Evaluation of weather radar rainfall estimation for nowcasting

Luiz Carlos Salgueiro Donato Bacelar, Carlos Frederico de Angelis

Abstract


This article presents the first evaluation of the method used by the Brazilian Centre for Monitoring and Early Warning of Natural
Disasters for the short term forecast (nowcasting) of precipitation by weather radar. In this evaluation, four cases of intense
rainfall in the radius of Pico do Couto radar were studied, giving the flood risk alerts sent for the municipality of Nova Friburgo,
in the state of Rio de Janeiro. In relation to rain gauge data, a median under rate of 43% for the radar precipitation was
observed when using the SRI (Surface Rainfall Intensity) method. After the rainfall correction, the cross-correlation extrapolation
method was evaluated for the 30, 60, 90 and 120 minute forecast horizons, with accumulated precipitation every 30 minutes. The
probabilities of detection (POD) obtained higher values for lower rainfall thresholds (at least 1 or 5 mm of accumulated rainfall)
when compared to larger amount accumulated (20 and 30 mm). The spatial and temporal series of rainfall presented higher errors
(MAE and RMSE) for 90 and 120 minutes of forecast. For all the events, an overestimate (PBIAS positive) of the predictions was
observed in relation to the observed radar rain field itself.

Keywords


Nowcasting. Hydrometeorology. Rainfall estimation. Precipitation. Remote sensing.

References


Bacelar, L., Angelis, C., Costa, I., Rodiguez, M., Damé, R., Teixeira, C. (2013). Limiares de chuva deflagrafores de inundação brusca para bacias da região serrana do rio de janeiro: Radar meteorológico versus pluviômetros. Em: Proceedings..., Simpósio Brasileiro de Recursos Hídricos.

Berenguer, M., Corral, C., Sanchez-Diezma, R., Sempere-Torres, D. (2005). Hydrological validation of a radar-based nowcasting technique. Journal of Hydrometeorology, 6, 532–549.

Biggerstaff, M. I., Listemaa, S. A. (2000). An improved scheme for convective/stratiform echo classification using radar reflectivity. Journal of Applied Meteorology, 39(12), 2129–2150, URL https://doi.org/10.1175/1520-0450(2001)040<2129:AISFCS>2.0.CO;2,https://doi.org/10.1175/1520-0450(2001)040<2129:AISFCS>2.0.CO;2.

Ceped-UFSC (2012). Atlas brasileiro de desastres naturais 1991 a 2010: volume brasil. Relatório Técnico, relatório Técnico.

Dixon, M., Wiener, G. (1993). Thunderstorm identification, tracking, analysis and nowcasting – a radar based methodology. Journal of atmospheric and oceanic technology, 10(6), 785 –797.

Dixon, M., Wiener, G., Dixon, M., Wiener, G. (1993). Titan: Thunderstorm identification, tracking, analysis, and nowcasting — a radar-based methodology. Journal of Atmospheric and Oceanic Technology, 10, 785–797, URL http://journals.ametsoc.org/doi/abs/10.1175/15200426{%}281993{%}29010{%}3C0785{%}3ATTITAA{%}3E2.0.CO{%}3B2.

Ebert, E. E., Wilson, L. J., Brown, B. G., Nurmi, P., Brooks, H. E., Bally, J., Jaeneke, M. (2004). Verification of nowcasts from wwrp sydney 2000 forecast demonstration project. Weather and Forecasting, 19, 73 – 96.

Germann, U., Zawadzki, I. (2004). Scale dependence of the predictability of precipitation from continental radar images. part ii: Probability forecasts. Journal of Applied Meteorology, 43, 74–89.

Hamill, T. M., Nehrkorn, T. (1993). A short-term cloud forecast scheme using cross correlations. CWeather and Forecasting, 8(4),401–411.

Intrieri, E., Gigli, G., Mugnai, F., Fanti, R., Casagli, N. (2012). Design and implementation of a landslide early warning system. Engineering Geology, 147–148, 124–136.

Lee, G., Seed, A. W., Zawadzki, I. (2007). Modeling the variability of drop size distributions in space and time. Journal of Applied Meteorology and Climatology, 46, 742–756.

Liang, Q., Feng, Y., Deng, W., Hu, S., Huang, Y., Zeng, Q., Chen, Z. (2010). A composite approach of radar echo extrapolation based on trec vectors in combination with model-predicted winds. Advances in Atmospheric Sciences, 27(5), 1119– 1130.

Machado, L. A., Maria, A., Heuminski, G., Felipe, P., Albrecht, R. (2017). PROJETO SOS- CHUVA ( Sistema de Observação e Previsão de Tempo Severo ) Previsão Imediata de Tempestades Intensas e Entendimento dos Processos Físicos no Interior dasNuvens. , pp. 1–48.11 Autores: Título curto do artigo

Nielsen, J. E., Throndahl, S., Rasmussen, M. R. (2014). A numerical method to generate high temporal resolution precipitation time series by combining weather radar measurements with a nowcast model. Atmospheric Research, pp. 1– 12.

Poli, V., Alberoni, P., Cesari, D. (2008). Intercomparison of two nowcasting methods: preliminary analysis. Meteorology and Atmospheric Physics, 101(doi: 10.1007/s00703-007-0282-3), 229–244.

Rastogi, R. G., Deshpande, M. R., Vadher, M. N., Davies, K., Parikh, P. B. (1978). Three-dimensional storm motion detection by conventional weather radar. Nature, 273.

Ruzanski, E., Chandrasekar, V., Wang, Y. (2011). The casa nowcasting system, journal of atmospheric and oceanic technology. , 28, 640–655.

Seed, A. (2003). A dynamic and spatial scaling approach to advection modeling. Journal of Applied Meteorology, 42, 381 – 388.

SELEX (2012). Rainbow 5 sofware manual - products and algorithms. Selex ES GmBH Gematronik Weather Radar Systems, Release 5.46.0, 514.

Steiner, M., Jr., R. A. H., Yuter, S. E. (1995). Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. Journal of Applied Meteorology,y, 34(9), 1978–2007,URL https://doi.org/10.1175/15200450(1995)034<1978:CCOTDS>2.0.CO;2,https://doi.org/10.1175/1520-0450(1995)034<1978:CCOTDS>2.0.CO;2.

Thorndahl, S., Rasmussen, M. R. (2013). Short-term forecasting of urban storm wat Thorndahl, S., Rasmussen, M. R. (2013). Short-term forecasting of urban storm water runoff in real-time using extrapolated radar rainfall data. Journal of Hydroinformatics, 15(3), 897, URL http://www.iwaponline.com/jh/015/jh0150897.htm.

Thorndahl, S., Poulsen, T. S., Thomas, Borup, M., Ahm, M., Nielsen, J. E., Grum, M., Rasmussen, M. R., Gill, R., Mikkelsen, P. S. (2013). Comparison of short-term rainfall forecasts for modelbased flow prediction in urban drainage systems. Water Scienceand Technology, 68(2), 472–478.

Tominaga, L., Santoro, J., Amaral, R. (2009). Desastres naturais. : conhecer para prevenir. São Paulo : Instituto Geológico, URL http://www.igeologico.sp.gov.br/downloads/livros/DesastresNaturais.pdf.

UCAR (2010). Flash flood early warning system reference guide. URL http://www.meted.ucar.edu/communities/hazwarnsys/ffewsrg/FF{_}EWS.pdf.

Vicente, G. A., Scofield, R. A., Menzel, W. P. (1998). The operational goes infrared rainfall estimation technique. Bull Amer Meteor Soc, 79, 1883–1898.

Vila, D. A., de Goncalves, L. G. G., Toll, D. L., Rozante, J. R. (2009). Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimates over Continental South America. Journal of Hydrometeorology, 10(2), 533–543.

Wang, J. (2009). Overview of the beijing 2008 olympics project. part i. Forecast Demonstration Project, A report to the WMO World Weather Research Programme.




DOI: http://dx.doi.org/10.5902/2179460X29995

Refbacks

  • There are currently no refbacks.


Copyright (c) 2018 Ciência e Natura



Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.