FACETS Dynamical Downscaling Simulations over North America by the CAM-MPAS Variable-Resolution Model

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Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through development of metrics and their demonstration on a hierarchy of downscaled climate datasets to quantify aspects of climate change projections that are credible, particularly for supporting decisions related to the energy-water-land nexus. As a part of this effort, we have produced a regional climate dataset using the Model for Prediction Across Scales coupled to the Community Atmosphere Model (CAM-MPAS). This global modeling framework is configured with variable-resolution meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The variable-resolution configurations allow fine-scale features to be better resolved inside the refinement and interact with global-scale circulations. The dataset includes multiple uniform- (240km and 120km) and variable-resolution (200-50km, 100-25km, and 46-12km) simulations that are designed to be compatible with other regional climate simulations that contribute to the hierarchy of downscaled climate datasets of the project. Furthermore, the dataset consists of simulations for both the present-day (1989-2010) and future (2079-2100) climate and post-processing of the model output has been coordinated across the project for consistency to facilitate common analysis across the hierarchy of datasets. Altogether, this CAM-MPAS model dataset provides a unique opportunity to assess the influence of resolutions and modeling framework on model credibility and climate change projection.

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Projects (1)
FACETS: A Hierarchical Evaluation Framework for Assessing Climate Simulations Relevant to the Energy-Water-Land Nexus Applicant Institution
People (5)

Koichi Sakaguchi received his Ph.D. degree in Hydrometeorology in 2013 from the University of Arizona and joined PNNL in the same year. His main research interests are process coupling within and at the boundaries of the atmosphere, in particular through the processes related to turbulence. His...

https://staff.ucar.edu/users/mcginnis Seth McGinnis has worked as an Associate Scientist in IMAGe at NCAR since 2003, shortly after he received his Ph.D. in geophysics from CU-Boulder. He has a strong background in computer programming and works on a variety of projects related to making atmospheric...

https://ge-at.iastate.edu/directory/william-gutowski/ Dr. Gutowski’s research concentrates on the role of atmospheric dynamics in climate. Central focuses are the dynamics of the hydrologic cycle and regional climate. Because processes on a wide range of spatial and temporal scales are important for...

Lu Dong got her PhD degree at the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences in June 2015 under her Ph.D advisor Dr. Tianjun Zhou. During her PhD career, she mainly focused on the long-term change of sea surface temperatures in both the Indian and Pacific Oceans and compared...

Dr. L. Ruby Leung is a Battelle Fellow at PNNL. Her research broadly cuts across multiple areas in modeling and analysis of climate and the hydrological cycle, including land-atmosphere interactions, orographic processes, monsoon climate, climate extremes, land surface processes, and aerosol-cloud...