ALBERT

Description: Fennoskandien ist seit jeher ein Gebiet, auf das sich die geowissenschaftlichen Interessen konzentrierten. Ein Grund dafür ist die seit langem bekannte Landhebung von ca. 10 mm pro Jahr im Zentrum, das im nördlichen Teil des Bottnischen Meerbusens liegt. Neben den seismischen Untersuchungen der Struktur der Lithosphäre wird seit 1966 mit Hilfe der Präzisionsgravimetrie entlang der sog. Landhebungslinien versucht, durch wiederholte Schweremessungen den Effekt der Landhebung zu erfassen und dadurch, neben den Präzisionsnivellements, auch Hinweise auf den Mechanismus zu erhalten. Parallel dazu wurden an vielen Orten gravimetrische Gezeitenbeobachtungen durchgeführt, um realistische Gezeitenparameter für die Korrektur der Präzisionsgravimetrie zu ermitteln. Dabei stellte sich heraus, daß im Bereich der norwegischen Küste eine starke Anomalie der Parameter von bis zu 35% in der Amplitude und mehr als 20° in der Phase festzustellen ist, die man auf die Wirkung der ozeanischen Auf lastgezeiten zurückführen kann. Die vorliegende Arbeit befaßt sich mit den gravimetrischen Gezeitenregistrierungen entlang der Geotraverse "Blaue Straße". Dieses Profil beginnt an der norwegischen Küste in der Nähe des Polarkreises und läuft mit etwa 125° in südöstlicher Richtung bis an den Finnischen Meerbusen nahe der sowjetischen Grenze. Die Besonderheit der Stationsauswahl liegt in der Verdichtung der Meßorte im Bereich der Küste: Hierdurch ist es möglich, das Abklingen des Effektes der ozeanischen Auflast zu erfassen. Dies erlaubt gezielte Mode 11 Untersuchungen zur Überprüfung von lokalen Meeresgezeitenmodellen mit einer unabhängigen Methode: Neben den elastischen Eigenschaften der Lithosphäre, insbesondere der Tiefe der Krusten-/Mantelgrenze gehen lediglich die Verteilung der Amplituden und Phasen der Meeresgezeit in die Rechnung ein, nicht aber die Parameter und die Randbedingungen, die zu ihrer Modellierung benötigt werden. Durch die Verdichtung der Stationen im Küstenbereich können auch Aufschlüsse über die Struktur der Lithosphäre, vor allem die Moho - Tiefe, gewonnen werden. Es standen für die Messungen in den Jahren 1980 bis 1983 fünf Gravimeter zur Verfügung, mit denen insgesamt sieben Stationen vermessen wurden. Die Registrierzeiträume lagen zwischen 10 und 26 Monaten. Im Folgenden werden die bisherigen geowissenschaftlichen Befunde für Fennoskandien und für das Pof il "Blaue Staße" im Besonderen zusammengefaßt, die Methoden der Auflastberechnung diskutiert und die Problematik der Modellierung der Meeresgezeiten dargestellt. Die Messungen schließen intensive experimentelle Arbeiten wie auch Überlegungen zur Datenbearbeitung und Analyse ein. Besonderer Wert war dabei auf die Kalibrierung der Gravimeter zu legen, die im Berliner Gezeitenobservatorium (Insulaner) erfolgte. Die Interpretation der Residuen der Welle M2 hinsichtlich der Auf lastgezeiten ergab schließlich, daß die Schelfgezeiten bei der Modellierung in der Phase um 15 bis 20° verzögert werden müßten, um der Beobachtung zu entsprechen. Hierdurch wird natürlich das Meeresgezeitenmodell nicht korrigiert, die gefundenen Abweichungen sind aber ein Hinweis für die Berechnung der Modelle. Überdies ergab sich eine besonders gute Übereinstimmung für eine flache Kruste. Dies steht im Einklang mit seismischen Ergebnissen aus dem Küstenbereich und bestätigt das Fehlen einer Gebirgswurzel unter den Kaledoniden. Auch für das Residuum der Welle 01 wird eine Inkonsistenz mit dem Meeresgezeitenmodell festgestellt, die sich hier allerdings nicht aus der Modellierung der Schelfgezeiten erklären läßt: Die Amplituden von 01 liegen bei 3 bis 5 cm. Die lokale Wirkung ist demnach gegenüber M2 (80 bis 100 cm) zu klein. Für die Korrekturen der Präzisionsschweremessungen komplettiert dieses Profil das bereits vorhandene Stationsnetz und ermöglicht die flächenhafe Interpolation. Daraus lassen sich dann später unter Hinzuziehung der anderen Hauptwellen realistische Gezeitenkorrekturen für alle Stationen ermitteln.

Description: Fennoscandia has always been an area of special interest for geoscientists. One reason for that ist certainly the well known land uplift of about 10mm/yr in its center, which is located in the northern part of the Gulf of Bothnia. Besides the seismic research of the structure of the Lithosphere since 1966 precise gravity surveys are carried out along the so called land uplift lines. By repetition of these measurements it is hoped to monitor the effect of land uplift, and to get indications of its mechanism. In addition tidal gravity observations were carried out at many places to achieve realistic tidal parameters for the correction of the precise gravity surveys. It was found that esp. adjacent to the sea there is a strong anomaly of the parameters of up to 35% in amplitude and more than 20° in phase. This can be allocated to the effect of the ocean tides. The present work deals with the tidal gravity measurements along the geotraverse 'Blue Road'. This profile starts at the Norwegian coast close to the polar circle running about 125° south-east till the Gulf of Finland, close to the Sowjet border. The speciality of the choice of the station locations is in their concentration near the coast. By these means it is possible to monitor the decrease of the effect of the ocean loading. This enables the check of local ocean tide models by an independent method: In addition to the elastic properties of the Lithosphere, esp. the depth of the crust/mantle boundary, only the distribution of the calculated ocean tidal amplitudes and phases are included into the calculations; the parameters and boundary conditions necessary for the calculation of these models are not used. By concentration of the stations near the coast also hints on the structure of the Lithosphere, esp. the depth of the Moho can be achieved. The measurements were carried out during a period from 1980 to 1983, and five gravimeters were available to measure at seven stations. The recording intervals were between 10 and 23 months each. In the following the geoscientif ic findings obtained up to now for Fennoscandia are put together, in detail for the 'Blue Road' profile. The methods of loading calculations and the problem of modelling the ocean tides are reviewed. The preparations of the measurements include intense experimental work as well as efforts in data treatment and analysis. Special care was necessary for the calibration of the gravimeters which was performed at the Tidal Observatory Berlin (Insulaner). The interpretation of the tidal residuals of the constituent M2 resulted in the fact, that the shelf tides should be retarded by 15 to 20° to fit the observations. Of course, this is no way to correct the tidal chart, but it provides boundary conditions for the calculation of these models. In addition, the best fit was achieved assuming a fairly thin crust in the coastal area. This corresponds to seismic results and confirms the lack of a mountain root below the Caledonides. For the residual of 01 the interpretation showed a significant restvector, too. But here it is not possible to use the shelf area for an explanation: In contrary to M2 (amplitudes of up to 100 cm) the 01 amplitudes of the shelf tides are only in the order of 3 to 5 cm, which is too small. These profile measurements complete the Fennoscandian net of tidal results. This enables the spatial interpolation of the values and, by addition of the other main tidal constituents, it will be possible to derive realistic tidal corections for the repeated precise gravity surveys.

Description: thesis

Description: DFG, SUB Göttingen

Description: In a regional study based upon a large set of sea-level data and meteorological data, the long-period variations in sea-level and the fluctuations of meteorological parameters have been investigated for the Norwegian coast. In the period range between 1 and 20 years, the sea-level is found to be dominated by a few distinct signals. The interaction between meteorological parameters and sea-level is discussed. The sea-level is found to respond to long-period air pressure variations as an inverse barometer. Most of the sea-level signals with periods between 1 and 5 years are at least partly due to similar signals in air pressure and/or wind stress. In the Chandler band, the meteorological parameters contain at least two distinct signals. The oceanic pole tide signal is masked by the atmospheric forcing of the sea-level. This leads to temporal variations in the apparent pole tide, which are uncorrelated with the temporal variations of the Chandler wobble. The air pressure corrected pole tide is still not an equilibrium tide, but the large deviations in phase from equilibrium may well be due to unaccounted effects of wind stress and temperature. The Chandler wobble in polar motion is important as the driving force of the pole tide. In an extensive numerical investigation, the simple and physically reasonable model of a single frequency, damped, harmonic oscillation, which is frequently excited at random times and with random amplitude is found to explain all features of the observed Chandler and annual wobbles. Comparing the results from the numerical investigations to the results from analyses of the polar motion gives strong evidence for the Chandler wobble period to be either 428.5± 1.0 days or 437.2±0.8 days and not the usually assumed period of ≈434 days. No final decision can be made which of the two periods is the true Chandler period, though the shorter one is favoured by several facts. The signals in meteorological parameters can all be related to the variations in sunspot numbers. A non-linear response of the atmosphere to the annual solar forcing, which is modulated by the sunspot cycles explains the observed frequency patterns. The excess of the observed sunspot effects in surface air temperature over those predicted from simple climate models by a factor of 10 indicates the existence of strong positive feedback mechanisms, which are responsible for the signals in air pressure and wind stress, too. The 18.6-year nodal tide lags the equilibrium tide by 0.8 radian, while the amplitudes exceed the equilibrium amplitudes by a factor of 3 to 5. At most parts of the coast, the nodal modulation of the amplitude of the fortnightly lunar tide Mf also lags the equilibrium modulation by 0.5 to 0.7 radian. The amplitude of the nodal modulation is close to equilibrium, except for Oslo and Bergen. At the latter stations, resonance effects may modify the modulation. Mf itself is found to have an amplitude of two to three times the equilibrium amplitude and a phase lag of slightly more than π. Determining the land uplift at the Norwegian coast from the trend in sea-level leads to a varying pattern of isolines, with the land uplift gradient being perpendicular to the general direction of the coast line, and being rather large at parts of the coast. At most parts of the coast, the zero line is further out in the sea than given on other published charts.

Description: Die vorliegende Arbeit über langperiodische Variationen des Meeresspiegels entlang der norwegischen Küste basiert auf umfangreichen Datensätzen von Meeresgezeiten und Meteorologie. Alle verwendeten Meeresgezeitendaten lagen als Stundenstützstellen vor, die nach sorgfältiger Fehlersuche auf monatliche Mittelwerte reduziert wurden. Die längsten Meeresgezeiten-Registrierungen an der norwegischen Küste sind für Oslo und Bergen verfügbar, wo die Zeitreihen das Intervall von 1914 bis 1985 umfassen. Für sieben Stationen lagen Registrierungen von 1952 bis 1985 vor, und für jeweils weitere 2 Stationen waren Registrierung für die Zeiträume von 1961 bis 1985 bzw. von 1970 bis 1985 verfügbar. Die meteorologischen Daten standen an drei Station für die längeren Zeiträume von 1952 bis 1983 (Oslo und Bergen) bzw. von 1957 bis 1975 (Narvik ) zur Verfügung, und für 15 Stationen waren die Daten für den kürzeren Zeitraum von 1970 bis 1984 vorhanden. Dabei ist der Luftdruck mit einem Stützstellenabstand von drei Stunden registriert worden, während die übrigen Parameter (Windgeschwindigkeit und -richtung, Lufttemperatur) mit einem Stützstellenabstand von 6 Stunden vorliegen. Auch hier wurden aus den Daten monatliche Mittelwerte berechnet. Da die Wirkung des Windes auf die Meeresoberfläche als dem tangentialen Windstress proportional angenommen wird, wurden aus den Winddaten monatliche Mittelwerte für die beiden tangentialen Windstress-Komponenten berechnet. In dem Periodenbereich von einem bis etwa zwanzig Jahren sind die Schwankungen des Meeresspiegels von einigen wenigen, fast-periodischen Variationen bestimmt. Die Perioden, die in den Meeresspiegelschwankungen gefunden wurden, sind überwiegend auch in den untersuchten meteorologischen Parametern zu finden. Dabei sind diese Signale in Periode, Amplitude und Phase räumlich sehr homogen. Bei der Untersuchung der Signale in den meteorologischen Parametern Luftdruck, Ost-West- und Nord-Süd- Komponente des Windstress und Lufttemperatur zeigte sich, daß der überwiegende Teil der Perioden in ein Muster paßt, daß sich aus der Modulation der jährlichen solaren Anregung der Atmosphäre durch den Sonnenfleckenzyklus ergibt. Aus der Literatur ist bekannt, daß die Variationen in den Sonnenflecken mit Schwankungen in der Solarkonstanten und damit mit Variationen im Wärme-Input in das System Atmosphäre-Ozean verbunden sind. Die in der Lufttemperatur gefundenen Schwankungen mit Perioden zwischen einem und zwanzig Jahren haben Amplituden von ≈0.5°C und liegen damit um eine Größenordnung höhere als die aus einfachen Klima-Modellen abgeschätzten Effekte des Sonnenfleckenzyklus. Nur wenn man die Existenz positiver Rückkopplungs- Mechanismen annimmt, können die in den Beobachtungen gefundenen Variationen erklärt werden. Diese Rückkopplungen sind in beobachteten Veränderungen der vorherrschenden Wetterbedingungen mit dem Sonnenfleckenzyklus zu suchen. Änderun- gen der vorherrschenden Wetterbedingungen erklären dann auch das Vorhandensein dieser Perioden in Luftdruck und Windstress. Benutzt man die monatlichen Mittelwerte um die Antwort des Meeresspiegels auf Luftdruckschwankungen zu ermitteln, so ergibt sich für den größten Teil der Küste eine isostatische Antwort, vergleichbar einem inversen Barometer. Abweichungen finden sich insbesondere an Stationen am Ende von Fjorden (Oslofjord, Ofotfjord). Dort ist dann aber die Korrelation zwischen Windstress und Meeresspiegel höher als an Stationen an der offenen Küste, so daß diese Abweichungen von der isostatischen Antwort in wesentlichen durch Windeffekte bewirkt werden. Im Bereich der Chandler Periode sind im Luftdruck mindestens zwei Signale vorhanden, die mit Perioden von ≈1.14 Jahren und ≈1.22 Jahren die vom Chandler Wobble bewirkte Poltide verdecken. Die Signale im Luftdruck haben Amplituden (bis zu 200 Pa), die bei einer isostatischen Antwort des Meeresspiegels (etwa -1 cm/HPa) zu Signalen im Meeresspiegel führen, deren Amplituden deutlich über der Amplitude einer Gleichgewichts-Poltide (etwa 0.5 cm an der norwegischen Küste) liegen. Zu diesen Signalen im Luftdruck kommen noch Signale im Windstress und in der Lufttemperatur hinzu. Die Veränderungen in der Lufttemperatur können mit einiger Phasenverschiebung zu Signalen in der Wassertemperatur und über den Dichteeffekt zu entsprechenden Signalen im Meeresspiegel führen. Signale in der Temperatur des Meerwassers im Chandler-Band sind aus der Literatur bekannt. Diese komplizierte Wechselwirkung zwischen Atmosphäre und Ozean führt zu einer Verdeckung der vom Chandler Wobble bewirkten Poltide. Die Frequenz-Unterschiede zwischen den Signalen im Chandler-Band in der Atmosphäre und der Chandler Periode selbst (die auch der Periode der Poltide entspricht), führen zu langperiodischen Modulationen einer scheinbaren Poltide. Dadurch sind die beobachteten zeitlichen Variationen der Poltide nicht korreliert mit den zeitlichen Variation des Chandler Wobbles. Wird der isostatische Effekt des Luftdrucks auf den Meeresspiegel eliminiert, so ergibt sich eine Poltide, deren Amplitude nahe der Gleichgewichtsamplitude liegt. Der wesentliche Teil der Amplituden-Überhöhung der beobachteten Poltide gegenüber der Gleichgewichtsamplitude ist damit auf Luftdruckeffekte zurückzuführen. Die Phasenbeziehung zwischen beobachteter Poltide und der Gleichgewichtstide zeigt allerdings starke zeitliche Variationen. So ist im Interval von 1970 bis 1979 die Phase der beobachtete Poltide nahe der Gleichgewichtstide, während sich für das Interval von 1957 bis 1979 deutliche Abweichungen ergeben. Diese zeitliche Variabilität ist durch das Zusammenwirken verschiedener Signale im Chandler Band zu erklären. Insbesondere die in der Temperatur und im Wind gefundenen Signale mit Perioden nahe bei 14 Monaten können diese Variationen bewirken. Insgesamt wurden keine Hinweise gefunden auf eine von der Gleichgewichtstide abweichende Poltide. Der Chandler Wobble in der Polbewegung ist als Ursache für die Poltide wichtig für die vorliegende Arbeit. Da die in der Literatur publizierten Resultate bezüglich des Chandler Wobbles sehr widersprüchlich sind, wurden die Polbewegungsdaten des ILS/IPMS und vom BIH im Rahmen dieser Arbeit erneut analysiert. Mit Hilfe umfangreicher numerischer Untersuchungen konnte gezeigt werden, daß das einfache und physikalisch sinnvolle Modell eines mono-frequenten Chandler Wobbles, der häufig an zufälligen Zeitpunkten mit zufälliger Amplitude angeregt wird, ausreicht, um alle Eigenschaften des beobachteten Chandler Wobbles zu erklären. Durch Vergleich der Modellrechungen mit den Ergebnissen aus der beobachteten Polbewegung ergab sich, daß die tatsächliche Chandler Periode entweder bei 428.5± 1.0 Tagen oder bei 437.2±0.8 Tagen liegt, und nicht bei den üblicherweise angenommenen ≈434 Tagen. Dieses überraschende Ergebnis ist von großer Bedeutung für alle Arbeiten zur rheologischen Struktur der Erde. Dabei ist anzumerken, daß noch keine endgültige Aussage möglich ist, welche der beiden Perioden der tatsächlichen Chandler Periode entspricht. Allerdings wird die Periode von 428.5 Tagen durch einige Ergebnisse bevorzugt. Die in der Literatur üblicherweise genannte Periode von 434 Tagen ergibt sich gewöhnlich aus stark geglätteten Spektren. Diese Glättung führt bei einer Anregung nach dem oben beschriebenen Modell zu fehlerhaften Perioden. Die Untersuchung der aus den Polbewegungen ermittelten Gleichgewichtsbewegungen des Meeresspiegels erbrachte eine weitere interessante Korrelation: Eliminiert man aus diesen Gleichgewichtsbewegungen Poltide und jährliche Variation, so findet sich in den Residuen eine quasi-periodische Schwankung mit einer Periode von grob 30 Jahren. Diese Variation in den Gleichgewichtsbewegungen ist auf die als Markowitz Wobble bezeichnete Polbewegung zurückzuführen. Eine entsprechende, phasengleiche Variation findet sich auch in den Residuen der Meeresspiegelschwankungen, wenn man alle wichtigen Signale mit Perioden von einschließlich einem Jahr bis hin zu etwa 10 Jahren eliminiert. Falls diese Korrelation nicht zufällig ist, so müßte sie auch global zu finden sein. In der globalen Oberflächentemperatur und in der Änderung der Tageslänge finden sich ebenfalls Variationen, die mit den im residualen Meeresspiegel und in den Gleichgewichtsbewegungen gefundenen Signalen korrelieren, wobei die Variationen in der globalen Temperatur gegenüber den andern Parametern phasenverschoben sind. Die nodale Tide mit einer Periode von 18.6 Jahren zeigt entlang der norwegischen Küste gegenüber der Gleichgewichtstide eine Phasenverschiebung von etwa 0.8 Radian, und die Amplituden liegen um einen Faktor von 3 bis 5 über der entsprechenden Gleichgewichtsamplitude. Die Untersuchung der Variationen der Amplitude der vierzehntägigen Tide Mf zeigt eine ähnlich große Phasenverschiebung zwischen der beobachteten und der erwarteten nodalen Modulation, wobei hier die relativen Amplituden für alle Stationen mit Ausnahme von Oslo und Bergen nahe den Erwartungen liegen. Allerdings ist hier zu bemerken, daß die Amplituden der Mf um den Faktor 2 bis 3 über der Gleichgewichtstide liegen, und somit auch die Modulationen entsprechend erhöht sind. Die Unterschiede in Oslo und Bergen deuten auf Resonanz-Effekte hin. Der Trend im Meeresspiegel relativ zum Land ist an der norwegischen Küste im wesentlichen auf die Landhebung infolge der post-glazialen Entlastungsbewegungen zurückzuführen. Bestimmt man die Isolinien der Landhebungen aus den in dieser Arbeit ermittelten Trends, so ergeben sich Linien, die zu dem generellen Verlauf der Küste parallel sind. Bei Ålesund ergibt sich eine deutliche Verzerrung dieser Linien. In Ålesund finden sich starke zeitliche Variationen im Trend, die mit kleinräumigen Prozessen in Verbindung stehen müssen. Generell ist der Gradient der Landhebung senkrecht zum großräumigen Verlauf der Küste. Der hier ermittelte Gradient ist aber höher als in bisher publizierten Arbeiten, und die Lage der Nullinie ist weiter zur See hin verschoben.

Description: thesis

Description: DFG, SUB Göttingen

Description: Se caracterizó y evaluó el estado de conservación de los pastos marinos en áreas de interés conservacionista del Archipiélago Sabana-Camagüey en el periodo 2001-2003, considerando variables descriptivas de las angiospermas marinas, de la estructura del macrofitobentos y abióticas para conocer las causas de su afectación. Las áreas estudiadas fueron las bahías de Cárdenas, Santa Clara, Buena Vista, de Perros, Jigüey, La Gloria y Nuevitas, así como algunas lagunas arrecifales. Los pastos marinos mejor conservados se encontraron en las zonas con mayor intercambio con el océano, destacándose las lagunas arrecifales. El deterioro de los pastos marinos se debió principalmente al aumento de la turbidez por contaminación orgánica cerca de la isla principal en sectores costeros de las bahías de Cárdenas, Santa Clara y Buena Vista, y a este factor, junto con el incremento de la salinidad, en las bahías de Perros y Jigüey. Las condiciones más propicias para el desarrollo de los pastos parecen ser: la visibilidad submarina 〉 1 m, la salinidad 〈 43 ups, la variabilidad de salinidad 〈 10 ups, la DQO 〈 5,6 mgO2 L-1 y el nitrógeno total 〈 173 μM en el agua. La especie de angiosperma dominante fue Thalassia testudinum, seguida por Syringodium filiforme y Halodule wrightii, que dominaron donde disminuyó la luz y aumentaron los nutrientes. El inventario del macrofitobentos en el ASC acumuló 227 especies (100 Rhodophyta, 26 Ochrophyta, 96 Chlorophyta y cinco Magnoliophyta), con 66 nuevos registros para la zona y 16, para Cuba. Las macroalgas más frecuentes fueron de los órdenes Bryopsidales (Chlorophyta) y Ceramiales (Rhodophyta). La estructura del macrofitobentos estuvo modulada por los mismos factores que afectan el desarrollo de las angiospermas, con una riqueza específica menor donde está deteriorado el hábitat.

Description: PhD

Description: Groundwater is a vital resource for humans, non-human species, and ecosystems. It has allowed the development of human evolution and civilizations throughout history (e.g., Wittfogel 1956, Tempelhoff et al. 2009, Cuthbert and Ashley 2014, Roberts 2014). However, it faces multiple potential threats that make it vulnerable and fragile. Climate change and human activities are the primary causes that have led to water cycle disruptions, particularly a decline in groundwater quality and quantity (e.g., Gleeson et al. 2020, Chaminé et al. 2022, Richardson et al. 2023). Climate variability has induced droughts, floods, and other extreme weather conditions, significantly impacting groundwater in many regions. Meanwhile, human activities such as over-abstraction, ground contamination, deforestation, land-use change, and other anthropogenic pressures have further compromised groundwater status. Nonetheless, groundwater continues to fulfill water demands in many regions or during specific periods. Therefore, concerted efforts are imperative to ensure its sustainability. So, conservation practices and nature-based solutions must be adopted to efficiently manage groundwater and shield it from additional potential hazards or risks (e.g., contamination, pollution, or over-abstraction). Failure to act quickly can result in the loss of this critical resource, with severe consequences for the economy, society, and ecosystems. From this perspective, it is imperative to prioritize actions underscored by technical-scientific integrity, environmental responsibility, societal sensitivity, and ethical practices.

Description: Published

Description: 97

Description: OS: Terza missione

Description: OSA5: Energia e georisorse

Description: JCR Journal

Description: In the marine realm, microorganisms are responsible for the bulk of primary production, thereby sustaining marine life across all trophic levels. Longhurst provinces have distinct microbial fingerprints; however, little is known about how microbial diversity and primary productivity change at finer spatial scales. Here, we sampled the Atlantic Ocean from south to north (~50°S–50°N), every ~0.5° latitude. We conducted measurements of primary productivity, chlorophyll-a and relative abundance of 16S and 18S rRNA genes, alongside analyses of the physicochemical and hydrographic environment. We analysed the diversity of autotrophs, mixotrophs and heterotrophs, and noted distinct patterns among these guilds across provinces with high and low chlorophyll-a conditions. Eukaryotic autotrophs and prokaryotic heterotrophs showed a shared inter-province diversity pattern, distinct from the diversity pattern shared by mixotrophs, cyanobacteria and eukaryotic heterotrophs. Additionally, we calculated samplewise productivity-specific length scales, the potential horizontal displacement of microbial communities by surface currents to an intrinsic biological rate (here, specific primary productivity). This scale provides key context for our trophically disaggregated diversity analysis that we could relate to underlying oceanographic features. We integrate this element to provide more nuanced insights into the mosaic-like nature of microbial provincialism, linking diversity patterns to oceanographic transport through primary production.

Description: Contrasting models predict two different climate change scenarios for the Southern Ocean (SO), forecasting either less or stronger vertical mixing of the water column. To investigate the responses of SO phytoplankton to these future conditions, we sampled a natural diatom dominated (63%) community from today’s relatively moderately mixed Drake Passage waters with both low availabilities of iron (Fe) and light. The phytoplankton community was then incubated at these ambient open ocean conditions (low Fe and low light, moderate mixing treatment), representing a control treatment. In addition, the phytoplankton was grown under two future mixing scenarios based on current climate model predictions. Mixing was simulated by changes in light and Fe availabilities. The two future scenarios consisted of a low mixing scenario (low Fe and higher light) and a strong mixing scenario (high Fe and low light). In addition, communities of each mixing scenario were exposed to ambient and low pH, the latter simulating ocean acidification (OA). The effects of the scenarios on particulate organic carbon (POC) production, trace metal to carbon ratios, photophysiology and the relative numerical contribution of diatoms and nanoflagellates were assessed. During the first growth phase, at ambient pH both future mixing scenarios promoted the numerical abundance of diatoms (∼75%) relative to nanoflagellates. This positive effect, however, vanished in response to OA in the communities of both future mixing scenarios (∼65%), with different effects for their productivity. At the end of the experiment, diatoms remained numerically the most abundant phytoplankton group across all treatments (∼80%). In addition, POC production was increased in the two future mixing scenarios under OA. Overall, this study suggests a continued numerical dominance of diatoms as well as higher carbon fixation in response to both future mixing scenarios under OA, irrespective of different changes in light and Fe availability.

Description: Mesopelagic fish (meso-fish) are central species within the Southern Ocean (SO). However, their ecosystem role and adaptive capacity to climate change are rarely integrated into marine protected area (MPAs) assessments. This is a pity given their importance as crucial prey and predators in food webs, coupled with the impacts of climate change. Here, we estimate the habitat distribution of nine meso-fish using an ensemble model approach (MAXENT, random forest, and boosted regression tree). Four climate model simulations were used to project their distribution under two representative concentration pathways (RCP4.5 and RCP8.5) for short-term (2006–2055) and long-term (2050–2099) periods. In addition, we assess the ecological representativeness of established and proposed MPAs under climate change scenarios using meso-fish as indicator species. Our models show that all species shift poleward in the future. Lanternfishes (family Myctophidae) are predicted to migrate poleward more than other families (Paralepididae, Nototheniidae, Bathylagidae, and Gonostomatidae). In comparison, lanternfishes were projected to increase habitat area in the eastern SO but lose area in the western SO; the opposite was projected for species in other families. Important areas (IAs) of meso-fish are mainly distributed near the Antarctic Peninsula and East Antarctica. Proposed MPAs cover 23% of IAs at present and 38% of IAs in the future (RCP8.5, long-term future). Many IAs of meso-fish still need to be included in MPA proposals, such as the Prydz Bay and the seas around the Antarctic Peninsula. Our results provide a framework for designing new MPAs incorporating climate change adaptation strategies for MPA management.

Description: Sediment reworking by benthic infauna, namely bioturbation, is of pivotal importance in expansive soft-sediment environments such as the Wadden Sea. Bioturbating fauna facilitate ecosystem functions such as bentho-pelagic coupling and sediment nutrient remineralization capacities. Yet, these benthic fauna are expected to be profoundly affected by current observed rising sea temperatures. In order to predict future changes in ecosystem functioning in soft-sediment environments like the Wadden Sea, knowledge on the underlying processes such as sediment reworking, is crucial. Here, we tested how temperature affects bioturbation and its associated ecosystem processes, such as benthic nutrient fluxes and sediment oxygen consumption, using luminophore tracers and sediment incubation cores. We used a controlled mesocosm experiment set-up with key Wadden Sea benthos species: the burrowing polychaetes Arenicola marina and Hediste diversicolor, the bivalve Cerastoderma edule, and the tube-building polychaete Lanice conchilega. The highest bioturbation rates were observed from A. marina, reaching up to 375 cm2yr−1; followed by H. diversicolor, with 124 cm2yr−1 being the peak bioturbation rate for the ragworm. Additionally, the sediment reworking activity of A. marina facilitated nearly double the amount of silicate efflux compared to any other species. Arenicola marina and H. diversicolor accordingly facilitated stronger nutrient effluxes under a warmer temperature than L. conchilega and C. edule. The oxygen uptake of A. marina and H. diversicolor within the sediment incubation cores was correspondingly enhanced with a higher temperature. Thus, increases in sea temperatures may initially be beneficial to ecosystem functioning in the Wadden Sea as faunal bioturbation is definitely expedited, leading to a tighter coupling between the sediment and overlying water column. The enhanced bioturbation activity, oxygen consumption, and facilitated nutrient effluxes from these invertebrates themselves, will aid in the ongoing high levels of primary productivity and organic matter production.

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:sec〉〈jats:title〉Aim〈/jats:title〉〈jats:p〉Within the intensively‐studied, well‐documented latitudinal diversity gradient, the deep‐sea biodiversity of the present‐day Norwegian Sea stands out with its notably low diversity, constituting a steep latitudinal diversity gradient in the North Atlantic. The reason behind this has long been a topic of debate and speculation. Most prominently, it is explained by the deep‐sea glacial disturbance hypothesis, which states that harsh environmental glacial conditions negatively impacted Norwegian Sea diversities, which have not yet fully recovered. Our aim is to empirically test this hypothesis. Specific research questions are: (1) Has deep‐sea biodiversity been lower during glacials than during interglacials? 〈jats:italic〉(〈/jats:italic〉2) Was there any faunal shift at the Mid‐Brunhes Event (MBE) when the mode of glacial–interglacial climatic change was altered?〈/jats:p〉〈/jats:sec〉〈jats:sec〉〈jats:title〉Location〈/jats:title〉〈jats:p〉Norwegian Sea, deep sea (1819–2800 m), coring sites MD992277, PS1243, and M23352.〈/jats:p〉〈/jats:sec〉〈jats:sec〉〈jats:title〉Time period〈/jats:title〉〈jats:p〉620.7–1.4 ka (Middle Pleistocene–Late Holocene).〈/jats:p〉〈/jats:sec〉〈jats:sec〉〈jats:title〉Taxa studied〈/jats:title〉〈jats:p〉Ostracoda (Crustacea).〈/jats:p〉〈/jats:sec〉〈jats:sec〉〈jats:title〉Methods〈/jats:title〉〈jats:p〉We empirically test the deep‐sea glacial disturbance hypothesis by investigating whether diversity in glacial periods is consistently lower than diversity in interglacial periods. Additionally, we apply comparative analyses to determine a potential faunal shift at the MBE, a Pleistocene event describing a fundamental shift in global climate.〈/jats:p〉〈/jats:sec〉〈jats:sec〉〈jats:title〉Results〈/jats:title〉〈jats:p〉The deep Norwegian Sea diversity was not lower during glacial periods compared to interglacial periods. Holocene diversity was exceedingly lower than that of the last glacial period. Faunal composition changed substantially between pre‐ and post‐MBE.〈/jats:p〉〈/jats:sec〉〈jats:sec〉〈jats:title〉Main conclusions〈/jats:title〉〈jats:p〉These results reject the glacial disturbance hypothesis, since the low glacial diversity is the important precondition here. The present‐day‐style deep Norwegian Sea ecosystem was established by the MBE, more specifically by MBE‐induced changes in global climate, which has led to more dynamic post‐MBE conditions. In a broader context, this implies that the MBE has played an important role in the establishment of the modern polar deep‐sea ecosystem and biodiversity in general.〈/jats:p〉〈/jats:sec〉

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉Extensive investigation of continental rift systems has been fundamental for advancing the understanding of extensional tectonics and modes of formation of new ocean basins. However, current rift classification schemes do not account for conjugate end members formed by Large Igneous Province crust, referring to thick mafic crust, sometimes including continental fragments. Here, we investigate the rifting of William's Ridge (Kerguelen Plateau) and Broken Ridge, components of the Kerguelen Large Igneous Province now situated in the Southeast Indian Ocean, and incorporate these end members into the deformation migration concept for rifted margins. We use multichannel seismic reflection profiles and data from scientific drill cores acquired on both conjugate margins to propose, for the first time, a combined tectono‐stratigraphic framework. We interpret seismic patterns, tectonic features, and magnetic anomaly picks to determine an across‐strike structural domain classification. This interpretation considers the rift system overall to be “magma‐poor” despite being located proximal to the Kerguelen plume but suggests that syn‐rift interaction between the Kerguelen mantle plume and the lithospheric structure of William's Ridge and Broken Ridge has controlled the along‐strike segmentation of both conjugates. We integrate seismic reflection and bathymetric data to test the hypothesis of predominantly transform motion, between the Australian and Antarctic plates, in Late Cretaceous and Paleogene time.〈/jats:p〉

Description: Ongoing climate warming in the western Canadian Arctic is leading to thawing of permafrost soils and subsequent mobilization of its organic matter pool. Part of this mobilized terrestrial organic matter enters the aquatic system as dissolved organic matter (DOM) and is laterally transported from land to sea. Mobilized organic matter is an important source of nutrients for ecosystems, as it is available for microbial breakdown, and thus a source of greenhouse gases. We are beginning to understand spatial controls on the release of DOM as well as the quantities and fate of this material in large Arctic rivers. Yet, these processes remain systematically understudied in small, high-Arctic watersheds, despite the fact that these watersheds experience the strongest warming rates in comparison. Here, we sampled soil (active layer and permafrost) and water (porewater and stream water) from a small ice wedge polygon (IWP) catchment along the Yukon coast, Canada, during the summer of 2018. We assessed the organic carbon (OC) quantity (using dissolved (DOC) and particulate OC (POC) concentrations and soil OC content), quality (δ13C DOC, optical properties and source apportionment) and bioavailability (incubations; optical indices such as slope ratio, Sr; and humification index, HIX) along with stream water properties (temperature, T; pH; electrical conductivity, EC; and water isotopes). We classify and compare different landscape units and their soil horizons that differ in microtopography and hydrological connectivity, giving rise to differences in drainage capacity. Our results show that porewater DOC concentrations and yield reflect drainage patterns and waterlogged conditions in the watershed. DOC yield (in mg DOC g−1 soil OC) generally increases with depth but shows a large variability near the transition zone (around the permafrost table). Active-layer porewater DOC generally is more labile than permafrost DOC, due to various reasons (heterogeneity, presence of a paleo-active-layer and sampling strategies). Despite these differences, the very long transport times of porewater DOC indicate that substantial processing occurs in soils prior to release into streams. Within the stream, DOC strongly dominates over POC, illustrated by ratios around 50, yet storm events decrease that ratio to around 5. Source apportionment of stream DOC suggests a contribution of around 50 % from permafrost/deep-active-layer OC, which contrasts with patterns observed in large Arctic rivers (12 ± 8 %; Wild et al., 2019). Our 10 d monitoring period demonstrated temporal DOC patterns on multiple scales (i.e., diurnal patterns, storm events and longer-term trends), underlining the need for high-resolution long-term monitoring. First estimates of Black Creek annual DOC (8.2 ± 6.4 t DOC yr−1) and POC (0.21 ± 0.20 t yr−1) export allowed us to make a rough upscaling towards the entire Yukon Coastal Plain (34.51 ± 2.7 kt DOC yr−1 and 8.93 ± 8.5 kt POC yr−1). Rising Arctic temperatures, increases in runoff, soil organic matter (OM) leaching, permafrost thawing and primary production are likely to increase the net lateral OC flux. Consequently, altered lateral fluxes may have strong impacts on Arctic aquatic ecosystems and Arctic carbon cycling.

Description: 〈jats:p〉This study presents the results of research on the climatic signal of radial growth of Siberian larch (〈jats:italic〉Larix cajanderi Mayr〈/jats:italic〉.) in the Omoloy River Basin, (north-eastYakutia). Tree-ring width chronologies were obtained from three sites  located in the valley complexes of subarctic tundra and forest-tundra ecotone, with chronologies spanning up to 498 years. Comparative analysis of radial growth dynamics and its statistical parameters indicated similar variability patterns within the study region. Dendroclimatic analysis revealed that the primary limiting factor determining the magnitude of radial growth in Siberianlarch is the air temperature during the first half of the growing season. Increasing temperatures have led to an increased role of precipitation and changes in the strength of growth-temperature correlations, especially in northern sites.This study highlights the potential for dendroclimatic and dendroecological researchin northern Yakutia.〈/jats:p〉

Description: Palaeoenvironmental records from permafrost sequences complemented by infrared stimulated luminescence (IRSL) and 230Th/U dates from Bol'shoy Lyakhovsky Island (73°20′N, 141°30′E) document the environmental history in the region for at least the past 200 ka. Pollen spectra and insect fauna indicate that relatively wet grasssedge tundra habitats dominated during an interstadial c. 200-170 ka BP. Summers were rather warm and wet, while stable isotopes reflect severe winter conditions. The pollen spectra reflect sparser grass-sedge vegetation during a Taz (Late Saalian) stage, c. 170-130 ka BP, with environmental conditions much more severe compared with the previous interstadial. Open Poaceae and Artemisia plant associations dominated vegetation at the beginning of the Kazantsevo (Eemian) c. 130 ka BP. Some shrubs (Alnus fruticosa, Salix, Betula nana) grew in more protected and wetter places as well. The climate was relatively warm during this time, resulting in the melting of Saalian ice wedges. Later, during the interglacial optimum, shrub tundra with Alnus fruticosa and Betula nana s.l. dominated vegetation. Climate was relatively wet and warm. Quantitative pollen-based climate reconstruction suggests that mean July temperatures were 4-5°C higher than the present during the optimum of the Eemian, while late Eemian records indicate significant climate deterioration. © 2004 Taylor & Francis.

Description: Paleoceanographic reconstructions show that the strength of North Atlantic currents decreased during the Little Ice Age. In contrast, the role of ocean circulation in climate regulation during earlier historical epochs of the Common Era (C.E.) remains unclear. Here, we reconstruct sea surface temperature (SST) and salinity in the Caribbean Basin for the past 1700 years using the isotopic and elemental composition of planktic foraminifera tests. Centennial-scale SST and salinity variations in the Caribbean co-occur with (hydro)climate changes in the Northern Hemisphere and are linked to a North Atlantic SST forcing. Cold phases around 600, 800, and 1400 to 1600 C.E. are characterized by Caribbean salinification and Gulf of Mexico freshening that implies reductions in the strength of North Atlantic surface circulation. We suggest that the associated changes in the meridional salt advection contributed to the historical climate variability of the C.E.

Description: 〈jats:p〉Reconstructing interglacial marine environments helps us understand the climate change mechanisms of the past. To contribute to this body of knowledge, we studied a high-resolution 455 cm-thick sediment sequence of the Boreal (Eemian) marine beds directly overlying Moscovian (Saalian) moraine in the Bychye-2 section on the Pyoza River. We analyzed lithological and microfossil (foraminifers, ostracods, pollen, aquatic palynomorphs) variations at the studied site. Stratigraphical zonation is based on the local and well-established regional pollen zones, correlated with the western European pollen zones. The studied marine beds accumulated from the end of the Moscovian glacial (>131 ka) until ca. 119.5 ka. We distinguished three successive phases: a seasonally sea-ice-covered, relatively deep, freshened basin in the initial rapid flooding stage (>131–130.5 ka); a deep basin in the maximum flooding phase with less extensive sea ice cover (130.5–130.25 ka); and a shallow basin with reduced sea ice cover (130.25–119.5 ka). According to a pollen zone comparison with other sites, the regional glacioisostatic rebound started ca. 130 ka. The diverse warm-water assemblages of benthic foraminifers and ostracods containing typical Baltic Sea species occurred during the regression, mainly 128–124 ka, thus giving evidence for a relatively long-lasting connection between the White and Baltic Seas.〈/jats:p〉

Description: Around 9.7 million years ago there was an abrupt collapse in diversity; the so-called 'Vallesian Crisis'. This was seen as the transition point to a climate with more seasonality and open landscapes.Using a fossil dataset from Miocene Eurasia, the influence of dataset quality on the severity of this crisis, which animals were most affected and their distribution patterns was studied.The crisis’ victims have three things in common: they are mainly forest dwellers, they date back to the Middle Miocene (16-11.1 Ma), and they are rare during the early Vallesian. The high Vallesian biodiversity was caused by the arrival of new immigrants in addition to older transient groups, possibly due to the unique coastal conditions.Major differences existed between the coastal region and the interior of the Iberian Peninsula. Some species appeared in the Vallès-Penedès, but never reached the inland. The 'Vallesian Crisis', while seen understandably as a time of abrupt and severe extinction, was thus largely a local turnover event.

Description: New records of notoaturine water mites (Aturidae: Notoaturinae) from New Zealand are presented. Five new species are described: Evidaturus longiscutatus n. sp., Kritaturus (Kritaturus) longipalpis n. sp., Planaturus simpsonensis n. sp., Tryssaturus longwood n. sp. and Zelandalbia thibaulti n. sp. The males are described for the first time for Planaturus pileatus Smit, 2017 and Zelandalbia cf. hopkinsi Imamura, 1978 and the females are described for the first time for Kritaturus (Kritaturus) sornus Cook, 1983, Paratryssaturus zodelus Cook, 1983 and Taintaturus accidens Cook, 1983.

Description: A number of studies expect an increase of carbon export by rivers to the Arctic Ocean due to rapidly changing climate in the Arctic One possible reason for the increase of carbon export is thawing permafrost, which can lead to a mobilization of previously frozen dissolved organic matter (DOM). Scarce measurements of DOC and the coloured fraction of DOM (CDOM) (〈 8 samples/year) were previously used to estimate fluxes to the Arctic Ocean for the whole year. Here, we present a new high frequency sampling program and its viability to monitor export fluxes of DOM and its biogeochemistry in the Lena River. This dataset includes measurements of several water parameters, such as temperature, electric conductivity, dissolved organic carbon (DOC), spectral CDOM absorption (aCDOM), stable water isotopes and major ions. The high sampling frequency throughout the whole year facilitats the identification of the main drivers behind the seasonality of DOM concentration and biogeochemistry of the Lena River. The high number of samples throughout the whole year allows flux calculations that are independently from load models that likely lead to a large variation of earlier studies. Optical indices reveal changing composition and sources of DOM throughout the year. This dataset represents the first year (April 2018 to April 2019) of a planned long-term monitoring program at the Research Station Samoylov Island and provides a baseline data set against which future change of this large integrative system may be measured. A continuous sampling of Arctic River water will facilitate to identify intra and inter-annual trends with ongoing climate change.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: Radio-echo sounding (RES) data from Jutulstraumen Glacier in western Dronning Maud Land (East Antarctica) recorded with the Alfred Wegener Institutes multi-channel ultra-wideband (AWI UWB) radar system in the Austral summer season 2018/19. The survey region is centered on the initiation zone of accelerating ice flow (~ 5 to 50 meters per year) at the onset of the Jutulstraumen Ice Stream, located within the Jutulstraumen drainage basin in western Dronning Maud Land, East Antarctica. This region marks the a transition from the thick ice sheet of the central plateau to the dynamic convergent ice flow regime leading through the Jutulstraumen Graben, which ultimately feeds into the Fimbul Ice Shelf. The RES profiles are organized into two distinct sets, each aligned approximately perpendicular to ice flow and spaced at intervals of 7.5 km. The data was mainly recorded in a frequency range between 180-210 MHz and is SAR processed. For further details see Franke et al., 2021 (https://doi.org/10.1002/esp.5203).

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.