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Study of method for synthetic precipitation data for ungauged sites using quantitative precipitation model

机译:基于定量降水模型的非灌流场地合成降水数据方法研究

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A method was developed to estimate a synthetic precipitation record for ungauged sites using irregular coarse observations. The proposed synthetic precipitation data were produced with ultrahigh hourly resolution on a regular 1 x 1 km grid. The proposed method was used to analyze selected real-time observational data collected in South Korea from 2010 to the end of 2014. The observed precipitation data were measured using the Automatic Weather System and Automated Synoptic Observing System. The principal objective of the proposed method was to estimate the additional effects of orography on precipitation introduced by ultrahigh- resolution (1 x 1 km) topography provided by a digital elevation model. The Global Forecast System analysis of the National Centers for Environmental Prediction was used for the upper-atmospheric conditions, necessary for estimating the orographic effects. Precipitation data from 48 of the more than 600 observation sites used in the study, which matched the grid points of the synthetic data, were not included in the synthetic data estimation. Instead, these data were used to evaluate the proposed method by direct comparison with the real observations at these sites. A bias score was investigated by comparison of the synthetic precipitation data with the observations. In this comparison, the number of Hit, False, Miss, and Correct results for 2010-2014 was 74738, 25778, 7544, and 367981, respectively. In the Hit cases, the bias score was 1.22 and the correlation coefficient was 0.74. The means of the differences between the synthetic data and the observations were 0.3, -3.9, -14.4, and -34.9 mm h(-1) and the root mean square errors (RMSEs) were 2.7, 8.3, 19.3, and 39.6 mm h(-1) for the categories of 0.5-10.0, 10.0-30.0, 30.0-50.0, and 50.0-100.0 mm h(-1), respectively. In addition, in each range, the 60% difference between the synthetic precipitation data and the observation data was -1.5 to +1.5, -5.0 to +5.0, -17.0 to +17.0, and -33.0 to +33.0 mm h(-1), respectively. Overall, the correlation coefficient of the synthetic precipitation data was > 0.7 for 43 of the 48 test stations and the RMSE was < 4 mm h(-1) at 31 stations. The results are significant at all evaluation stations at the 0.05 significance level.
机译:开发了一种方法,可以使用不规则的粗略观测来估算未加水位的合成降水记录。拟议的合成降水数据是在常规的1 x 1 km网格上以超高的每小时分辨率生成的。该方法用于分析从2010年到2014年底在韩国收集的部分实时观测数据。使用自动天气系统和自动天气观测系统对观测到的降水数据进行了测量。提出的方法的主要目的是估计地形对数字高程模型提供的超高分辨率(1 x 1 km)地形引入的降水的附加影响。国家环境预报中心的全球预报系统分析被用于高气压条件,这是估计地形影响的必要条件。来自研究中使用的600多个观测点中的48个的降水数据与合成数据的网格点相匹配,不包括在合成数据估计中。取而代之的是,这些数据通过与这些站点上的实际观测值直接比较而用于评估所提出的方法。通过将合成降水数据与观测值进行比较,研究了偏倚得分。在此比较中,2010-2014年的命中,错误,未命中和正确结果的数量分别为74738、25778、7544和367981。在命中案例中,偏差得分为1.22,相关系数为0.74。合成数据与观测值之间的差异的平均值为0.3,-3.9,-14.4和-34.9 mm h(-1),均方根误差(RMSE)为2.7、8.3、19.3和39.6 mm h (-1)分别用于0.5-10.0、10.0-30.0、30.0-50.0和50.0-100.0 mm h(-1)。此外,在每个范围内,合成降水量数据与观测数据之间的60%差异为-1.5至+ 1.5,-5.0至+ 5.0,-17.0至+17.0和-33.0至+33.0 mm h(-1 ), 分别。总体而言,对于48个测试站中的43个,合成降水数据的相关系数> 0.7,而31个站的RMSE <4 mm h(-1)。结果在所有评估站中的显着性水平为0.05。

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