首页|Comparison of bulk snow density measurements using different methods

Comparison of bulk snow density measurements using different methods

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
Snow density is one of the basic properties used to describe snow cover characteristics,and it is critical for remote sensing retrieval,water resources assessment and modeling inputs.There are many instruments available to measure snow density in situ.However,there are mea-surement errors of snow density for bulk and layers or gravimetric and electronic instruments,which may affect the accuracy of remote sensing retrieval and model simulation.Especially in China,due to the noticeable heterogeneity of snowpacks,it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions.This study evaluated the performance of different snow density instruments:the Federal Sampler,the model VS-43 snow density cylinder(VS-43),the wedge snow density cutter(WC1000 and WC250),and the Snow Fork.The average bulk snow density of all instrument measurements was set as the reference value for evaluation.The results showed that as compared with the reference,the VS-43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE(11 kg m-3),BIAS(3 kg m-3),and MRE(1.6％).For layer observation,bulk snow density was overestimated by 8.1％with WC1000 and underestimated by 11.4％with Snow Fork which was the worst performance compared with the reference value,and there were greater measurement errors of snow density in the depth hoar than other snow layers.Compared with grassland,the uncertainty of snow density measurements was slightly lower in forests.Overall,the Federal Sampler and VS-43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China,and it is recommended to use WC1000,WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.

Snow densityMeasurementUncertainty comparison

Hang SU、Xin-Yue ZHONG、Bin CAO、Yuan-Tao HU、Lei ZHENG、Tingjun ZHANG

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State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan,430072,China

Key Laboratory of Remote Sensing of Gansu Province,Heihe Remote Sensing Experimental Research Station,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China

Key Laboratory of Tibetan Plateau Earth System,Environment and Resources,National Tibetan Plateau Data Center Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100101,China

Climate Centre of Shaanxi Province,Xi'an,710000,China

School of Geospatial Engineering and Science,Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China

Key Laboratory of Western China s Environmental Systems(Ministry of Education),College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China

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2024

10.1016/j.accre.2024.07.005

气候变化研究进展(英文版)
国家气候中心

气候变化研究进展(英文版)

影响因子：0.806
ISSN：1674-9278
年,卷(期)：2024.15(4)