Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

Analysis of snowpack dynamics during the spring melt season for a sub‐alpine site using point measurements and numerical modeling

Snowpack dynamics through October 2014–June 2017 were described for a forested, sub‐alpine field site in southeastern Wyoming. Point measurements of wetness and density were combined with numerical modeling and continuous time series of snow depth, snow temperature, and snowpack outflow to identify 5 major classes of distinct snowpack conditions. Class (i) is characterized by no snowpack outflow and variable average snowpack temperature and density. Class (ii) is characterized by short durations of liquid water in the upper snowpack, snowpack outflow values of 0.0008–0.005 cm hr^?1, an increase in snowpack temperature, and average snow density between 0.25–0.35 g cm^?3. Class (iii) is characterized by a partially saturated wetness profile, snowpack outflow values of 0.005–0.25 cm hr^?1, snowpack temperature near 0 °C, and average snow density between 0.25–0.40 g cm^?3. Class (iv) is characterized by strong diurnal snowpack outflow pattern with values as high as 0.75 cm hr^?1, stable snowpack temperature near 0 °C, and stable average snow density between 0.35–0.45 g cm^?3. Class (v) occurs intermittently between Classes (ii)–(iv) and displays low snowpack outflow values between 0.0008–0.04 cm hr^?1, a slight decrease in temperature relative to the preceding class, and similar densities to the preceding class. Numerical modeling of snowpack properties with SNOWPACK using both the Storage Threshold scheme and Richards' equation was used to quantify the effect of snowpack capillarity on predictions of snowpack outflow and other snowpack properties. Results indicate that both simulations are able to predict snow depth, snow temperature, and snow density reasonably well with little difference between the 2 water transport schemes. Richards' equation more accurately simulates the timing of snowpack outflow over the Storage Threshold scheme, especially early in the melt season and at diurnal timescales.     

An examination of snow redistribution over smooth land‐fast sea ice

An understanding of temporal evolution of snow on sea ice at different spatial scales is essential for improvement of snow parameterization in sea ice models. One of the problems we face, however, is that long‐term climate data are routinely available for land and not for sea ice. In this paper, we examine the temporal evolution of snow over smooth land‐fast first‐year sea ice using observational and modelled data. Changes in probability density functions indicate that depositional and drifting events control the evolution of snow distribution. Geostatistical analysis suggests that snowdrifts increased over the study period, and the orientation was related to the meteorological conditions. At the microscale, the temporal evolution of the snowdrifts was a product of infilling in the valleys between drifts. Results using two shore‐based climate reporting stations (Paulatuk and Tuktoyuktuk, NWT) suggest that on‐ice air temperature and relative humidity can be estimated using air temperature recorded at either station. Wind speed, direction and precipitation on ice cannot be accurately estimated using meteorological data from either station. The temporal evolution of snow distribution over smooth land‐fast sea ice was modelled using SnowModel and four different forcing regimes. The results from these model runs indicate a lack of agreement between observed distribution and model outputs. The reasons for these results are lack of meteorological measurements prior to the end of January, lack of spatially adequate surface topography and discrepancies between meteorological variables on land and ice. Copyright © 2009 John Wiley & Sons, Ltd.     

Etude isotopique de la pluie et de la neige sur le Mont Liban: premiers résultats / Isotope study of snow and rain on Mount Lebanon: preliminary results

Résumé

Résumé Quelques analyses isotopiques préliminaires ont été réalisées sur les précipitations pluvio-neigeuses, sur un profil de neige et sur deux sources karstiques sur le Mont Liban. Elles confirment la variabilité saisonnière du signal atmosphérique et en particulier que l’excès en deutérium est en relation avec l’origine des masses d’air et avec les recharges de vapeur sur la Méditerranée. Elles montrent également une relative stabilité du signal isotopique du couvert neigeux, peu ou pas influencé par les phénomènes de sublimation, d’évaporation ou de fonte/regel. La participation progressive de la fonte du manteau neigeux à l’alimentation des sources karstiques est qualitativement observée.     

Monitoring over‐winter soil water dynamics in a freezing and snow‐covered environment using a thermally insulated tensiometer

Water potential below a frozen soil layer was continuously monitored over an entire winter period (using thermally insulated tensiometers sheltered in a heated chamber) along with other soil, snow and atmospheric variables. In early winter, the freezing front advanced under a thin snow cover, inducing upward soil water flow in the underlying unfrozen soil. The freezing front started to retreat when the snow cover became thick enough to insulate the soil, resulting in the reversal of the flow direction in the unfrozen zone. These data provide a clear illustration of soil water dynamics, which have rarely been monitored with a tensiometer. Copyright © 2005 John Wiley & Sons, Ltd.     

Contained density currents with high volume of release

Contained density currents with high volume of release reflect against the boundaries of the reception environment commonly leading to oscillatory flow. These flows exist in sediment clarifiers, compromising their operations, and deposited signatures of contained turbidity currents are found as part of the infill of sedimentary basins; for operation of the former and interpretation of the latter it is essential to understand the dynamic processes of these flows. Six lock‐exchange experiments with different initial densities were made in a horizontal flume, where the volume of the saline mixture in the lock was equivalent to the volume of the ambient fluid. A further two tests, with a repeated initial density, were made: one with high volume of release and very long duration; and another with low volume of release. Firstly, the movement of the current is discussed, including the oscillations within the experimental tank involving the density current and an upper layer counter‐current. It is shown that the cyclic behaviour is self‐similar with the reduced gravity of the initial density in the lock. Secondly, entrainment and water mixing processes are characterized. The time evolution of mixing is characterized qualitatively by analysing the background potential energy of the density distributions to show that mixing occurs even in the earlier stages of the current, and mainly within the first cycle of the oscillation. Quantified analysis reveals that, in currents with high volume of release, entrainment discharge is one order of magnitude higher, mainly due to the larger interface between the ambient fluid and the current. A model for the evolution of the mixing process is proposed for density currents with high volume of release. Finally, the dynamics of the head of the current is analysed. The entrainment in the head, when compared to the entrainment in the remainder body of the flows, is less important for the configuration with a larger lock.     

Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R² = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding.     

利用多光谱卫星遥感和深度学习方法进行青藏高原积雪判识

青藏高原积雪对全球气候变化十分重要,针对已有积雪遥感判识方法中普遍采用的可见光与红外光谱数据易受复杂地形与高海拔影响,导致青藏高原地区积雪判识精度较低的问题,提出了一种基于多光谱遥感与地理信息数据特征级融合的积雪遥感判识方法:以风云三号卫星可见光与红外多光谱遥感资料与多要素地理信息作为数据源,由地面实测雪深数据与现有积雪产品交叉筛选出样本标签,构建并训练基于层叠去噪自编码器(SDAE)的特征融合与分类网络,从而有效辨识青藏高原遥感图像中的云、积雪以及无雪地表。经地面实测雪深数据验证,该方法分类精度显著高于使用相同数据源的FY-3A/MULSS积雪产品,略高于国际主流积雪产品MOD10A1与MYD10A1,并且年均云覆盖率最低。试验结果表明该方法可有效地减少云层对积雪判识的干扰,提升分类精度。     

基于规则格网的DEM插值实验

通过地形建模,将6个地形隶属函数按照101×101,112×112,126×126,144×144,168×168,201×201,257×257 7种格网密度生成6种局部地形单元的规则格网DEM;使用反距离加权(IDW)等7种插值算法,将前6种格网密度下的DEM插值成257×257规格;从原始257×257DEM中随机抽取检查点计算残差,并对残差中误差进行分析。通过分组插值实验,运用控制变量法、方差分析等方法研究地貌类型、采样密度和插值算法对DEM插值精度的影响。     

基于重力全张量数据的Parker-Oldenburg算法研究

相比重力数据,重力张量数据通常包含更多的异常信息。本文根据重力数据与重力张量数据的关系,利用位场转化技术,将重力张量数据应用于传统的Parker-Oldenburg密度界面反演算法中。通过模型试验,证明了在网格间距较大或者数据存在一定噪音时,使用本文算法进行反演能得到更好的效果。实验结果说明利用重力张量数据可以有效地提高密度界面反演的分辨率。