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Andrew J. Newman

Publications and source records attributed to Andrew J. Newman.

3 recordsLinked to original sources

Toward co-designed Earth System Models: Reflecting end-user priorities in local applications from a modeler's perspective

Earth System Models (ESM) are crucial for quantifying climate impacts across Earth's interconnected systems and supporting science-based adaptation and mitigation. However, not including end-users, especially decision-makers representing communities vulnerable to climate change, can limit model utility, increase epistemic risks, and lead to information misuse in decision-making. While the ESM community increasingly values broad community engagement, end-users may not initially perceive models as useful for local planning. Co-designing models with end-users fosters two-way learning: users better understand models and their outputs, while modelers gain insights into fine-scale local processes like monitoring practices and management priorities. Higher-level co-design can lead to more customized, priority-driven, and useful modeling products. Despite these benefits, modelers often struggle to initiate meaningful partnerships with local communities. Therefore, this paper explores model co-design from the perspective of modelers. This study presents two case studies where modelers and social scientists collaborated with Indigenous communities' decision-makers to reflect their priorities in model design and application. In the Arctic Rivers Project, high-resolution climate and hydrology data sets for Alaska were developed with guidance from an Indigenous Advisory Council, using optimized, coupled land-atmosphere models. In the Mid-Klamath Project, we partnered with the Karuk Tribe's Department of Natural Resources to assess climate change and prescribed burning impacts on terrestrial hydrology in the Klamath River Basin. Drawing from these studies, we introduce a four-level framework: (a) Co-design Configuration; (b) Model Tuning; (c) Incorporate Contextual Knowledge; (d) Co-develop New Model Functions. We aim to help researchers consider and compare co-design across diverse modeling projects systematically and coherently.

Alaska, California, Oregon

Warming Alaskan rivers affect first-year growth in critical northern food fishes

Arctic and subarctic rivers are warming rapidly, with unknown consequences for migratory fishes and the human communities dependent on them. To date, few studies have provided a comprehensive assessment of possible climate change impacts on the hydrology and temperature of Arctic rivers at the regional scale, and even fewer have connected those changes to multiple fish species with input and guidance from Indigenous communities. We used climate, hydrologic, and fish-growth simulations of historical (1990–2021) and future (2034–2065) young-of-year (YOY) growth potential of Chinook salmon ( Oncorhynchus tshawytscha ) and Dolly Varden ( Salvelinus malma ) for seven river basins in the Arctic-Yukon-Kuskokwim (AYK) region of Alaska, USA and Yukon Territory, Canada. Historically, summer water temperatures of all river basins remained below thresholds regarded as deleterious for Chinook salmon (14.6 °C) and Dolly Varden (16 °C), even in the warmest years. However, by the mid-century, Chinook salmon growth was limited, with declines in the warmest years in most river basins. Conversely, Dolly Varden are expected to benefit, with a near-doubling in growth projections in all river basins. This suggests that there may be an increase in suitable habitat for Dolly Varden by mid-century. The results highlight species-specific consequences of climate change and can guide future research on refugia for these species of cultural and subsistence importance to Indigenous communities in the AYK region and throughout the Arctic.

Alaska

New projections of 21st century climate and hydrology for Alaska and Hawaiʻi

In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.

Alaska, Hawaii