MM5伴随模式中云导风的同化对调整模式参数的试验研究
|
摘要
本文详细介绍了以变分法为基础，以伴随码技术为核心的MM5伴随模式，并将常规资料和非常规资料应用于该模式进行了同化问题的研究。该研究是用一个个例进行对比分析，我们选用1998年7月29日00时至30日00时发生于长江流域的一次暴雨过程。对比研究结果表明，MM5伴随模式能有效同化常规观测资料，调整初始场。使用调整后的初始场对降水及其它物理量场的预报均有所改善。其次进行了将MM5伴随模式用于修正模式地形参数的试验研究。利用MM5伴随模式对常规资料和非常规资料云导风进行同化，通过不同的试验研究，结果发现，在伴随模式中加入非常规资料云导风能够比仅使用常规资料更有效地修正模式地形参数，将此地形场作为模式地形所做预报结果比只使用常规资料能够有效改善。
In this paper, the MM5 adjoint-model that is based on variational method with adjoint codes technique as the core is introduced, on the basis of which, conventional observation data and unconventional observation data is applied into this Assimilation System for the purpose of assimilation research. First, choosing the conventional data of the heavy rain case that occurred in the Yangtze river drainage basin on July 29th, 1998 and putting it into the Assimilation System to study the assimilation effect. The result shows that the MM5 Adjoint-model Assimilation System can effectively assimilate the conventional data and adjust the initial field. The forecasting of meteorological element fields and precipitation is improved by use of the adjusted initial field. Second, the experiments of modifying the terrain parameter by means of the MM5 Adjoint-model Assimilation System are carried out. In these experiments, conventional observation data and unconventional data (cloud-derived wind) is used. By comparison
of the results of different experiments, it is known that the using of unconventional data in the adjoint assimilation model will correct the topography more effectively than using only the conventional observation data. The forecasting conducted on the basis of this terrain field can be improved by contrast to the results using only conventional data.
In this paper, the MM5 adjoint-model that is based on variational method with adjoint codes technique as the core is introduced, on the basis of which, conventional observation data and unconventional observation data is applied into this Assimilation System for the purpose of assimilation research. First, choosing the conventional data of the heavy rain case that occurred in the Yangtze river drainage basin on July 29th, 1998 and putting it into the Assimilation System to study the assimilation effect. The result shows that the MM5 Adjoint-model Assimilation System can effectively assimilate the conventional data and adjust the initial field. The forecasting of meteorological element fields and precipitation is improved by use of the adjusted initial field. Second, the experiments of modifying the terrain parameter by means of the MM5 Adjoint-model Assimilation System are carried out. In these experiments, conventional observation data and unconventional data (cloud-derived wind) is used. By comparison
of the results of different experiments, it is known that the using of unconventional data in the adjoint assimilation model will correct the topography more effectively than using only the conventional observation data. The forecasting conducted on the basis of this terrain field can be improved by contrast to the results using only conventional data.
引文
1．廖洞贤，王两铭．数值天气预报原理及其应用．气象出版社，1986：367．
2. Cressmen G P. An operational objective analysis system. Mon Wea Rev, 1959, 87(7): 367～374.
3. Lorence A C. A global three-dimensional multivariate statistical interpolation scheme. Mon Wea Rev, 1981, 109(3): 701～721.
4. Sasaki Y. An objective analysis based on variational method. J Meteor Soc Japan, 1958, 36(3):77～88.
5. Sasaki Y. Some basic formalisms in numerical variational analysis. Mon Wea Rev, 1970, 98(12):875～883.
6. LeDimet F X, Talagrand O. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus, 1986, 38A(2):97～110.
7. Sasaki Y. Numerical variational analysis formulated under the constraints as determined by longwave equations and a low-pass filter. Mon Wea Rev, 1970, 98(12):884～898.
8. Sasaki Y. Numerical variational analysis with weak constraint and application to surface analysis of severe storm gust. Mon Wea Rev, 1970, 98(12):899～910.
9. Lewis J M, Derber J C. The use of adjoint equations to solve a variational adjustment problem with advective constrains. Tellus, 1985, 37A(4):309～322
10. Derber J. C. Variational four-dimensional analysis using quasi-geostrophie constraints. Mon. Wea. Rev. 1987, 115(5):998～1008.
11. Courtier P. and Talagrand O. Variational assimilation of meteorological observations with the direct and adjoint shallow-water equations Tellus, 1990, 42A(5):531～549.
12. Thepaut J N, Courtier P. Four dimension variational assimilation using the adjoint of a multilevel equation model. Quart J R Meteo Soc, 1991, 117(5): 1225～1254.
13. Navon I M, Zou X, Derber J et al. Variational data assimilation with an adiabatic version of the NMC spectral model. Mon Wea Rev, 1992, 120(7):1433～1446.
14. Winston C C, Chang L P. Development of a four-dimension variational analysis system using the adjoint method at GLA. part Ⅰ: Dynamic. Mon Wea
Rev, 1992, 120(8): 1661～1673.
15. Zou X., Kuo H., Guo Y. R. Assimilation of atmosphere radio refractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev., 1995, 123(7):2229～2247.
16. Zou X, Navon I M, Sela J G. Variational data assimilation with moist threshold process using the NMC spectral model. Tellus, 1993, 45A(5): 370～387.
17. Dusanka Z, Fedor M. Four-dimension variational assimilation of precipitation data. Mon Wea Rev, 1995, 123(4): 1112～1127.
18. Holt T R, Chang S W. Impact of SSM/I precipitable water assimilation on mesoscale simulations of the ERICA IOP4 cyclone. Preprints 10 th conf on numerical weather prediction Amer Meteo Soc, 1994(2): 164～186.
19. Zou X. Rainfall assimilation through an optimal control of initial and boundary conditions in a limited-area mesoscale model. Mon Wea Rev, 996, 124(12):2859～2882.
20. Kuo Y H, Zou X, Guo Y R. Variational assimilation of precipitable using a nonhydrostatic mesoscale adjoint model. Part Ⅰ: moisture retrieval and sensitivity experiments. Mon Wea Rev, 1996, 124(1): 122～147.
21. Wu X H. Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and colunm cloud liquid water amounts. Mon Wea Rev, 1995, 123(2):347～365.
22. Fillion L, Ronald M E. Variational assimilation of precipitation data using moist convective parameterization schemes: AID-Var study. Mon Wea Rev, 1997, 125(11 ):2917～2942.
23. Andrew S, Jones I C C, Thomas H. Data assimilation of satellite-derived heating rates as proxy surface wetness data into a regional atmospheric mesoscale model.Part Ⅰ: Meteorology. Mon Wea Rev, 1998, 26(3):634～645.
24. Cacucci D G. Sensitivity theory for nonlinear system. Ⅰ: Nonlinear functional analysis approach. J Math Phys, 1981, 22(12):2794～2802.
25. Derber J C. A variational continuous assimilation technique. Mon Wea Rev, 1989, 117(11):2437～2446.
26. Ronald M E, Tomislava V. Sensitivity analysis using an adjoint of the PSU-NCAR Mesoscale Model. Mon Wea Rev, 1992, 120 (8): 1644～1660.
27. Bao J W, Ronald M E. An adjoint examination of a nudging method for data assimilation.
Mon Wea Rev, 1997, 125(6):1355～1373.
28. Pu Z X. Sensitivity of forecast errors to initial conditions with a quasi-inverse linear method. Mon Wea Rev, 1997, 125(10):2479～2503.
29. Nils G, Xiang Y. Sensitivity experiments with spectral HIRLAM and its adjoint. Tellus, 1996, 48A(4): 501～517.
30. David R S, Bao J W. Optimal determination of nudging coefficients using the adjoint equations. Tellus, 1993, 45A(5):358～369.
31．郜吉东，丑纪范．数值天气预报中的两类反问题及一种数值解法——理想试验．气象学报，1994，52(2)：129～139
32．龚建东，邱崇践，王强，陈伟民．区域四维变分资料同化的数值试验．气象学报，1999，57(2)：131～142
33．蒲朝霞，丑纪范．对中尺度遥感资料进行四维同化的共轭方法及数值研究．高原气象，1994，13(4)：419～429
34．邱崇践．变分四维同化方法中的不连续问题．兰州大学学报 (自然科学版)，1997，33(1)：115～119
35．陈子通，沈桐立，丁一汇，孙麟平．中尺度数值模式的资料同化系：(一)伴随模式的设计．南京气象学院学报，1998，21(2)：165～172
36．沈桐立，陈子通，丁一汇，孙麟平．中尺度数值模式的资料同化系：(二)伴随模式系统的检验和试验．南京气象学院学报，1998，21(2)：173～180
37．冯伍虎，邱崇践．变分四维同化方法若干问题的数值试验．高原气象，1999，18(2)：138～146
38．李晓莉，沈桐立，孙麟平．中尺度模式的四维伴随同化系统及其同化试验．南京气象学院学报，2002，25(1)：36-44
39．王栋梁，沈桐立．中尺度模式MM5的四维变分资料同化系统．南京气象学院学报，2002，25(5)：603-610
40. Purl R., Miller M. J. The use of satellite data in the specification of convective heating for diabatic initialization and moisture adjustment in numerical weather prediction models. Mon. Wea. Rev., 1990, 118:67～93.
41. Heckly W. A., Kelly G., Tieddtke M. On the use of satellite-derived heating rates for data assimilation within the tropics. Mon. Wea. Rev., 1990, 118:1743～1757.
42. Eyre J. R., G. A. Kelly, et al. Assimilation of TOVS radiance information through
one-dimensional variational analysis. Q. J. Roy. Met. Soc. 1993, 119:1427～1463.
43. Alan E. L., George D. M. Assimilation of visible-band satellite data for mesoscale forecasting in cloudy conditions. Mon. Wea. Rev., 1999, 127(3):265～278.
44．沈桐立，闵锦忠，吴诚鸥．有限区域卫星云图资料变分分析的试验研究．高原气象．1996，15(1)，58～67．
45．张守峰，王诗文．在台风业务系统中使用卫星云导风资料的试验．气象，1999，25(8)：22～25．
46．翁永辉，徐祥德．TOVS 资料的变分处理方法在青藏高原地区的数值试验．大气科学，1999，23(6)：703～712．
47．闵锦忠，沈桐立，陈海山等．卫星云图资料反演的质量控制及变分同化数值试验．应用气象学报，2000，11(4)：410～418．
48. Gao J., Xue M. A variational method for the analysis of three-dimensional wind fields from Two-Doppler radars. Mon. Wea. Rev., 1999, 127,:2128～2141.
49. Alexander G. D., Weinman J. A. The effect of assimilation rain rates derived from satellites and lighting on forecasts of the 1993 superstorm. Mon. Wea. Rev., 1999, 127:1433～1456.
50. Deblone G. Variational assimilation of SSM/I total precipitable water retrievals in the CMC analysis system. Mon. Wea. Rev., 1999, 127:1485～1476.
51．柳崇健．数值天气预报中的若干新技术．北京：气象出版社，1993：262～294．
52．柳崇健，丑纪范．改进数值天气预报的一个新途径．中国科学B辑，1987(8)：903～910．
2. Cressmen G P. An operational objective analysis system. Mon Wea Rev, 1959, 87(7): 367～374.
3. Lorence A C. A global three-dimensional multivariate statistical interpolation scheme. Mon Wea Rev, 1981, 109(3): 701～721.
4. Sasaki Y. An objective analysis based on variational method. J Meteor Soc Japan, 1958, 36(3):77～88.
5. Sasaki Y. Some basic formalisms in numerical variational analysis. Mon Wea Rev, 1970, 98(12):875～883.
6. LeDimet F X, Talagrand O. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus, 1986, 38A(2):97～110.
7. Sasaki Y. Numerical variational analysis formulated under the constraints as determined by longwave equations and a low-pass filter. Mon Wea Rev, 1970, 98(12):884～898.
8. Sasaki Y. Numerical variational analysis with weak constraint and application to surface analysis of severe storm gust. Mon Wea Rev, 1970, 98(12):899～910.
9. Lewis J M, Derber J C. The use of adjoint equations to solve a variational adjustment problem with advective constrains. Tellus, 1985, 37A(4):309～322
10. Derber J. C. Variational four-dimensional analysis using quasi-geostrophie constraints. Mon. Wea. Rev. 1987, 115(5):998～1008.
11. Courtier P. and Talagrand O. Variational assimilation of meteorological observations with the direct and adjoint shallow-water equations Tellus, 1990, 42A(5):531～549.
12. Thepaut J N, Courtier P. Four dimension variational assimilation using the adjoint of a multilevel equation model. Quart J R Meteo Soc, 1991, 117(5): 1225～1254.
13. Navon I M, Zou X, Derber J et al. Variational data assimilation with an adiabatic version of the NMC spectral model. Mon Wea Rev, 1992, 120(7):1433～1446.
14. Winston C C, Chang L P. Development of a four-dimension variational analysis system using the adjoint method at GLA. part Ⅰ: Dynamic. Mon Wea
Rev, 1992, 120(8): 1661～1673.
15. Zou X., Kuo H., Guo Y. R. Assimilation of atmosphere radio refractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev., 1995, 123(7):2229～2247.
16. Zou X, Navon I M, Sela J G. Variational data assimilation with moist threshold process using the NMC spectral model. Tellus, 1993, 45A(5): 370～387.
17. Dusanka Z, Fedor M. Four-dimension variational assimilation of precipitation data. Mon Wea Rev, 1995, 123(4): 1112～1127.
18. Holt T R, Chang S W. Impact of SSM/I precipitable water assimilation on mesoscale simulations of the ERICA IOP4 cyclone. Preprints 10 th conf on numerical weather prediction Amer Meteo Soc, 1994(2): 164～186.
19. Zou X. Rainfall assimilation through an optimal control of initial and boundary conditions in a limited-area mesoscale model. Mon Wea Rev, 996, 124(12):2859～2882.
20. Kuo Y H, Zou X, Guo Y R. Variational assimilation of precipitable using a nonhydrostatic mesoscale adjoint model. Part Ⅰ: moisture retrieval and sensitivity experiments. Mon Wea Rev, 1996, 124(1): 122～147.
21. Wu X H. Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and colunm cloud liquid water amounts. Mon Wea Rev, 1995, 123(2):347～365.
22. Fillion L, Ronald M E. Variational assimilation of precipitation data using moist convective parameterization schemes: AID-Var study. Mon Wea Rev, 1997, 125(11 ):2917～2942.
23. Andrew S, Jones I C C, Thomas H. Data assimilation of satellite-derived heating rates as proxy surface wetness data into a regional atmospheric mesoscale model.Part Ⅰ: Meteorology. Mon Wea Rev, 1998, 26(3):634～645.
24. Cacucci D G. Sensitivity theory for nonlinear system. Ⅰ: Nonlinear functional analysis approach. J Math Phys, 1981, 22(12):2794～2802.
25. Derber J C. A variational continuous assimilation technique. Mon Wea Rev, 1989, 117(11):2437～2446.
26. Ronald M E, Tomislava V. Sensitivity analysis using an adjoint of the PSU-NCAR Mesoscale Model. Mon Wea Rev, 1992, 120 (8): 1644～1660.
27. Bao J W, Ronald M E. An adjoint examination of a nudging method for data assimilation.
Mon Wea Rev, 1997, 125(6):1355～1373.
28. Pu Z X. Sensitivity of forecast errors to initial conditions with a quasi-inverse linear method. Mon Wea Rev, 1997, 125(10):2479～2503.
29. Nils G, Xiang Y. Sensitivity experiments with spectral HIRLAM and its adjoint. Tellus, 1996, 48A(4): 501～517.
30. David R S, Bao J W. Optimal determination of nudging coefficients using the adjoint equations. Tellus, 1993, 45A(5):358～369.
31．郜吉东，丑纪范．数值天气预报中的两类反问题及一种数值解法——理想试验．气象学报，1994，52(2)：129～139
32．龚建东，邱崇践，王强，陈伟民．区域四维变分资料同化的数值试验．气象学报，1999，57(2)：131～142
33．蒲朝霞，丑纪范．对中尺度遥感资料进行四维同化的共轭方法及数值研究．高原气象，1994，13(4)：419～429
34．邱崇践．变分四维同化方法中的不连续问题．兰州大学学报 (自然科学版)，1997，33(1)：115～119
35．陈子通，沈桐立，丁一汇，孙麟平．中尺度数值模式的资料同化系：(一)伴随模式的设计．南京气象学院学报，1998，21(2)：165～172
36．沈桐立，陈子通，丁一汇，孙麟平．中尺度数值模式的资料同化系：(二)伴随模式系统的检验和试验．南京气象学院学报，1998，21(2)：173～180
37．冯伍虎，邱崇践．变分四维同化方法若干问题的数值试验．高原气象，1999，18(2)：138～146
38．李晓莉，沈桐立，孙麟平．中尺度模式的四维伴随同化系统及其同化试验．南京气象学院学报，2002，25(1)：36-44
39．王栋梁，沈桐立．中尺度模式MM5的四维变分资料同化系统．南京气象学院学报，2002，25(5)：603-610
40. Purl R., Miller M. J. The use of satellite data in the specification of convective heating for diabatic initialization and moisture adjustment in numerical weather prediction models. Mon. Wea. Rev., 1990, 118:67～93.
41. Heckly W. A., Kelly G., Tieddtke M. On the use of satellite-derived heating rates for data assimilation within the tropics. Mon. Wea. Rev., 1990, 118:1743～1757.
42. Eyre J. R., G. A. Kelly, et al. Assimilation of TOVS radiance information through
one-dimensional variational analysis. Q. J. Roy. Met. Soc. 1993, 119:1427～1463.
43. Alan E. L., George D. M. Assimilation of visible-band satellite data for mesoscale forecasting in cloudy conditions. Mon. Wea. Rev., 1999, 127(3):265～278.
44．沈桐立，闵锦忠，吴诚鸥．有限区域卫星云图资料变分分析的试验研究．高原气象．1996，15(1)，58～67．
45．张守峰，王诗文．在台风业务系统中使用卫星云导风资料的试验．气象，1999，25(8)：22～25．
46．翁永辉，徐祥德．TOVS 资料的变分处理方法在青藏高原地区的数值试验．大气科学，1999，23(6)：703～712．
47．闵锦忠，沈桐立，陈海山等．卫星云图资料反演的质量控制及变分同化数值试验．应用气象学报，2000，11(4)：410～418．
48. Gao J., Xue M. A variational method for the analysis of three-dimensional wind fields from Two-Doppler radars. Mon. Wea. Rev., 1999, 127,:2128～2141.
49. Alexander G. D., Weinman J. A. The effect of assimilation rain rates derived from satellites and lighting on forecasts of the 1993 superstorm. Mon. Wea. Rev., 1999, 127:1433～1456.
50. Deblone G. Variational assimilation of SSM/I total precipitable water retrievals in the CMC analysis system. Mon. Wea. Rev., 1999, 127:1485～1476.
51．柳崇健．数值天气预报中的若干新技术．北京：气象出版社，1993：262～294．
52．柳崇健，丑纪范．改进数值天气预报的一个新途径．中国科学B辑，1987(8)：903～910．