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The usage of Ensemble Prediction System (EPS)-based weather forecasts is nowadays becoming very popular and widespread, because ensemble means better represent weather-related risks than a single (deterministic) forecast. Perturbations of the lower boundary state (i.e., layers of soil and the boundary between soil and the lower atmosphere) applied to the governing system are also believed to play an important role at any resolution. As a part of the research project of the Consortium for Small-scale Modelling (COSMO) at the Institute of Meteorology and Water Management – National Research Institute (IMWM-NRI), a simple and efficient method was proposed to produce a reasonable number of valid ensemble members, taking into consideration predefined soil-related model parameters. Tests, case studies and long-term evaluations confirmed that small perturbations of a selected parameter(s) were sufficient to induce significant changes in the forecast of the state of the atmosphere and to provide qualitative selection of a valid member of the ensemble members. Another important factor that added a significant increment to ensemble spread was the time-lagged approach. All these aspects resulted in the preparation of a well-defined ensemble based on the perturbation of soil-related parameters, and introduced in the COSMO model operational setup at the IMWM-NRI. This system is intended for the use in forecasters’ routine work.
Rocznik
Tom
Strony
43--51
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wykr.
Twórcy
autor
- Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw
autor
- Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw
autor
- Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw
autor
- Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw
Bibliografia
- 1. Baldauf M., Seifert A., Förstner J., Majewski D., Raschendorfer M., Reinhardt T., 2011, Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities, Monthly Weather Review, 139, 3887-3905, DOI: 10.1175/MWR-D-10-05013.1
- 2. Barkmeijer J., Bouttier F., van Gijzen M., 1998, Singular vectors and estimates of the analysis error covariance metric, Quarterly Journal of the Royal Meteorological Society, 124 (549), 1695-1713, DOI: 10.1002/qj.49712454916
- 3. Bonanno R., Loglisci N., 2017, Introducing lower boundary conditions’ perturbations in a convection-permitting ensemble system: sensitivity to soil moisture perturbation, Meteorology and Atmospheric Physics, DOI: 10.1007/s00703-0170505-1
- 4. Buizza R., Houtekamer P.L., Pellerin G., Toth Z., Zhu Y., Wei M., 2005, A comparison of the ECMWF, MSC, and NCEP global Ensemble Prediction Systems, Monthly Weather Review, 133, 1076-1097, DOI: 10.1175/MWR2905.1
- 5. Chen M., Wang W., Kumar A., 2013, Lagged ensembles, forecast configuration and seasonal predictions, Monthly Weather Review, 141, 3477-3497, DOI: 10.1175/MWR-D-12-00184.1
- 6. Doms G., Forstner J., Heise E., Herzog H.-J., Raschendorfer M., Reinhardt T., Ritter B., Schrodin R., Schulz J.-P., Vogel G., 2007, A description of the Nonhydrostatic Regional Model LM, Part II: Physical parameterization, DWD
- 7. Duniec G., Mazur A., 2014, COTEKINO priority project – results of sensitivity tests, COSMO Newsletter, 14, 106-113
- 8. Houtekamer P.L., Lefaivre L., Derome J., Ritchie H., Mitchell H.L., 1996, A system simulation approach to ensemble prediction, Monthly Weather Review, 124, 1225-1242, DOI: 10.1175/1520-0493(1996)124<1225:ASSATE>2.0.CO;2
- 9. Lu C., Yuan H., Schwartz B.E., Benjamin S.G., 2007, Shortrange numerical weather prediction using time-lagged ensembles, Weather and Forecasting, 22, 580-595, DOI: 10.1175/WAF999.1
- 10. Krishnamurti T.N., Kishtawal C.M., Zhang Z., LaRow T., Bachiochi D., Williford E., Gadgil S., Surendran S., 2000, Multimodel ensemble forecasts for weather and seasonal climate, Journal of Climate, 13, 4196-4216, DOI: 10.1175/1520-0442(2000)013<4196:MEFFWA>2.0.CO;2
- 11. Mazur A., Duniec G., 2014a, Sensitivity test on the behavior of different COSMO suites to different lower boundary initial conditions, presented during COSMO User Seminar, Offenbach, Germany, 2014
- 12. Mazur A., Duniec G., 2014b, Soil state perturbations as an input for Ensemble Prediction System (EPS) forecast, [in:] 9th International Soil Science Congress on “The Soul of Soil and Civilization”, Side, Antalya/Turkey, 14-16 October, DOI: 10.13140/2.1.1397.5840
- 13. Mazur A., Duniec G., 2015, Ensemble Prediction System (EPS)based forecast prepared from perturbation of soil conditions, COSMO Newsletter, 15, 63-71
- 14. Quintanar A.I., Mahmood R., 2012, Ensemble forecast spread induced by soil moisture changes over the mid-south and neighboring mid-western region of the USA, Tellus A: Dynamic Meteorology and Oceanography, 64 (1), 17156, DOI: 10.3402/tellusa.v64i0.17156
- 15. Sattler K., Feddersen H., 2005, Limited-area short-range ensemble predictions targeted for heavy rain in Europe, Hydrology and Earth System Sciences, 9 (4), 300-312, DOI: 10.5194/ hess-9-300-2005
- 16. Sivillo J.K., Ahlquist J.E., Toth Z., 1997, An ensemble forecasting primer, Weather Forecast, 12, 809-818, DOI: 10.1175/ 1520-0434(1997)012<0809:AEFP>2.0.CO;2
- 17. Stensrud D.J., Bao J.-W., Warner T.T., 2000, Using initial condition and model physics perturbations in short-range ensembles, Monthly Weather Review, 128, 2077-2107, DOI: 10.1175/1520-0493(2000)128<2077:UICAMP>2.0.CO;2
- 18. Sutton C., Hamill T., Warner, T., 2006, Will perturbing soil moisture improve warm-season ensemble forecasts? A proof of concept, Monthly Weather Review, 134, 3174-3189, DOI: 10.1175/MWR3248.1
- 19. Tennant W., Beare S., 2014, New schemes to perturb sea-surface temperature and soil moisture content in MOGREPS, Quarterly Journal of the Royal Meteorological Society, 140 (681), 1150-1160, DOI: 10.1002/qj.2202
- 20. Toth Z., Kalnay E., 1997, Ensemble forecasting at NCEP and the breeding method, Monthly Weather Review, 125, 32973319, DOI: 10.1175/1520-0493(1997)125,3297:EFANAT.2. 0.CO;2
- 21. Wang Y., Kann A., Bellus M., Pailleux J., Wittmann C., 2010, A strategy for perturbing surface initial conditions in LAMEPS, Atmospheric Science Letters, 11 (2), 108-113, DOI: 10.1002/asl.260
- 22. Zängl G., Reinert D., Rpodas P., Baldauf M., 2015, The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Quarterly Journal of the Royal Meteorological Society, 141 (687), 563-579, DOI: 10.1002/qj.2378
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Bibliografia
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