The Ross Sea region, including three main polynya areas in McMurdo Sound, Terra Nova Bay, and in front of the Ross Ice Shelf, has experienced a significant increase in sea ice extent in the first four decades of satellite observations. Here, we use Co-Registration of Optically Sensed Images and Correlation (COSI-Corr) to estimate 894 high-resolution sea ice motion fields of the Western Ross Sea in order to explore ice-atmosphere interactions based on sequential high-resolution Advanced Synthetic Aperture Radar (ASAR) images from the Envisat satellite acquired between 2002–2012. Validation of output motion vectors with manually drawn vectors for 24 image pairs show Pearson correlation coefficients of 0.92 ± 0.09 with a mean deviation in direction of −3.17 ± 6.48 degrees. The high-resolution vectors were also validated against the Environment and Climate Change Canada sea ice motion tracking algorithm, resulting in correlation coefficients of 0.84 ± 0.20 and the mean deviation in the direction of −0.04 ± 17.39 degrees. A total of 480 one-day separated velocity vector fields have been compared to an available NSIDC low-resolution sea ice motion vector product, showing much lower correlations and high directional differences. The high-resolution product is able to better identify short-term and spatial variations, whereas the low-resolution product underestimates the actual sea ice velocities by 47% in this important near-coastal region. The large-scale pattern of sea ice drift over the full time period is similar in both products. Improved image coverage is still desired to capture drift variations shorter than 24 h.

Sea ice drift data at high spatial resolution and surface wind model output are used to explore atmosphere-sea ice interactions in the Western Ross Sea including the three main polynyas areas; McMurdo Sound polynya (MSP), Terra Nova Bay polynya (TNBP), and the Ross Sea polynya (RSP). This study quantifies the relationship between the winds and sea ice drift and observes the average and annual anomalies across the region. Sea ice drift velocities are based on high-resolution (150 m) Advanced Synthetic Aperture Radar (ASAR) images from Envisat for winters between 2002 and 2012. Sea ice motion vectors were first correlated with the corresponding Antarctic Mesoscale Prediction System (AMPS) surface wind velocities, and the sensitivity of the spatial correlations and residuals were examined. Four drift parameters were selected (mean drift, the correlation between drift and wind, drift to wind scaling factor, and the directional drift constancy) to perform an unsupervised k-means classification to automatically distinguish six zones of distinctive sea ice characteristics solely based on ice drift and wind information. Results indicate a heterogeneous pattern of sea ice movement at a rate ranging from 0.41 to 2.24% of the wind speed in different areas. We also find that the directional constancy of sea ice drift is closely related to the wind fields. Sea ice drift and wind velocities display the highest correlation in free-drift areas (R = 0.70), followed by deformational drift zones (R = 0.54), and more random drift areas (R = 0.28). The classification illustrates the significance of localized wind-driven sea ice drift in this coastal area resulting in zones of convergence, shear, and free drift. The results also indicate that the most persistent patterns of sea ice motion are near the RSP and TNBP areas, both being driven by strong localized winds. Our findings identify that large-scale sea ice motion is predominantly wind-driven over much of the study area while ocean currents play only a minor role.

A well-developed banking system is prerequisite for a fast-growing economy. The introduction of financial instruments is a collaborative effort that pits the results of analysis of the banking sector's development and impact on the economy against basic regulatory standards and approaches to state regulation of the financial system's development and banking subsystem. Banking sectors, according to economic literature, play an intermediation role by enabling money transfers between fund-suppliers and fund-demanders. This can be accomplished by attracting savings and then directing those funds into loans to fund various economic activities, resulting in economic growth (EG). Every bank has its own internal component that affects financial performance in a particular way the more efficient a country's financial sector develops, the more likely its limited resources will be channeled to the most productive use. Openness in the banking sector may have a direct impact on growth by enhancing access to financial services and indirectly by improving the efficiency of financial intermediaries, both of which lower the cost of financing and, as a result, encourage capital accumulation and economic growth. A variety of macroeconomic links, notably the one between financial development and long-run growth, have been studied using cross-country regressions. Microeconomic explanation differs from the traditional perspective, which sees financial intermediaries as a bridge between borrowers and lenders' differing interests in terms of the size, maturity, and risk of a financial investment.