Derivation of a new continuous adjustment function for correcting wind-induced loss of solid precipitation: results of a Norwegian field study
Derivation of a new continuous adjustment function for correcting wind-induced loss of solid precipitation: results of a Norwegian field study
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DOI：
10.5194/hess-19-951-2015
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发表时间：
2015-02
影响因子：
6.3
通讯作者：
M. Wolff;K. Isaksen;A. Petersen‐Øverleir;K. Ødemark;T. Reitan;R. Brækkan
中科院分区：
文献类型：
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作者：
M. Wolff;K. Isaksen;A. Petersen‐Øverleir;K. Ødemark;T. Reitan;R. Brækkan
由于大风条件下的降水量不足，降水测量显示出较大的冷季偏差。这些不确定性影响水平衡计算、积雪监测以及遥感算法和地表模型的校准。更准确的数据将提高预测降雪地区未来水资源变化和山地灾害的能力。 2010年，在挪威南部的山区高原建立了降水测量综合试验场。自动降水计数据与作为参考的双栅比对参考 (DFIR) 防风罩结构中降水计的数据进行比较。大量其他传感器为相关气象参数提供支持数据。本文利用三个冬季的数据来研究和确定风引起的固体降水量不足。定性分析和贝叶斯统计用于评估和客观地选择最能描述数据的模型。针对所有类型的冬季降水（从雨到干雪）的测量导出了连续调整函数及其不确定性。回归分析并未揭示调整函数的任何重大错误指定，但表明所选模型并未最佳地描述回归噪声。该调整功能在操作上可用，因为它仅基于标准自动气象站可用的数据。结果表明，冬季降水事件期间，捕获量不足与风速之间存在非线性关系，并且存在明显的温度依赖性，主要反映了降水类型。该结果首次允许基于 7 m s -1 以上的测量推导调整函数。调整函数的这种扩展有效性表明风引起的降水损失对于较高风速而言是稳定的。
Precipitation measurements exhibit large cold-season biases due to under-catch in windy conditions. These uncertainties affect water balance calculations, snowpack monitoring and calibration of remote sensing algorithms and land surface models. More accurate data would improve the ability to predict future changes in water resources and mountain hazards in snow-dominated regions. In 2010, a comprehensive test site for precipitation measurements was established on a mountain plateau in southern Norway. Automatic precipitation gauge data are compared with data from a precipitation gauge in a Double Fence Intercomparison Reference (DFIR) wind shield construction which serves as the reference. A large number of other sensors are provided supporting data for relevant meteorological parameters. In this paper, data from three winters are used to study and determine the wind-induced under-catch of solid precipitation. Qualitative analyses and Bayesian statistics are used to evaluate and objectively choose the model that best describes the data. A continuous adjustment function and its uncertainty are derived for measurements of all types of winter precipitation (from rain to dry snow). A regression analysis does not reveal any significant misspecifications for the adjustment function, but shows that the chosen model does not describe the regression noise optimally. The adjustment function is operationally usable because it is based only on data available at standard automatic weather stations. The results show a non-linear relationship between under-catch and wind speed during winter precipitation events and there is a clear temperature dependency, mainly reflecting the precipitation type. The results allow, for the first time, derivation of an adjustment function based on measurements above 7 m s −1 . This extended validity of the adjustment function shows a stabilization of the wind-induced precipitation loss for higher wind speeds.