Global simulations of the atmosphere at 1.45 km grid-spacing with the Integrated Forecasting System

[1]  Hiroaki Miura,et al.  Global cloud‐system‐resolving model NICAM successfully simulated the lifecycles of two real tropical cyclones , 2008 .

[2]  Torsten Hoefler,et al.  Reflecting on the Goal and Baseline for Exascale Computing: A Roadmap Based on Weather and Climate Simulations , 2019, Computing in Science & Engineering.

[3]  Hartwig Deneke,et al.  Large‐eddy simulations over Germany using ICON: a comprehensive evaluation , 2017 .

[4]  Thomas Dubos,et al.  Dynamically consistent shallow‐atmosphere equations with a complete Coriolis force , 2013 .

[5]  D. Lüthi,et al.  Evaluation of the convection‐resolving climate modeling approach on continental scales , 2017 .

[6]  N. Jeevanjee.  Vertical Velocity in the Gray Zone , 2016 .

[7]  J. Geleyn,et al.  A Turbulence Scheme with Two Prognostic Turbulence Energies , 2018, Journal of the Atmospheric Sciences.

[8]  Nils Wedi,et al.  Assessing the scales in numerical weather and climate predictions: will exascale be the rescue? , 2019, Philosophical Transactions of the Royal Society A.

[9]  Luca Cinquini,et al.  Requirements for a global data infrastructure in support of CMIP6 , 2018, Geoscientific Model Development.

[10]  Peter Bauer,et al.  The quiet revolution of numerical weather prediction , 2015, Nature.

[11]  Francis X. Giraldo,et al.  Current and Emerging Time-Integration Strategies in Global Numerical Weather and Climate Prediction , 2019 .

[12]  Nils Wedi,et al.  A framework for testing global non‐hydrostatic models , 2009 .

[13]  H. Yashiro,et al.  Deep moist atmospheric convection in a subkilometer global simulation , 2013 .

[14]  Masaki Satoh,et al.  Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations , 2008, J. Comput. Phys..

[15]  S. Bony,et al.  RCEMIP: Radiative Convective Equilibrium Model Inter-comparison Project , 2017 .

[16]  Francis X. Giraldo,et al.  Strong scaling for numerical weather prediction at petascale with the atmospheric model NUMA , 2015, Int. J. High Perform. Comput. Appl..

[17]  N. Wedi,et al.  Increasing horizontal resolution in numerical weather prediction and climate simulations: illusion or panacea? , 2014, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[18]  J. Dudhia.  A Nonhydrostatic Version of the Penn State–NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front , 1993 .

[19]  Pierre Bénard,et al.  Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of the ARPEGE/Aladin NWP system , 1995 .

[20]  Hiroaki Miura,et al.  A Madden-Julian Oscillation Event Realistically Simulated by a Global Cloud-Resolving Model , 2007, Science.

[21]  T. L. Keller,et al.  Implications of the Hydrostatic Assumption on Atmospheric Gravity Waves , 1994 .

[22]  I. Orlanski,et al.  The Circulation Associated with a Cold Front. Part II: Moist Case , 1977 .

[23]  Torsten Hoefler,et al.  Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0 , 2017 .

[24]  T. Hoefler,et al.  Kilometer-Scale Climate Models: Prospects and Challenges , 2020 .

[25]  Shian-Jiann Lin,et al.  DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains , 2019, Progress in Earth and Planetary Science.

[26]  Peter D. Düben,et al.  Single Precision in Weather Forecasting Models: An Evaluation with the IFS , 2017 .

[27]  I. Orlanski.  The Quasi-Hydrostatic Approximation , 1981 .

[28]  Joanna Szmelter,et al.  FVM 1.0: a nonhydrostatic finite-volume dynamical core for the IFS , 2019, Geoscientific Model Development.

[29]  Yong Wang,et al.  The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1 , 2017 .

[30]  Peter D. Düben,et al.  Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware , 2014 .

[31]  Mats Hamrud,et al.  A Fast Spherical Harmonics Transform for Global NWP and Climate Models , 2013 .

[32]  Sophie Valcke,et al.  Crossing the chasm: how to develop weather and climate models for next generation computers? , 2017 .

[33]  William M. Putman,et al.  Global Cloud-Resolving Models , 2019, Current Climate Change Reports.

[34]  C. Bretherton,et al.  Convective self‐aggregation feedbacks in near‐global cloud‐resolving simulations of an aquaplanet , 2015 .

[35]  T. Kato.  Hydrostatic and non-hydrostatic simulations of moist convection: Review and further study , 1997 .

[36]  Pierre Bénard,et al.  Semi‐implicit integration of the unified equations in a mass‐based coordinate: model formulation and numerical testing , 2019, Quarterly Journal of the Royal Meteorological Society.

[37]  T. Palmer,et al.  A personal perspective on modelling the climate system , 2016, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[38]  Chris Snyder,et al.  Atmospheric Kinetic Energy Spectra from Global High-Resolution Nonhydrostatic Simulations , 2014 .

[39]  W. Skamarock,et al.  The resolution dependence of explicitly modeled convective systems , 1997 .

[40]  Daniel Thiemert,et al.  The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale , 2019 .

[41]  Roger Daley,et al.  The normal modes of the spherical non‐hydrostatic equations with applications to the filtering of acoustic modes , 1988 .