Fronts are ubiquitous in the climate system. In the Southern Ocean, fronts delineate water masses, which correspond to upwelling and downwelling branches of the overturning circulation. A robust understanding of Southern Ocean fronts is key to projecting future changes in overturning and the associated air-sea partitioning of heat and carbon. Classically, oceanographers define Southern Ocean fronts as a small number of continuous linear features that encircle Antarctica. However, modern observational and theoretical developments are challenging this traditional framework to accommodate more localized views of fronts [Chapman et al. 2020]. In this work, we present two related methods for calculating fronts from oceanographic data. The first method uses unsupervised classification (specifically, Gaussian Mixture Modeling or GMM) and an interclass metric to define fronts. This approach produces a discontinuous, probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The second method uses Sobel edge detection to highlight rapid changes [Hjelmervik & Hjelmervik, 2019]. This approach produces a more local view of fronts, with the advantage that it can highlight the movement of individual eddy-like features (such as the Agulhas rings). The fronts detected using the Sobel method are moderately correlated with the magnitude of the velocity field, which is consistent with the theoretically expected spatial coincidence of fronts and jets. We will present our python GitHub repository, which will allow researchers to easily apply these methods to their own datasets. Figure caption Two methods for interpretable front detection. Solid lines represent classical fronts. (a) The “inter-class” metric, which indicates the probability that a grid cell is a boundary between two classes. The classes are defined by GMM of principal component values (PCs) derived from both temperature and salinity. The different colors indicate different class boundaries. (b) Sobel edge detection: approximately the magnitude of the spatial gradient of the PCs divided by each field’s standard deviation, which highlights locations of rapid change.

An outreach presentation on the uses for measuring thorium in the marine environment, modeled after a children's book and presented at AGU Fall Meeting 2022 Up-Goer Five Challenge: Making Big Ideas Simpler by Talking About Them in Words We Use a Lot.Pictures by Neil Redmond and Midjourney AI

Coastlines in most ocean general circulation models are piecewise constant. Accurate representation of boundary currents along staircase-like coastlines is a long-standing issue in ocean modelling. Pioneering work by Adcroft and Marshall (1998) revealed that artificial indentation of model coastlines, obtained by rotating the numerical mesh within an idealized square basin, generates a \textit{spurious form drag} that slows down the circulation. Here, we revisit this problem and show how this spurious drag may be eliminated. First, we find that \textit{physical} convergence (i.e. the main characteristics of the flow are insensitive to the increase of the mesh resolution) allows simulations to become independent of the mesh orientation. An advection scheme with a wider stencil also reduces sensitivity to mesh orientation from coarser resolution. Second, we show that indented coastlines behave as straight and slippery shores when a true mirror boundary condition on the flow is imposed. This finding applies to both symmetric and rotational-divergence formulations of the stress tensor, and to both flux and vector-invariant forms of the equations. Finally, we demonstrate that the detachment of a vortex flowing past an outgoing corner of the coastline is faithfully simulated with exclusive implementation of impermeability conditions. These results provide guidance for a better numerical treatment of coastlines (and isobaths) in ocean general circulation models.

Because of its responsiveness to changes in the marine environment, it has been suggested by Rose in 2005 that the capelin, a small pelagic fish that is key to the ecology and fisheries of the North Atlantic, could be seen as a "canary in the coalmine" to detect signals of changes in the Arctic and sub-Arctic Ocean. We describe the historical data that make possible a quantitative assessment of the geographical shift capelin migration-paths and spawning grounds undergo, with increasing temperature, and the time it takes to make these shifts long-lasting. Then we introduce recent data that make these quantitative measurements more accurate and predictive. Direct measurements made in the fall expeditions of Iceland's Marine and Freshwater Research Institute along the East Coast of Greenland, and the Copernicus database of the European Union, are used to examine the evolution of the returning Atlantic water (from Svalbard) that is forming a warmer and saltier boundary current under the colder and fresher East Greenland polar current. The returning Atlantic water has a temperature range (1 to 4 degrees Centigrade) suitable for feeding migrations of the capelin. This current is reaching further north along the coast of North East Greenland and we use simulated data from Copernicus to monitor this evolution. We calibrate the Copernicus data with the direct measurements made by the Marine and Freshwater Research Institute, in Iceland. A trend emerges, both in the direct measurements and in Copernicus data, showing that the returning Atlantic water boundary current may reach Greenland's major Northeastern glacier streams, draining the bulk of the Greenland Glacier in the relatively near future We use the capelin data to predict when this may happen.

Waves, rivers, and tides play a leading role in shaping delta morphology. Recent studies have enabled predictions of their relative influence for deltas globally, but methods and associated uncertainties have remained poorly described. Here we aim to address that gap and assess the quality of delta morphology predictions compared to observations for 31 deltas globally. We expand on seminal works that quantified the Galloway ternary diagram from the balance between river, wave, and tidal sediment fluxes. Our data includes uncertainties for delta shoreline protrusion angles set by wave influence (14.1°±12° predicted vs. 20.8°±16.1° observed), channel widening, set by tidal influence (53.5±170.8 predicted vs. 6.5±11.5 observed), and number of distributary channels, set by river influence (55.9±127.5 predicted vs. 21.4±43.0 observed). Within the ternary diagram for delta morphology, we find an average error of 8% (±11%, 1 standard deviation), linked to uncertainties in wave and tide sediment fluxes. Relative uncertainties are greatest for mixed-process deltas (e.g., Sinu, error of 49%) and tend to decrease for end-member morphologies where either one of wave, tide, or river sediment fluxes dominates (e.g., Fly, error of 0.2%). Large sources of prediction uncertainties are (1) delta morphology data, e.g., delta slopes that modulate tidal fluxes, (2) data on river sediment flux distribution between individual delta river mouths, and (3) theoretical basis behind fluvial and tidal dominance. Future work could help address these three sources and improve predictions of delta morphology.

The current narrative of artificial upwelling (AU) is to use ocean pipes to pump nutrient rich deep water to the ocean surface, thereby stimulating the biological carbon pump. This simplistic concept of AU does not take the response of the solubility pump or the CO2 emission scenario into account. Using global ocean-atmosphere model experiments and several idealized model tracers we show that the effectiveness of almost globally applied AU from the year 2020 to 2100 to draw down CO2 from the atmosphere is strongly dependent on the CO2 emission scenario and ranges from 1.01 Pg C / year under RCP 8.5 to 0.32 Pg C / year under RCP 2.6. The solubility pump becomes equally effective compared to the biological carbon pump under the highest emission scenario (RCP 8.5), but responds with CO2 outgassing under low CO2emission scenarios.

The variability of the Southern Hemisphere (SH) extratropical large-scale circulation is dominated by the Southern Annular Mode (SAM), whose timescale is extensively used as a key metric in evaluating state-of-the-art climate models. Past observational and theoretical studies suggest that the SAM lacks any internally generated (intrinsic) periodicity. Here, we show, using observations and a climate model hierarchy, that the SAM has an intrinsic 150-day periodicity. This periodicity is robustly detectable in the power spectra and principal oscillation patterns (aka dynamical mode decomposition) of the zonal-mean circulation, and in hemispheric-scale precipitation and ocean surface wind stress. The 150-day period is consistent with the predictions of a new reduced-order model for the SAM, which suggests that this periodicity is tied with a complex interaction of turbulent eddies and zonal wind anomalies, as the latter propagate from low to high latitudes. These findings present a rare example of periodic oscillations arising from the internal dynamics of the extratropical turbulent circulations. Based on these findings, we further propose a new metric for evaluating climate models, and show that some of the previously reported shortcomings and improvements in simulating SAM’s variability connect to the models’ ability in reproducing this periodicity. We argue that this periodicity should be considered in evaluating climate models and understanding the past, current, and projected Southern Hemisphere climate variability.

Underwater fiber optic cables commonly traverse a variety of seafloor conditions, which leads to an uneven mechanical coupling between the cable and the ocean bottom. On rough seafloor bathymetry, some cable portions might be suspended and thus susceptible to Vortex-Induced Vibrations (VIV) driven by deep ocean currents. Here, we examine the potential of Distributed Acoustic Sensing (DAS) to monitor deep-sea currents along suspended sections of underwater telecom fiber optic cables undergoing VIV. Oscillations of a seafloor fiber optic cable located in southern France are recorded by DAS along cable sections presumably hanging. Their characteristic frequencies are lower than 1 Hz, at different ocean depths, and have an amplitude-dependency consistent with the driving mechanism being VIV. Based on a theoretical proportionality between current speed and VIV frequencies, we derive ocean current speed time series at 2390 m depth from the vortex shedding frequencies recorded by DAS. The DAS-derived current speed time series is in agreement with recordings by a current meter located 3.75 km away from the hanging cable section (similar dominant period, high correlation after time shift). The DAS-derived current speed time series displays features, such as characteristic periods and spectral decay, associated with the generation of internal gravity waves and weak oceanic turbulence in the Mediterranean Sea. The results demonstrate the potential of DAS along hanging segments of fiber optic cables to monitor a wide range of oceanography processes, at depths barely studied with current instrumentation.

Antarctic landfast sea ice (fast ice) is stationary sea ice that is attached to the coast, grounded icebergs, ice shelves, or other protrusions on the continental shelf. Fast ice forms in narrow (generally up to 200 km wide) bands, and ranges in thickness from centimeters to tens of meters. In most regions, it forms in autumn, persists through the winter and melts in spring/summer, but can remain throughout the summer in particular locations. Despite its relatively limited horizontal extent (comprising between about 4 and 13 \% of overall sea ice), its presence, variability and seasonality are drivers of a wide range of physical, biological and biogeochemical processes, with both local and far-ranging ramifications for various Earth systems. Antarctic fast ice has, until quite recently, been overlooked in studies, likely due to insufficient knowledge of its distribution, leading to its reputation as a “missing piece of the Antarctic puzzle”. This review presents a synthesis of current knowledge of the physical, biogeochemical and biological aspects of fast ice, based on the sub-domains of: fast ice growth, properties and seasonality; remote-sensing and distribution; interactions with the atmosphere and the ocean; biogeochemical interactions; its role in primary production; and fast ice as a habitat for grazers. Finally, we consider the potential state of Antarctic fast ice at the end of the 21st Century, underpinned by Coupled Model Intercomparison Project model projections. This review also gives recommendations for targeted future work to increase our understanding of this critically-important element of the global cryosphere.

A document by Balaji Senapati. Click on the document to view its contents.

Feasibility of observing near-inertial waves with a single cast of a lowered Acoustic Doppler Current Profiler is quantitatively assessed in simulated Garrett-Munk internal waves. Because the inertial period is shorter in higher latitudes and the interval between the upand downcasts is longer in shallower depths, the performance of the estimator is better in higher latitudes at shallower depths. Even in the best conditions, however, the estimates are contaminated by relative uncertainties greater than 100%. It is not feasible to estimate nearinertial waves accurately using a LADCP cast. Nevertheless, repeated casts at one station are capable of resolving typical near-inertial waves.

We examine how zooplankton influence phytoplankton bloom phenology from the top-down, then use inverse modelling to infer the distribution and drivers of mean community zooplankton grazing dynamics based on the skill with which different simulated grazing formulations are able to recreate the observed seasonal cycle in phytoplankton biomass. We find that oligotrophic (eutrophic) biomes require more (less) efficient grazing dynamics, characteristic of micro- (meso-) zooplankton, leading to a strong relationship between the observed mean annual phytoplankton concentration in a region and the optimal grazing parameterization required to simulate it’s observed phenology. Across the globe, we found that a type III functional response consistently exhibits more skill than a type II response, suggesting the mean dynamics of a coarse model grid-cell should offer stability and prey refuge at low biomass concentrations. These new observationally-based global distributions will be invaluable to help constrain, validate and develop next generation of biogeochemical models.

The Southern Ocean Seasonal Sea Ice Zone (SSIZ) is characterized by the development of spring phytoplankton blooms following retreating sea ice. Until recently, assessing SSIZ bloom carbon export has been limited by a lack of under ice observations. Here, we relate the timing of phytoplankton growth to the drawdown of surface nutrients and sea ice cover and estimate spring bloom net community production (bNCP) using biogeochemical profiling float observations. The onset of biological production follows initial sea ice breakup with 64% of bNCP under partial sea ice cover. Estimates of bNCP range from <1 to >4 mol C m-2 bloom-1, with earlier sea ice breakup associated with higher bNCP, and the highest bNCP where micronutrient supply is likely enhanced by topographic-driven mixing. These results indicate that satellite-derived export estimates will underestimate bNCP in the SSIZ and have implications for future carbon export in a changing Southern Ocean sea ice regime.

Natural hazards such as floods, hurricanes, heatwaves, and wildfires cause significant economic losses (e.g., agricultural and property damage) as well as a high number of fatalities. Natural hazards are often driven by univariate or multivariate hydrometeorological drivers. Therefore, it is crucial to understand how and which hydrometeorological variables (i.e., drivers) combine to contribute to the impacts of these hazards. Additionally, when multiple drivers are associated with a hazard, traditional univariate risk assessment approaches are insufficient to cover the full spectrum of impact-relevant conditions originating from different combinations of multiple drivers. Based on historical socioeconomic loss data, we develop an impact-based approach to assess the influence of different hydrometeorological drivers on the impacts caused by different hazard event types. We use the Spatial Hazard Events and Losses Database for the United States (SHELDUS™) to identify the historical hazard events that caused socioeconomic impacts (property and crop damage, injuries, and fatalities) in our case study area, Miami-Dade County, in south Florida. For 9 different hazard types, we obtained data for 13 hydrometeorological drivers from historical in-situ observations and reanalysis products corresponding to the timing and locations of the hazard events found in the SHELDUS database. The relative importance of each hazard driver in generating impacts and the frequency of multiple drivers was then assessed. We found that many high-impact events were caused by multiple hydrometeorological drivers (i.e., compound events). For example, 61% of the recorded flooding events were compound events rather than univariate hazards and these contributed 99% of total property damage and 98.2% of total crop damage in Miami-Dade County. For several hazards, such as hurricanes/tropical storms and wildfires, all the events that caused damage are classified as compound events in our framework. Our findings emphasize the benefit of including socioeconomic impact information when analyzing hazard events, as well as the importance of analyzing all relevant hydrometeorological drivers to identify compound events.

The northern Antarctic Peninsula (NAP) is a key region of the Southern Ocean due to its complex ocean dynamics, distinct water mass sources, and the climate-driven changes taking place in the region. Despite the importance of macronutrients in fuelling primary production and driving the strong carbon uptake and storage, little is known about their spatiotemporal variability along the NAP. Hence, we explored a 24-year time series in this region, primarily sampled by the Brazilian High Latitude Group, to understand the processes involved in the spatial and interannual variability of macronutrients. We found high macronutrients concentrations, even in surface waters and under strong phytoplankton blooms. Minimum concentrations of dissolved inorganic nitrogen (16 μmol/ kg), phosphate (0.7 μmol/kg), and silicic acid (40 μmol/kg) along the NAP are higher than those recorded in surrounding regions. The main source of macronutrients is the intrusions of modified Circumpolar Deep Water (mCDW), and this is enhanced by local sources, such as organic matter remineralisation, water mass mixing, and mesoscale structures. However, we identified a depletion in silicic acid due to influence of Dense Shelf Water (DSW) from the Weddell Sea. Macronutrient concentrations shows substantial interannual variability driven by the balance between the intrusions of mCDW and advection of DSW, which is largely modulated by the Southern Annular Mode and to some extent by El Niño-Southern Oscillation. These findings are critical to improving our understanding of the natural variability of this Southern Ocean ecosystem and how it is responding to climate changes. Associate Editor

A document by Yan Wang. Click on the document to view its contents.

Oceanographic structure is often represented as a collection of vertical profiles, i.e. temperature, salinity, and/or biogeochemical values at various depths. These profiles contain information about water mass structures and the boundaries between them, which are consequences of the integrated effects of water mass formation, advection, and destruction. In recent years, researchers have applied various unsupervised profile classification methods in an attempt to identify a set of “profile types” and the spatially coherent regimes associated with them. These efforts have identified a number of regimes that are consistent with existing oceanographic knowledge, and they have also identified previously under-appreciated structural differences. However, as this application area matures, questions remain about the strengths and limitations of these methods as applied to oceanography. A key question is “under what circumstances does unsupervised profile classification produce interpretable and scientifically useful knowledge?” Here, I explore the mechanisms and parameters of various unsupervised learning approaches, in particular Gaussian Mixture Modeling, in an attempt to clarify the conditions under which unsupervised learning produces robust, interpretable, and trustworthy understanding. As with pattern classification approaches in general, there is a tradeoff between interpretability and accuracy (the ability of the method to represent the full underlying structure of the system). As a case study, I explore an unsupervised profile classification application in the Weddell Gyre. I show that, using a combination of statistical guidance, expert judgment, and traditional oceanographic analysis, we can, in some cases, increase the interpretability of a profile classification model with acceptable losses in accuracy. The goal is to elucidate the conditions under which unsupervised learning can be fully integrated into the oceanographic knowledge generation process, both by confronting existing understanding and by highlighting new avenues for exploration.

Intense short-term wind events can flush multiple-inlet systems and even renew the water entirely. Nonetheless, little is known about the effect of wind variations at seasonal and interannual scales on the flushing of such systems. Here, we computed two Lagrangian transport time scales (LTTS), the residence and exposure times, for a multiple-inlet system (the Dutch Wadden Sea) over 36 years using a realistic numerical model simulation. Our results reveal pronounced seasonal and interannual variability in both system-wide LTTS. The seasonality of the LTTS is strongly anti-correlated to the wind energy from the prevailing directions, which are from the southwesterly quadrant and coincidentally aligned with the geographical orientation of the system. This wind energy, which is stronger in autumn-winter than in spring-summer, triggers strong flushing (and hence low values of the LTTS) during autumn-winter. The North Atlantic Oscillation (NAO) and the Scandinavia Pattern (SCAN) are shown to be the main drivers of interannual variability in the local wind and, ultimately, in both LTTS. However, this coupling is much more efficient during autumn-winter when these patterns show larger values and variations. During these seasons, a positive NAO and a negative SCAN induce stronger winds in the prevailing directions, enhancing the flushing efficiency of the system. The opposite happens during positive SCAN and negative NAO, when weaker flushing during autumn-winter is observed. Thus, large-scale atmospheric patterns strongly affect the interannual variability in flushing and are potential drivers of the long-term ecology and functioning of multiple-inlet systems.

Continental margins play an essential role in global ocean biogeochemistry and the carbon cycle; however, global assessments of this role remain highly uncertain. This uncertainty arises from large variability over a broad range of temporal and spatial scales of the processes that characterize these environments. High-resolution simulations with ocean biogeochemical models have emerged as essential tools to advance biogeochemical assessments at regional scales. Here, we examine the processes and balances for carbon, oxygen, and nitrogen cycles along the U.S. West Coast in an 11-year hindcast simulation with a submesoscale-permitting oceanic circulation-biogeochemical model. We highlight the importance of biogeochemical cycles on the continental shelf, and their connection to the broader regional context encompassing the California Current System. On the shelf, coastal and wind stress curl upwelling drive a vigorous overturning circulation that supports biogeochemical rates and fluxes that are approximately twice as large as offshore. Exchanges with the proximate sediments, submesoscale shelf currents, bottom boundary layer transport, and intensified cross-shelf export of shelf-produced materials impact coastal and open-ocean balances. While regional variability prevents extrapolation of our results to global margins, our approach provides a powerful tool to identify the dominant dynamics in different shelf setting and quantify their large-scale consequences.

During hurricane season, the U.S. Geological Survey (USGS) forecasts the probability of coastal change prior to named storm landfall. Forecasts both quantify potential storm effects on the sandy coastlines and test our understanding of the drivers of coastal change. The forecasts can also be used to aid emergency response and management decisions in real-time. This study analyzed the skill of three USGS forecasts of coastal change, defined as the probability of collision, overwash, and inundation (PCOI) along the approximately 250 km of Louisiana coast from Hurricanes Laura, Delta, and Zeta in 2020. To test forecast skill, forecasts were compared with coastal changes identified in post-storm emergency response aerial imagery. Forecasts accurately identified areas where overwash and inundation were likely (true positive forecast ratios >0.75). Forecasts also produced an overly conservative estimation of overwash and inundation (false positive forecast ratios 0.56). High false positive forecast ratios for overwash and inundation may be the result of an overestimate in forecast extreme water levels.

Two coupled climate models, differing primarily in horizontal resolution and treatment of mesoscale eddies, were used to assess the impact of perturbations in wind stress and Antarctic ice sheet (AIS) melting on the Southern Ocean meridional overturning circulation (SO MOC), which plays an important role in global climate regulation. The largest impact is found in the SO MOC lower limb, associated with the formation of Antarctic Bottom Water (AABW), which in both models is enhanced by wind and weakened by AIS meltwater perturbations. Even though both models under the AIS melting perturbation show similar AABW transport reductions of 4-5 Sv (50-60%), the volume deflation of AABW south of 30˚S is four times greater in the higher resolution simulation (-20 vs -5 Sv). Water mass transformation (WMT) analysis reveals that surface-forced dense water formation on the Antarctic shelf is absent in the higher resolution and reduced by half in the lower resolution model in response to the increased AIS melting. However, the decline of the AABW volume (and its inter-model difference) far exceeds the surface-forced WMT changes alone, which indicates that the divergent model responses arise from interactions between changes in surface forcing and interior mixing processes. This model divergence demonstrates an important source of uncertainty in climate modeling, and indicates that accurate shelf processes together with scenarios accounting for AIS melting are necessary for robust projections of the deep ocean’s response to anthropogenic forcing and role as the largest sink in Earth’s energy budget.

Persistent warming and water cycle change due to anthropogenic climate change modifies the temperature and salinity distribution of the ocean over time. This ‘forced’ signal of temperature and salinity change is often masked by the background internal variability of the climate system. Analysing temperature and salinity change in watermass-based coordinate systems has been proposed as an alternative to traditional Eulerian (e.g., fixed-depth, zonally-averaged) co-ordinate systems. The impact of internal variability is thought to be reduced in watermass co-ordinates, enabling a cleaner separation of the forced signal from background variability - or a higher ‘signal-to-noise’ ratio. Building on previous analyses comparing Eulerian and water-mass-based one-dimensional coordinates, here we recast two-dimensional co-ordinate systems - temperature-salinity (𝑇 − 𝑆), latitude-longitude and latitude-depth - onto a directly comparable equal-volume framework. We compare the internal variability, or ‘noise’ in temperature and salinity between these remapped two-dimensional co-ordinate systems in a 500 year pre-industrial control run from a CMIP6 climate model. We find that the median internal variability is lowest (and roughly equivalent) in 𝑇 − 𝑆 and latitude-depth space, compared with latitude-longitude co-ordinates. A large proportion of variability in 𝑇 − 𝑆 and latitude-depth space can be attributed to processes which operate over a timescale greater than 10 years. Overall, the signal-to-noise ratio in 𝑇 − 𝑆 co-ordinates is roughly comparable to latitude-depth co-ordinates, but is greater in regions of high historical temperature change. Conversely, latitude-depth co-ordinates have greater signal-to-noise ratio in regions of historical salinity change. Thus, we conclude that the climatic temperature change signal can be more robustly identified in watermass-co-ordinates.

Mesoscale eddies are abundant in the global oceans and known to affect marine biogeochemistry. Understanding their cumulative impact on the air-sea carbon dioxide (CO2) flux is likely important for quantifying the ocean carbon sink. Here, observations and Lagrangian tracking are used to estimate the air-sea CO2 flux of 67 long lived (i.e. > 1 year) mesoscale eddies in the South Atlantic Ocean over a 16 year period. We find that anticyclonic eddies originating from the Agulhas retroflection and cyclonic eddies originating from the Benguela upwelling act as net CO2 sinks over their lifetimes. In combination, the eddies significantly enhanced the CO2 sink into the South Atlantic Ocean by 0.08 ± 0.01%. Although this modification appears small, long lived eddies account for just ~0.4% of global ocean eddies and eddy activity is increasing; therefore, explicitly resolving eddy processes within all models used to assess the ocean carbon sink would appear critical.

Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Their seasonal development features fast and local changes in fractions of surface types demonstrating the necessity of improving melt pond fraction (MPF) products. We present a renewed method to extract MPF from Sentinel-2 satellite imagery, which is evaluated by MPF products from higher resolution satellite and helicopter-borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs amount to 17 % before and 23 % after the major drainage. Arctic-wide analysis of MPF for years 2017-2021 shows a consistent seasonal cycle in all regions and years.