Peer-reviewed publications relevant to MPAS
Gilliam, R. C., J. A. Herwehe, O. R. Bullock Jr, J. E. Pleim, L. Ran, P. C. Campbell, and H. Foroutan, 2021: Establishing the suitability of the Model for Prediction Across Scales for global retrospective air quality modeling. Journal of Geophysical Research: Atmospheres, 126, e2020JD033588.
Tian, X. and X. Zou, 2021: Validation of a Prototype Global 4D-Var Data Assimilation System for the MPAS-Atmosphere Model, Mon. Wea. Rev., 149(8), 2803-2817.
Tian, X. and K. Ide, 2021: Hurricane Predictability Analysis with Singular Vectors of the Multiresolution Global Shallow Water Model, J. Atmos. Sci., 78(4), 1259-1273.
Imberger, M., Larsén, X.G. & Davis, N. Investigation of Spatial and Temporal Wind-Speed Variability During Open Cellular Convection with the Model for Prediction Across Scales in Comparison with Measurements. Boundary-Layer Meteorology (2021). (pdf)
Tian, X., 2020: Evolutions of Errors in the Global Multiresolution Model for Prediction Across Scales - Shallow Water (MPAS-SW), Q. J. Royal Meteorol. Soc., 147, 382-391.
Tian, X. and X. Zou, 2020: Development of the Tangent Linear and Adjoint Models of the MPAS-Atmosphere Dynamic Core and Applications in Adjoint Relative Sensitivity Studies. Tellus A, 71(1), 1-17.
Rios‐Berrios, R., Medeiros, B., & Bryan, G. H. (2020). Mean climate and tropical rainfall variability in aquaplanet simulations using the Model for Prediction Across Scales‐Atmosphere. Journal of Advances in Modeling Earth Systems, 12, e2020MS002102. (pdf)
Fowler, L.D., M.C. Barth, and K. Alapaty, 2020: Impact of scale-aware deep convection on the cloud liquid and ice water paths and precipitation using the Model for Prediction Across Scales (MPASv-5.2). Geosci. Model Dev., 13, 2851-2877, (pdf)
Hsu, L., L. Tseng, S. Hou, B. Chen, and C. Sui, 2020: A Simulation Study of Kelvin Waves Interacting with Synoptic Events during December 2016 in the South China Sea and Maritime Continent. J. Climate, 33, 6345–6359, (pdf)
Judt, F., 2019: Atmospheric Predictability of the Tropics, Middle Latitudes, and Polar Regions Explored through Global Storm-Resolving Simulations. JAS, 77, 257-276. doi: 10.1175/JAS-D-19-0116.1 (pdf)
Michaelis, A. C., G. M. Lackmann, and W. A. Robinson, 2019: Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1. Geosci. Model Dev., 12, 3725-3743. doi: 10.5194/gmd-12-3725-2019 (pdf)
Schwartz, C. S., 2019: Medium-Range Convection-Allowing Ensemble Forecasts with a Variable-Resolution Global Model. Mon. Wea. Rev., 147, 2997-3023. doi: 10.1175/MWR-D-18-0452.1 (pdf)
Skamarock, W. C., C. Snyder, J. B. Klemp, and S-H. Park, 2019: Vertical Resolution Requirements in Atmospheric Simulations. Mon. Wea. Rev., 147, 2641-2656. doi: 10.1175/MWR-D-19-0043.1 (pdf)
Zhao, C., M. Xu, Y. Wang, M. Zhang, J. Guo, Z. Hu, L. R. Leung, M. Duda, and W. Skamarock, 2019: Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics. Geosci. Model Dev., 12, 2707-2726. doi: 10.5194/gmd-12-2707-2019 (pdf)
Bullock Jr., O. R., Foroutan, H., Gilliam, R. C., and Herwehe, J. A., 2018: Adding four-dimensional data assimilation by analysis nudging to the Model for Prediction Across Scales – Atmosphere (version 4.0), Geosci. Model Dev., 11, 2897–2922, (pdf)
Skamarock, W. C., M. G. Duda, S. Ha, and S-H. Park, 2018: Limited-Area Atmospheric Modeling Using an Unstructured Mesh. Mon. Wea. Rev., 146, 3445-3460. doi: 10.1175/MWR-D-18-0155.1 (pdf)
Judt, F., 2018: Insights into Atmospheric Predictability through Global Convection-Permitting Model Simulations. JAS, 75, 1477-1497. doi: 10.1175/JAS-D-17-0343.1 (pdf)
Ha, S., C. Snyder, W. C. Skamarock, J. Anderson, and N. Collins, 2017: Ensemble Kalman Filter Data Assimilation for the Model for Prediction Across Scales (MPAS). Mon. Wea. Rev., 145, 4673-4692. doi: 10.1175/MWR-D-17-0145.1 (pdf)
Huang, C.-Y., Z. You, W. C. Skamarock, and L.-H. Hsu, 2017: Influences of Large-scale Flow Variations on the Track Evolution of Typhoons Morakot (2009) and Megi (2010): Simulations with a Global Variable-Resolution Model. Mon. Wea. Rev., 145, 1691-1716. doi:10.1175/MWR-D-16-0363.1 (pdf)
Ringler, T. D., Saenz, J.A., Wolfram, P.J., and Van Roekel, L., 2017: A Thickness-Weighted Average Perspective of Force Balance in an Idealized Circumpolar Current J. Phys. Oceanogr., 47(2), 285-302. doi:10.1175/JPO-D-16-0096.1 (pdf)
Wolfram, P. J. and Ringler, T. D., 2017: Quantifying Residual, Eddy, and Mean Flow Effects on Mixing in an Idealized Circumpolar Current J. Phys. Oceanogr., 47(8), 1897-1920. doi:10.1175/JPO-D-16-0101.1 (pdf)
Davis, C. A., D. A. Ahijevych, W. Wang, and W. C. Skamarock, 2016: Evaluating medium-range tropical cyclone forecasts in uniform- and variable-resolution global models. Monthly Weather Review, 144, 4141-4160, doi:10.1175/MWR-D-16-0021.1. (pdf)
Wong, M. and W. C. Skamarock, 2016: Spectral characteristics of convective-scale precipitation observations and forecasts, Mon. Wea. Rev., 144, 4183-4196, doi:10.1175/MWR-D-16-0183.1 (pdf)
Zhao, C., L. R. Leung, S.-H. Park, S. Hagos, J. Lu, K. Sakaguchi, J. Yoon, B. E. Harrop, W. Skamarock, and M. G. Duda, 2016: Exploring the impacts of physics and resolution on aqua-planet simulations from a nonhydrostatic global variable-resolution modeling framework. JAMES, 8 (4), 1751-1768. doi:10.1002/2016MS000727 (pdf)
Pilon, R., C. Zhang, and J. Dudhia, 2016: Roles of deep and shallow convection and microphysics in the MJO simulated by the Model for Prediction Across Scales, J. Geophys. Res. Atmos., 121, 10,575–10,600, doi:10.1002/2015JD024697. (pdf)
Fowler, L. D., W. C. Skamarock, G. A. Grell, S. R. Freitas, and M. G. Duda, 2016: Analyzing the Grell–Freitas Convection Scheme from Hydrostatic to Nonhydrostatic Scales within a Global Model. Mon. Wea. Rev., 144, 2285–2306. doi:10.1175/MWR-D-15-0311.1 (pdf)
Heinzeller, D., M.G. Duda, and H. Kunstmann, 2016: Towards convection-resolving, global atmospheric simulations with the Model for Prediction Across Scales (MPAS) v3.1: an extreme scaling experiment. Geosci. Model Dev., 9, 77-110, 2016, doi:10.5194/gmd-9-77-2016 (pdf)
Klemp, J. B., W. C. Skamarock, and S.-H. Park (2015), Idealized global nonhydrostatic atmospheric test cases on a reduced-radius sphere, J. Adv. Model. Earth Syst., 7, 1155–1177, doi:10.1002/2015MS000435. (pdf)
Martini, M. N., W. I. Gustafson Jr., T. O'Brien, and P.-L. Ma (2015), Evaluation of tropical channel refinement using MPAS-A aquaplanet simulations, J. Adv. Model. Earth Syst., 7, 1351–1367, doi:10.1002/2015MS000470 (pdf)
Sandbach, S., J. Thuburn, D. Vassilev, and M. G. Duda, 2015: A Semi-Implicit Version of the MPAS-Atmosphere Dynamical Core. Mon. Wea. Rev., 143, 3838–3855. doi:10.1175/MWR-D-15-0059.1 (pdf)
Sakaguchi, K., L. R. Leung, C. Zhao, Q. Yang, J. Lu, S. Hagos, S. A. Rauscher, L. Dong, T. D. Ringler, and P. H. Lauritzen, 2015: Exploring a Multiresolution Approach Using AMIP Simulations. J. Climate, 28, 5549-5574. doi:10.1175/JCLI-D-14-00729.1 (pdf)
Hagos, S., L. R. Leung, Q. Yang, C. Zhao, and J. Lu, 2015: Resolution and Dynamical Core Dependence of Atmospheric River Frequency in Global Model Simulations. J. Climate, 28, 2764-2776. doi:10.1175/JCLI-D-14-00567.1 (pdf)
Wolfram, P. J., Ringler, T. D., Maltrud, M. E., Jacobsen, D. W., Petersen, M. R., 2015: Diagnosing isopycnal diffusivity in an eddying, idealized midlatitude ocean basin via Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). J. Phys. Oceanogr., 45(8), 2114-2133. doi:10.1175/JPO-D-14-0260.1 (pdf)
Atmospheric kinetic energy spectra from global high-resolution nonhydrostatic simulations. Skamarock, W. C., S.-H. Park, J. B. Klemp, and C. Snyder, 2014, J. Atmos. Sci., 71(11), 4369-4381. doi:10.1175/JAS-D-14-0114.1 (pdf)
A Comparison of Mesh Refinement in the Global MPAS-A and WRF Models Using an Idealized Normal-Mode Baroclinic Wave Simulation. Park, S.-H., J. B. Klemp and W. C. Skamarock, 2014, Mon. Wea. Rev., 142, 3614-3634. doi:10.1175/MWR-D-14-00004.1 (pdf)
Impact of Variable-Resolution Meshes on Midlatitude Baroclinic Eddies Using CAM-MPAS-A. Rauscher, S. A., & Ringler, T. D., 2014, Monthly Weather Review, 142(11), 4256–4268. doi:10.1175/MWR-D-13-00366.1 (pdf)

Visualizing Large 3D Geodesic Grid Data with Massively Distributed GPUs. J. Xie, H, Yoy, K. Ma. IEEE Symposium on Large Data Analysis and Visualization 2014 October 9–10, Paris, France

The Dependence of ITCZ Structure on Model Resolution and Dynamical Core in Aquaplanet Simulations. Landu, K., Leung, L. R., Hagos, S., Vinoj, V., Rauscher, S. A., Ringler, T., & Taylor, M., 2014, Journal of Climate, 27(6), 2375–2385. doi:10.1175/JCLI-D-13-00269.1 (pdf)
Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations. Yang, Q., Leung, L. R., Rauscher, S. A., Ringler, T. D., & Taylor, M. A., 2014, Journal of Climate, 27(10), 3565–3581. doi:10.1175/JCLI-D-13-00468.1 (pdf)
Evaluation of global atmospheric solvers using extensions of the Jablonowski and Williamson baroclinic wave test case. S.-H. Park, W. Skamarock, J. Klemp, L. Fowler, and M. Duda, 2013, Mon. Wea. Rev., 141, 3116-13129, doi:10.1175/MWR-D-12-00096.1 pdf

A Multi-Resolution Approach to Global Ocean Modeling. Ringler, T., Petersen, M., Higdon, R. L., Jacobsen, D., Jones, P. W., & Maltrud, M. (2013). Ocean Modelling. Ocean Modelling, 69(C), 211–232. doi:10.1016/j.ocemod.2013.04.010 (pdf)


Jacobsen, D. W., Gunzburger, M., Burkardt, J., & Peterson, J. (2013). Parallel algorithms for planar and spherical Delaunay construction with an application to centroidal Voronoi tessellations. Geoscientific Model Development Discussions, 6(1), 1427–1466. doi:10.5194/gmdd-6-1427-2013 (pdf)

Unified Matching Grids for Multidomain Multiphysics Simulations. Womeldorff, G., Peterson, J., Gunzburger, M., & Ringler, T. (2013), SIAM Journal on Scientific Computing, 35(6), A2781–A2806. doi:10.1137/130906611 (pdf)
A hierarchical evaluation of regional climate simulations. L Ruby Leung, Todd Ringler, William D Collins, Mark Taylor, Moetasim Ashfaq, Eos, Transactions American Geophysical Union, 94 (34) (pdf)

Error Characteristics of Two Grid Refinement Approaches in Aquaplanet Simulations: MPAS-A and WRF. Hagos, S., Leung, R., Rauscher, S. A., & Ringler, T., 2013, 141(9), 3022–3036. doi:10.1175/MWR-D-12-00338.1 (pdf)



Exploring a Global Multi-Resolution Modeling Approach Using Aquaplanet Simulations. S. Rauscher, T. Ringler, W. Skamarock, and A. Mirin, 2012, J. Climate., 26, 2432-2452, doi:10.1175/JCLI-D-12- 00154.1 pdf
A Multi-scale Nonhydrostatic Atmospheric Model Using Centroidal Voronoi Tesselations and C-Grid Staggering. William C. Skamarock, Joseph B. Klemp, Michael G. Duda, Laura Fowler, Sang-Hun Park, and Todd D. Ringler. 2012 Monthly Weather Review, 240, 3090-3105, doi:10.1175/MWR-D-11-00215.1 pdf
A Terrain-Following Coordinate with Smoothed Coordinate Surfaces. Joseph B. Klemp, 2011, Monthly Weather Review, 139(7), 2163–2169. doi:10.1175/MWR-D-10-05046.1
Conservative Transport Schemes for Spherical Geodesic Grids: High-Order Flux Operators for ODE-Based Time Integration. W. Skamarock and A. Gassmann, 2011, Monthly Weather Review, Vol. 139, pp. 2962-2975, doi:10.1175/MWR-D-10-05056.1 pdf
Exploring a Multi-Resolution Modeling Approach within the Shallow-Water Equations. Ringler, T., D.W. Jacobsen, M. Gunzburger, L. Ju, M. Duda and W. Skamarock, 2011, Monthly Weather Review, DOI: 10.1175/MWR-D-10-05049.1
Ringler, T., J. Thuburn, J. Klemp and W. Skamarock, 2010: A unified approach to energy conservation and potential vorticity dynamics on arbitrarily structured C-grids, Journal of Computational Physics, published online, doi:10.1016/
Ju, L., T. Ringler and M. Gunzburber, 2010, Voronoi Diagrams and Application in Climate and Global Modeling, Numerical Techniques for Global Atmospheric Models, Lecture Notes in Computational Science, draft. pdf
Thuburn, J., T. Ringler, J. Klemp and W. Skamarock, 2009: Numerical representation of geostrophic modes on arbitrarily structured C-grids, Journal of Computational Physics, 2009: 228 (22), 8321-8335. doi:10.1016/
Ringler, T., L. Ju and M. Gunzburger, 2008, A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations, Ocean Dynamics, 58 (5-6), 475-498. doi:10.1007/s10236-008-0157-2
Du, Q., M. Gunzburger and L. Ju, 2003, Constrained centroidal Voronoi tessellations for surfaces, SIAM Journal on Scientific Computing, 24, 1488-1506. doi:10.1137/S1064827501391576
Du, Q., M. Gunzburger, L. Ju, 2003, Voronoi-based finite volume methods, optimal Voronoi meshes, and PDEs on the sphere, Computer Methods in Applied Mechanics and Engineering, 2003, 192, 3933-3957. doi:10.1016/S0045-7825(03)00394-3
Ju, L., Q. Du and M. Gunzburger, 2002, Probabilistic methods for centroidal Voronoi tessellations and their parallel implementations, Parallel Computing, 28, 1477-1500. doi:10.1016/S0167-8191(02)00151-5
Du, Q., V. Faber and M. Gunzburger, 1999, Centroidal Voronoi tessellations: Applications and algorithms, SIAM Review, 41, 637-676. doi:10.1137/S0036144599352836

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