Representativity of in situ precipitation measurements - A case study for the LITFASS area in North-Eastern Germany
Representativity of in situ precipitation measurements - A case study for the LITFASS area in North-Eastern Germany
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DOI：
10.1016/j.jhydrol.2011.01.052
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发表时间：
2011-04
影响因子：
6.4
通讯作者：
S. Bohnenstengel;K. H. Schluenzen;F. Beyrich
中科院分区：
文献类型：
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作者：
S. Bohnenstengel;K. H. Schluenzen;F. Beyrich
现场测量的降雨量在空间和时间上可能会有极大的差异。考虑到单个站点的时空代表性有限和不确定性，对于验证中尺度数值模式的结果以及解释遥感数据都很重要。分析了来自德国东北部一个高分辨率网络的现场降水数据，以确定它们的时间和空间代表性。2003年干旱年，分布在林登堡气象台(理查德-阿贝曼天文台)周围25公里×25公里范围内的14个雨量计以10分钟的分辨率提供了降雨量。我们的分析表明，短期(长达6小时)降水事件占主导地位(占所有事件的94%)，而且这种分布是倾斜的，降水量很低的频率很高。持续时间长的降水事件很少见(占所有降水事件的6%)，但占年降水量的近50%。随着测量间隔的延长，单点测量的空间代表性略有增加，变异性减小。在11公里×11公里的地区，每小时降水量具有代表性。对于25公里×25公里的区域，日降水量似乎是可靠的，不确定系数为3.3，与25公里×25公里的平均值相比，周和月降水量的不确定系数分别为2和1.4。
In situ precipitation measurements can extremely differ in space and time. Taking into account the limited spatial–temporal representativity and the uncertainty of a single station is important for validating mesoscale numerical model results as well as for interpreting remote sensing data. In situ precipitation data from a high resolution network in North-Eastern Germany are analysed to determine their temporal and spatial representativity. For the dry year 2003 precipitation amounts were available with 10min resolution from 14 rain gauges distributed in an area of 25km×25km around the Meteorological Observatory Lindenberg (Richard-Aßmann Observatory). Our analysis reveals that short-term (up to 6h) precipitation events dominate (94% of all events) and that the distribution is skewed with a high frequency of very low precipitation amounts. Long-lasting precipitation events are rare (6% of all precipitation events), but account for nearly 50% of the annual precipitation. The spatial representativity of a single-site measurement increases slightly for longer measurement intervals and the variability decreases. Hourly precipitation amounts are representative for an area of 11km×11km. Daily precipitation amounts appear to be reliable with an uncertainty factor of 3.3 for an area of 25km×25km, and weekly and monthly precipitation amounts have uncertainties of a factor of 2 and 1.4 when compared to 25km×25km mean values.