1 Introducing the new Regional Community Earth System Model, 2 R-CESM 3 Dan Fu1,2, Justin Small*1,3, Jaison Kurian*1,2, Yun Liu1,2, Brian Kauffman1,3, Abishek Gopal1,2, 4 Sanjiv Ramachandran1,2, Zhi Shang2, Ping Chang1,2,4, Gokhan Danabasoglu1,3, Katherine Thayer- 5 Calder3, Mariana Vertenstein3, Xiaohui Ma1,5,6, Hengkai Yao2,5, Mingkui Li1,5,6, Zhao Xu 5,6, 6 Xiaopei Lin5,6, Shaoqing Zhang1,5,6, and Lixin Wu5,6 7 1International Laboratory for High-Resolution Earth System Prediction (iHESP), Texas A&M 8 University, College Station, Texas, USA. 9 2Department of Oceanography, Texas A&M University, College Station, Texas, USA. 10 3National Center for Atmospheric Research, Boulder, Colorado, USA. 11 4Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA. 12 5Key Laboratory of Physical Oceanography/Frontiers Science Center for Deep Ocean 13 Multispheres and Earth System (DOMES), Ocean University of China, Qingdao, China 14 6Laboratory for Ocean Dynamics and Climate, Qingdao Pilot National Laboratory for Marine 15 Science and Technology, Qingdao, China. 16 Submitted to BAMS October 16 2020, Revised March 15 2021, May 10th 2021 17 *Correspondence to: Justin Small ([email protected]) 18 19 1 1 Early Online Release: This preliminary version has been accepted for publication in Bulletin of the American Meteorological Society, may be fully cited, and has been assigned DOI 10.1175/BAMS-D-20-0024.1. The final typeset copyedited article will replace the EOR at the above DOI when it is published. © 2021 American Meteorological Society Unauthenticated | Downloaded 09/25/21 10:13 PM UTC 20 ABSTRACT 21 The development of high-resolution, fully-coupled, regional Earth system model systems is 22 important for improving our understanding of climate variability, future projections, and extreme 23 events at regional scales. Here we introduce and present an overview of the newly-developed 24 Regional Community Earth System Model (R-CESM). Different from other existing regional 25 climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) 26 framework. We have incorporated the Weather Research and Forecasting (WRF) model and 27 Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R- 28 CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM 29 solutions or/and as a standalone high-resolution regional coupled model. The user interface of R- 30 CESM follows that of CESM, making it readily accessible to the broader community. Among 31 countless potential applications of R-CESM, we showcase here a few preliminary studies that 32 illustrate its novel aspects and value. These include: 1) assessing the skill of R-CESM in a multi- 33 year, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact 34 of WRF and CESM ocean-atmosphere coupling physics on tropical cyclone simulations; and 3) a 35 convection-permitting simulation of submesoscale ocean-atmosphere interactions. We also 36 discuss capabilities under development such as i) regional refinement using a high-resolution 37 ROMS nested within global CESM; and ii) “online” coupled data assimilation. Our open-source 38 framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad 39 range of applications that are of interest to the users of CESM, WRF, and ROMS. 40 41 42 2 Unauthenticated | Downloaded 09/25/21 10:13 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0024.1. 43 CAPSULE 44 A new regional community Earth system model is now publicly available, enabling high-resolution 45 regional coupled simulations for bridging the gap between weather and climate within a widely- 46 used global modeling framework. 47 48 3 Unauthenticated | Downloaded 09/25/21 10:13 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0024.1. 491. INTRODUCTION 50 51 Earth System Models (ESMs), in which different components such as atmosphere, land, 52 ocean, sea-ice, biogeochemistry, and river runoff interact with each other, are the most 53 comprehensive tools to understand and predict the earth’s weather (minutes to days) and climate 54 (seasons to centuries) systems. Due to computational costs, current global ESMs are often 55 configured with coarse horizontal resolutions but usually have multiple ensemble members, and 56 are typically designed to study climatic evolution (e.g., Kay et al. 2015. In contrast, regional ESMs 57 are configured with much higher resolution and dedicated to either weather applications or high- 58 resolution dynamical downscaling of climate information from coarse resolution global models, 59 and most do not contain active ocean components (e.g., Giorgi 2019; Gutowski et al. 2020). The 60 global and regional ESMs differ in many other aspects, including available component models, 61 resolved and parameterized physics, and model framework. Given the ever-increasing demand for 62 high-resolution regional weather and climate information for decision and policy making, it is 63 desirable to have a system where one can switch seamlessly from global to regional and weather 64 to climate applications. This is the primary motivation for us to develop and introduce the Regional 65 Community Earth System Model (R-CESM). 66 Existing approaches to bridge the gap between global and regional ESMs involve methods 67 such as running global models at a uniform high-resolution, regional mesh refinement, and 68 downscaling from global to regional ESMs. Advances in supercomputing have made it possible to 69 run global models on grids which permit tropical cyclones (TCs) and ocean eddies for long climate 70 time scales (e.g., Kirtman et al 2012; Delworth et al. 2012; Small et al. 2014; Chang et al. 2020; 71 Roberts et al. 2020). However, these simulations are so far somewhat rare and very 4 Unauthenticated | Downloaded 09/25/21 10:13 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0024.1. 72 computationally expensive, and the grid resolutions may still be insufficient to fully resolve the 73 grid scale forcing and processes (e.g., complex topography and bathymetry) and dynamical 74 evolutions at regional scales. Mesh refinement (where the spatial resolution can be made higher 75 over an area of interest) is a relatively new technique available only in a few models. The most 76 common method is downscaling the global model results with regional models, which is the 77 approach taken here. However we have identified at least 4 aspects that are needed in an advanced 78 regional modeling system which are not addressed in existing systems: 79 1. Model physics consistency: The schemes and formulations used to parameterize physical 80 processes (e.g., air-sea fluxes, planetary boundary layer, cloud microphysics, and convection) 81 are different between the global and regional models. 82 2. Modeling framework: The absence of community-based coupling software in some models 83 makes it difficult to add new component models. In some cases, there is an air-sea flux 84 consistency issue because the component models compute fluxes independently instead of 85 using a common flux field computed either in a coupler or any of the individual component 86 models. 87 3. Two-way interaction: Typically, the global models influence the regional models through 88 lateral boundary conditions (one-way), without any feedback from the regional models to the 89 global models. 90 4. Coupled data assimilation: Data assimilation capacities inherited from uncoupled systems can 91 not directly fit in a coupled system; the lack of coupled data assimilation system tends to 92 degrade the prediction ability of a regional ESM forecast system. 93 To advance ESMs and help overcome these issues, R-CESM has been developed jointly by 94 the Texas A&M University (TAMU), the National Center for Atmospheric Research (NCAR), and 5 Unauthenticated | Downloaded 09/25/21 10:13 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0024.1. 95 the Ocean University of China (OUC). R-CESM is based on the latest infrastructure of the 96 Community Earth System Model version 2 (CESM2; Danabasoglu et al. 2020) and its Common 97 Infrastructure for Modeling the Earth (CIME) framework. Furthermore, R-CESM includes non- 98 standard CESM2 components, i.e., the Regional Ocean Modeling System (ROMS; Haidvogel et 99 al. 2008; Shchepetkin and McWilliams 2005) for the ocean and Weather Research and Forecasting 100 (WRF; Skamarock et al. 2008) for the atmosphere. The CIME infrastructure allows users to swap 101 with ease between the global model (CESM2) and regional models. 102 The main scope of this paper is to introduce this newly developed R-CESM to the research 103 community and showcase its versatility in studying various Earth systems across different 104 temporal and spatial scales. We start with an overview of the system in section 2. Section 3 105 highlights particular features of R-CESM that distinguish it from other regional systems. Section 106 4 describes illustrative simulations of the broad range of applications, including a 9-year 107 simulation of regional climate in the Gulf of Mexico to examine long-term stability of the R- 108 CESM, TC simulations with different air-sea flux parameterizations, and a high-resolution 109 simulation to explore submesoscale air-sea interactions in the Kuroshio Extension. Then we 110 describe two ongoing efforts – i) embedding of ROMS within CESM to facilitate the 111 communication between regional and global models, and ii) development of an “online” coupled 112 data assimilation capability within R-CESM for regional climate predictions.