Asymilacja trójwymiarowej odbiciowości radarowej do numerycznego modelu meteorologicznego metodą zespołowego filtru Kalmana : metodyka i eksperyment

• Autorzy: Szturc J. , Jakubiak J. , Jurczyk A. , Ośródka K.
• Języki publikacji: PL

Abstrakty

EN

Assimilation of 3d weather radar reflectivity to nwp model using ensemble Kalman filtering: methodology and experiment

Słowa kluczowe

PL

numeryczny model meteorologiczny; radar meteorologiczny; asymilacja danych

EN

numerical weather prediction model; weather radar; data assimilation

• Wydawca: Polskie Towarzystwa Geofizyczne ; Komitet Geofizyki PAN
• Czasopismo: Przegląd Geofizyczny
• Rocznik: 2014
• Tom: Z. 1-2
• Strony: 19--38
• Opis fizyczny: Bibliogr. 27 poz., mapki, tab., wykr.

Twórcy

autor

Szturc J.

• Ośrodek Teledetekcji Naziemnej, IMGW-PIB – Warszawa

autor

Jakubiak J.

• Interdyscyplinarne Centrum Modelowania UW

autor

Jurczyk A.

• Ośrodek Teledetekcji Naziemnej, IMGW-PIB – Warszawa

autor

Ośródka K.

• Ośrodek Teledetekcji Naziemnej, IMGW-PIB – Warszawa

Bibliografia

• 1. Arakawa A., Lamb V.R., 1977, Computational design of the basic dynamical processes of the UCLA general circulation model. Methods in Computational Physisc, 17, Accademic Press, 173-265.
• 2. Bech J., Gjertsen U., Haase G., 2007, Modelling weather radar beam propagation and topographical blockage at northern high latitudes. Q, J. R. Meteorol. Soc., 133, 1191-1204.
• 3. Bishop C., Etherton B., Majumdar S., 2001, Adaptive sampling with the ensemble transform Kalman filter, part I: Theoretical aspects. Mon. Wea. Rev., 129, 420-435.
• 4. Collier C.G., 1989, Applications of weather radar system. A guide to uses of radar data in meteorology and hydrology. Ellis Horwood Limited, New York.
• 5. Ebert E.E., 2008, Fuzzy verification of high-resolution gridded forecasts: a review and proposed framework. Meteorol. Appl., 15, 51-64.
• 6. Einfalt T., Szturc J., Ośrodka K., 2010. The quality index for radar precipitation data : a tower of Babel? Atmos. Sci. Let., 11, 139-144
• 7. Fletcher N.H., 1962, The physics of rainclouds. Cambridge University Press, ss. 386.
• 8. Hodur R.M., 1997, The Naval Research Laboratory Coupled Ocean-Atmosphere mesoscale Prediction System (COAMPS). Mon. Wea. Rev 125, 1414-1430.
• 9. Houtekamer RL., Mitchell H.L., Pellerin G., Buehner M., Charron M., Spacek L., Hansen B., 2005, Atmospheric data assimilation with an ensemble Kalman filter: results with real observations. Mon. Wea. Rev., 133, 604-620.
• 10. Jakubiak B., 2008, Data assimilation experiments with ensemble Kalman filter. Proceedings of the Joint MAP D-PHASE Scientific Meeting COST 731 mid-term seminar: Challenges in hydrometeorological forecasting in complex terrain, 19-22 May 2008, Conference Centre of CNR, Bologna, Italy, 159-163.
• 11. Jakubiak B., Szpindler M., 2009, Real data assimilation experiments using filtering methods. Geophysical Research Abstracts, 11, EGU2009-11675.
• 12. Jazwinski A.H., 1970, Stochastic processing and filtering theory. Academic Press, New York.
• 13. Jurczyk A., Ośrodka K., Szturc J., 2008, Research studies on improvement in real-time estimation of radar- based precipitation in Poland. Meteorol. Atmos. Phys., 101, 159-173.
• 14. Kalman R.E., 1960, A new approach to linear filtering and prediction problems. Trans. ASME, Series D, Journal of Basic Engineering, 82, 35-45.
• 15. Kessler E. Ill, 1969, On the distribution and continuity of water substance in atmospheric circulations. Meteor. Monogr. no 32, Amer. Meteor. Soc., ss. 84.
• 16. Klemp J., Wilhelmson R., 1978, The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci., 35, 1070-1096.
• 17. Marshall J.S., Palmer W.M., 1948, The distribution of raindrops with size. J. Meteor., 5, 165-166.
• 18. Rezacova D., Sokol Z., Pesice P., 2007, A radar-based verification of precipitation forecast for local convective storms. Atmos. Res., 83, 211-224.
• 19. Rutledge S.A., Hobbs RV, 1983, The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-front rainbands. J. Atmos. Sci., 41, 2949-2972.
• 20. Snyder C., Zhang F., 2003, Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131, 1663-1677.
• 21. Sun J., Crook N.A., 1997, Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments. J. Atmos. Sci., 54, 1642-1661.
• 22. Sun Crook N.A., 1998, Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci., 55, 835-852.
• 23. Venugopal V., Basu S., Foufoula-Georgiu E., 2005, A new metric for comparing precipitation patterns with an application to ensemble forecasts. J. Geophys. Res., 110, D08111.
• 24. Whitaker J., Hamill T., 2002, Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913-1924.
• 25. Xue M., 2006, Data assimilation and prediction at the convective scale: recent progresses. 4th Joint US-Korea Workshop on Mesoscale Observation, Data Assimilation and Modeling for Severe Weather. 13-15.02.2006, Seoul, Korea.
• 26. Zejdlik T., Novak P., 2010, Frequency Protection of the Czech Weather Radar Network. Proceedings of ERAD 2010 (www).
• 27. Zhang F., Snyder C., Sun J., 2004, Impacts of initial estimate and observations on the convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238-1253.