The recent global warming and climate change have significantly altered the extents of sea ice and snow. Declining thickness of the Arctic sea ice increases maritime activities for resource extraction, refueling communities, tourism, and shipping. Changes of snowpack threaten water availability for agriculture, drinking water, and hydropower in dependent regions. Thus, remote sensing approach is essential for detecting and monitoring snowfall and oil-contaminated sea ice. This thesis focuses on studying two main objectives: 1) monitoring oil spills within freezing seawater (by aiming to understand the potential impacts of diesel fuel and wind on the growth, thermophysical, and C-band backscattering responses of newly forming sea ice.), and 2) investigating terrestrial snowfall events (by aiming to examine the capabilities of C-band and L-band scatterometers in detecting the presence of dry and wet snow, along with monitoring the thermophysical changes within the snowpacks). In order to investigate the objectives, three experiments were conducted during 2022-23 at the University of Manitoba research facilities (SERF and The Point). The experiments were centered on change detection, dual-frequency, and multi-scenario approaches to provide intercomparable results and interpretations. By accomplishing these objectives, this thesis makes a substantial contribution in developing both contemporary and future C-band and L-band satellites missions. It provides essential data, such as the location and extent of the snow on the ground, as well as the oil-contaminated sea ice in the Arctic for modeling and mapping programs. Consequently, the outcomes will provide successful supports to many climate change counter-responses and strategies around the world.