- 标题
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- 实验方案
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Terrestrial Remote Sensing of Snowmelt in a Diverse High-Arctic Tundra Environment Using Time-Lapse Imagery
摘要： Snow cover is one of the crucial factors influencing the plant distribution in harsh Arctic regions. In tundra environments, wind redistribution of snow leads to a very heterogeneous spatial distribution which influences growth conditions for plants. Therefore, relationships between snow cover and vegetation should be analyzed spatially. In this study, we correlate spatial data sets on tundra vegetation types with snow cover information obtained from orthorectification and classification of images collected from a time-lapse camera installed on a mountain summit. The spatial analysis was performed over an area of 0.72 km2, representing a coastal tundra environment in southern Svalbard. The three-year monitoring is supplemented by manual measurements of snow depth, which show a statistically significant relationship between snow abundance and the occurrence of some of the analyzed land cover types. The longest snow cover duration was found on 'rock debris' type and the shortest on 'lichen-herb-heath tundra', resulting in melt-out time-lag of almost two weeks between this two land cover types. The snow distribution proved to be consistent over the different years with a similar melt-out pattern occurring in every analyzed season, despite changing melt-out dates related to different weather conditions. The data set of 203 high resolution processed images used in this work is available for download in the supplementary materials.
关键词： tundra vegetation,arctic,snow cover dynamics,snowmelt,orthorectification,time-lapse photography,ground based camera,Svalbard,tundra environment
更新于2025-09-23 15:23:52
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Analyzing carotenoids of snow algae by Raman microspectroscopy and high-performance liquid chromatography
摘要： We tested the potential of Raman microspectroscopy to determine carotenoid pigments — both primary (lutein, beta-carotene) and secondary (astaxanthin) carotenoids — in the different species and life-cycle stages of snow algae from the order Chlamydomonadales (Chlorophyta). We compared the performance of Raman spectrometry to a reference method of biological pigment analysis, high-performance liquid chromatography (HPLC). The three main carotenoid Raman bands of the astaxanthin-rich red cysts were located at 1520, 1156 and 1006 cm-1. The shifts (orange aplanozygotes and green motile cells with flagella) in the position of the ν1(C=C) Raman band of the polyenic chain is consistent with the expected changes in the ratios of the various carotenoid pigments. Flagellated green cells commonly contain lutein as a major carotenoid, together with minor amounts of β-carotene and varying amounts of antheraxanthin, violaxanthin and neoxanthin. Aplanozygotes contain mixtures of both primary and secondary carotenoids. In most cases, the ν1(C=C) band is an overlapping set of bands, which is due to the signal of all carotenoid pigments in the sample, and a deconvolution along with the band position shifts (mainly ν1) could be used to characterize the mixture of carotenoids. However, the ability of Raman spectroscopy to discriminate between structurally slightly differing carotenoid pigments or several carotenoids in an admixture in an unknown biological system remains limited.
关键词： HPLC,Snow algae,Biomarker,Raman spectroscopy,Exobiology,Carotenoids
更新于2025-09-23 15:22:29
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Soil Temperature Variability in Complex Terrain Measured Using Fiber-Optic Distributed Temperature Sensing
摘要： Soil temperature (Ts) exerts critical controls on hydrologic and biogeochemical processes, but the magnitude and nature of Ts variability in a landscape setting are rarely documented. Fiber-optic distributed temperature sensing (DTS) systems potentially measure Ts at high density across a large extent. A fiber-optic cable 771 m long was installed at a depth of 10 cm in contrasting landscape units (LUs) defined by vegetative cover at Upper Sheep Creek in the Reynolds Creek Experimental Watershed (RCEW) and Critical Zone Observatory in Idaho. The purpose was to evaluate the applicability of DTS in remote settings and to characterize Ts variability in complex terrain. Measurement accuracy was similar to other field instruments (±0.4°C), and Ts changes of approximately 0.05°C at a monitoring spatial scale of 1 m were resolved with occasional calibration and an ambient temperature range of 50°C. Differences in solar inputs among LUs were strongly modified by surface conditions. During spatially continuous snow cover, Ts was practically homogeneous across LUs. In the absence of snow cover, daily average Ts was highly variable among LUs due to variations in vegetative cover, with a standard deviation (SD) greater than 5°C, and relatively uniform (SD < 1.5°C) within LUs. Mean annual soil temperature differences among LUs of 5.2°C was greater than those of 4.4°C associated with a 910-m elevation difference within the RCEW. In this environment, effective Ts simulation requires representation of relatively small-scale (<20 m) LUs due to the deterministic spatial variability of Ts.
关键词： landscape units,complex terrain,vegetative cover,fiber-optic cable,snow cover,spatial variability,Soil temperature,distributed temperature sensing
更新于2025-09-23 15:22:29
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Télédétection satellitaire des surfaces enneigées et englacées
摘要： This article presents an overview of recent advances in remote sensing applied to the study of snow and glacierized areas, in which the French scientific community has been involved. Whatever the type of satellite data, optical, radar, lidar or gravimetric, these works on seasonal or perennial snow cover, mountain glaciers, ice caps, sea ice, and lake or river ice, aim at documenting both the physical characteristics of these objects and their spatial and temporal variability at local, regional or global scales.
关键词： glaciers,remote sensing,snow,ice,spatial variability,satellite data,temporal variability
更新于2025-09-23 15:21:21
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Snow Loss Prediction for Photovoltaic Farms Using Computational Intelligence Techniques
摘要： With the recent widespread deployment of Photovoltaic (PV) panels in the northern snow-prone areas, performance analysis of these panels is getting much more importance. Partial or full reduction in energy yield due to snow accumulation on the surface of PV panels, which is referred to as snow loss, reduces their operational efficiency. Developing intelligent algorithms to accurately predict the future snow loss of PV farms is addressed in this article for the first time. The article proposes daily snow loss prediction models using machine learning algorithms solely based on meteorological data. The algorithms include regression trees, gradient boosted trees, random forest, feed-forward and recurrent artificial neural networks, and support vector machines. The prediction models are built based on the snow loss of a PV farm located in Ontario, Canada which is calculated using a 3-stage model and hourly data records over a 4-year period. The stages of the aforementioned model consist of: stage I: yield determination, stage II: power loss calculation, and stage III: snow loss extraction. The functionality of the proposed prediction models is validated over the historical data and the optimal hyperparameters are selected for each model to achieve the best results. Among all the models, gradient boosted trees obtained the minimum prediction error and thus the best performance. The results achieved prove the effectiveness of the proposed models for the prediction of daily snow loss of PV farms.
关键词： snow loss,Intelligent prediction,snowfall,photovoltaic (PV) farm,machine learning
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE Pulsed Power & Plasma Science (PPPS) - Orlando, FL, USA (2019.6.23-2019.6.29)] 2019 IEEE Pulsed Power & Plasma Science (PPPS) - Development of An Electron-Beam Pumped, Argon Fluoride Laser for Inertial Confinement Fusion
摘要： Snow changes its morphology permanently from the moment a snow flake touches the ground. Under the influence of meteorological factors such as temperature, humidity, and wind, snow grains form complex structures of ice bonds enclosing variable portions of air. The characteristics of such structures are important for the formation of snow avalanches. Certain snow types such as surface hoar, ice crusts, or windblown snow play a major role in the formation of weak layers and slabs, which are precondition for dangerous slab avalanches. The reflection properties of snow depend on the optical equivalent grain size of the ice particles that constitute the snow cover. High spatial resolution remote sensing instruments with near-infrared (0.7–1.4 μm) bands are able to detect such differences in the optical reflection of snow. We use normalized difference index band ratios from a spaceborne and an airborne remote sensing instrument to distinguish and map different snow-surface types in the neighborhood of Davos, Switzerland, enabling a valuable visualization of the spatial variability of the snow surface.
关键词： snow,snow avalanches,snow grain size,optical,Near infrared (NIR)
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE International Ultrasonics Symposium (IUS) - Glasgow, United Kingdom (2019.10.6-2019.10.9)] 2019 IEEE International Ultrasonics Symposium (IUS) - Simultaneous dictionary learning and reconstruction from subsampled data in photoacoustic microscopy
摘要： The Global Precipitation Measurement (GPM) Core Observatory will carry a Dual-frequency Precipitation Radar (DPR) consisting of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). In this study, “at-launch” codes of DPR precipitation algorithms, which will be used in GPM ground systems at launch, were evaluated using synthetic data based upon the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. Results from the codes (Version 4.20131010) of the KuPR-only, KaPR-only, and DPR algorithms were compared with “true values” calculated based upon drop size distributions assumed in the synthetic data and standard results from the TRMM algorithms at an altitude of 2 km over the ocean. The results indicate that the total precipitation amounts during April 2011 from the KuPR and DPR algorithms are similar to the true values, whereas the estimates from the KaPR data are underestimated. Moreover, the DPR estimates yielded smaller precipitation rates for rates less than about 10 mm/h and greater precipitation rates above 10 mm/h. Underestimation of the KaPR estimates was analyzed in terms of measured radar re?ectivity ( ) of the KaPR at an altitude of 2 km. The underestimation of the KaPR data was most pronounced during strong precipitation events of (high attenuation cases) over heavy precipitation areas in the Tropics, whereas the underestimation was less pronounced when the (moderate attenuation cases). The results suggest that the underestimation is caused by a problem in the attenuation correction method, which was veri?ed by the improved codes.
关键词： simulation,spaceborne radar,rain,Global Precipitation Measurement (GPM),snow,Tropical Rainfall Measuring Mission (TRMM),Algorithms,attenuation
更新于2025-09-19 17:13:59
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[IEEE 2019 International Conference on Meteorology Observations (ICMO) - Chengdu, China (2019.12.28-2019.12.31)] 2019 International Conference on Meteorology Observations (ICMO) - Comparison Test Method and Analysis between Laser Snow Depth Observation Instrument and Manual Observation
摘要： From the sensor principle and design, data processing algorithm were introduced from the aspects such as a laser automatic viewer deep the snow, and in November 2018 - April 2019,The meteorological detection center of the China meteorological administration carried out a comparison test on the equipment of laser automatic snow depth in Aletai prefecture of Xinjiang in winter.This paper provides a very complete snow depth comparison test method to evaluate and analyze the observation data in terms of accuracy, data stability and data integrity. The differences in the data analyzed by the comprehensive test were mainly caused by the wind speed, the mixture of ice water and the large temperature difference between day and night. Through the consistency analysis between the data of automatic snow depth equipment and the manual standard data, the measurement accuracy reaches the requirements of the "specification for ground meteorological observation". The laser automatic snow depth equipment can continuously and accurately reflect the change of snow cover. Finally, the existing problems of the laser snow depth observation instrument are discussed and some Suggestions for improvement are put forward.
关键词： Contrast test,Experimental difference,Laser automatic snow depth observation instrument,Consistency analysis
更新于2025-09-19 17:13:59
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Observation of the process of snow accumulation on the Antarctic Plateau by time lapse laser scanning
摘要： Snow accumulation is the main positive component of the mass balance in Antarctica. In contrast to the major efforts deployed to estimate its overall value on a continental scale – to assess the contribution of the ice sheet to sea level rise – knowledge about the accumulation process itself is relatively poor, although many complex phenomena occur between snowfall and the definitive settling of the snow particles on the snowpack. Here we exploit a dataset of near-daily surface elevation maps recorded over 3 years at Dome C using an automatic laser scanner sampling 40–100 m2 in area. We find that the averaged accumulation is relatively regular over the 3 years at a rate of +8.7 cm yr?1. Despite this overall regularity, the surface changes very frequently (every 3 d on average) due to snow erosion and heterogeneous snow deposition that we call accumulation by “patches”. Most of these patches (60 %–85 %) are ephemeral but can survive a few weeks before being eroded. As a result, the surface is continuously rough (6–8 cm root-mean-square height) featuring meter-scale dunes aligned along the wind and larger, decameter-scale undulations. Additionally, we deduce the age of the snow present at a given time on the surface from elevation time series and find that snow age spans over more than a year. Some of the patches ultimately settle, leading to a heterogeneous internal structure which reflects the surface heterogeneity, with many snowfall events missing at a given point, whilst many others are overrepresented. These findings have important consequences for several research topics including surface mass balance, surface energy budget, photochemistry, snowpack evolution, and the interpretation of the signals archived in ice cores.
关键词： snow deposition,surface elevation,Antarctic Plateau,laser scanning,snow accumulation,snow erosion
更新于2025-09-16 10:30:52
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Particle swarm optimisation-based model and analysis of photovoltaic module characteristics in snowy conditions
摘要： In this study, a novel methodology of photovoltaic (PV) modelling is proposed to represent the instantaneous electrical characteristics of PV modules covered with snow. The attenuation of the transmitted solar radiation penetrating a layer of snow is rigorously estimated based on the Giddings and LaChapelle theory. This theory introduced the level of radiation that reaches the surface of the PV module through the snowpack, significantly affected by the snow properties and thickness. The proposed modelling approach is based on the single-diode-five-parameter equivalent circuit model. The parameters of the model are updated through instantaneous measurements of voltage and current that are optimised by the particle swarm optimisation algorithm. The proposed approach for modelling snow-covered PV modules was successfully validated in outdoor tests using three different types of PV module technologies typically used in North America's PV farms under different cold weather conditions. In addition, the validity of the proposed model was investigated using real data obtained from the SCADA system of a 12-MW grid-connected PV farm. The proposed model can help to improve PV performance under snow conditions and can be considered a powerful tool for the design and selection of PV modules subjected to snow accretion.
关键词： photovoltaic,Giddings and LaChapelle theory,solar radiation,PV modelling,particle swarm optimisation,SCADA system,snow conditions
更新于2025-09-11 14:15:04