عنوان مقاله [English]
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.