Improvement of mesoscale numerical weather prediction WRF-ARW in the Republic of Belarus by assimilation of radar wind and reflectivity data

  • Palina A. Zaiko Republican Center of Hydrometeorology, Control of Radioactive Contamination and Environmental Monitoring of the Republic of Belarus, 110 Niezaliežnasci Avenue, Minsk 220114, Belarus https://orcid.org/0000-0003-0197-247X
  • Aliaksandr N. Krasouski National Research Center for Ozonosphere Monitoring, Belarusian State University, 7 Kurčatava Street, Minsk 220045, Belarus
  • Siarhei K. Barodka National Research Center for Ozonosphere Monitoring, Belarusian State University, 7 Kurčatava Street, Minsk 220045, Belarus

Abstract

The forecasts of severe weather events obtained with the WRF numerical mesoscale model with the adapted system for assimilation of reflectivity and radial velocity data from the network of Belarusian Doppler weather radars used in Belhydromet in 2019 are analysed. A description of the system for the echo quality control based on the radar dual-polarisation characteristics and the method for three-dimensional variational assimilation (3D-VAR) used to assimilate data in the WRF model are described. The results of case studies on the simulation of precipitation and strong wind for various circulation types in Belarus with and without radar data assimilation are given. The statistical and object-oriented verification of these forecasts is provided. The results of the comprehensive assessment reveal a decrease in the forecast error for 10-m wind speed for the early forecast hours (+6 h) by 1.34 m/s, as well as a more accurate forecast of the location, orientation of the cloud systems and precipitation zones, and a decrease in the number of false alarms in the version with assimilation. A preliminary conclusion on the possibility of using the forecast results in nowcasting systems is also made.

Author Biographies

Palina A. Zaiko, Republican Center of Hydrometeorology, Control of Radioactive Contamination and Environmental Monitoring of the Republic of Belarus, 110 Niezaliežnasci Avenue, Minsk 220114, Belarus

software engineer at the numerical weather prediction department.

Aliaksandr N. Krasouski, National Research Center for Ozonosphere Monitoring, Belarusian State University, 7 Kurčatava Street, Minsk 220045, Belarus

PhD (physics); researcher.

Siarhei K. Barodka, National Research Center for Ozonosphere Monitoring, Belarusian State University, 7 Kurčatava Street, Minsk 220045, Belarus

researcher.

References

  1. Gustafsson N, Janjic T, Schraff C, Leuenberger D, Weissmann M, Reich H, et al. Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres. Quarterly Journal of the Royal Meteorological Society. 2018;144:1218–1256. DOI: 10.1002/qj.3179.
  2. Gotyur IA, Deviatkin AM, Zhukov VY, Kuleshov UV, Shchukin GG. The informational capabilities of doppler weather radar with dual polarization. Uchenye zapiski RGGMU. 2013;32:66–82. Russian.
  3. Zaiko PО. [System of assimilation of ground and upper-air observations into the mesoscale numerical model WRF-ARW at Belhydromet]. Prirodnye resursy. 2019;1:89. Russian.
  4. Vulpiani G, Montopoli M, Passeri LD, Gioia AG, Giordano P, Marzano FS. On the use of dual-polarized C-band radar for operational rainfall retrieval in mountainous areas. Journal of Applied Meteorology and Climatology. 2012;51(2):405–425. DOI: 10.1175/JAMC-D-10-05024.1.
  5. Crisologo I, Vulpiani G, Abon CC, David CPC, Bronstert A, Heistermann M. Polarimetric rainfall retrieval from a C-band weather radar in a tropical environment (The Philippines). Asia-Pacific Journal of Atmospheric Sciences. 2014;50(1):595–607. DOI: 10.1007/s13143-014-0049-y.
  6. Zaiko PO. Meteorological data assimilationin mesoscale numerical model WRF-ARW in the Republic of Belarus. East European Scientific Journal. 2020;55(2):4–12. Russian.
  7. Ipatova VM, Shutyaev VP. Algoritmy i zadachi assimilyatsii dannykh dlya modelei dinamiki atmosfery i okeana [Algorithms and data assimilation problems for models of atmospheric and oceanic dynamics]. Dolgoprudny: Moscow Institute of Physics and Technology; 2013. 30 p. Russian.
  8. Loginov VF, Brovka JA, Mikutskiy VS. Change of climate, extreme weather and climatic phenomena and their link with types of atmospheric circulation of Northern hemisphere by B. L. Dzerdzeevskii. Prirodopol’zovanie. 2013;24:5–10. Russian.
  9. Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, et al. A description of the Advanced Research WRF Version 3 (No. NCAR/TN-475+STR). Boulder: National Center for Atmospheric Research; 2008. 125 p. DOI: 10.5065/D68S4MVH.
  10. Dementsova IA, et al., compilers. Metodicheskoe posobie po verifikatsii mezomasshtabnykh prognozov [Methodological guide for verification of mesoscale forecasts]. Minsk: Belgydromet; 2014. 35 p. Russian.
  11. Zaripov RB, Pavlyukov YuB, Shumilin AA, Travov AV. Application of radar information for verification of the high-resolution numerical weather prediction. Gidrometeorologicheskie issledovaniya i prognozy. 2018;2:60–86. Russian.
  12. Shlender TV, Zhuchkevich VV, Krasouski AN. Regional influence of stratospheric processes in the formation of weather and climate of the Republic of Belarus employing monitoring data. Journal of the Belarusian State University. Geography and Geology. 2018;2:25–38. Russian.
  13. Pavlyukov YB, Zaripov RB, Luk’yanov AN, Shestakova AA, Shumilin AA, Travov AV. The impact of radar data assimilation on atmosphere state analysis in the Moscow region. Meteorologiya i gidrologiya. 2017;6:5–21. Russian.
  14. Ivanova AR, Shakina NP. Future development of nowcasting for aviation meteorological service in the framework of Global aeronavigation plan (GANP) implementation. Trudy Gidromettsentra Rossii. 2016;360:113–134. Russian.
  15. Yusupov YuI. [Naukasting v tekhnologii GIS Meteo]. Meteospektr. 2015;1:43–49. Russian.
  16. Borderies M, Caumont O, Delanoë J, Ducrocq V, Fourrie N, Marquet P. Impact of airborne cloud radar reflectivity data assimilation on kilometre-scale numerical weather prediction analyses and forecasts of heavy precipitation events. Natural Hazards Earth System Sciences. 2019;19(4):907–926. DOI: 10.5194/nhess-19-907-2019.
Published
2020-12-29
Keywords: short-range weather forecast, WRF-ARW, data assimilation, Doppler weather radar, dual-polarisation, verification, nowcasting
How to Cite
Zaiko, P. A., Krasouski, A. N., & Barodka, S. K. (2020). Improvement of mesoscale numerical weather prediction WRF-ARW in the Republic of Belarus by assimilation of radar wind and reflectivity data. Journal of the Belarusian State University. Geography and Geology, 2, 3-13. https://doi.org/10.33581/2521-6740-2020-2-3-13