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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >A comparison of 18 winter seasons of in situ and passive microwave-derived snow water equivalent estimates in Western Canada
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A comparison of 18 winter seasons of in situ and passive microwave-derived snow water equivalent estimates in Western Canada

机译:加拿大西部18个冬季原位和被动微波衍生雪水当量估算值的比较

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The Meteorological Service of Canada (MSC) has developed an operational snow water equivalent (SWE) retrieval algorithm suite for western Canada that can be applied to both Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) data. Separate algorithms derive SWE for open environments, deciduous, coniferous, and sparse forest cover. A final SWE value represents the area-weighted average based on the proportional land cover within each pixel. The combined SSM/I and SMMR time series of dual polarized, multichannel, spaceborne passive microwave brightness temperatures extends back to 1978, providing a lengthy time series for algorithm assessment. In this study, 5-day average (pentad) passive microwave-derived SWE imagery for 18 winter seasons (December, January, February 1978/79 through 1995/96) was compared to SWE estimates taken from a distributed network of surface measurements throughout western Canada. Results indicated both vegetative and snowpack controls on the performance of MSC algorithms. In regions of open and low-density forest cover, the in situ and passive microwave SWE data exhibited both strong agreement and similar levels of interannual variability. In locations where winter season SWE typically exceeded 75 mm, and/or dense vegetative cover was present, dataset agreement weakened appreciably, with little interannual variability in the passive microwave SWE retrievals. These results have important implications for extending the SWE monitoring capability of the MSC algorithm suite to northern regions such as the Mackenzie River basin. Crown Copyright
机译:加拿大气象局(MSC)已为加拿大西部开发了可操作的雪水当量(SWE)检索算法套件,该套件可应用于扫描多通道微波辐射计(SMMR)和特殊传感器微波/成像仪(SSM / I)数据。用于开放环境,落叶,针叶和稀疏森林覆盖的单独算法得出SWE。最终的SWE值表示基于每个像素内的比例土地覆盖的面积加权平均值。双极化,多通道,星载无源微波亮度温度的SSM / I和SMMR组合时间序列可以追溯到1978年,为算法评估提供了一个漫长的时间序列。在这项研究中,比较了18个冬季(1978/12月,1978年2月,79/1995至1995/96年)的5天平均(五元)被动微波衍生的SWE图像与从整个西部地区的分布式表面测量网络获得的SWE估计值加拿大。结果表明营养控制和积雪控制对MSC算法的性能都有影响。在开阔和低密度的森林覆盖地区,原位和被动微波SWE数据显示出强一致性和类似的年际变化水平。在冬季SWE通常超过75毫米和/或存在茂密的植物覆盖的地区,数据集一致性显着减弱,被动微波SWE的年际变化很小。这些结果对于将MSC算法套件的SWE监视功能扩展到北部地区(例如Mackenzie流域)具有重要意义。皇冠版权

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