LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Nunes, A. M. B.; Cocke, S. (2004)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Subjects:
In this paper we describe the implementation of a physical initialization procedure in the recently developed Florida State University nested regional spectral model, and its impact on short-term forecasting over South America. Because the regional model forecasts perturbations to the global model results, we seek to determine the impact of the boundary condition on the regional model assimilation. The regional model is able to assimilate the satellite-derived rain rates rather well, regardless of whether the global model, providing the boundary conditions, has been physically initialized. The regional model is able to assimilate higher-resolution precipitation data, and also the global model assimilates coarser resolution data as reported in earlier studies. Ten experiments are performed over the northern part of South America during the tropical rainy season of January and February 1999. The initial correlation coefficients of the rain rates exceed 0.9 for all physically initialized cases. The subsequent 24-h forecast is also improved, as measured by spatial correlation coefficients and equitable threat scores.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Anthes, R. A. 1974. Data assimilation and initialization of hurricane prediction models. J. Atmos. Sci. 31, 702-719.
    • Anthes, R. A., Hsie, E.-Y. and Kuo, Y.-H. 1987. Description of the Penn State/NCAR Mesoscale Model Version 4 (MM4). NCAR Technical Note NCAR/TN-282+STR. Boulder, CO, USA, 66 pp.
    • Aonashi, K. 1993. An initialization method to incorporate precipitation data into a mesoscale numerical weather prediction model. J. Meteorol. Soc. Japan 71, 393-406.
    • Arakawa, A. and Schubert, W. H. 1974. Interaction of cumulus cloud ensemble with the large-scale environment. J. Atmos. Sci. 31, 674- 701.
    • Arkin, P. A. 1979. The relationship between fractional coverage of high cloud and rainfall accumulation during GATE over the B-scale array. Mon. Wea. Rev. 107, 1382-1387.
    • Baer, F. and Tribbia, J. J. 1977. On complete filtering of gravity modes through nonlinear initialization. Mon. Wea. Rev. 105, 1536-1539.
    • Cocke, S. 1998. Case study of Erin using the FSU Nested Regional Spectral Model. Mon. Wea. Rev. 126, 1337-1346.
    • Cocke, S. and LaRow, T. E. 2000. Seasonal predictions using a regional spectral model embedded within a coupled ocean-atmosphere model. Mon. Wea. Rev. 128, 689-708.
    • Daley, R. 1991. Atmospheric data analysis (eds. J. T. Houghton, M. J. Rycroft andA. J. Dessler). Cambridge Univ. Press, Cambridge, 457 pp.
    • Donner, L. J. 1988. An initialization for cumulus convection in numerical weather prediction models. Mon. Wea. Rev. 116, 377-385.
    • Ferraro, R. R. and Marks, G. F. 1995. The development of SSM/I rainrate retrieval algorithms using ground-based radar measurements. J. Atmos. Oceanic Technol. 12, 755-770.
    • Fillion, L. and Errico, R. 1997. Variational assimilation of precipitation data using moist convective parametrization schemes: A 1D-Var study. Mon. Wea. Rev. 125, 2917-2942.
    • Gairola, R. M. and Krishnamurti, T. N. 1992. Rain rates based on SSM/I, OLR and raingauge data sets. Meteorol. Atmos. Phys. 50, 165-174.
    • Haase, G., Crewell, S., Simmer, C. and Wergen, W. 2000. Assimilation of radar data in mesoscale models: physical initialization and latent heat nudging. Phys. Chem. Earth (B) 25, 1237-1242.
    • Hamming, R. W. 1989. Digital filters. Prentice-Hall, Englewood Cliffs, NJ, 284 pp.
    • Heckley, W. A., Kelly, G. and Tiedtke, M. 1990. On the use of satellitederived heating rates for data assimilation within the tropics. Mon. Wea. Rev. 118, 1743-1757.
    • Hoke, J. E. and Anthes, R. A. 1976. The initialization of numerical models by dynamic initialization technique. Mon. Wea. Rev. 104, 1551- 1556.
    • Hou, A. Y., Ledvina, D. V., Da Silva, A. M., Zhang, S. Q., Joiner, J. and Atlas, R. M. 2000. Assimilation of SSM/I-derived surface rainfall and total precipitation water for improving the GEOS analysis for climate studies. Mon. Wea. Rev. 128, 509-537.
    • Huang, X. Y. and Lynch, P. 1993. Diabatic digital-filtering initialization - application to the HIRLAM model. Mon. Wea. Rev. 121, 589-603.
    • Huang, X. Y., Cederskov, A. and Kallen, E. 1994. A comparison between digital filtering initialization and nonlinear normal-mode initialization in a data assimilation system. Mon. Wea. Rev. 122, 1001-1015.
    • Kanamitsu, M. 1975. On numerical prediction over a global tropical belt. Report No. 75-1, 282 pp. (Available from the Dept. of Meteorology, FSU, Tallahassee, FL, USA.)
    • Kanamitsu, M., Wesley, E., Woollen, S.-K. Yang, Hnilo, J. J., Fiorino, M. and Potter, G. L. 2002. NCEP-DOE AMIP-II reanalysis (R-2). Bull. Am. Meteorol. Soc. 83, 1631-1643.
    • Kasahara, A., Mizze, A. P. and Donner, L. J. 1994. Diabatic initialization for improvement in the tropical analysis of divergence and moisture using satellite radiometric imagery data. Tellus 46A, 242-264.
    • Kitade, T. 1983. Non-linear normal mode initialization with physics. Mon. Wea. Rev. 11, 2194-2213.
    • Krishnamurti, T. N., Low-Nam, S. and Pasch, R. 1983. Cumulus parametrization and rainfall rates II. Mon. Wea. Rev. 111, 815-828.
    • Krishnamurti, T. N., Ingles, K., Cocke, S., Pasch, R. and Kitade, T. 1984. Details of low latitude medium range numerical weather prediction using a global spectral model II. Effect of orography and physical initialization. J. Meteorol. Soc. Japan 62, 613-649.
    • Krishnamurti, T. N., Bedi, H. S., Heckley, W. and Ingles, K. 1988. Reduction of the spinup time for evaporation and precipitation in a spectral model. Mon. Wea. Rev. 116, 907-920.
    • Krishnamurti, T. N., Xue, J., Bedi, H. S., Ingles, K. and Oosterhof, D. 1991. Physical initialization for numerical weather prediction over the tropics. Tellus 43AB, 53-81.
    • Krishnamurti, T. N., Bedi, H. S. and Ingles, K. 1993. Physical initialization using SSM/I rain rates. Tellus 45A, 247-269.
    • Krishnamurti, T. N., Rohaly, G. D. and Bedi, H. S. 1994. On the improvement of precipitation forecast skill from physical initialization. Tellus 46A, 598-614.
    • Krishnamurti, T. N., Bhowmik, S. K. R., Oosterhof, D. and Rohaly, G. D. 1995. Mesoscale signatures within the tropics generated by physical initialization. Mon. Wea. Rev. 123, 2771-2790.
    • Kuo, H. L. 1974. Further studies of the parametrization of the influence of cumulus convection on large-scale flow. J. Atmos. Sci. 31, 1232-1240.
    • Lewis, J. M. and Deber, J. C. 1985. The use of adjoint equation to solve variational adjustment problem with advective constraints. Tellus 37A, 309-322.
    • Lynch, P. and Huang, X. Y. 1992. Initialization of the HIRLAM model using a digital-filter. Mon. Wea. Rev. 120, 1019-1034.
    • Lynch, P. and Huang, X. Y. 1994. Diabatic initialization using recursive filters. Tellus 46A, 583-597.
    • Lynch, P., Giard, D. and Ivanovici, V. 1997. Improving the efficiency of a digital filtering scheme for diabatic initialization. Mon. Wea. Rev. 125, 1976-1982.
    • Machenhauer, B. 1976. An initialization procedure based on the elimination of gravity oscillations in a spectral barotropic primitive equation model. Ann. Meteorol. 11, 135-138.
    • Machenhauer, B. 1977. On the dynamics of gravity oscillations in a shallow water model with applications to normal mode initialization. Beitr. Phys. Atmos. 50, 253-271.
    • Manobianco, J., Koch, S., Karayampudi, V. M. and Negri, A. J. 1994. The impact of assimilating satellite-derived precipitation rates on numerical simulations of the ERICA IOP 4 cyclone. Mon. Wea. Rev. 122, 341-365.
    • Mare`cal, V. and Mahfouf, J.-F. 2000. Variational retrieval of temperature and humidity profiles from TRMM precipitation data. Mon. Wea. Rev. 128, 3853-3866.
    • Navon, I. M., Zou, X., Derber, J. and Sela, J. 1992. Variational data assimilation with an adiabatic version of the NMC spectral model. Mon. Wea. Rev. 120, 1433-1446.
    • Nunes, A. M. B. 2001. Assimilation of rain rates using satellite data by a regional spectral model. Proc. 9th Conference on Mesoscale Processes, Fort Lauderdale, FL, USA, 226-227.
    • Nunes, A. M. B. 2002. Physical initialization in weather prediction models and a study of its effects on the energy partition in the vertical and horizontal modes over the tropics and South America. (In Portuguese). PhD Thesis. Available from INPE, S. J. Campos, SP, Brazil, 220 pp.
    • Pan, H.-L. and Wu, W. S. 1994. Implementing a mass flux convection parametrization package for the NMC MRF model. Proc. 10th Conference on Numerical Weather Prediction, Portland, OR. American Meteorological Society, Washington, DC, 96-98.
    • Polavarapu, S., Tanguay, M. and Fillion, L. 2000. Four-dimensional variational data assimilation with digital filter initialization. Mon. Wea. Rev. 128, 2491-2510.
    • Puri, K. and Miller, M. J. 1990. The use of satellite data in the specification of convective heating for diabatic initialization and moisture adjustment in numerical weather prediction. Mon. Wea. Rev. 118, 67- 93.
    • Puri, K. and Davidson, N. E. 1992. The use of infrared satellite cloud imagery as proxy data for moisture and diabatic heating in data assimilation. Mon. Wea. Rev. 120, 2329-2341.
    • Ramamurthy, M. K. and Carr, F. H. 1987. Four-dimensional data assimilation in the monsoon region. Part I: Experiments with wind data. Mon. Wea. Rev. 115, 1678-1706.
    • Sasaki, Y. 1970. Numerical variational analysis with weak constraint and application to surface analysis of severe storm gust. Mon. Wea. Rev. 98, 899-910.
    • Schaefer, J. T. 1990. The critical success index as an indicator of warning skill. Wea. Forecasting 5, 570-575.
    • Treadon, R. E. 1996. Physical initialization in the NMC global data assimilation system. Meteorol. Atmos. Phys. 60, 57-86.
    • Tsuyuki, T. 1997. Variational data assimilation in the tropics using precipitation data. Part III: Assimilation of SSM/I precipitation rates. Mon. Wea. Rev. 125, 1447-1464.
    • Williamson, D. L. 1976. Normal mode initialization procedure applied to forecasts with the global shallow water equations. Mon. Wea. Rev. 104, 195-206.
    • Williamson, D. L. and Temperton, C. 1981. Normal mode initialization for a multilevel grid-point model. Part II: Non-linear aspects. Mon. Wea. Rev. 109, 745-757.
    • Yap, K. -S. 1995. Impact of Newtonian assimilation and physical initialization on the initialization and prediction by a tropical mesoscale model. Mon. Wea. Rev. 123, 833-861.
    • Zou, X. and Kuo, Y.-H. 1996. Rainfall assimilation through an optimal control of initial and boundary conditions in a limited-area mesoscale model. Mon. Wea. Rev. 124, 2859-2882.
    • Zˇ upanski, D. and Mesinger, F. 1995. Four-dimensional variational assimilation of precipitation data. Mon. Wea. Rev. 123, 1112- 1127.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article

Collected from