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Hydroclimate and terrestrial hydrology greatly influence the local community, ecosystem, and economy in Alaska and Yukon River Basin. A high‐resolution simulation of the historical climate in Alaska can provide an important benchmark for climate change studies. In this study, we utilized the Regional Arctic System Model (RASM) and conducted coupled land‐atmosphere modeling for Alaska and Yukon River Basin at 4‐km grid spacing. In RASM, the land model was replaced with the Community Terrestrial Systems Model (CTSM) given its comprehensive process representations for cold regions. The microphysics schemes in the Weather Research and Forecast (WRF) atmospheric model were manually tuned for optimal model performance. This study aims to maintain good model performance for both hydroclimate and terrestrial hydrology, especially streamflow, which was rarely a priority in coupled models. Therefore, we implemented a strategy of iterative testing and optimization of CTSM. A multi‐decadal climate data set (1990–2021) was generated using RASM with optimized land parameters and manually tuned WRF microphysics. When evaluated against multiple observational data sets, this data set well captures the climate statistics and spatial distributions for five key weather variables and hydrologic fluxes, including precipitation, air temperature, snow fraction, evaporation‐to‐precipitation ratios, and streamflow. The simulated precipitation shows wet bias during the spring season and simulated air temperatures exhibit dampened seasonality with warm biases in winter and cold biases in summer. We used transfer entropy to investigate the discrepancy in connectivity of hydrologic and energy fluxes between the offline CTSM and coupled models, which contributed to their discrepancy in streamflow simulations. 

Hydroclimate and terrestrial hydrology greatly influence the local communities, ecosystems, and economies across Alaska and Yukon River Basin. Therefore, we utilized the Regional Arctic Systems Model (RASM) to model the coupled land-atmosphere, and generated a climate and hydrology dataset at 4-km grid spacing to improve our understanding of the regional hydroclimate and terrestrial hydrology. Our model domain encompasses all of the U.S. State of Alaska, the entire Yukon River Basin, part of Western Canada, and the eastern coastal region of Russia. This dataset includes 1) one simulation of the historical climate (Water Years 1991-2021), which serves as a benchmark for climate change studies, and 2) two future simulations (Equivalent Water Years 2035-2065) using the Pseudo-Global Warming method under future greenhouse gas emission scenario SSP2-4.5. The two future scenarios represent median and high changes derived from ensemble means across different Global Climate Models in the Coupled Model Intercomparison Project Phase 6 within SSP2-4.5 respectively. The microphysics schemes in the Weather Research and Forecast (WRF) atmospheric model were manually tuned for optimal model performance. The land component in RASM was replaced using the Community Terrestrial Systems Model (CTSM) given its comprehensive process representations for cold regions. We conducted optimization for uncoupled CTSM to improve its performance in terrestrial hydrologic simulations, especially streamflow and snow (Cheng et al., 2023). In order to maintain the quality for both hydroclimate and terrestrial hydrologic simulation, we implemented a strategy of iterative testing and re-optimization of CTSM. This dataset was then generated using RASM with optimized CTSM parameters and manually tuned WRF microphysics. The historical simulation was evaluated against multiple observational datasets for five key weather variables and hydrologic fluxes, including precipitation, air temperature, snow fraction, evaporation-to-precipitation ratios, and streamflow. The evaluation details can be found in Cheng et al. (2024).