Young Sea Ice Research Articles

Investigation of the sensitivity response of Touzi target scattering decomposition to modeled early ice growth

ABSTRACT Touzi’s scattering vector model allows for a unified decomposition of both coherent and incoherent target scattering. Based on this model, a unique and roll-invariant model can be developed for target decomposition. Our study aims at the investigation of the Touzi decomposition for lake and sea ice monitoring. Thus, we investigate the sensitivity of the target parameters obtained from the Touzi incoherent decomposition to modeled ice growth. Our study focuses on thermodynamically-grown fast lake and sea ice during the early ice growth. A time-series quad pol synthetic aperture radar (SAR) imagery was acquired over a study site around the Resolute Bay area. Results indicate that for lake ice, the scattering type magnitude () decreases within a thickness up to 20 cm. This means switching from volume scattering to dominant surface scattering. The same sensitivity is observed for young sea ice with thickness up to 30 cm, which corresponds to modeled ice bulk salinity of 8.5‰. Remarkably, we found a trend of increasing target orientation angle () for thin sea ice up to 20 cm, which corresponds to a bulk salinity of 10.3‰. This trend is unique to the case of sea ice.

Snow redistribution onto young sea ice: Observations and implications for climate models

Vertical heat conduction through young ice is a major source of wintertime sea ice growth in the Arctic. However, field observations indicate that young ice preferentially accumulates wind-blown snow, resulting in greater snow thickness on young ice than would be expected from precipitation alone, and hence greater snow thickness on young ice than climate models represent. As snow has a low thermal conductivity, this additional snow thickness due to redistribution will reduce the actual heat conduction. We present new observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate Expedition which show that young ice rapidly accumulates a snow thickness of 2.5–8 cm, when wind-blown snow is available from the nearby mature ice. By applying a simple redistribution scheme and heat flux model to simulated conditions from the Community Earth System Model 2.0, we suggest that neglecting this snow redistribution onto young ice could result in the potential overestimation of conductive heat flux—and hence ice growth rates—by 3–8% on average in the Arctic in the winter in the absence of climate feedbacks. The impacts of snow redistribution are highest in the springtime and in coastal regions.

A Winter-to-Summer Transition of Bacterial and Archaeal Communities in Arctic Sea Ice.

The Arctic is warming 2–3 times faster than the global average, leading to a decrease in Arctic sea ice extent, thickness, and associated changes in sea ice structure. These changes impact sea ice habitat properties and the ice-associated ecosystems. Sea-ice algal blooms provide various algal-derived carbon sources for the bacterial and archaeal communities within the sea ice. Here, we detail the transition of these communities from winter through spring to early summer during the Norwegian young sea ICE (N-ICE2015) expedition. The winter community was dominated by the archaeon Candidatus Nitrosopumilus and bacteria belonging to the Gammaproteobacteria (Colwellia, Kangiellaceae, and Nitrinocolaceae), indicating that nitrogen-based metabolisms, particularly ammonia oxidation to nitrite by Cand. Nitrosopumilus was prevalent. At the onset of the vernal sea-ice algae bloom, the community shifted to the dominance of Gammaproteobacteria (Kangiellaceae, Nitrinocolaceae) and Bacteroidia (Polaribacter), while Cand. Nitrosopumilus almost disappeared. The bioinformatically predicted carbohydrate-active enzymes increased during spring and summer, indicating that sea-ice algae-derived carbon sources are a strong driver of bacterial and archaeal community succession in Arctic sea ice during the change of seasons. This implies a succession from a nitrogen metabolism-based winter community to an algal-derived carbon metabolism-based spring/ summer community.

Fractal scaling behavior of a sea ice draft field in the Chukchi Sea

In the event that an Arctic oil spill occurs, oil spill modelers need to understand how oil moves along the subsurface of sea ice to predict how a slick will migrate. Currently, modeling the subsurface topography of sea ice has been hampered by a lack of understanding of this complex surface. Using sonar data from the Chukchi Sea, an investigation into whether this subsurface topography exhibited fractal scaling behavior was initiated. It was established that young sea ice exhibits multifractal scaling geometry parameters α, c1, and H as 1.2, 0.03, and 0.12, respectively. Fractal scaling behavior was not found for other types of sea ice. Having established such an analysis is useful, future efforts to expand the work are suggested.

On the phenology and seeding potential of sea-ice microalgal species

Sea ice is an important habitat for a wide variety of microalgal species. Depending on the species composition, sea ice can be a seeding source for pelagic phytoplankton blooms after ice melt in spring. Sea-ice algal communities were studied over 2 full winter seasons in 2014 and 2016 at Rothera Research Station, situated at the Western Antarctic Peninsula (WAP). Algal pigment patterns and microscopic observations were combined with photophysiological studies based on fluorescence analyses to monitor and explain the phenology of ice-algal species. Clear patterns in species succession were identified. Young sea ice contained a mixture of algal species including dinoflagellates, cryptophytes and diatoms like Chaetoceros spp. and Fragillariopsis spp. In winter, severe environmental conditions resulted in a decline in species diversity and selection towards heterotrophy. Pennate diatoms like Amphiprora kufferathii and Berkeleya adeliensis were the first to dominate the nutrient-enriched bottom-ice layers in early spring. The bottom communities exhibited a remarkably stable value for the photoadaptation parameter, Ek, of circa 25 µmol photons m–2 s–1. Whereas pennate diatoms were most abundant in spring ice, the initial seeding event linked to ice melt was associated with flagellate species. Haptophyte species like Phaeocystis antarctica and prymnesiophytes like Pyramimonas spp. best sustained the transition from sea ice to seawater. Comparison with previous studies shows that the seeding patterns observed in Ryder Bay were characteristic over the wider sea-ice domain, Arctic and Antarctic. Over the course of this century, the WAP is predicted to experience continuing thinning and decline in sea-ice cover. For the near future, we expect that especially microalgal communities of haptophytes and chlorophytes will benefit from the changes, with yet unknown implications for carbon fluxes and higher trophic levels.

Simulating tropospheric BrO in the Arctic using an artificial neural network

An intriguing natural phenomenon occurs every polar spring, namely the bromine explosion, in which plumes of tropospheric bromine monoxide (BrO) are formed. These plumes are observed in the BrO vertical column densities (VCDs), retrieved from satellite sensors. Tropospheric BrO depletes tropospheric ozone and facilitates the deposition of mercury. Bromine molecules are mainly released from young sea ice, and meteorological parameters determine the formation and evolution of enhanced BrO VCD plumes. Due to the complexity of the physicochemical processes involved in the bromine explosion, the modeling of tropospheric BrO VCDs in chemical transport models is challenging and not yet adequate. The first of its type, this study demonstrates the potential of using an artificial neural network (ANN), which uses meteorological parameters and sea ice age as inputs to simulate and predict tropospheric BrO VCDs in the Arctic. The ANN is trained and validated using a 22-year satellite remote sensing dataset of Arctic tropospheric BrO VCDs. A generally satisfactory spatial agreement between observed and simulated tropospheric BrO VCDs is observed. However, the magnitude of the observed BrO VCD plumes is underestimated. Air temperature and mean sea level pressure are the most important parameters influencing the magnitude of tropospheric BrO VCD simulations. Although the changing spatial distribution of tropospheric BrO VCDs over time is well captured, the trend reported in the observations of tropospheric BrO VCDs is not reproduced by the ANN, suggesting that additional parameters not included in the ANN also influence the formation of tropospheric BrO VCD plumes.

Cross-platform classification of level and deformed sea ice considering per-class incident angle dependency of backscatter intensity

Abstract. Wide-swath C-band synthetic aperture radar (SAR) has been used for sea ice classification and estimates of sea ice drift and deformation since it first became widely available in the 1990s. Here, we examine the potential to distinguish surface features created by sea ice deformation using ice type classification of SAR data. Also, we investigate the cross-platform transferability between training sets derived from Sentinel-1 Extra Wide (S1 EW) and RADARSAT-2 (RS2) ScanSAR Wide A (SCWA) and fine quad-polarimetric (FQ) data, as the same radiometrically calibrated backscatter coefficients are expected from the two C-band sensors. We use a novel sea ice classification method developed based on Arctic-wide S1 EW training, which considers per-ice-type incident angle (IA) dependency of backscatter intensity. This study focuses on the region near Fram Strait north of Svalbard to utilize expert knowledge of ice conditions during the Norwegian young sea ICE (N-ICE2015) expedition. Manually drawn polygons of different ice types for S1 EW, RS2 SCWA and RS2 FQ data are used to retrain the classifier. Different training sets yield similar classification results and IA slopes, with the exception of leads with calm open water, nilas or newly formed ice (the “leads” class). This is caused by different noise floor configurations of S1 and RS2 data, which interact differently with leads, necessitating dataset-specific retraining for this class. SAR scenes are then classified based on the classifier retrained for each dataset, with the classification scheme altered to separate level from deformed ice to enable direct comparison with independently derived sea ice deformation maps. The comparisons show that the classification of C-band SAR can be used to distinguish areas of ice divergence occupied by leads, young ice and level first-year ice (LFYI). However, it has limited capacity in delineating areas of ice deformation due to ambiguities between ice types with higher backscatter intensities. This study provides reference to future studies seeking cross-platform application of training sets so they are fully utilized, and we expect further development of the classifier and the inclusion of other SAR datasets to enable image-classification-based ice deformation detection using only satellite SAR.

Coherent GNSS-Reflections Characterization Over Ocean and Sea Ice Based on Spire Global CubeSat Data

This article assesses the coherency of Global Navigation Satellite System (GNSS) signals reflected off the oceans and sea ice under grazing angle geometries and received aboard low Earth orbit (LEO) CubeSats for precision altimetry applications. The coherency is characterized as a function of ocean surface conditions and reflected signal parameters based on Spire Global CubeSat data collected from January to April 2019. The data contain 50-Hz GPS L1 and L2 carrier phase estimations obtained by open-loop tracking. Indicators based on the circular statistics of the excess-phase noise are developed to identify coherent and semicoherent reflections. Based on these indicators, we found that ~1% and 44% of GPS reflections over the ocean and sea ice, respectively, have potential for precision altimetry. The coherent and semicoherent reflection rates reach 23% in areas less than 200 km from the coastline and under calm sea conditions. Over young sea ice over the Arctic, this rate can be as high as 70%. There is a strong relationship between coherency and signal strength, and the coherency occurrence rate improves as the grazing angle decreases. The quality of the L1 and L2 coherent reflections is similar over sea ice, while, for reflections over the ocean, L1 signals are predominantly noisier and less coherent than the L2 signals. Using a postprocessing filtering method, the semicoherent reflections can achieve a similar level of altimetry precision as that of the coherent ones, thereby increasing the along-track length of the retrieved altimetry profile.

Microstructure evolution of young sea ice from a Svalbard fjord using micro-CT analysis

AbstractWe analysed the three-dimensional microstructure of sea ice by means of X-ray-micro computed tomography. Microscopic (brine- and air- pore sizes, numbers and connectivity) and macroscopic (salinity, density, porosity) properties of young Arctic sea ice were analysed. The analysis is based on ice cores obtained during spring 2016. Centrifuging of brine prior to CT imaging has allowed us to derive confident relationships between the open, vertically connected and total porosity of young sea ice at relatively high temperatures. We analysed the dependence of the microscopic properties on vertical position and total brine porosity. Most bulk properties (salinity, density) and pore space properties (pore sizes and their distribution) show a strong dependence on total brine porosity, but did not change significantly over the course of the field work. However, significant changes were observed for pore numbers (decreasing over time) and pore connectivity (increasing over time). CT-based salinity determinations are subject to larger than standard uncertainties (from conductivity), while the CT method yields important information about the salinity contributions from closed and open pores. We also performed a comparison of CT-based air porosity with calculations based on density from hydrostatic weighing. The consistency is encouraging and gives confidence to our CT-based results.

An X-ray micro-tomographic study of the pore space, permeability and percolation threshold of young sea ice

Abstract. The hydraulic permeability of sea ice is an important property that influences the role of sea ice in the environment in many ways. As it is difficult to measure, so far not many observations exist, and the quality of deduced empirical relationships between porosity and permeability is unknown. The present work presents a study of the permeability of young sea ice based on the combination of brine extraction in a centrifuge, X-ray micro-tomographic imaging and direct numerical simulations. The approach is new for sea ice. It allows us to relate the permeability and percolation properties explicitly to characteristic properties of the sea ice pore space, in particular to pore size and connectivity metrics. For the young sea ice from the present field study we obtain a brine volume of 2 % to 3 % as a threshold for the vertical permeability (transition to impermeable sea ice). We are able to relate this transition to the necking of brine pores at a critical pore throat diameter of ≈0.07 mm, being consistent with some limited pore analysis from earlier studies. Our optimal estimate of critical brine porosity is half the value of 5 % proposed in earlier work and frequently adopted in sea ice model studies and applications. By placing our results in the broader context of earlier studies, we conclude that the present threshold is more significant in that our centrifuge experiments and high-resolution 3D image analysis enable us to more accurately identify the threshold below which fluid connectivity ceases by examining the brine inclusion microstructure on finer scales than were previously possible. We also find some evidence that the sea ice pore space should be described by directed rather than isotropic percolation. Our revised porosity threshold is valid for the permeability of young columnar sea ice dominated by primary pores. For older sea ice containing wider secondary brine channels, for granular sea ice and for the full-thickness bulk permeability, other thresholds may apply.

Exploration of the Types of Rarity in the Arctic Ocean from the Perspective of Multiple Methodologies.

The Arctic Ocean is facing rapid environmental changes with cascading effects on the entire Arctic marine ecosystem. However, we have a limited understanding of the consequences such changes have on bacteria and archaea (prokaryotes) at the base of the marine food web. In this study, we show how the prokaryotic rare biosphere behaves over a range of highly heterogeneous environmental conditions using 16S rRNA gene reads from amplicon and metagenome sequencing data from seawater samples collected during the Norwegian young sea ICE expedition between late winter and early summer. The prokaryotic rare biosphere was analyzed using different approaches: amplicon sequence variants and operational taxonomic units from the 16S rRNA gene amplicons and operational taxonomic units from the 16S rRNA genes of the metagenomes. We found that prokaryotic rare biosphere communities are specific to certain water masses, and that the majority of the rare taxa identified were always rare and disappeared in at least one sample under changing conditions, suggesting their high sensitivity to environmental heterogeneity. In addition, our methodological comparison revealed a good performance of 16S rRNA gene amplicon sequencing in describing rare biosphere patterns, while the metagenome-derived data were better to capture a significant diversity of so-far uncultivated rare taxa. Our analysis on the dynamics of the rare prokaryotic biosphere, by combining different methodological approaches, improves the description of the types of rarity predicted from Community Assembly theory in the Arctic Ocean.

Investigating the Uptake and Fate of Poly- and Perfluoroalkylated Substances (PFAS) in Sea Ice Using an Experimental Sea Ice Chamber.

Poly- and perfluoroalkyl substances (PFAS) are contaminants of emerging Arctic concern and are present in the marine environments of the polar regions. Their input to and fate within the marine cryosphere are poorly understood. We conducted a series of laboratory experiments to investigate the uptake, distribution, and release of 10 PFAS of varying carbon chain length (C4–C12) in young sea ice grown from artificial seawater (NaClsolution). We show that PFAS are incorporated into bulk sea ice during ice formation and regression analyses for individual PFAS concentrations in bulk sea ice were linearly related to salinity (r2 = 0.30 to 0.88, n = 18, p < 0.05). This shows that their distribution is strongly governed by the presence and dynamics of brine (high salinity water) within the sea ice. Furthermore, long-chain PFAS (C8–C12), were enriched in bulk ice up to 3-fold more than short-chain PFAS (C4–C7) and NaCl. This suggests that chemical partitioning of PFAS between the different phases of sea ice also plays a role in their uptake during its formation. During sea ice melt, initial meltwater fractions were highly saline and predominantly contained short-chain PFAS, whereas the later, fresher meltwater fractions predominantly contained long-chain PFAS. Our results demonstrate that in highly saline parts of sea ice (near the upper and lower interfaces and in brine channels) significant chemical enrichment (ε) of PFAS can occur with concentrations in brine channels greatly exceeding those in seawater from which it forms (e.g., for PFOA, εbrine = 10 ± 4). This observation has implications for biological exposure to PFAS present in brine channels, a common feature of first-year sea ice which is the dominant ice type in a warming Arctic.

Toward a Better Surface Radiation Budget Analysis Over Sea Ice in the High Arctic Ocean: A Comparative Study Between Satellite, Reanalysis, and local‐scale Observations

AbstractReanalysis datasets from atmospheric models and satellite products are often used for Arctic surface shortwave (SW) and longwave (LW) radiative budget analyses, but they suffer from limitations and require validation against local‐scale observations. These are rare in the high Arctic, especially for longer periods that include seasonal transitions. In this study, radiation and meteorological observations acquired during the Norwegian Young Sea Ice Cruise (N‐ICE2015) campaign over sea ice north of Svalbard (80–83°N, 5–25°E) from January–June 2015, cloud lidar observations from the Ice‐Atmosphere‐Ocean Observing System and the Cloud and Aerosol Lidar with Orthogonal Polarization are compared to daily and monthly satellite retrievals from the Clouds and the Earth's Radiant Energy System (CERES) and ERA‐Interim and ERA5 reanalysis. Results indicate that surface temperature is a significant driver for winter LW radiation biases in both satellite and reanalysis data, along with cloud optical depth in CERES. In May, the SW and LW downwelling irradiances are close to observations and cloud properties are well captured (except for ERA‐Interim), while SW upward irradiances are biased low due to surface albedo biases in all datasets. Net SW and LW radiation biases are comparable (∼20–30 Wm−2) but opposite in sign for ERA‐Interim and CERES in May, which allows for error compensation. Biases reduce to ±10 Wm−2 in ERA5. In June downward LW remains biased low (8–10 Wm−2) in all datasets suggesting unsettled cloud representation issues. Surface albedo always differs by more than 0.1 between datasets, leading to significant SW and total flux differences.

SAR image wave spectra to retrieve the thickness of grease-pancake sea ice using viscous wave propagation models

Young sea ice composed of grease and pancake ice (GPI), as well as thin floes, considered to be the most common form of sea ice fringing Antarctica, is now becoming the “new normal” also in the Arctic. A study of the rheological properties of GPI is carried out by comparing the predictions of two viscous wave propagation models: the Keller model and the close-packing (CP) model, with the observed wave attenuation obtained by SAR image techniques. In order to fit observations, it is shown that describing GPI as a viscous medium requires the adoption of an ice viscosity which increases with the ice thickness. The consequences regarding the possibility of ice thickness retrieval from remote sensing data of wave attenuation are discussed. We provide examples of GPI thickness retrievals from a Sentinel-1 C band SAR image taken in the Beaufort Sea on 1 November 2015, and three CosmoSkyMed X band SAR images taken in the Weddell Sea on March 2019. The estimated GPI thicknesses are consistent with concurrent SMOS measurements and available local samplings.

Robustness of SAR Sea Ice Type Classification Across Incidence Angles and Seasons at L-Band

In recent years, space-borne synthetic aperture radar (SAR) polarimetry has become a valuable tool for sea ice type retrieval. L-band SAR has proven to be sensitive toward deformed sea ice and is complementary compared with operationally used C-band SAR for sea ice type classification during the early and advanced melt seasons. Here, we employ an artificial neural network (ANN)-based sea ice type classification algorithm on a comprehensive data set of ALOS-2 PALSAR-2 fully polarimetric images acquired with a range of incidence angles and during different environmental conditions. The variability within the data set means that it is ideal for making a novel assessment of the robustness of the sea ice classification, investigating the intraclass variability, the seasonal variations, and the incidence angle effect on the sea ice classification results. The images coincide with two different Arctic campaigns in 2015: the Norwegian Young Sea Ice Cruise 2015 (N-ICE2015) and the Polarstern’s (PS92) Transitions in the Arctic Seasonal Sea Ice Zone (TRANSSIZ). We find that it is essential to take into account seasonality and intraclass variability when establishing training data for machine learning-based algorithms though moderate differences in incidence angle are possible to accommodate by the classifier during the dry and cold winter season. We also conclude that the incidence angle dependence of backscatter for a given ice type is consistent for different Arctic regions.

Mathematical modeling of binary compounds with the presence of a phase transition layer

When looking for solutions to nonstationary problems in the field of binary melts or solutions, the scientific community regularly faces the need to transform the classical Stefan‐type approach in order to obtain both new analytical results and explicit solutions. Within the framework of the current paper, we present the analysis of the problem of directional crystallization of binary solutions or melts in the presence of a mushy layer, based on the consideration of field data under the prism of a modified formulation, which made it possible to obtain such characteristics of the behavior of the mushy zone as the thickness and growth rate of the solid phase, temperature distribution, and also to determine heat‐conducting and latent heat flows. The simulation results are presented, including in the form of illustrative material; a good agreement was noted between the predicted values of the growth rates and temperature profiles of the mushy zone and the area of solid matter with the existing observations of young sea ice dynamics.

Observations of SAR polarimetric parameters of lake and fast sea ice during the early growth phase

This study examines links between two sets of parameters obtained from Radarsat-2 Quad-pol data and geophysical information of lake ice and landfast sea ice in the Resolute Bay area, Nunavut, Canada. The first set includes the three orthogonal backscatter coefficients (σhh0, σvv0, σvh0) in addition to the total backscatter power (SPAN). The second set includes polarimetric decomposition parameters obtained using Cloude-Pottier and Yamaguchi decomposition methods. Data were collected during the early freezing period from 20 September until 28 December 2017. Meteorological and ice climatological data from the weather station of Resolute Bay were used to facilitate this task. Ice thickness and salinity were obtained from established empirical models. Results show that single-bounce and multiple-bounce scattering mechanisms are active in lake ice during the entire freezing period while multiple-bounce scattering is active in sea ice only during the initial freezing. Backscatter parameters can be used to determine the thickness of lake ice up to any depth, while both backscatter and the tested decomposition parameters are related to the thickness of young sea ice (<30 cm thick). Physical explanations are offered in each case. Spatial maps of ice thickness are produced. Polarimetric decomposition parameters demonstrate erratic behavior throughout the development of lake ice. High entropy (>0.6) is found to be associated with comparable single- and multiple-bounce scattering mechanisms, hence can be used to identify new ice. Orthogonal backscatter coefficients and polarimetric decomposition parameters provide different information, yet their combination offers clues to better identify ice conditions and investigate questions about scattering mechanisms.

Effect of frequent winter warming events (storms) and snow on sea-ice growth – a case from the Atlantic sector of the Arctic Ocean during the N-ICE2015 campaign

AbstractWe examine the relative effect of warming events (storms) and snow cover on thermodynamic growth of Arctic sea ice in winter. We use a 1-D snow and ice thermodynamic model to perform sensitivity experiments. Observations from the winter period of the Norwegian young sea ICE (N-ICE2015) campaign north of Svalbard are used to initiate and force the model. The N-ICE2015 winter was characterized by frequent storm events that brought pulses of heat and moisture, and a thick snow cover atop the sea ice (0.3–0.5 m). By the end of the winter, sea-ice bottom growth was negligible. We show that the thermodynamic effect of storms to the winter sea-ice growth is controlled by the amount of snow on sea ice. For 1.3 m initial ice thickness, the decrease in ice growth caused by the warming events ranged from −1.4% (for 0.5 m of snow) to −7.5% (for snow-free conditions). The decrease in sea-ice growth caused by the thick snow (0.5 m) was more important, ranging from −17% (with storms) to −23% (without storms). The results showcase the critical role of snow on winter Arctic sea-ice growth.

Winter storms accelerate the demise of sea ice in the Atlantic sector of the Arctic Ocean

A large retreat of sea-ice in the ‘stormy’ Atlantic Sector of the Arctic Ocean has become evident through a series of record minima for the winter maximum sea-ice extent since 2015. Results from the Norwegian young sea ICE (N-ICE2015) expedition, a five-month-long (Jan-Jun) drifting ice station in first and second year pack-ice north of Svalbard, showcase how sea-ice in this region is frequently affected by passing winter storms. Here we synthesise the interdisciplinary N-ICE2015 dataset, including independent observations of the atmosphere, snow, sea-ice, ocean, and ecosystem. We build upon recent results and illustrate the different mechanisms through which winter storms impact the coupled Arctic sea-ice system. These short-lived and episodic synoptic-scale events transport pulses of heat and moisture into the Arctic, which temporarily reduce radiative cooling and henceforth ice growth. Cumulative snowfall from each sequential storm deepens the snow pack and insulates the sea-ice, further inhibiting ice growth throughout the remaining winter season. Strong winds fracture the ice cover, enhance ocean-ice-atmosphere heat fluxes, and make the ice more susceptible to lateral melt. In conclusion, the legacy of Arctic winter storms for sea-ice and the ice-associated ecosystem in the Atlantic Sector lasts far beyond their short lifespan.

Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer

AbstractThis study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.