Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates
References
-
Bannister
, R., Migliorini, S.and Dixon, M. 2011. Ensemble prediction with a convection-permitting model for nowcasting. Part II: Forecast error statistics., this issue. -
Bloom
, S., Takacs, L., da Silva, A.and Ledvina, D. 1996. Data as-similation using incremental analysis updates. Mon. Wea. Re v. 124, 1256– 1271. -
Bowler
, N. E., Arribas, A., Mylne, K. R., Robertson, K. B.and Beare, S. E. 2008. The MOGREPS short-range ensemble prediction system. Quart. J. Roy. Meteor Soc. 134, 703– 722. -
Clark
, P. 2009. Limited area modelling in CRM mode. In: Proceedings of the ECMWF Seminar on Parametrization of. ECMWF, 165-192. Available at: http://www.ecmwf.int/publications/. -
Davies
, T., Cullen, M. J. P., Malcolm, A. J., Mawson, M. H., Stani-forth, A., and co-authors. 2005. A new dynamical core for the Met Office’s global and regional modelling of the atmosphere. Quart. J. Roy. Meteor Soc. 131, 1759– 1782. -
Dixon
, M., Li, Z., Lean, H., Roberts, N.and Ballard, S. 2009. Impact of data assimilation on forecasting convection over the United Kingdom using a high-resolution version of the Met Office Unified Model. Mon. Wea. Re v. 137, 1562– 1584. -
Done
, J. M., Craig, G. C., Gray, S. L., Clark, P. A.and Gray, M. E. B. 2006. Mesoscale simulations of organized convection: importance of convective equilibrium. Quart. J. Roy. Meteor Soc. 132, 737– 756. -
Fritsch
, J. M.and Carbone, R. R. 2004. Improving quantitative precipi-tation forecasts in the warm season: a USWRP research and develop-ment strategy. Bull. Amer Meteor. Soc. 85, 955– 965. -
Gilmore
, M. S., Straka, J. M.and Rasmussen, E. N. 2004. Precipi-tation uncertainty due to variations in precipitation particle param-eters within a simple microphysics scheme. Mon. Wea. Re v. 132, 2610– 2627. -
Golding
, B. W. 1998. Nimrod: a system for generating automated very short range forecasts. Meteor Appl. 5, 1– 16. -
Hamill
, T. M. 2001. Interpretation of rank histograms for verifying ensemble forecasts. Mon. Wea. Re v. 129, 550– 560. -
Harrison
, D. L., Driscoll, S. J.and Kitchen, M. 2000. Improving precip-itation estimates from weather radar using quality control and correc-tion techniques. Meteor. AppL, 135– 144. -
Hohenegger
, C.and Schär, C. 2007. Predictability and error growth dynamics in cloud-resolving models.. 64, 4467– 4478. -
Jones
, C. D.and Macpherson, B. 1997. A latent heat nudging scheme for the assimilation of precipitation data into an operational mesoscale model. Meteor. AppL, 269– 277. -
Koizumi
, K., Ishilcawa, Y.and Tsuyulci, T. 2005. Assimilation of pre-cipitation data to the JMA mesoscale model with a four-dimensional variational method and its impact on precipitation forecasts. SOLA, 45– 48. -
Lean
, H. W., Clark, P. A., Dixon, M., Roberts, N. M., Fitch, A.and co-authors. 2008. The Met. Office global three-dimensional variational data assimilation scheme. Quart. J. Roy. Meteor Soc. 131, 1759– 1782. -
Lilly
, D. K. 1990. Numerical prediction of thunderstorms-has its time come?. 116, 779– 798. -
Lorene
, A. C., Ballard, S. P., Bell, R. S., Ingleby, N. B., Andrews, P. L. E and co-authors. 2000. Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Mon. Wea. Rev. 136, 3408-342 4. -
Macpherson
, B., Wright, B. J., Hand, W. H.and Maycock, A. J. 1996. The impact of MOPS moisture data in the U.K. Meteorological Office Mesoscale Data Assimilation Scheme. Mon. Wea. Re v. 124, 1746– 1766. -
Mass
, C. F., Ovens, D., Westrick, K.and Colle, B. A. 2002. Does in-creasing horizontal resolution produce more skilful forecasts?. 83, 407– 430. -
Page
, C., Fillion, L.and Zwack, P. 2007. Diagnosing summertime mesoscale vertical motion: implications for atmospheric data assimi-lation. Mon. Wea. Re v. 135, 2076– 2094. -
Park
, S. K.and Droegemeier, K. K. 2000. Sensitivity analysis of a 3D convective storm: implications for variational data assimilation and forecast error. Mon. Wea. Re v. 128, 140– 159. -
Pires
, C. A., Talagrand, 0. and Bocquet, M 2010. Diagnosis and im-pacts of non-Gaussianity of innovations in data assimilation. Phys. D: Nonlinear Phenom. 239, 1701– 1717. -
Sakov
, P.and Oke, P. R. 2008. Implications of the form of the ensemble transformation in the ensemble square root filters. Mon. Wea. Re v. 136, 1042– 1053. -
Stensrud
, D. J., Xue, M., Wicker, L. J., Kelleher, K. E., Foster, M. P.and co-authors. 2009. Convective-scale warn-on-forecast system. Bull. Amer. Meteor Soc. 90, 1487-149 9. -
Sun
, J. 2005. Convective-scale assimilation of radar data: progress and challenges. Quart. J. Roy. Meteor Soc. 131, 3439– 3463. -
Talagrand
, O., Vautard, R.and Strauss, B.In: Proceedings, ECMWF Workshop on Predictability, Shinfield Park, Reading, UK, 1- 25. -
Tong
, M.and Xue, M. 2008. Simultaneous estimation of microphysi-cal parameters and atmospheric state with radar data and ensemble Kalman filter. Part I: Sensitivity analysis and parameter identifiability. Mon. Wea. Re v. 136, 1630– 1648. -
Wang
, X.and Bishop, C. H. 2003. A comparison of breeding and en-semble transform Kalman filter ensemble forecast schemes., 1140– 1158. -
Wang
, X., Bishop, C. H.and Julier, S. J. 2004. Which is better, an ensemble of positive-negative pairs or a centered spherical simplex ensemble?. Mon. Wea. Re v. 132, 1590– 1605. -
Wilks
, D. S. 2006. Statistical Methods in the Atmospheric Sciences, 2nd edition, Volume 59. International Geophysics Series. Academic Press. -
Wilson
, D. R.and Ballard, S. P. 1999. A microphysically based pre-cipitation scheme for the UK Meteorological Office Unified Model. Quart. J. Roy. Meteor. Soc. 131, 1607– 1636.
DOI: https://doi.org/10.1111/j.1600-0870.2010.00503.x | Journal eISSN: 3035-9554
Language: English
Page range: 468 - 496
Submitted on: Apr 14, 2010
Accepted on: Dec 13, 2010
Published on: Jan 1, 2011
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
© 2011 Stefano Migliorini, Mark Dixon, Ross Bannister, Sue Ballard, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.