Changes in Arctic sea ice and hydrology of pan-Arctic river basins under the impact of climate change

Abstract

Under the impact of global warming, the hydro-climatology over the Arctic has changed significantly. Warming over the Arctic region is twice the global mean warming rate since the 1980s, known as Arctic Amplification, which occurs because warming induces melting of sea ice, leading to feedbacks that accelerate the ice loss, such as the ice-albedo feedbacks, water-vapor feedbacks, cloud feedbacks, and lapse-rate feedbacks. The rapid increase in air temperature leads to substantial decline of Arctic sea ice and more intensive hydrologic processes in the pan-Arctic river basins. As the primary freshwater source to the Arctic Ocean, streamflow from the pan-Arctic river basins plays a crucial role in the sea ice formation, oceanic circulation, and the thermohaline balance in the Arctic. With a warmer atmosphere, the melting season of sea ice has lengthened and the ice cover has become younger and thinner, while the streamflow from pan-Arctic river basins have shown an increasing trends in recent years. Numerous studies detected the teleconnections between the decline in Arctic sea ice and climate patterns, and the feedbacks, but the focus of these studies was more about average changes and the effects of individual climate patterns instead of their combined impacts. In addition, partly because of limited observed hydro-climatologic data available in pan-Arctic river basins, there have been relatively few studies on hydrologic responses of pan-Arctic river basins to climate change impact compared with studies in southern, highly populated regions. This dissertation began with an investigation on the decline of Arctic sea ice using a quantile regression method at all quantile levels. Next, hydrologic responses of the pan-Arctic river basins, such as non-stationarities and trends, and changes in wet and dry spells were analyzed by statistical and probabilistic analysis, and an artificial neural network. Therefore, the objectives of this dissertation are: (1) to analyze changes of Arctic sea ice under the possible impacts of climate patterns and the physical mechanisms behind the teleconnection with climate patterns; (2) to identify non-stationarities and trends of streamflow from three Great Siberian river basins using statistical analysis; (3) to simulate the streamflow of four large pan-Arctic river basins with machine learning models and to project hydrologic impact of climate warming to these pan-Arctic river basins; (4) to analyze the probabilistic characteristics of the duration and temperature of both wet and dry spells of the Siberian river basins, and the joint and conditional probabilities of extreme dry and wet spells occurring in these river basins estimated from a Copulas function.