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Remote communities often rely on fossil fuels to produce their electricity. The climate change impacts of these generation systems are exacerbated by the transportation of fuel to the generation sites. Additionally, the volatile cost of fuel and transportation services places a financial burden on these communities.
When available, direct observations are the most accurate way to characterize atmospheric variables. However, the necessary observing network does not exist and would be impractical to build; therefore, models are used to fill in the temporal and spatial gaps.