4月24日（火）に、毎年恒例の「アラスカ大学フェアバンクス校Research Day」が開催される。Research Dayは大学のあらゆる分野で研究を行っている大学院生、学部生を、ポスター発表や研究室のオープンハウスなどを通じて紹介。IARCは当日、大学院生がポスター研究発表により参加。催しは午前10時〜午後2時。
Using local knowledge, hydrology, and climate scenarios to develop a driftwood harvest model for Tanana, Alaska
Chas Jones, Graduate Student/ Research Assistant
Many rural Alaskan residents rely on harvested driftwood from the Yukon River for fuel and construction materials, however they have stated that the character of the summer discharge in the Yukon River is changing and affecting their ability to harvest this resource. We examined whether the perceived changes in driftwood availability are related to changes in river hydrology and how changes in hydrology may affect future driftwood flows and the livelihoods of rural Alaskans. The Yukon River flows northwesterly through British Columbia and the Yukon Territory before flowing southwest through Alaska. In most summers, major driftwood flows occur in the Yukon River during two different periods. Typically, driftwood accompanies high flows on the Yukon River associated with spring break‐up. A few weeks later, a second series of driftwood appears, associated with the "2nd rise," which is reported to occur during early June, which is when the rural residents of Tanana, Alaska plan to harvest their annual supply of driftwood. This study examined the nature of the differential timing of high flow events in the Yukon River. Increasingly, villages in rural Alaska are trying to lessen their dependence upon expensive fossil fuels. To achieve this goal, a number of Alaskan villages have recently installed wood chip‐fired boilers to generate heat and/or electricity and additional boilers are slated to be installed in rural Alaska in the near future. These boilers are largely fed by driftwood, a cheap and easily processed wood source. Some Tanana residents have expressed concern that in recent years, driftwood was not readily available because the "2nd rise" flood event was absent. Rural Alaskans find this disconcerting because they have offset a dependence on fossil fuel use for heat and electricity with an increased reliance on wood. In our study, the local knowledge of rural Alaskans was used in conjunction with the historic hydrology to model the historic driftwood harvest from the Yukon River near Tanana. The model allowed us to explore how various hydrologic scenarios might influence the lives of rural Alaskans.
Can the Community Earth System Model Simulate Variability over the Bering Sea?
Joshua M. Walston, Graduate Student/ Research Assistant
The National Center of Atmospheric Research (NCAR) has produced a coupled climate model, the Community Climate System Model (CCSM4), for the purpose of simulating the Earth's climate system. Analyzing the dynamics of the Earth’s physical system can provide potential predictions and possible solutions for certain climate issues. Being one of the world's most productive ecosystems, fisheries in the Bering Sea account for more than half of the marine harvest in the United States waters. For this reason, it is imperative to analyze the performance of the model over the Arctic domain to understand how the model captures atmospheric forcing variables that impact ecosystem processes. Since this has not yet been assessed, the goal of this project is to determine the ability of the CCSM4 model to capture the variability of the Arctic's physical system. Ultimately this project will ascertain the impact of high latitude variability on marine ecosystem productivity. Preliminary findings indicate that the model captures observed annual cycles in pressure and temperature. However, the model shows more temporal variability over a monthly time scale of sea level pressures compared to NCEP Reanalysis data. Simulated and observed temporal variance of air temperatures are more closely correlated, and are very similar in magnitude. Simulated seasonal means also show more variability in both sea level pressure and air temperature than the data. Again, the model simulation of sea level pressure has more than 2.5 times as much variance as the the observed sea level pressure.
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