We present an unprecedented set of high-resolution climate simulations, consisting of a 500-year pre-industrial control simulation and a 250-year historical and future climate simulation from 1850 to 2100. A high-resolution configuration of the Community Earth System Model version 1.3 (CESM1.3) is used for the simulations with a nominal horizontal resolution of 0.25°for the atmosphere and land models and 0.1°for the ocean and sea-ice models. At these resolutions, the model permits tropical cyclones and ocean mesoscale eddies, allowing interactions between these synoptic and mesoscale phenomena with large-scale circulations. An overview of the results from these simulations is provided with a focus on model drift, mean climate, internal modes of variability, representation of the historical and future climates, and extreme events. Comparisons are made to solutions from an identical set of simulations using the standard resolution (nominal 1°) CESM1.3 and to available observations for the historical period to address some key scientific questions concerning the impact and benefit of increasing model horizontal resolution in climate simulations. An emerging prominent feature of the high-resolution pre-industrial simulation is the intermittent occurrence of polynyas in the Weddell Sea and its interaction with an Interdecadal Pacific Oscillation. Overall, high-resolution simulations show significant improvements in representing global mean temperature changes, seasonal cycle of sea-surface temperature and mixed layer depth, extreme events and in relationships between extreme events and climate modes. Plain Language Summary Although the current generation of climate models has demonstrated high fidelity in simulating and projecting global temperature change, these models show large uncertainties when it comes to questions concerning how rising global temperatures will impact local weather conditions. This is because the resolution (~100 km) at which the majority of climate models simulate the climate is not fine enough to resolve these small-scale regional features. Conducting long-term (multi-centuries) high-resolution (~10 km) climate simulations has been a great challenge for the research community due to the extremely high computational demands. Through international

Abstract. With semiconductor technology gradually approaching its physical and thermal limits, recent supercomputers have adopted major architectural changes to continue increasing the performance through more power-efficient heterogeneous many-core systems. Examples include Sunway TaihuLight that has four management processing elements (MPEs) and 256 computing processing elements (CPEs) inside one processor and Summit that has two central processing units (CPUs) and six graphics processing units (GPUs) inside one node. Meanwhile, current high-resolution Earth system models that desperately require more computing power generally consist of millions of lines of legacy code developed for traditional homogeneous multicore processors and cannot automatically benefit from the advancement of supercomputer hardware. As a result, refactoring and optimizing the legacy models for new architectures become key challenges along the road of taking advantage of greener and faster supercomputers, providing better support for the global climate research community and contributing to the long-lasting societal task of addressing long-term climate change. This article reports the efforts of a large group in the International Laboratory for High-Resolution Earth System Prediction (iHESP) that was established by the cooperation of Qingdao Pilot National Laboratory for Marine Science and Technology (QNLM), Texas A&M University (TAMU), and the National Center for Atmospheric Research (NCAR), with the goal of enabling highly efficient simulations of the high-resolution (25 km atmosphere and 10 km ocean) Community Earth System Model (CESM-HR) on Sunway TaihuLight. The refactoring and optimizing efforts have improved the simulation speed of CESM-HR from 1 SYPD (simulation years per day) to 3.4 SYPD (with output disabled) and supported several hundred years of pre-industrial control simulations. With further strategies on deeper refactoring and optimizing for remaining computing hotspots, as well as redesigning architecture-oriented algorithms, we expect an equivalent or even better efficiency to be gained on the new platform than traditional homogeneous CPU platforms. The refactoring and optimizing processes detailed in this paper on the Sunway system should have implications for similar efforts on other heterogeneous many-core systems such as GPU-based high-performance computing (HPC) systems.

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Cloud computing has attracted more and more attentions due to its ability to deliver computing utilities as Internet services. Many industrial companies have successfully applied their Clouds with different technologies and architectures. But the existing Clouds are all computer-based and designed for Web browser. In this paper we propose a Cloud architecture which is based on digital appliances in smart home to provide IT Services that can be accessed and used by appliances users. As the vinculum that links Cloud and smart home, home gateway, which helps smart home merge into Cloud to provide more information services and access services provided by Cloud, plays a significant role in this architecture. Thus this Cloud architecture extends Cloud computing applications to a new domain so that more users could benefit from Clouds. The architecture that we propose in this paper is a conceptual model and more work need to be done to implement it.