Development of the tangent linear and adjoint models of the MPAS-Atmosphere dynamic core and applications in adjoint relative sensitivity studies

References

• Carrier, M. J., Zou, X. and Lapenta, W. M. 2008. Comparing the vertical structures of weighting functions and adjoint sensitivity of radiance and verifying mesoscale forecasts using AIRS radiance observations. Monthly Weather Rev. 136, 1327–1348. doi:10.1175/2007MWR2057.1
   Google Scholar
• Courtier, P., Derber, J., Errico, R., Louis, J. F. J.-F. and Vukicevic, T. 1993. Review of the use of adjoint, variational methods, and Kalman filters in meteorology. Tellus A 45, 342–357. doi:10.3402/tellusa.v45i5.14898
   Google Scholar
• Courtier, P. and Talagrand, O. 1990. Variational assimilation of meteorological observations with the direct and adjoint shallow-water equations. Tellus A 42, 531–549. doi:10.3402/tellusa.v42i5.11896
   Google Scholar
• Courtier, P., Thépaut, J. N. and Hollingsworth, A. 1994. A strategy for operational implementation of 4D‐Var, using an incremental approach. Q. J. Royal Meteorol. Soc. 120, 1367–1387. doi:10.1002/qj.49712051912
   Google Scholar
• Errico, R. M. 1997. What is an adjoint model? Bull. Am. Meteorol. Soc. 78, 2577–2592. doi:10.1175/1520-0477(1997)078<2577:WIAAM>2.0.CO;2
   Google Scholar
• Errico, R. M. and Vukicevic, T. 1992. Sensitivity analysis using an adjoint of the PSU-NCAR mesoseale model. Monthly Weather Rev. 120, 1644–1660. doi:10.1175/1520-0493(1992)120<1644:SAUAAO>2.0.CO;2
   Google Scholar
• Giering, R. and Kaminski, T. 2003. Applying TAF to generate efficient derivative code of Fortran 77‐95 programs. Proc. Appl. Math. Mech. 2, 54–57. doi:10.1002/pamm.200310014
   Google Scholar
• Hagos, S., Leung, R., Rauscher, S. A. and Ringler, T. 2013. Error characteristics of two grid refinement approaches in aquaplanet simulations: MPAS-A and WRF. Monthly Weather Rev. 141, 3022–3036. doi:10.1175/MWR-D-12-00338.1
   Google Scholar
• Jablonowski, C. and Williamson, D. L. 2006a. A Baroclinic Wave Test Case for Dynamical Cores of General Circulation Models: Model Intercomparisons. NCAR Technical Note (NCAR/TN–469 + STR). University Corporation for Atmospheric Research, Boulder, CO, USA.
   Google Scholar
• Jablonowski, C. and Williamson, D. L. 2006b. A baroclinic instability test case for atmospheric model dynamical cores. Q. J. Royal Meteorol. Soc. 132, 2943–2975. doi:10.1256/qj.06.12
   Google Scholar
• Le Dimet, F.-X. and Talagrand, O. 1986. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus A 38, 97–110. doi:10.3402/tellusa.v38i2.11706
   Google Scholar
• Lin, J. W.-B. 2012. Why Python is the next wave in earth sciences computing. Bull. Am. Meteorol. Soc. 93, 1823–1824. doi:10.1175/BAMS-D-12-00148.1
   Google Scholar
• Lutz, M. 2013. Learning Python: Powerful Object-Oriented Programming. 5th ed. O'Reilly Media, Inc. Newton, MA, USA.
   Google Scholar
• Park, S.-H., Skamarock, W. C., Klemp, J. B., Fowler, L. D. and Duda, M. G. 2013. Evaluation of global atmospheric solvers using extensions of the Jablonowski and Williamson baroclinic wave test case. Monthly Weather Rev. 141, 3116–3129. doi:10.1175/MWR-D-12-00096.1
   Google Scholar
• Peterson, P. 2009. F2PY: a tool for connecting Fortran and Python programs. Int. J. Comput. Sci. Eng.. 4, 296–305.
   Google Scholar
• Rabier, F., Courtier, P. and Talagrand, O. 1992. An application of adjoint models to sensitivity analysis. Beitr. Phys. Atmos. 65, 177–192.
   Google Scholar
• Rabier, F., Klinker, E., Courtier, P. and Hollingsworth, A. 1996. Sensitivity of forecast errors to initial conditions. Q. J. Royal Meteorol. Soc. 122, 121–150. doi:10.1002/qj.49712252906
   Google Scholar
• Rauscher, S. A. and Ringler, T. D. 2014. Impact of variable-resolution meshes on midlatitude baroclinic eddies using CAM-MPAS-A. Monthly Weather Rev. 142, 4256–4268. doi:10.1175/MWR-D-13-00366.1
   Google Scholar
• Ringler, T., Ju, L. and Gunzburger, M. 2008. A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations. Ocean Dyn. 58, 475–498. doi:10.1007/s10236-008-0157-2
   Google Scholar
• Satoh, M., Matsuno, T., Tomita, H., Miura, J., Nasuno, T. and co-authors. 2008. Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations. Comput. Phys. 227, 3486–3514. doi:10.1016/j.jcp.2007.02.006
   Google Scholar
• Skamarock, W. C. and Klemp, J. B. 2008. A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. Comput. Phys. 227, 3465–3485. doi:10.1016/j.jcp.2007.01.037
   Google Scholar
• Skamarock, W. C., Klemp, J. B., Duda, M. G., Fowler, L. D., Park, S.-H. and co-authors. 2012. A multiscale nonhydrostatic atmospheric model using centroidal Voronoi tesselations and C-grid staggering. Monthly Weather Rev. 140, 3090–3105. doi:10.1175/MWR-D-11-00215.1
   Google Scholar
• Xiao, Q., Kuo, Y.-H., Ma, Z., Huang, W., Huang, X.-Y. and co-authors. 2008. Application of an adiabatic WRF adjoint to the investigation of the May 2004 McMurdo, Antarctica, severe wind event. Monthly Weather Rev. 136, 3696–3713. doi:10.1175/2008MWR2235.1
   Google Scholar
• Zou, X., Barcilon, A., Navon, I. M., Whitaker, J. and Cacuci, D. G. 1993. An adjoint sensitivity study of blocking in a two-layer isentropic model. Monthly Weather Rev. 121, 2833–2857. doi:10.1175/1520-0493(1993)121<2833:AASSOB>2.0.CO;2
   Google Scholar
• Zou, X. and Kuo, Y. H. 1996. Rainfall assimilation through an optimal control of initial and boundary conditions in a limited-area mesoscale model. Monthly Weather Rev. 124, 2859–2882. doi:10.1175/1520-0493(1996)124<2859:RATAOC>2.0.CO;2
   Google Scholar
• Zou, X., Kuo, Y. H. and Guo, Y. R. 1995. Assimilation of atmospheric radio refractivity using a nonhydrostatic adjoint model. Monthly Weather Rev. 123, 2229–2250. doi:10.1175/1520-0493(1995)123<2229:AOARRU>2.0.CO;2
   Google Scholar
• Zou, X., Vandenberghe, F., Pondeca, M. and Kuo, Y.-H. 1997. Introduction to adjoint techniques and the MM5 adjoint modeling system (No. NCAR/TN-435 + STR). University Corporation for Atmospheric Research..
   Google Scholar