Maximum Entropy를 이용한 정량적 레이더 강우추정 불확실성 분석
Uncertainty Analysis of Quantitative Radar Rainfall Estimation Using the Maximum Entropy
0
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Existing studies on radar rainfall uncertainties were performed to reduce the uncertainty for each stage by using bias correction during the quantitative radar rainfall estimation process. However, the studies do not provide quantitative comparison with the uncertainties for all stages. Consequently, this study proposes a suitable approach that can quantify the uncertainties at each stage of the quantitative radar rainfall estimation process. First, the new approach can present initial and final uncertainties, increasing or decreasing the uncertainty, and the uncertainty percentage at each stage. Furthermore, Maximum Entropy (ME) was applied to quantify the uncertainty in the entire process. Second, for the uncertainty quantification of radar rainfall estimation at each stage, this study used two quality control algorithms, two rainfall estimation relations, and two bias correction techniques as post-processing and progressed through all stages of the radar rainfall estimation. For the proposed approach, the final uncertainty (ME = 3.81) from the ME of the bias correction stage was the smallest while the uncertainty of the rainfall estimation stage was higher because of the use of an unsuitable relation. Additionally, the ME of the quality control was at 4.28 (112.34%), while that of the rainfall estimation was at 4.53 (118.90%), and that of the bias correction at 3.81 (100%). However, this study also determined that selecting the appropriate method for each stage would gradually reduce the uncertainty at each stage. Finally, the uncertainty due to natural variability was 93.70% of the final uncertainty. Thus, the results indicate that this new approach can contribute significantly to the field of uncertainty estimation and help with estimating more accurate radar rainfall.
Abstract
Existing studies on radar rainfall uncertainties were performed to reduce the uncertainty for each stage by using bias correction during the quantitative radar rainfall estimation process. However, the studies do not provide quantitative comparison with the uncertainties for all stages. Consequently, this study proposes a suitable approach that can quantify the uncertainties at each stage of the quantitative radar rainfall estimation process. First, the new approach can present initial and final uncertainties, increasing or decreasing the uncertainty, and the uncertainty percentage at each stage. Furthermore, Maximum Entropy (ME) was applied to quantify the uncertainty in the entire process. Second, for the uncertainty quantification of radar rainfall estimation at each stage, this study used two quality control algorithms, two rainfall estimation relations, and two bias correction techniques as post-processing and progressed through all stages of the radar rainfall estimation. For the proposed approach, the final uncertainty (ME = 3.81) from the ME of the bias correction stage was the smallest while the uncertainty of the rainfall estimation stage was higher because of the use of an unsuitable relation. Additionally, the ME of the quality control was at 4.28 (112.34%), while that of the rainfall estimation was at 4.53 (118.90%), and that of the bias correction at 3.81 (100%). However, this study also determined that selecting the appropriate method for each stage would gradually reduce the uncertainty at each stage. Finally, the uncertainty due to natural variability was 93.70% of the final uncertainty. Thus, the results indicate that this new approach can contribute significantly to the field of uncertainty estimation and help with estimating more accurate radar rainfall.
참고문헌 (28)
- Austin, P. M., "Relation between measured radar reflectivity and surface rainfall", Mon. Wea. Rev, 115, pp.1053~1070 (1987)
- Campos, E., "Instrumental uncertainties in Z-R relations", J. Appl. Meteorol, 39, pp.1088~1102 (2000)
- Ciach, G. J., "Product-error-driven uncertainty model for probabilistic quantitative precipitation estimation with NEXRAD data", J. Hydrometeor, 8, pp.1325~1347 (2007)
- Ciach, G. J., "On the estimation of radar rainfall error variance", Adv. Water Resour, 22, pp.585~595 (1999)
- Gay, C., "Objective probabilities about future climate are a matter of opinion", Climatic Change, 99, pp.27~46 (2010)
- Germann, U., "Radar precipitation measurement in a mountainous region", Quart. J. Roy. Meteor. Soc, 132, pp.1669~1692 (2006)
- Huff, F. A., "Sampling errors in measurement of mean precipitation", J. Appl. Meteorol, 9, pp.35~44 (1970)
- Climate Change 2001, Impacts, Adaptations, and Vulnerability, "IPCC", Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, ~ (2001)
- Kim, D. -S., "Reflectivity Z and differencial reflectivity ZDR correction for polarimetric radar rainfall measurement", Proceeding of the Spring Meeting of Korean Meteorological Society, pp.130~131 (2006)
- Krajewski, W. F., "Radar hydrology : rainfall estimation", Adv. Water Resour, 25, pp.1387~1394 (2002)
- Krajewski, W. F., "Radar-rainfall uncertainties", Bull. Amer. Meteor. Soc, 91, pp.87~94 (2010)
- 이재경, "정량적 강우강도 정확도 향상을 위한 단일편파와 이중편파레이더 강수량 합성", 대기, 24(3), pp.365~378 (2014), 한국기상학회[DOI]
- 이재경, "국지우량계보정방법을 이용한 레이더강우량의 수문모델 적용", 한국방재학회논문집, 14(4), pp.67~78 (2014), 한국방재학회
- Marshall, J. S., "Measurement of rainfall by radar", J. Meteor, 4, pp.186~192 (1947)
- McMillan, H., "Rainfall uncertainty in hydrological modeling : An evaluation of multiplicative error models", J. Hydrol, 400, pp.83~94 (2011)
- Morin, E., "Radar Z-R relationship for summer monsoon storm in Arizona", Wea. Forecasting, 20, pp.672~679 (2005)
- Moulin, L., "Uncertainties in mean areal precipitation : assessment and impact on streamflow simulations", Hydrol. Earth Syst. Sci, 13, pp.99~114 (2009)
- Oh, H. -M., "Precipitation rate combined with the use of optimal weighting of radar and rain gauge data", Atmosphere, 13, pp.316~317 (2003)
- Rosenfeld, D., "The window probability matching method for rainfall measurements with radar", J. Appl. Meteorol, 33, pp.682~693 (1994)
- Shannon, C. E., "A Mathematical Theory of Communication", Bell Syst. Tech. J, 27, pp.379~423 (1948)
- Villarini, G., "Empirically-based modeling of spatial sampling uncertainties associated with rainfall measurements by rain gauges", Adv. Water Resour, 31, pp.1015~1023 (2008)
- Villarini, G., "Sensitivity studies of the models of radar-rainfall uncertainties", J. Appl. Meteorol. Clim, 49, pp.288~309 (2010)
- Weather Radar Center, "Weather radar data analysis guidance", Weather Radar Center technical note WRC, 201, pp.3~02 (2013)
- Wilson, J. W., "Radar measurement of rainfall", Bull. Amer. Meteor. Soc, 60, pp.1048~1058 (1979)
- Woodley, W., "Comparison of gage and radar methods of convective rain measurement", J. Appl. Meteorol, 14, pp.909~928 (1975)
- Yoo, C., "Use of the Kalman filter for the correction of mean-field bias of radar rainfall", The 5th Korea-Japan-China Joint Conference on Meteorology, Busan, Korea (2011)
- Zhang, Y., "Subpixelscale rainfall variability and the effects on the separation of radar and gauge rainfall errors", J. Hydrometeor, 8, pp.1348~1363 (2007)
- Zhange, J., "National mosaic and multi-sensor QPE(NMW)", system. Bull. Amer. Meteor. Soc, 92, pp.1321~1338 (2011)