Description: Large freshwater anomalies clearly exist in the Arctic Ocean. For example, liquid freshwater has accumulated in the Beaufort Gyre in the decade of the 2000s compared to 1980-2000, with an extra ≈ 5000 km3 — about 25% — being stored. The sources of freshwater to the Arctic from precipitation and runoff have increased between these periods (most of the evidence comes from models). Despite flux increases from 2001 to 2011, it is uncertain if the marine freshwater source through Bering Strait for the 2000s has changed, as observations in the 1980s and 1990s are incomplete. The marine freshwater fluxes draining the Arctic through Fram and Davis straits are also insignificantly different. In this way, the balance of sources and sinks of freshwater to the Arctic, Canadian Arctic Archipelago (CAA), and Baffin Bay shifted to about 1200 ± 730 km3 yr− 1 freshening the region, on average, during the 2000s. The observed accumulation of liquid freshwater is consistent with this increased supply and the loss of freshwater from sea ice. Coupled climate models project continued freshening of the Arctic during the 21st century, with a total gain of about 50,000 km3 for the Arctic, CAA, and Baffin Bay (an increase of about 50%) by 2100. Understanding of the mechanisms controlling freshwater emphasizes the importance of Arctic surface winds, in addition to the sources of freshwater. The wind can modify the storage, release, and pathways of freshwater on timescales of O(1-10) months. Discharges of excess freshwater through Fram or Davis straits appear possible, triggered by changes in the wind, but are hard to predict. Continued measurement of the fluxes and storage of freshwater is needed to observe changes such as these.

Description: Empirical error functions for 6 different low-resolution Arctic sea-ice drift products are presented on monthly time-scales. To assess the error statistics of the Eulerian ice-drift products, we use high-resolution Lagrangian sea-ice drift obtained from synthetic aperture radar (SAR) images. We processed the Lagrangian drift to Eulerian drift vectors and used them as a reference for the error assessment. Unlike sea-ice buoy trajectory data traditionally used for that purpose, SAR offers a much larger number of data, which enables us to do a thorough assessment of the error statistics of the Eulerian products under different ice conditions. We find that the error statistics differ between the products and between the seasons. For some products the error is dependent on ice drift speed, while for others the error is rather dependent on ice concentration or on both. The summer ice drifts have roughly a two times larger error than the winter drifts, and show significant mean biases. The calculated empirical error functions allow us to derive uncertainty maps for the respective products. These maps can be used for model validation and data assimilation.

Description: Time-space varying uncertainty maps of monthly mean Arctic summer ice drift are presented. To assess the error statistics of two low-resolution Eulerian ice drift products, we use high-resolution Lagrangian ice motion derived from synthetic aperture radar (SAR) imagery. The Lagrangian trajectories from the SAR data are converted to an Eulerian format to serve as reference for the error assessment of the Eulerian products. The statistical error associated with the conversion is suppressed to an acceptable level by applying a threshold for averaging. By using the SAR ice drift as a reference, we formulate the uncertainty of monthly mean ice drift as an empirical function of drift speed and ice concentration. The empirical functions are applied to derive uncertainty maps of Arctic ice drift fields. The estimated uncertainty maps reasonably capture an increase of uncertainty with the progress of summer melting season. The uncertainties range from 1.0 cm s−1 to 2.0 cm s−1, which indicates that the low-resolution Eulerian products for summer seasons are of practical use for climate studies, model validation and data assimilation, if their uncertainties are appropriately taken into account.

Description: With a numerical model we test the sensitivity of the Arctic Ocean circulation at mid-depth (212-1200 m) to the change in the sea ice rheology parameter P* that controls the sea ice compressive strength. We show that the reduction of the sea ice strength via P* within commonly used envelope reduces the sea ice extent and consequently enhances the ocean surface heat loss in the marginal ice zone. This leads to cooling of the Atlantic water inflow into the Arctic Ocean. As a result Eurasian Basin and Amerasian Basin temperatures are in average cooled by 0.1 °C and 0.05 °C, respectively. An increased sea ice drift speed in the central Arctic leads to an enhanced circulation of the anticyclonic Beaufort Gyre of the Amerasian Basin, which in turn weakens the cyclonic Atlantic water circulation below and enhances the recirculation of the Atlantic water in the Eurasian Basin. Consequently the balance of the volume fluxes through the Arctic gateways changes. Fram Strait net outflow increases by 0.46 Sv, Barents Sea Opening net inflow increases by 0.19 Sv and Davis Strait net outflow decreases by 0.28 Sv. This can spread the effects of the sea ice strength change beyond the limits of the Arctic Ocean and into the deep water convection zones in the North Atlantic. These substantial effects should be considered also in the model optimization efforts where P* is commonly used as one of the tuning parameters to achieve better sea ice simulations, whereas the effects on the ocean circulation are rarely taken into account.

Description: Improvement/optimization of a sea ice model is of great significance for understanding the sea ice physics and for understanding the Arctic climate system and its linkage to the global climate. For better representation of modeled sea ice properties, we develop a parameter optimization system for a couped ocean-sea ice model. Since the sensitivities of dynamic and thermodynamic parameters of sea ice models are interrelated, the system handles both sets of parameters simultaneously. The system also handles a long assimilation window of 33 years. Such a long time window has never been tested by other algorithms (e.g., adjoint method, EnKF). Since the cost function defined by the model - data misfit may have an ill-shaped structure (multiple local minima), we apply an algorithm, which can find the global minimum of an ill-shaped function. A micro-Genetic Algorithm is one of the possible solutions to optimize sea ice model parameters.

Description: Recent decades have shown substantial changes in the Arctic Ocean, yet observations are still relatively sparse compared to most other parts of the world's oceans. Results from numerical models still differ in the distribution of key variables, such as the pathways of liquid freshwater. From salinity and temperature profiles observed by a variety of platforms since 1992 we are able to show a substantial freshening in the upper Arctic Ocean impacting an increase in stratification between the mixed-layer and the lower halocline. Based on temperature and salinity profiles, we will present an objective analysis of mixed-layer depth, sea surface height and geostrophic velocity during the recent two decades. We are able to derive decadal trends as well as seasonal cycles during the most recend decade. Surface geostrophic velocity points to a flow in the Amerasian Basin toward the Lomonosov Ridge. Although most of the freshwater volume increase occurred on the Amerasian side of the Arctic Ocean, the changes on the Eurasian side have strong implications not only for the stratification but also the vertical exchange of nutrients in the upper ocean.