oalib
Search Results: 1 - 10 of 100 matches for " "
All listed articles are free for downloading (OA Articles)
Page 1 /100
Display every page Item
A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model
S. Kolberg, H. Rue,L. Gottschalk
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2006,
Abstract: A method for assimilating remotely sensed snow covered area (SCA) into the snow subroutine of a grid distributed precipitation-runoff model (PRM) is presented. The PRM is assumed to simulate the snow state in each grid cell by a snow depletion curve (SDC), which relates that cell's SCA to its snow cover mass balance. The assimilation is based on Bayes' theorem, which requires a joint prior distribution of the SDC variables in all the grid cells. In this paper we propose a spatial model for this prior distribution, and include similarities and dependencies among the grid cells. Used to represent the PRM simulated snow cover state, our joint prior model regards two elevation gradients and a degree-day factor as global variables, rather than describing their effect separately for each cell. This transformation results in smooth normalised surfaces for the two related mass balance variables, supporting a strong inter-cell dependency in their joint prior model. The global features and spatial interdependency in the prior model cause each SCA observation to provide information for many grid cells. The spatial approach similarly facilitates the utilisation of observed discharge. Assimilation of SCA data using the proposed spatial model is evaluated in a 2400 km2 mountainous region in central Norway (61° N, 9° E), based on two Landsat 7 ETM+ images generalized to 1 km2 resolution. An image acquired on 11 May, a week before the peak flood, removes 78% of the variance in the remaining snow storage. Even an image from 4 May, less than a week after the melt onset, reduces this variance by 53%. These results are largely improved compared to a cell-by-cell independent assimilation routine previously reported. Including observed discharge in the updating information improves the 4 May results, but has weak effect on 11 May. Estimated elevation gradients are shown to be sensitive to informational deficits occurring at high altitude, where snowmelt has not started and the snow coverage is close to unity. Caution is therefore required when using early images. Final Revised Paper (PDF, 2504 KB) Discussion Paper (HESSD) Citation: Kolberg, S., Rue, H., and Gottschalk, L.: A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model, Hydrol. Earth Syst. Sci., 10, 369-381, doi:10.5194/hess-10-369-2006, 2006. Bibtex EndNote Reference Manager XML
Snow satellite images for calibration of snow dynamic in a continuous distributed hydrological model
C. Corbari,J. Martinelli,G. Ravazzani,M. Mancini
Hydrology and Earth System Sciences Discussions , 2007,
Abstract: The snow accumulation and melt processes are well known to play an important role on the river flow regime, in particular this is enhanced for basin with complex topography where the snow dynamic is strongly affected by hillslope exposition. This paper presents a simplified numerical model for snow dynamic simulation based on air temperature thresholds that rule the snow melt and accumulation processes implemented into a continuous distributed hydrological model for hydrograph simulations at basin scale. The possibility to calibrate these temperature thresholds from snow cover maps derived from NOAA satellite images is discussed. Snow covered pixels are classified according to a procedure based on aspect and elevation of each pixel, that allows to identify snow covered pixels also in shadowed areas. Snow model performance is proved at local and basin scale. The former shows a good agreement between modelled snow dynamic and observed snow height data at the Antrona station in the Toce basin; the latter shows agreement between observed and simulated hydrographs for the three gauge stations of Toce, Ticino and Maggia rivers.
Iodine and Bromine speciation in snow and the effect of elevation  [PDF]
B. S. Gilfedder,M. Petri,H. Biester
Atmospheric Chemistry and Physics Discussions , 2007,
Abstract: Iodine is an essential trace element for all mammals and may also influence climate through new aerosol formation. Atmospheric bromine cycling is also important due to its well-known ozone depletion capabilities. Despite precipitation being the ultimate source of iodine in the terrestrial environment, the processes effecting the distribution, speciation and transport of these elements are relatively unknown. The aim of this study was to determine the effect of orographic lifting on iodine concentrations and also quantify inorganic and organic iodine and bromine species. Snow samples were collected over an altitude profile (~800 m) from the northern Black Forest and were analysed (IC-ICP-MS) for iodine and bromine species and trace metals (ICP-MS). All elements and species showed a significant (r2>0.65) inverse relationship with altitude despite the short (5 km) horizontal distance of the transect. In fact, total iodine more than halved (38 to 13 nmol/l) over the 800 m height change. The results suggest that orographic lifting of cloud masses has a major influence on iodine levels in precipitation and is perhaps more important than lateral distances in determining iodine concentrations in terrestrial precipitation. The microphysical removal process was common to all elements. We also show that organically bound iodine is the dominant iodine species in snow (61–75%), followed by iodide. Iodate was only found in two samples despite a detection limit of 0.3 nmol/l. Two unknown but most likely anionic organo-I species were also identified in IC-ICP-MS chromatograms and comprised 2–10% of the total iodine. The majority of the bromine was inorganic bromide with a max.~of 32% organo-Br.
Topographic control of snow distribution in an alpine watershed of western Canada inferred from spatially-filtered MODIS snow products
J. Tong, S. J. Déry,P. L. Jackson
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2009,
Abstract: A spatial filter (SF) is used to reduce cloud coverage in Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow cover extent products (MOD10A2) from 2000–2007, which are obtained from MODIS daily snow cover extent products (MOD10A1), to assess the topographic control on snow cover fraction (SCF) and snow cover duration (SCD) in the Quesnel River Basin (QRB) of British Columbia, Canada. Results show that the SF reduces cloud coverage and improves by 2% the accuracy of snow mapping in the QRB. The new product developed using the SF method shows larger SCF and longer SCD than MOD10A2, with higher altitudes experiencing longer snow cover and perennial snow above 2500 m. The gradient of SCF with elevation (d(SCF)/dz) during the snowmelt season is 8% (100 m) 1. The average ablation rates of SCF are similar for different 100 m elevation bands at about 5.5% (8 days) 1 for altitudes <1500 m with decreasing values with elevation to near 0% (8 days) 1 for altitudes >2500 m. Different combinations of slopes and aspects also affect the SCF with a maximum difference of 20.9% at a given time. Correlation coefficients between SCD and elevation attain 0.96 (p<0.001). Mean gradients of SCD with elevation are 3.8, 4.3, and 11.6 days (100 m) 1 for the snow onset season, snowmelt season, and entire year, respectively. The SF decreases the standard deviations of SCDs compared to MOD10A2 with a maximum difference near 0.6 day, 0.9 day, and 1.0 day for the snow onset season, snowmelt season, and entire year, respectively.
Topographic control of snow distribution in an alpine watershed of western Canada inferred from spatially-filtered MODIS snow products
J. Tong,S. J. Déry,P. L. Jackson
Hydrology and Earth System Sciences Discussions , 2008,
Abstract: A spatial filter (SF) is used to reduce cloud coverage in MODIS 8-day maximum snow cover extent products (MOD10A2) from 2000–2007 to assess the topographic control on snow cover fraction (SCF) and snow cover duration (SCD) in the Quesnel River Basin (QRB) of British Columbia, Canada. Results show that the SF reduces cloud coverage and improves by 2% the accuracy of snow mapping in the QRB. The SF shows larger SCF and longer SCD than MOD10A2, with higher altitudes experiencing longer snow cover and perennial snow above 2500 m. The gradient of SCF with elevation (d(SCF)/d(elevation)) during the snowmelt season is 8% (100 m) 1. The average melt rates of SCF are similar for different 100 m elevation bands at about 5.5% (8 days) 1 for altitudes <1500 m with decreasing values with elevation to near 0% (8 days) 1 for altitudes >2500 m. Different combinations of slopes and aspects also affect the SCF with a maximum difference of 20.9% at a given time. Correlation coefficients between SCD and elevation attain 0.96 (p<0.001). Mean gradients of SCD with elevation are 3.8, 4.3, and 11.6 days (100 m) 1 for the snow onset, snowmelt, and entire year, respectively. The SF decreases the standard deviations of SCDs compared to MOD10A2 with a maximum difference near 0.63 days, 0.89 days, and 1.04 days for the snow onset, snowmelt and entire year, respectively.
The impact of different elevation steps on simulation of snow covered area and the resulting runoff variance
J. Bellinger, S. Achleitner, J. Sch ber, F. Sch berl, R. Kirnbauer,K. Schneider
Advances in Geosciences (ADGEO) , 2012,
Abstract: This study analyses the impact of vertical model discretisation on modelling snow covered area and the consequential effects on runoff formation of the semi-distributed water balance model HQsim. Therefore, the parameters relevant for snow modelling are varied within the frame of a uniformly distributed Monte Carlo Simulation (MCS). Since the model is based on the hydrological response unit (HRU) approach, the effect of building the HRUs with different elevation steps (250 m and 500 m) is tested for two alpine catchments. In total 5000 parameter combinations were generated for simulation. The results of modelled snow covered area were compared with thirty MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover maps for the melting periods in 2003–2011. Based on a contingency table the comparisons were evaluated by different skill measures. Finally, the pareto optimal parameter settings of each skill measure were detected. Evaluation of runoff variability within the MCS and their pareto optimal runs show reduced variances of model output resulting from an improved simulation of the snow covered area.
Elemental composition in surface snow from the ultra-high elevation area of Mt. Qomolangma (Everest)
Elemental composition in surface snow from the ultra-high elevation area of Mt. Qomolangma (Everest)

ZHANG QiangGong,KANG ShiChang,CONG ZhiYuan,HOU ShuGui,LIU YongQin,

科学通报(英文版) , 2008,
Abstract: A total of 14 surface snow (0–10 cm) samples were collected along the climbing route (6500–8844 m a.s.l.) on the northern slope of Mt. Qomolangma in May, 2005. Analysis of elemental concentrations in these samples showed that there are no clear trends for element variations with elevation due to redistribution of surface snow by strong winds during spring. In addition, local crustal aerosol inputs also have an influence on elemental composition of surface snow. Comparison between elemental concentration datasets of 2005 and 1997 indicated that data from 2005 were of higher quality. Elemental concentrations (especially for heavy metals) at Mt. Qomolangma are comparable with polar sites, and far lower than large cities. This indicates that anthropogenic activities and heavy metal pollution have little effect on the Mt. Qomolangma atmospheric environment, which can be representative of the background atmospheric environment. Supported by the National Natural Science Foundation of China (Grant Nos. 40401054, 90411003 and 40121101), the National Basic Research Program of China (Grant No.2005CB422004), Social Commonweal Research Project of Ministry of Science and Technology of China (Grant No.2005DIA3J106),the “Talent Project” and Innovation Project (Grant No.KZCX3-SW-334/339) of CAS, and Dean Foundation of CAS
Elemental composition in surface snow from the ultra-high elevation area of Mt. Qomolangma (Everest)
QiangGong Zhang,ShiChang Kang,ZhiYuan Cong,ShuGui Hou,YongQin Liu
Chinese Science Bulletin , 2008, DOI: 10.1007/s11434-007-0446-z
Abstract: A total of 14 surface snow (0–10 cm) samples were collected along the climbing route (6500–8844 m a.s.l.) on the northern slope of Mt. Qomolangma in May, 2005. Analysis of elemental concentrations in these samples showed that there are no clear trends for element variations with elevation due to redistribution of surface snow by strong winds during spring. In addition, local crustal aerosol inputs also have an influence on elemental composition of surface snow. Comparison between elemental concentration datasets of 2005 and 1997 indicated that data from 2005 were of higher quality. Elemental concentrations (especially for heavy metals) at Mt. Qomolangma are comparable with polar sites, and far lower than large cities. This indicates that anthropogenic activities and heavy metal pollution have little effect on the Mt. Qomolangma atmospheric environment, which can be representative of the background atmospheric environment.
Quantitative analysis of snow water equivalent in the region of northern Xinjiang
新疆北疆地区雪水当量遥感定量研究

LIU Yan,ZHANG Pu,LI Yang,
刘艳
,张璞,李杨

红外与毫米波学报 , 2011,
Abstract: The purpose of the study was to approach the feasibility of the snow water equivalent retrieved with optical remote sensing data. Field measurement for separate layer snow density and other snow parameters was made in Feb 2009 and 2010. For different snow types, by using continuum removal method, spectral absorption characteristics of snow were analyzed. It comes to the conclusion that snow depth has a significant effect on its spectral absorption at near 1028nm, 1252nm, 1494nm and 1940nm. The deeper the depth, the smaller the absorption depth is. The image of moderate-resolution imaging spectroradiometer with spatial 500m resolution was used as the experimental optical remote sensing data in this study. Based on correlation analysis of the test sample, including reflectance of MODIS channel 5 and 6, elevation and snow pressure, the remote sensing model for the retrieval of snow pressure was built by statistical regression equations. The evaluation results of the model showed that its root mean square error is 0.075 and correlation coefficient between predicted and measured values is 0.72 when snow depth is less than 30 cm.
Simulation of snow accumulation and melt in needleleaf forest environments
C. R. Ellis, J. W. Pomeroy, T. Brown,J. MacDonald
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2010,
Abstract: Drawing upon numerous field studies and modelling exercises of snow processes, the Cold Regions Hydrological Model (CRHM) was developed to simulate the four season hydrological cycle in cold regions. CRHM includes modules describing radiative, turbulent and conductive energy exchanges to snow in open and forest environments, as well as account for losses from canopy snow sublimation and rain evaporation. Due to the physical-basis and rigorous testing of each module, there is a minimal need for model calibration. To evaluate CRHM, simulations of snow accumulation and melt were compared to observations collected at paired forest and clearing sites of varying latitude, elevation, forest cover density, and climate. Overall, results show that CRHM is capable of characterising the variation in snow accumulation between forest and clearing sites, achieving a model efficiency of 0.51 for simulations at individual sites. Simulations of canopy sublimation losses slightly overestimated observed losses from a weighed cut tree, having a model efficiency of 0.41 for daily losses. Good model performance was demonstrated in simulating energy fluxes to snow at the clearings, but results were degraded from this under forest cover due to errors in simulating sub-canopy net longwave radiation. However, expressed as cumulative energy to snow over the winter, simulated values were 96% and 98% of that observed at the forest and clearing sites, respectively. Overall, the good representation of the substantial variations in mass and energy between forest and clearing sites suggests that CRHM may be useful as an analytical or predictive tool for snow processes in needleleaf forest environments.
Page 1 /100
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.