosenduetoitsopennessto 335 long-wavesfromtheNorthernBalticProperanditsgentlyslopingbottom,whichkeepsthespatial 336 wave height gradient small. 337 Themooringconsistedofa60mropefromtheanchortothesurfaceﬂoatanda20mropefrom 338 the ﬂoat to the wave buoy. Unfortunately, LP3 started leaking during the ﬁeld campaign, causing 339 the MEMS sensor not to register data. We exclude this instrument from further analysis. After 340 retrieval, the instrument was cleaned and dried, and subsequent tests showed that no permanent 341 harm was done to the electronics. 342 18 The mean wind speed during the measurement campaign was 4.1 ms1, but gusts at the Pakri 343 weather station reached 16.5 ms1. During moderate wind speeds (over 6 ms1), the wind was 344 mainly blowing from north or south. The maximum signiﬁcant wave height was 1.22 m, and 345 the maximum wave period was 5.97 s (Fig. 12). With the exception of the northerly winds, the 346 waves and wind were misaligned. The misalignment was caused by the slanting fetch (Donelan 347 et al. 1985; Pettersson et al. 2010) and local topography. The slanting fetch also increased the 348 directionalspreading,sincelongerwavesusuallycamefromthewesteventhoughtheshortwaves 349 werealignedwiththewind. Fornortherlywinds,thewaveandwinddirectionsaligned,leadingto 350 a lower spreading compared to other wind directions. 351 Thewaveparametersbetweenthediﬀerentbuoysagreedwell(Fig. 12). The '2values(between 352 LP1–LP2,LP1–LP4andLP2–LP4)forsigniﬁcantwaveheightareover0.99andover0.98formean 353 wave period and for directional spreading. The scatter index between <0was 3–5 %, reﬂecting 354 the variability caused by sampling a random process (Donelan and Pierson 1983; Forristall et al. 355 1996). 356 The outlier was the mean wave direction of LP1. During the Suomenlinna UAV deployment 357 (describedinthenextsection)thereleasesystemmalfunctionedandthebuoyfelltorockyground 358 fromapproximately2m. Althoughbulkomnidirectionalparametersanddirectionalspread(which 359 does not depend on true north reference) were reasonable, the yaw angle probably lost its north 360 referencing capabilities, thus rendering the directional estimates unreliable. 361 c. Deployment with an Unmanned Aerial Vehicle as a drifter 362 Vääna-Jõesuu (VJ) was the ﬁrst ever deployment of LP with an UAV (Fig. 13a). The buoy took 363 about2hourstodriftbacktotheshore. Signiﬁcantwaveheightwasabout1m,whichalsomatched 364 the value from a Copernicus CMEMS product (not shown here). 365 19 During the Suomenlinna deployment the buoy was dropped near the moored DWR (Fig. 13b). 366 Windgustsreached15ms1andthesigniﬁcantwaveheightwasaround1mwithawavedirection 367 from SSW. The buoy drifted until the next day and was picked up from a rocky island with a pilot 368 boat. 369 At Leppneeme (Fig. 13c), the buoy was deployed from the shore. Although the wave direction 370 wastowardstheshore,alongshorecurrentstransportedthebuoyeastwardforabout12hoursbefore 371 it got stuck in pancake ice close to the coast (Fig. 1c). The signiﬁcant wave height was roughly 372 0.5 m. 373 TheUAVgroundstationswereabout2kmfromthedeploymentsites. Duringthesethreeexper- 374 iments, we operationally estimated the drift of the buoys with Seatrack Web (https://stw.smhi.se/) 375 and found that the wind leeway coeﬃcient is around 2.5 %, which is in the same range as similar 376 spherical drifting buoys (Sutherland et al. 2020). 377 IntheGulfofRiga,wedeployedthreebuoysfromiceontoice(Fig. 13d). UAVgroundstations 378 were approximately 2 km from shore at locations where pack ice was still safe to walk on. The 379 buoys drifted with ice (with occasionally entering open water) up to month. One buoy stopped 380 sending data 10 days after the deployment because it was brought directly from another (moored) 381 experimentandthebatterylevelwasalreadylow. Luckily,localsfounditonshoreandnotiﬁedus 382 usingthecontactinformationonthebuoy. Theresultsfromthemeasurementsinicearedescribed 383 in Section 5d. 384 The description of the UAV deployment procedures are presented in Appendix C. 385 d. Waves in ice measurements 386 We deployed three drifting buoys in the eastern part of the Gulf of Riga (see Section 5c). On 6 387 March 2021 a strong southwesterly wind event occurred, with the average measured wind speed 388 20 and wind gusts being 15 ms1and 21 ms1, respectively (Fig. 15a). Sentinel-1 overﬂights in the 389 morning (04 UTC) and in the evening (16 UTC) showed that the ice edge retreated more than 10 390 km in about 12 hours (Fig. 14a,b). The Copernicus CMEMS wave ﬁeld forecast predicted a 2 m 391 signiﬁcant wave height near the ice edge close to the wave buoys (Fig. 14c). The predicted peak 392 period was 7 s, and the wave direction was between SW and W. 393 All three buoys started picking up the wave signal at around noon, and in the evening the 394 signiﬁcantwaveheightreachedupto1.2cmatthebuoythatwasclosesttotheiceedge(Fig. 15b). 395 The measured energy was above the sensor noise threshold for frequencies 0.10–0.14 Hz, and the 396 surfacedisplacementtimeseriesshowedidentiﬁablewavegroupsduringthetimeofthemaximum 397 signiﬁcant wave height (Fig. 15c–d). The roll and pitch angles deviated less than 1 °, indicating 398 that the buoys were ﬁrmly lodged in ice during the wave event. 399 6. Discussion 400 Researchanddevelopmentofprototypeminiaturewavebuoysandloggershasincreasedinthelast 401 decade,e.g.,(Loehretal.2013;Kennedyetal.2014;Hirakawaetal.2016;Centurionietal.2017; 402 YurovskyandDulov2017;Farberetal.2018;Skinneretal.2018;Zongetal.2019;Carandelletal. 403 2020; Cook et al. 2020). Small and aﬀordable emerging wave buoys, like Spotter (Raghukumar 404 etal.2019)andLP,openupnewpossibilitiesfordeployinglargenumbersofbuoyssimultaneously. 405 WiththeSpotter,thishasalreadybeenimplementedonoceanicscalesthroughassimilationofwave 406 data in an operational wave model (Houghton et al. 2021; Smit et al. 2021). The ice resistance 407 allows LP to be deployed in the marginal ice zone in large quantities, thus complementing the 408 existingwaves-in-iceloggers(Kohoutetal.2015;Rabaultetal.2016;Montieletal.2018). Thisis 409 of utmost importance since our knowledge on wave-ice interactions is still limited due to the low 410 number of measurements made in ice (Squire 2020), especially measurements of the directional 411 21 wave spectrum. Wave heights can be very low in the MIZ, and we have shown that a signiﬁcant 412 wave height of 1 cm is detectable by LP. 413 Intheseasonallyice-coveredwaterbodies,acauseforconcernisthefactthatoperationaldevices 414 have to be removed before the arrival of ice to avoid damaging the buoys. Nonetheless, the 415 harshest wind conditions, and therefore wave conditions, can typically distort the wave statistics 416 compiled purely from measurements (Björkqvist et al. 2018). Although LP is not designed to 417 replace operational wave buoys, one possible application would be to complement operational 418 measurements by replacing the operational buoy with LP when it is retrieved, thus capturing the 419 open water time before freezing. LP should survive the ice, but if the buoy is lost, the ﬁnancial 420 implications are not as severe as a loss of an expensive operational buoy, nor do they threaten the 421 continuity of the operational measurements as a whole. 422 Routine measurements also seldom capture waves shorter than 0.5-0.6 Hz, but LP extends the 423 measurement range to 1.28 Hz (roughly 1 m wavelength). These shorter waves have been exten- 424 sively studied with specialized research set-ups, e.g., using wave staﬀs or polarimetric cameras. 425 Thereasonforthepersistentscientiﬁcinterestforthispartofthewaveregimeisitsdecisiveimpact 426 onmanysea-atmosphereprocesses. Wavesbetween0.58–1.28Hzhavebeenshowntocontribute 427 26 % of the so-called Stokes drift (Lenain and Pizzo 2020), and they also carry a signiﬁcant part 428 of the wave-induced stress (Janssen 1991; Mueller and Veron 2009). These processes then aﬀect 429 thedriftoftheobject,oilandothersurfactantsandenhancetheupper-layerturbulenceandmixing, 430 thus contributing to the sea-atmosphere ﬂuxes of e.g., $ 2. One possible niche for LP could be 431 regions like archipelagos, fjords or small lakes. In these areas, the short waves can carry a major 432 partofthetotalwaveenergy,butestablishingelaborateresearchwavemeasurementstationsmight 433 not be feasible. From a practical perspective, the measurement of the high-frequency part might 434 22 require cleaning of the buoy after some time to avoid accumulation of added mass and change of 435 the buoy dimensions due to bio-fouling (Thomson et al. 2015; Campos et al. 2021). 436 Peak wave periods can reach 25 s in the world oceans (Hanaﬁn et al. 2012), but low-frequency 437 noise in wave measurements are unfortunately a common feature. Ashton and Johanning (2015) 438 found spurious low-frequency energy caused by high drift forces brought about by currents and 439 mooring. Low-frequency artefacts can also be created by a loss of the GPS-signal in buoys that 440 usetheDopplershifttomeasurethebuoyvelocity,e.g.,theDWR-G4(Björkqvistetal.2016). We 441 found that the MEMS sensor of the LP also suﬀers from low-frequency noise. This noise comes 442 from the gyroscope random noise, which aﬀects the pitch, roll and yaw angles. These angles are 443 then used to calculate the free acceleration inside the sensor, and the noise is further ampliﬁed by 444 double integration. Low-frequency noise was also present in drifting buoys. 445 YurovskyandDulov(2020)alsoidentiﬁedlow-frequencynoise,butdidn’tpresentanycorrection 446 method. Earle and Bush (1982) and Lang (1987) proposed a method for denoising by subtracting 447 energy present at low-frequencies from higher frequency. By comparing several months of LP 448 measurements to coinciding Waverider measurements, we concluded that a large part of the low- 449 frequency noise in the spectrum is actually variance density that is somehow redistributed from 450 higher frequencies. When the low frequency part was denoised, we quantiﬁed the amount of 451 variancethatwaslostandre-introducedthisvariancebacktothehigherfrequenciesinproportion 452 tothealreadyexistingvariance(seeAppendixB).ThiscorrectionwasperformedinFourierspace, 453 whichmeansthatalreadythetimeseries,determinedthroughtheinversetransformafterintegration 454 in Fourier space was corrected. Although this method is partially ad hoc, it was shown to correct 455 theﬁnalspectrumforbothdominantwavesandthespectraltail. Nonetheless,furtherdevelopment, 456 not excluding changing the MEMS sensor, is currently pursued. 457 23 Non-typical deployments, such as aerial deployments by UAVs, have recently been used as an 458 additional tool in observational studies (Zappa et al. 2020). UAVs are gaining popularity since 459 they can carry lightweight sensors (Fuertes et al. 2019). These innovative solutions are partially 460 motivated by environmental concerns, but they also allow to bypass the cost of a ship. Because 461 of its low weight, LP can be deployed by an industrial UAV as a drifter. It has already been 462 tested in deployments from shore and from sea ice with the deployment range extending to 2 463 km. These novel deployment techniques are still being established, but possible applications can 464 include collecting data from surf zones or transporting a buoy onto the MIZ. UAV deployments 465 will continue to be one part of the further development of LP. 466 It is possible to extend the operation time of LP by replacing rechargeable Li-ion batteries with 467 Lithium-Thionyl chloride primary batteries. These batteries have an energy density that is about 468 2.5timeshigherthanthatofrechargeableones. Thiswouldextendtheautonomousoperatingtime 469 to 5 months and make measurements in remote locations more feasible. Also, the buoy leaked 470 on two occasions over the course of 18 ﬁeld deployments. These incidents have been accounted 471 for when designing the new hull (Fig. 16). The new hull is made of molded plastic and has a 472 sealingO-ringonthetop. Externalconnectorsforchargingandaccessingdatahavebeenaddedto 473 removetheneedforopeningthebuoyandtoenhanceusability. Theinertialsensor,electronicsand 474 measurementmethodologyarekeptthesame. Firstlaboratorytestsofthenewdesignondurability 475 and waterproofness have been carried out successfully, but further testing is ongoing to validate 476 this new design in the ﬁeld. 477 24 7. Conclusions 478 Awavebuoy(LainePoiss,LP)wasdeveloped. LPweighs3.5kg,measureswavesupto1.28Hz, 479 has arechargeable battery with 2months of operation,and transmits wave parametersand spectra 480 operationally over cellular or satellite networks. From our study, we can conclude the following: 481 •Wave parameters measured in the ﬁeld were in good accordance with those measured by a 482 nearbyDirectionalWaverider: thebiasof <0was0.01m,correlation0.99andscatterindex 483 of8%.)<10bias0.14s,correlation0.98andscatterindex4%. Themeanabsolutedeviation 484 of mean wave direction was 7 °. 485 •The high frequency part of the spectrum (up to 1.28 Hz) compared well to a wave gauge in 486 the wave tank. The wave spectrum of LP was validated up to a Waverider cut-oﬀ frequency 487 of 0.58 Hz in the ﬁeld, and the spectral tail of LP had an expected power-law behavior up to 488 1.28 Hz. 489 •LPcanmeasurewavesinicewithasigniﬁcantwaveheightaslowas1cm. Thiswasconﬁrmed 490 inanoveramonth-longexperimentwhereseveralLP’sweredeployediniceintheBalticSea. 491 •Becauseofitslowweight,LPcanbedeployedasadriftertoadistanceofatleast2kmusing 492 an Unmanned Aerial Vehicle (UAV). 493 Noise in the gyroscopic sensor resulted in low-frequency artefacts, but the displacement time 494 series can be corrected (see Appendix B). We will continue testing the wave buoy and expand our 495 measurement areas outside of the Baltic Sea to capture longer waves. Depending on the MEMS 496 sensor noise levels in these conditions, we can decide whether to replace the wave buoy’s sensor 497 for one with several times less noise. 498 25 Acknowledgments. This work was supported by the Personal Research Funding of the Estonian 499 Ministry of Education and Research (grant number PSG22). 500 We would like to thank Lauri Laakso and Roine Tuomo for helping with Suomenlinna ﬁeld 501 experiments. We appreciate discussions with Kimmo Kahma. We thank Rivo Uiboupin, Jüri 502 Elken, Aarne Männik and Sigrid Aas for keeping the administrative matters under control. We 503 thank Tarmo Kõuts for helping us with the ﬁrst versions of real-time display of data on a website. 504 The ﬁrst author thanks (little) Aran Alari for inspiring the wave buoy name LP. 505 We thank the following institutions and enterprises for their successful participation in the 506 applications of LainePoiss: the Maritime Administration of Estonia, the Estonian Environment 507 Agency,ASSaarteLiinid,OÜLainemudel,TalTechSmallCraftCompetenceCentreandtheCity 508 of Helsinki. 509 Valdur Kaldvee and Kristjan Mölder are the founders, and the sole owners and employees 510 of WiseParker OÜ who produce the LainePoiss wave buoy presented in this manuscript. The 511 development of LainePoiss has been made in co-operation with Tallinn University of Technology 512 Dataavailabilitystatement. Thedatausedinthismanuscriptwillbemadeopenlyavailableupon 513 the publication of the ﬁnal paper. 514 APPENDIX A 515 Statistical parameters 516 With#is the number of data points we used the following statistical parameters: 517 Mean=G8=1 #Õ 8G8 (A1) 26 For angular quantities, \, the mean is deﬁned as 518 \8=arctan sin¹\8º cos¹\8º!  (A2) and the diﬀerence 519 j\1\2j=minfj\1\2j360j\1\2jg (A3) The covariance is 520 Cov¹G8A8º=s 1 #1Õ 8¹G8G8º¹A8A8º (A4) whereG8are observations and A8are the reference values (typically from the Waverider). 521 The variance and standard deviation are 522 Var¹G8º=Cov¹G8G8º (A5) Std¹G8º=p Var¹G8º (A6) For cross-comparison of data sets, we deﬁned the following parameters: 523 Bias=G8A8 (A7) The root-mean-square deviation, mean absolute deviation and scatter index (in percent) are 524 deﬁned: 525 RMSD=s 1 #Õ 8¹G8A8º2 (A8) MAD=Õ 8jG8A8j # (A9) 27 SI=100vuuuuuuutÕ 8»¹G8G8º¹A8A8º¼2 Õ 8A2 8 (A10) The slope is deﬁned as a least-squares-ﬁt G= A 526 =Í 8G8A8 Í 8A2 8 (A11) and the Pearson correlation coeﬃcient is 527 R=Cov¹xiriº Std¹G8ºStd¹A8º (A12) APPENDIX B 528 Renormalization in integration 529 The limitations of the sensor create low-frequency noise, but we have concluded that this noise 530 is actually a misplaced signal from other frequencies. If the low-frequency noise is removed, it 531 should be added back to the frequencies, so that the power spectrum fulﬁlls the following: 532 ¹5º=0¹5º¸Y0¹5ºÍ 50¹5º(B1) =0¹5º 1¸YÍ 50¹5º  (B2) where 533 Y=Õ 5ˆ¹5ºÕ 50¹5º (B3) and ˆ¹5ºand0¹5ºare the power spectra of the unprocessed and denoised signals. Y 534 quantiﬁes how much variance density of the signal has been lost. Especially, if Y=0then no 535 further correction is necessary. 536 28 Inpractise,thisdenoisingandcompensationisperformedduringtheintegration,whichresultsin 537 acleandisplacementsignalfromwhichthepowerspectrumcanbecalculatedinanormalfashion 538 without having to deal with the above compensation after the fact. 539 Low frequency acceleration data is ﬁrst denoised using the following procedure: the average 540 squared Fourier amplitude is calculated for the frequencies 1/100 to 1/30 Hz. 541 U=hjˆ¹5ºj2i11005130 (B4) where ˆ¹5º=F»0¹Cº¼is the Fourier transform of the acceleration signal and jˆ¹5ºjis its 542 modulus. 543 This mean value (the noise) is then removed from the Fourier transform by 544 0¹5º=maxf0ˆ¹5ºˆ¹5ºU1'5¹5º ˆ¹5ºg (B5) where'¹5ºis a response function: 545 '5¹5º=8>>>>>>>>> < >>>>>>>>>:0 0 5  5 1 1 2h 1cos c551 5251i 51552 1 52 55#(B6) Here51=008Hz and51=010Hz. In other words, the Fourier transform for 5 ¡010Hz is 546 not touched. 547 Followinge.g. Rabaultetal.(2020),theaccelerationvaluesarethenintegratedinFourierspace: 548 -0¹5º=0¹5º'5¹5º¹2c5º2(B7) ˆ-¹5º=ˆ¹5º'5¹5º¹2c5º2 (B8) 29 where51=005Hz and52=006Hz in the response function '5¹5º. 549 That is, ˆ-¹5ºand-0¹5ºare now the uncorrected and denoised Fourier transform of the dis- 550 placement signal. We quantify how much of the squared amplitudes of the signal were lost by the 551 low-frequency correction: 552 X2=Õ 5jˆ-¹5ºj2Õ 5j-0¹5ºj2 (B9) Thislostsignalinformationwillbeaddedbackinawaythatwillcompensatethepowerspectrum 553 as outlined in Eq. B2: 554 -¹5º=-0¹5ºs 1¸X2 Í 5j-0¹5ºj2(B10) =-0¹5ºvt 1¸Í 5jˆ-¹5ºj2Í 5j-0¹5ºj2 Í 5j-0¹5ºj2(B11) =-0¹5ºvt 1¸Í 5jˆ-¹5ºj2 Í 5j-0¹5ºj21 (B12) =-0¹5ºvtÍ 5jˆ-¹5ºj2 Í 5j-0¹5ºj2 (B13) The displacement time series is then given by the inverse Fourier transform: 555 G¹Cº=F1»-¹5º¼ (B14) This time series is now corrected for the low-frequency artefacts, which has been redistributed 556 to the other frequencies. The power spectrum or any other statistics can now be calculated from 557 this displacement time series without further corrections. 558 APPENDIX C 559 30 Experiences from UAV deployments 560 In this appendix, we document our experiences from six events where an industrial Unmanned 561 Aerial Vehicle (UAV) was used to deploy LainePoiss (LP) as a ﬂoating device. Our deployments 562 weremadeinEstoniaandFinlandduring2019–2021. Theguidelinesandregulationsgoverningthe 563 useofUAV’schangeanddiﬀerfromcountrytocountry,especiallyoutsideoftheEuropeanUnion. 564 Make sure to get correct information and follow any local laws and ordinances when considering 565 deploying LP with an UAV. Also note that the steps below do not guarantee a safe or successful 566 deployment. 567 The UAV should be regularly maintained to be sure of the condition of the equipment; motors, 568 blades, batteries and the remote controller have to be working properly. Firmware and software 569 should also be up to date. Notiﬁcations through e.g., the remote controller or pilot application 570 should be taken seriously, and they need to be resolved before ﬂight. Before deploying the actual 571 device, we recommend practising with, e.g., sand bags that have the same weight as LP. 572 A successful UAV deployment starts with a comprehensive preparation and plan for the ﬂight 573 and requires at least two persons. The ﬁrst person ﬂies the drone while the second person assists 574 at lift-oﬀ and landing. We used a DJI Matrice 600 Pro industrial drone with a release mechanism 575 (Fig. 1b). A 5 m long ﬁshing thread (we used Dyneema 0.3 mm with a breaking strength of 25 576 kg) was found suitable for connecting the UAV and the wave buoy. A longer thread could make 577 releasingtheLPmoreconvenientastheUAVcanbehigher,thushavingastrongersignalstrength. 578 Nonetheless, a shorter thread minimizes the motion of the buoy during ﬂight. The lift-oﬀ is the 579 riskiestpart: thesecondpersonhastoholdthethreaddownwindandlowtothegroundtominimize 580 theriskofthethreadbeingcaughtbytheUAVmotors. Thishastobedonewhilekeepingadistance 581 ofatleastafewmetersfromtheUAV.Forthesafetyoftheassistingperson,thepilotshouldguide 582 31 the UAV upwards for the ﬁrst couple of meters as quickly as possible. The rest of the lift-oﬀ can 583 happen at a slower pace until the wave buoy is up in the air. We used a ﬂight height of 20–30 m 584 when transporting the wave buoy to the drop-oﬀ location. 585 With fully charged batteries at lift-oﬀ, we deployed the buoy at a distance of up to 2 km. We 586 started guiding the UAV back towards the ground station before the battery dropped below 50 %. 587 In our deployments we ﬂew upwind with the heavy weight, thus returning to the ground station 588 downwind. We found that the battery charge at landing was still at about 20 %. 589 Below is a step-by-step checklist that we have used in our deployments: 590 •The pilot does an UAV pre-check a day before ﬂight as well as on the ﬁeld. If applicable, 591 follow the messages from the pilot application. 592 •The second person, crouching at least 2 m from the UAV, holds the thread under tension 593 between the UAV and the person’s hand, ready to give slack as the UAV is ascending. 594 •Thepilotloudlynotiﬁestheotherpersonsbeforeactivatingmotorsandmakessureeverybody 595 is ready for lift-oﬀ. 596 •Thepilotascendstheﬁrsttwometersasquicklyaspossible,andthesecondpersongivesslack 597 to the thread as the UAV takes oﬀ. 598 •AsecondpersonmustholdthethreadundertensionbetweentheUAVandtheirhanduntilthe 599 LP is up in the air. 600 •Thread should be downwind, even though the UAV might deviate also downwind where the 601 second person is holding the thread. 602 Recommendations for the pilot: 603 •Flight height between 20–30 meters. 604 32 •Donotﬂyfurtherthan50%ofthebatterycapacity;ideallyﬂyupwindwithpayloadandreturn 605 with tailwind. 606