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2018 | Vol. 6, Iss. 1 | 1--12
Tytuł artykułu

Precipitation estimation and nowcasting at IMGW-PIB (SEiNO system)

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A System for the Estimation and Nowcasting of Precipitation (SEiNO) is being developed at the Institute of Meteorology and Water Management – National Research Institute. Its aim is to provide the national meteorological and hydrological service with comprehensive operational tools for real-time high-resolution analyses and forecasts of precipitation fields. The system consists of numerical models for: (i) precipitation field analysis (estimation), (ii) precipitation nowcasting, i.e., extrapolation forecasting for short lead times, (iii) generation of probabilistic nowcasts. The precipitation estimation is performed by the conditional merging of information from telemetric rain gauges, the weather radar network, and the Meteosat satellite, employing quantitative quality information (quality index). Nowcasts are generated by three numerical models, employing various approaches to take account of different aspects of convective phenomena. Probabilistic forecasts are computed based on the investigation of deterministic forecast reliability determined in real time. Some elements of the SEiNO system are still under development and the system will be modernized continuously to reflect the progress in measurement techniques and advanced methods of meteorological data processing.
Wydawca

Rocznik
Strony
1--12
Opis fizyczny
Bibliogr. 29 poz., rys., tab., wykr.
Twórcy
autor
  • Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw, Poland, jan.szturc@imgw.pl
autor
  • Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw, Poland
  • Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw, Poland
  • Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw, Poland
  • Institute of Meteorology and Water Management – National Research Institute, Podleśna 61, 01-673 Warsaw, Poland
Bibliografia
  • 1. Atencia A., Rigo T., Sairouni A., Moré J., Bech J., Vilaclara E., Cunillera J., Llasat M.C. Garrote, L., 2010, Improving QPF by blending techniques at the Meteorological Service of Catalonia, Natural Hazards and Earth System Sciences, 10, 1443-1455, DOI: 10.5194/nhess-10-1443-2010
  • 2. Berndt C., Rabiei E., Haberlandt U., 2014, Geostatistical merging of rain gauge and radar data for high temporal resolutions and various station density scenarios, Journal of Hydrology, 508, 88-101, DOI: 10.1016/j.jhydrol.2013.10.028
  • 3. Bowler N.E., Pierce C E., Seed A.W., 2006, STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP, Quarterly Journal of the Royal Meteorological Society, 132 (620), 2127-2155, DOI: 10.1256/qj.04.100
  • 4. Dixon M., Wiener G., 1993, TITAN: thunderstorm identification, analysis, and nowcasting – A radar-based methodology, Journal of Atmospheric and Oceanic Technology, 10 (6), 785-797, DOI: 10.1175/1520-0426(1993)010<0785:TTITA A>2.0.CO;2
  • 5. Eckel F.A., Delle Monache L., 2016, A hybrid NWP-analog ensemble, Monthly Weather Review, 144, 897-911, DOI: 10.1175/MWR-D-15-0096.1
  • 6. Einfalt T., Szturc J., Ośródka K., 2010, The quality index for radar precipitation data: a tower of Babel?, Atmospheric Science Letters, 11 (2), 139-144, DOI: 10.1002/asl.271
  • 7. Germann U., Berenguer M., Sempere-Torres D., Zappa M., 2009, REAL – Ensemble radar precipitation estimation for hydrology in a mountainous region, Quarterly Journal of the Royal Meteorological Society, 135 (639), 445-456, DOI: 10.1002/qj.375
  • 8. Germann U., Zawadzki I., 2002, Scale-dependence of the predictability of precipitation from continental radar images. Part I: Description of the methodology, Monthly Weather Review, 130, 2859-2873, DOI: 10.1175/1520-0493(2002)130<2859:SDOTPO>2.0.CO;2
  • 9. Gilleland E., Ahijevych A.A., Brown B.G., Ebert E.E., 2010, Verifying forecasts spatially, Bulletin of the American Meteorological Society, 91, 1365-1373, DOI: 10.1175/2010BAMS2819.1
  • 10. Golding B.W., 1998, Nimrod: A system for generating automated very short range forecasts, Meteorological Applications, 5 (1), 1-16, DOI: 10.1017/S1350482798000577
  • 11. Haiden T., Kann A., Wittmann C., Pistotnik G., Bica B., Gruber C., 2011, The Integrated Nowcasting through Comprehensive Analysis (INCA) system and its validation over the Eastern Alpine Region, Weather and Forecasting, 26, 166-183, DOI: 10.1175/2010WAF2222451.1
  • 12. Jakubiak B., Szturc J., Ośródka K., Jurczyk A., 2014, Experiments with three-dimensional radar reflectivity data assimilation into the COAMPS model, Meteorology Hydrology and Water Management. Research and Operational Applications, 2 (1), 43-54, DOI: 10.26491/mhwm/28893
  • 13. Jurczyk A., Ośródka K., Szturc J., 2012, Convective cell identification using multi-source data, IAHS Publications, 351, 360-366
  • 14. Kann A., Pistotnik G., Bica B., 2012, INCA-CE: a Central European initiative in nowcasting severe weather and its applications, Advances in Science and Research, 8, 67-75, DOI: 10.5194/asr-8-67-2012
  • 15. Mecklenburg, S., Jurczyk, A., Szturc, J., Ośródka, K., 2005, Use of radar observation in hydrological and NWP models. Quantitative precipitation forecasts (QPF) based on radar data for hydrological models, COST Action 717, Luxembourg, 36 pp.
  • 16. Michelson D.B., Lewandowski R., Szewczykowski M., Beekhuis H., Haase G., 2014, EUMETNET OPERA weather radar information model for implementation with the HDF5 file format. Version 2.2, EUMETNET OPERA Document, 38 pp., available at http://eumetnet.eu/wp-content/uploads/2017/01/ OPERA_hdf_description_2014.pdf (data access 22.08.2017)
  • 17. NWC SAF, 2013, NWCSAF/MSG Basic Documents, v2013, EUMETSAT NWC SAF Program, available at http://www. nwcsaf.org/indexScientificDocumentation.html (data access 22.08.2017)
  • 18. Ośródka K., Szturc J., Jurczyk A., 2014, Chain of data quality algorithms for 3-D single-polarization radar reflectivity (RADVOL-QC system), Meteorological Applications, 21 (2), 256-270, DOI: 10.1002/met.1323
  • 19. Pierce C.E., Hardaker P.J., Collier C.G., Haggett C.M., 2000, GANDOLF: a system for generating automated nowcasts of convective precipitation, Meteorological Applications, 7 (4), 341-360, DOI: 10.1017/S135048270000164X
  • 20. Pierce C., Seed A., Ballard S., Simonin D., Li Z., 2012, Nowcasting, [in:] Doppler radar observations – weather radar, wind profiler, ionospheric radar, and other advanced applications, J. Bech, J.L. Chau (eds.), InTech, Rijeka, 97-142
  • 21. Roulin E., Vannitsem S., 2005, Skill of medium-range hydrological ensemble predictions, Journal of Hydrometeorology, 6, 729-744, DOI: 10.1175/JHM436.1
  • 22. Silvestro F., Rebora N., Cummings G., Ferraris L., 2015, Experiences of dealing with flash floods using an ensemble hydrological nowcasting chain: implications of communication, accessibility and distribution of the results, Journal of Flood Risk Management (early view), DOI: 10.1111/jfr3.12161
  • 23. Sinclair S., Pegram G., 2005, Combining radar and rain gauge rainfall estimates using conditional merging, Atmospheric Science Letters, 6 (1), 19-22, DOI: 10.1002/asl.85
  • 24. Szturc J., Jurczyk A., Ośródka K., Struzik P., Otop I., 2014, Estimation of a surface precipitation field based on multi-source data and quality information, (in Polish), Monografie Komitetu Gospodarki Wodnej PAN, 20 (2), 19-30
  • 25. Szturc J., Ośródka K., Einfalt T., Jurczyk A., 2010, Rainfall and runoff ensembles based on the quality index of radar precipitation data, [in:] Advances in radar applications, Proceedings of the 6th European Conference on Radar in Meteorology and Hydrology. ERAD, Sibiu, Romania, 446-452
  • 26. Szturc J., Ośródka K., Jurczyk A., Jelonek L., 2008, Concept of dealing with uncertainty in radar-based data for hydrological purpose, Natural Hazards and Earth System Sciences, 8, 267-279
  • 27. Ten Veldhuis J.A.E., Ochoa-Rodriguez S., Bruni B., Gires A., van Assel J., Wang L., Reinoso-Rodinel R., Kroll S., Schertzer D., Onof C. Willems P., 2014, Weather radar for urban hydrological applications: lessons learnt and research needs identified from 4 pilot catchments in North-West Europe, [in:] Proceedings of the International Symposium Weather Radar and Hydrology, Washington, April 7-10
  • 28. Tokarczyk T., Szalińska W., Tiukało A., Jełowicki J., Chorążyczewski A., 2016, Computational environment HYDRO-PATH as a flexible tool for operational rainfall-runoff model design, Meteorology Hydrology and Water Management. Research and Operational Applications, 4 (1), 65-77, DOI: 10.26491/mhwm/63366
  • 29. Villarini G., Krajewski W.F., 2010, Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall, Surveys in Geophysics, 31 (1), 107-129, DOI: 10.1007/s10712-009-9079-x
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-3ca95de7-8835-457b-a60e-9e3b9dc83266
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