Thursday, 29 September 2011

Grand Ballroom (William Penn Hotel)

Research is focused on the error from A

_{BS}regional radar precipitation estimation equation (Wan et al., 2010). It is pointed out that the presence of μ_{i}misestimate factor of single station is the fundamental reason for radar precipitation estimation error. This misestimate factor is caused by the relative bias between A_{Bi}(from single station observation) and A_{BS}(common coefficient from the whole region). Two important evaluation criterions for precipitation estimation on radar covered region are developed and their analytic expressions are given based on μ_{i}. The first criterion is the regional precipitation misestimate ratio μ_{S}, which is defined as the ratio of the sum of every single station's misestimate value (positive or negative) and the sum of the corresponding station's observed precipitation in the whole region. The misestimate ratio μ_{S}is used to evaluate the estimation error of the regional precipitation gross. The second criterion is the regional precipitation absolute misestimate ratio μ_{|S|}, which is given by the ratio of the sum of every single station's misestimate absolute value and the sum of the corresponding station's observed precipitation in the whole region. The absolute misestimate ratio μ_{|S|}is used to evaluate the gross absolute estimation error of the region and is the most widely used criterion for precipitation estimation error. The value of μ_{|S|}indicates the general polymerization and dispersion degree of A_{Bi}from A_{BS}of every station within the area S . Under the different raingauge network conditions of basic network, intensive network and grouping network, the difference and variance of μ_{|S|}during one same rain event is analyzed. It is revealed that due to the nonuniform distribution of A_{Bi}(the transform coefficient of Z_{B}-Q_{G}relationship on single station) in natural rainfall, the change in the estimated area S and its domain, raingauge network distribution and its density will all lead to different values of μ_{|S|}. This is the uncertainty of precipitation estimation error during radar-raingauge integration. In this paper a new data pair quality control method is proposed called single station misestimate factor μ_{i}control method. This method will decrease the dispersion degree of A_{Bi}from A_{BS}and increase the polymerization degree, thus the regional precipitation absolute misestimate ratio μ_{|S|}is diminished accordingly. Experimental evaluations from Wuhan radars during four rain events give a value μ_{|S|}of less than 30%, which is a 3-5% decrease compared with none quality control. - Indicates paper has been withdrawn from meeting

- Indicates an Award Winner