塞卡亚姆分流域热带降雨测量任务(TRMM)一天最大降雨量数据的修正方程

Roy Binsar Sahat Maruli Tua Simbolon, S. Soeryamassoeka, Umar Umar
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摘要

洪水泛滥可能是因为河流的水量超过了其排水能力。高强度降雨会导致 Sekayam 河在 Sanggau 地区泛滥。洪水控制和管理需要观测站提供最多 1(一)天的降雨量数据。但是,一些观测站仍然需要完整的 1(一)天最大降雨量数据。获取降雨量数据的一个替代方法是利用 TRMM 卫星。然而,由于受到大气层中红外线和微波辐射的干扰,TRMM 卫星生成的数据无法得到充分利用。在使用降雨数据之前,有必要先进行修正。校正是利用通过测试结果获得的校正方程进行的。 测试首先要对观测站降雨量数据进行质量测试,使用数据分析工具进行同质性测试,采用 t 检验法:在 MS.Excel 进行一致性测试,并使用 Worsley Likelihood Ratio Test 方法进行一致性测试。然后,根据观测站数据与 TRMM 卫星降雨量数据的相关系数≥ 0.5 的结果,对 TRMM 卫星降雨量数据进行筛选,筛选出具有同质性和一致性的数据。通过的 TRMM 雨量数据将进入校准和验证阶段。校准阶段得到的、在验证阶段产生最显著相关系数的校正方程将用于校正 TRMM 卫星降雨数据,从而得到校正后的 TRMM 卫星降雨数据。校正后的数据将与校正前的数据再次进行测试,通过均方根误差和相对偏差的结果来检验数据质量。通过数据过滤阶段的 TRMM 降水数据为 21 个网格。TRMM 降雨量数据的修正方程相关系数结果最高的是第 27 网格,其修正方程为 Y = 0.976 x - 10.685,相关系数为 0.737。该修正方程用于修正 21 个已通过数据过滤阶段的网格的降雨量数据。使用修正方程 Y = 0.976 x - 10.685 对 TRMM 雨量数据进行修正后,其 RMSE 和相对偏差结果显示极小,解释结果令人满意,因此可以利用修正方程对 Sekayam 流域的 TRMM 雨量数据进行修正。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CORRECTION EQUATION OF RAINFALL DATA MAXIMUM A DAY ON TROPICAL RAINFALL MEASURING MISSION (TRMM) IN SEKAYAM SUB-WATERSHED
Flooding can occur because the volume of water flowing in a river exceeds its drainage capacity. The high rainfall intensity can cause the Sekayam River to overflow in Sanggau Regency. A maximum of 1 (one) day of rainfall data from observation stations is needed for flood control and management. However, some observation stations still need complete 1 (one) day maximum rainfall data. One alternative that can be used to obtain rainfall data is to utilize the TRMM satellite. However, the data generated by the TRMM satellite cannot be fully utilized due to interference with infrared and microwave radiation in the atmosphere. It is necessary to make corrections first before rainfall data is used. Correction is done using the correction equation obtained through the test results.  Testing begins with quality testing of observation station rainfall data by conducting homogeneity testing using the data analysis tool with the t-test method: two samples assuming equal variances in MS. Excel and consistency testing using the Worsley Likelihood Ratio Test method. Then, the TRMM satellite rainfall data is filtered by looking at the correlation coefficient results with the condition ≥ 0.5 against the observation station data, which has homogeneous and consistent data properties. TRMM rainfall data that passes will go through the calibration and validation stages. The correction equation obtained during the calibration stage and produces the most significant correlation coefficient in the validation stage will be used to correct TRMM satellite rainfall data so that TRMM satellite rainfall data will be obtained after correction. Data after correction will be tested again with data before correction to see the data quality by looking at the results of RMSE and relative bias.The homogeneity and consistency test of observation stations states that all observation stations have homogeneous and consistent results. TRMM rainfall data that passes the data filtering stage is 21 Grids. TRMM rainfall data with a correction equation with the highest correlation coefficient results is on Grid 27 with the correction equation Y = 0.976 x - 10.685 and a correlation coefficient of 0.737. The correction equation is used to correct rainfall data on 21 Grids that have passed the data filtering stage. The results of RMSE and relative bias in TRMM rainfall data after correction using the correction equation Y = 0.976 x - 10.685 show tiny and satisfactory results in interpretation so that the correction equation can be utilized as a correction of TRMM rainfall data in the Sekayam Watershed. 
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