Calibration of Amirabad radar parameters for estimating precipitation in hot weather

Document Type : Research Notes

Authors

1 Ph.D. Student, Department of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran

2 Professor, Department of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran

3 Assistant Professor, Department of Geography, Faculty of Humanities, Golestan University, Gorgan, Iran

Abstract

Meteorological radar is usually used to estimate rainfall. The relationship between rainfall and the reflectivity of the radar is exponential. Measurement of the intensity and amount of precipitation in the management of water resources, agriculture, and flood alert is widely used. Radar and rain gauges can better estimate the amount and spatial distribution of rainfall. Marshall et al. (1947) proposed based on the relationship between the reflectivity coefficient Z and the precipitation intensity R. Here, a and b are coefficients of the model and may differ in different places and seasons. The factors affecting these variables are: 1- type of rainfall, 2- Season; 3-Geographic and Topographic Surface of the Region. The size of precipitation drops and their distribution varies in different rainfalls. The sources of error in the radar are (1) the difference in radar reflection height, that is related to the height of the ground, while the rain-gauge measures rainfall on the earth's surface. 2) Radar calibration error. 3) Echoes of recurrences from obstacles near the ground. 4) Radar beam attenuation 5) Unrealized echoes of solid phenomena such as hail, snow, melting region. Estimates are more credible near radar. The best way to collect rainbow data is to use both radar and rain gauge simultaneously.
Data used in this study include two series of ground station data and radar data. The rain gauge was used between 30 and 100 kilometers from Amirabad radar. The rainfall in July and September 2015 were selected. The severity of the two selected rainfall was appropriate, and their rainfall was remarkable. In this research, radar beam angles were measured at 0.2, 0.3, 0.4, 0.5 and 0.6 degrees as well as radar beam at constant altitudes of 200, 500 and 1000 meters from ground level. At the specified times, the radar reflection value was matched to the amount of precipitation obtained from the rainfalls during the same time interval.
In the coordinate system on the vertical axis, the values of log Z (logarithm of reflectivity) were plotted on the horizontal axis and log R (rainfall rainfall intensity logarithm) and correlation between the logarithm of reflection and the logarithm of precipitation were obtained by regression method by which linear equation is extracted where the slope of this line is equal to b and the width of its origin is log a.
For all the studied stations and for both selected precipitation and all selected angles, the values of the new radar parameter were obtained separately and the new values of radar precipitation were estimated with the help of new parameters and the relation .
Using the obtained coefficients, the intensity and total radar rainfall were estimated. The results were different for each station. Regarding estimated radar rainfall values and station distance from the radar, for each station, the optimal beam angle was chosen to have the best estimate of precipitation. In Gorgan, Sari, and Dash-e-Naz ratio of precipitation estimated by radar to rain gauge measurement is about 90 percent. Meanwhile in Babolsar and Banda-e-Gaz the ratio is only 2 percent. Estimated rainfall was 12 percent higher at Gomishan station. At Amol station, it was 25% less than the rain, measured.
Because it was difficult to get radar coefficients for each station as it took a lot of time. So, for the rain event of September 1 and 2, 2015, using the rainfall data of all ground stations and the radar reflection coefficient Z, a general equation was obtained. Comparison of total radar precipitation data before calibration and after calibration, with rainfall values of ground stations, showed that in most stations, the total estimated rainfall data of the radar after calibration, approached the amounts of actual rainfalls. The average rainfall increased from 6.8 mm to 28.5 mm, and just 3 mm lower than the average rain gauges.
Estimated rainfall data in two samples of the hot season of the Amir Abad radar showed that the range of radar parameters was high, and their value was very different from the radar default value. The estimated rainfall was much lower than the rainfall before calibration. If a radar is calibrated for each precipitation and location, the estimated radar precipitation value is very close to what is measured by ground stations. The results of this study showed that radar coefficients are different for each rainfall. It is also different for rainfall that occurs in one area at different times, and this depends on the geographic location and distance from the radar. To achieve better results, the number of additional stations and the number of additional rainfalls should be studied.

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اسکولین، م.، 1392، مقدمه­ای بر سیستم رادار، ترجمه: سهیلی­فرد، م. و آقابابایی، م.، انتشارات ادبستان (ویرایش سوم).
عبدالهی، ب.، حسینی، م. و ابراهیمی، ک.، 1396، ارزیابی داده­های ماهواره­ای CMORPH و
TRMM 3B42RT V7 به منظور تخمین بارش در حوضه­ی گرگانرود، علوم مهندسی و آبخیزداری ایران، 11 (36)، 55-68.
محمدیها، ا.، معماریان، م.ح. و ریحانی­پروری، م.، 1392، ارزیابی برآوردهای رادار هواشناسی تهران از کمیت بارش به‌روش Z-R برای سه رویداد بارش سال­های 2010 و 2011، مجله فیزیک زمین و فضا، 39 (2)، 187-204.
Atlas, D. and Ulbrich, C. W., 1977, Path- and area-integrated rainfall measurement by microwave attenuation in the 1-3 cm band. J. Appl. Meteorol., 16, 1322–1331.
Atlas, D., 1954, The estimation of cloud parameters by radar;Journal of meteorology;309-317
Battan, L. J., 1973, Radar observation of the atmosphere. The University of Chicago Press, Chicago, 324 pp.
Hagen, M. and Yuter, S., 2002, Relations between radar reflectivity, Liquid-water content and rainfall rate durins the MAP SOP; Journal Reserch Meteorological,Vol, 129,477-493
Gunn, R. and Kinzer, G. D., 1949, The terminal velocity of fall for water droplets in stagnant air. J. Meteorol., 6, 243–248.
Josephine, V. S., Mudgal, B. V. and Thampi, S. B., 2014, Applicability of Doppler weather radar based rainfall data for runoff estimation in Indian watersheds – A case study of Chennai basin, Sadhana, Vol. 39: 989–997
Lee, G. W. and Zawadazki, I., 2004,Variability of drop size distribution: Noise and Noise filtering in disdrometric data, Journal of applied meteorology , Vol 44 , 634-652
Lee, G. and Zawadzki, I., 2005, Variability of drop size distributions: time-scale dependence of the variability and its effects on rain estimation, Journal of Applied Meteorology 44(2), 241–255.
Marshall, J. S. and Palmer, W. M., 1948, The distribution of raindrops with size, Journal. Of Meteorological., 5, 165-166.
Marshall, J. S., Langille, R. C. and Palmer, W. M., 1947, Measurment of rainfall by radar;Journal of meteorology ; 186-192.
Marshall, J. S., Hitschfeld, W. and Gunn, K. L. S., 1955, Advances in radar weather, Adv. Geophys., 2, 1–56.
Michela, C., Alberto, D. F., Francesco, D., Marco, M. and Andrea, M., 2008, A Radar-based climatology of convective activity in the Veneto region , foralps, Technical Report, 4, Trento, Italy, 44 pp
Nikahd, A., Hashim, M. and Nazemosadat, M. J., 2016, An improved algorithm in unipolar weather radar calibration for rainfall estimation; Innov. Infrastruct. Solut; 1-11
Overeem, A., Buishand, T. A. and Holleman, I., 2009, Extreme rainfall analysis and estimation Of depth-duration-frequency curves using weather radar, Weter Resources Reserch, Vol. 45: 1-15
Pedersen, l., Jensen, N. E. and Madsen, H., 2010, Calibration of Local Area Weather Radar—Identifying significant factors affecting the calibration; Atmospheric Research 97 129–143
RB5-Manuals-Rainbow Training Manual, 2012.
Rollenbeck, R. and Bendix, V., 2006, Experimental calibration of a cost-effective X-band weather radar for climate ecological studies in southern Ecuador; Atmospheric Research 79 ; 296– 316.
Ryzhkov, A. and Zrnic, D. S., 1995, Precipitation and attenuation measurement at a 10-cm wavelength Journal of applied meteorology , Vol 34;2121-2134
Tokay, A., Hartmann, P. and Battaglia, A., 2008, A Field Study of Reflectivity and Z–R Relations Using Vertically Pointing Radars and Disdrometers, Journal of Atmosphric and Oceanic Technology Vol 26 ,1120-1134
Ulbrich, C. W., 1983, Natural variations in the analytical form of the raindrop size distribution. J. Clim. Appl. Meteorol., 22,1764–1775.
Uijlenhoet, R., 2001, Raindrop size distributions and radar reflectivity–rainrate relationships for radar hydrology. Hydrology and Earth System Sciences 5 (4), 615–627.
Wang, G., Liu, L. and Ding, Y., 2012, Improvement of Radar Quantitative Precipitation Estimation Based on Real-Time Adjustments to Z-R Relationships and Inverse Distance Weighting Correction Schemes Advancesin Atmospheric, Vol. 29, No. 3, 575-584
Zawadzki, I., 1984, Factors affecting the precision of radar measurements of rain. Preprints, 22nd Conf. on Radar Meteorology,Zurich, Switzerland, Amer. Meteor. Soc., 251–256.
Zawadzki, I., 1988, Equilibium raindrop size distributions in tropical rain; Journal of atemosoheric scinces, Vol 45 ,No 22,3552-3559.