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\begin{document}

\title{Coupled high-resolution land-atmosphere modeling for hydroclimate and
terrestrial hydrology in Alaska and the Yukon River Basin (1990-2021)}



\author[1]{Yifan Cheng}%
\author[2]{Anthony Craig}%
\author[3]{Keith Musselman}%
\author[4]{Andrew Bennett}%
\author[5]{Mark W. Seefeldt}%
\author[6]{Joseph Hamman}%
\author[7]{Andrew J Newman}%
\affil[1]{National Center for Atmospheric Research}%
\affil[2]{Naval Postgraduate School}%
\affil[3]{Institute of Arctic and Alpine Research}%
\affil[4]{University of Arizona}%
\affil[5]{University of Colorado Boulder}%
\affil[6]{Earthmover}%
\affil[7]{National Center for Atmospheric Research (UCAR)}%


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  \date{June 05, 2024}


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\begin{abstract}
Hydroclimate and terrestrial hydrology greatly influence the local
community, ecosystem, and economy in Alaska and Yukon River Basin. A
high-resolution re-simulation of the historical climate in Alaska can
provide an important benchmark for climate change studies. In this
study, we utilized the Regional Arctic Systems 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
re-optimization of CTSM. A multi-decadal climate dataset (1990-2021) was
generated using RASM with optimized land parameters and manually tuned
WRF microphysics. When evaluated against multiple observational
datasets, this dataset 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 fluxes between the offline
CTSM and coupled models, which contributed to their discrepancy in
streamflow simulations.%
\end{abstract}%



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\textbf{Hosted file}

\verb`cheng_et_al_2023_rasm_historical.submit.docx`  available at \url{https://authorea.com/users/532269/articles/725990-coupled-high-resolution-land-atmosphere-modeling-for-hydroclimate-and-terrestrial-hydrology-in-alaska-and-the-yukon-river-basin-1990-2021}

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