Development of the upgraded tangent linear and adjoint of the weather research and forecasting (WRF) model

Journal of Atmospheric and Oceanic Technology

Volumn 30, Issue 6, 2013, Pages 1180-1188

  Zhang, Xin ^a   Huang, Xiang Yu ^a   Pan, Ning ^b  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^b Fujian Meteorological Bureau   (China)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC DIFFERENTIATIONS; COMMUNICATION OPERATION; FORECAST SENSITIVITY; FOUR-DIMENSIONAL VARIATIONAL DATA ASSIMILATION; MESSAGE PASSING INTERFACE COMMUNICATIONS; PARALLEL EFFICIENCY; SOFTWARE DEVELOPMENT CYCLES; WEATHER RESEARCH AND FORECASTING MODELS;

COMMUNICATION; RESEARCH;

WEATHER FORECASTING;

DATA ASSIMILATION; LINEARITY; NUMERICAL MODEL; SOFTWARE; WEATHER FORECASTING;

EID: 84880712762     PISSN: 07390572     EISSN: 15200426     Source Type: Journal    
DOI: 10.1175/JTECH-D-12-00213.1     Document Type: Article

References (21)

1. Barker, D., and Coauthors, 2012: The Weather Research and Forecasting model's community variational/ensemble data assimilation system: WRFDA. Bull. Amer. Meteor. Soc., 93, 831-843.
2. Cheng, B., 2006: A duality between forward and adjoint MPI communication routines. Comput. Methods Sci. Technol., 12, 23-24. [Available online at http://www.man.poznan.pl/cmst/2005/las/03-Cheng-Gra.pdf.
3. Errico, R. M., 1997: What is an adjoint model? Bull. Amer. Meteor. Soc., 78, 2577-2591.
4. Errico, R. M., and T. Vukicevic, 1992: Sensitivity analysis using an adjoint of the PSU-NCAR mesoscale model. Mon. Wea. Rev., 120, 1644-1660.
5. Gilmour, I., L. Smith, and R. Buizza, 2001: Linear regime duration: Is 24 hours a long time in synoptic weather forecasting? J. Atmos. Sci., 58, 3525-3539.
6. Hascoët, L., and V. Pascual, 2004: TAPENADE 2.1 user's guide. INRIA Tech. Rep. 0300, 78 pp. [Available online at http://hal. inria.fr/docs/00/06/98/80/PDF/RT-0300.pdf.]
7. Huang, X.-Y., and Coauthors, 2009: Four-dimensional variational data assimilation for WRF: Formulation and preliminary results. Mon. Wea. Rev., 137, 299-314.
8. Kleist, D. T., and M. C. Morgan, 2005a: Application of adjointderived forecast sensitivities to the 24-25 January 2000 U.S. East Coast snowstorm. Mon. Wea. Rev., 133, 3148-3175.
9. Kleist, D. T.,and M. C. Morgan,2005b: Interpretation of the structure and evolution of adjoint-derived forecast sensitivity gradients. Mon. Wea. Rev., 133, 466-484.
10. Langland, R. H., R. Gelaro, G. D. Rohaly, and M. A. Shapiro, 1999: Target observations in FASTEX: Adjoint-based targeting procedures and data impact experiments in IOP17 and IOP18. Quart. J. Roy. Meteor. Soc., 125, 3241-3270.
11. Li, Z., A. Barcilon, and I. M. Navon, 1999: Study of block onset using sensitivity perturbations in climatological flows. Mon. Wea. Rev., 127, 879-900.
12. Michalakes, J., and D. Schaffer, 2004: WRF tiger team documentation: The registry. UCAR Tech. Rep., 17 pp. [Available online at http://www.mmm.ucar.edu/wrf/WG2/software_2.0/registry_schaffer.pdf.]
13. Navon, I. M., X. Zou, J. Derber, and J. Sela, 1992: Variational data assimilation with an adiabatic version of the NMC spectral model. Mon. Wea. Rev., 120, 1433-1446.
14. Rabier, F., E. Klinker, P. Courtier, and A. Hollingsworth, 1996: Sensitivity of forecast errors to initial conditions. Quart. J. Roy. Meteor. Soc., 122, 121-150.
15. Skamarock, W. C., and Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/ TN-4751STR, 113 pp. [Available from UCAR at 360 Communications, P.O. Box 3000, Boulder, CO 80307-3000.]
16. Utke, J., L. Hascoët, P. Heimbach, C. Hill, P. Hovland, and U. Naumann, 2009: Toward adjoinable MPI. Proc. 10th IEEE Int. Workshop on Parallel and Distributed Scientific and Engineering (PDSEC'09), Rome, Italy, IEEE, 8 pp. [Available online at http://www-sop.inria.fr/tropics/papers/Utke2009TAM.pdf.]
17. Vukicevic, T., 1991: Nonlinear and linear evolution of initial forecast errors. Mon. Wea. Rev., 119, 1602-1611.
18. Xiao, Q., X. Zou, M. Pondeca, M. A. Shapiro, and C. S. Velden, 2002: Impact of GMS-5 and GOES-9 satellite-derived winds on the prediction of a NORPEX extratropical cyclone. Mon. Wea. Rev., 130, 507-528.
19. Xiao, Q., and Coauthors, 2008: Application of an adiabatic WRF adjoint to the investigation of the May 2004 McMurdo, Antarctica, severe wind event. Mon. Wea. Rev., 136, 3696-3713.
20. Zhang, X., and X. Y. Huang, 2013: Development of GSI-based WRF 4DVAR system. Preprints, 17th Conf. on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface, Austin, TX, Amer. Meteor. Soc., 4A.2. [Available online at https://ams.confex.com/ams/93Annual/webprogram/Paper217182.html.]
21. Zhang, X., and X. Y. Huang, J. Liu, and J. Poterjoy, 2013: Development of an efficient regional four-dimensional variational data assimilation system for WRF. J. Atmos. Oceanic Technol., submitted.