An artificial neural network-based snow cover predictive modeling in the higher Himalayas

With trends indicating increase in temperature and decrease in winter precipitation, a significant negative trend in snow-covered areas has been identified in the last decade in the Himalayas. This requires a quantitative analysis of the snow cover in the higher Himalayas. In this study, a nonlinear autoregressive exogenous model, an artificial neural network （ANN）, was deployed to predict the snow cover in the Kaligandaki river basin for the next 30 years. Observed climatic data, and snow covered area was used to train and test the model that captures the gross features of snow under the current climate scenario. The range of the likely effects of climate change on seasonal snow was assessed in the Himalayas using downscaled temperature and precipitation change projection from - HadCM3, a global circulation model to project future climate scenario, under the AIB emission scenario, which describes a future world of very rapid economic growth with balance use between fossil and non-fossil energy sources. The results show that there is a reduction of 9% to 46% of snow cover in different elevation zones during the considered time period, i.e., 2Oll to 2040. The 4700 m to 52oo m elevation zone is the most affected area and the area higher than 5200 m is the least affected. Overall, however, it is clear from the analysis that seasonal snow in the Kaligandaki basin is likely to be subject to substantialchanges due to the impact of climate change.     

Effect of snow-cover duration on plant species diversity of alpine meadows on the eastern Qinghai-Tibetan Plateau

Although snow cover plays an important role in structuring plant diversity in the alpine zone, there are few studies on the relationship between snow cover and species diversity of alpine meadows on the eastern Qinghai-Tibetan Plateau. To assess the effect of snow cover on plant species diversity of alpine meadows, we used ten parallel transects of 60 m × 1 m for this study and described the changes in species diversity and composition associated with snow depth. With the division of snow depth into six classes, the highest species richness （S） and species diversity （H′） occurred with an intermediate snow depth, i.e., class Ⅲ and class Ⅳ, showing a unimodal curve with the increase in snow depth. The relationship between snow depth and plant diversity （both richness and Shannon index） could be depicted by quadratic equations. There was no evident relationship between diversity （both S and H′） and soil water content, which implied that other more important factors influenced species diversity. The patterns of diversity found in our study were largely attributed to freeze-thaw alteration, length of growing season and disturbances of livestock grazing. Furthermore, snow depth affected species composition, as evaluated by the Sorensen＇s index of similarity. In addition, almost all species limited to one snow depth class were found only in class Ⅲand class Ⅳ, indicating that intermediate snow depth was suitable for the survival and growth of many alpine species.     

Preliminary results of assessing the mixing of wave transport flux residualin the upper ocean with ROMS

The effects of the mixing of wave transport flux residual(Bvl) on the upper ocean is studied through carrying out the control run(CR) and a series of sensitive runs(SR) with ROMS model.In this study,the important role of Bvl is revealed by comparing the ocean temperature,statistical analysis of errors and evaluating the mixed layer depth.It is shown that the overestimated SST is improved effectively when the wave-induced mixing is incorporated to the vertical mixing scheme.As can be seen from the vertical structure of temperature 28℃ isotherm changes from 20 min CR to 35 m in SR3,which is more close to the observation.Statistic analysis shows that the root-mean-square errors of the temperature in 10 m are reduced and the correlation between model results and observation data are increased after considering the effect of Bvl.The numerical results of the ocean temperature show improvement in summer and in tropical zones in winter,especially in the strong current regions in summer.In August the mixed layer depth(MLD) which is defined as the depth that the temperature has changed 0.5℃ from the reference depth of 10 m is further analyzed.The simulation results have a close relationship with undetermined coefficient of Bvl,sensitivity studies show that a coefficient about 0.1 is reasonable value in the model.     

Spatial distribution of snow depth based on geographically weighted regression kriging in the Bayanbulak Basin of the Tianshan Mountains,China

Snow depth is a general input variable in many models of agriculture,hydrology,climate and ecology.This study makes use of observational data of snow depth and explanatory variables to compare the accuracy and effect of geographically weighted regression kriging(GWRK)and regression kriging(RK)in a spatial interpolation of regional snow depth.The auxiliary variables are analyzed using correlation coefficients and the variance inflation factor(VIF).Three variables,Height,topographic ruggedness index(TRI),and land surface temperature(LST),are used as explanatory variables to establish a regression model for snow depth.The estimated spatial distribution of snow depth in the Bayanbulak Basin of the Tianshan Mountains in China with a spatial resolution of 1 km is obtained.The results indicate that 1)the result of GWRK's accuracy is slightly higher than that of RK(R~2=0.55 vs.R~2=0.50,RMSE(root mean square error)=0.102 m vs.RMSE=0.077 m);2)for the subareas,GWRK and RK exhibit similar estimation results of snow depth.Areas in the Bayanbulak Basin with a snow depth greater than 0.15m are mainly distributed in an elevation range of 2632.00–3269.00 m and the snow in this area comprises 45.00–46.00% of the total amount of snow in this basin.However,the GWRK resulted in more detailed information on snow depth distribution than the RK.The final conclusion is that GWRK is better suited for estimating regional snow depth distribution.     

Mapping daily temperature and precipitation in the Qilian Mountains of northwest China

Daily meteorological data are the critical inputs for distributed hydrological and ecological models. This study modified mountain microclimate simulation model （MTCLIM） with the data from 19 weather stations, and compared and validated two methods （the MTCLIM and the modified MTCLIM） in the Qilian Mountains of Northwest China to estimate daily temperature （i.e., maximum temperature, minimum temperature） and precipitation at six weather stations from i January 2000 to 31December 2009. The algorithm of temperature in modified MTCLIM was improved by constructing the daily linear regression relationship between temperature and elevation, aspect and location information. There are two steps to modify the MTCLIM to predict daily precipitation： firstly, the linear regression relationship was built between annual average precipitation and elevation, location, and vegetation index; secondly, the distance weight for measuring the contribution of each weather station on target point was improved by average wind direction during the rainy season. Several regression analysis and goodness-of-fit indices （i.e., Pearson＇s correlation coefficient, coefficient of determination, mean absolute error, root-mean-square error and modelingefficiency） were used to validate these estimated values. The result showed that the modified MTCLIM had a better performance than the MTCLIM. Therefore, the modified MTCLIM was used to map daily meteorological data in the study area from 2000 to 2009. These results were validated using weather stations with short time data and the predicted accuracy was acceptable. The meteorological data mapped could become inputs for distributed hydrological and ecological models applied in the Qilian Mountains.     

Origin of the regional stress field along the Liquine-Ofqui Fault Zone （LOFZ）, Southern Chilean Andes by means of FE Simulation

The Liquine-Ofqui Fault Zone （LOFZ） of southern Chilean Andes is one of the largest active strike-slip fault zones. There is an ongoing debate regarding the origin of the stress field along the LOFZ due to its complex geometry. This paper represents a study of the origins of the LOFZ regional stress field. Stress fields are calculated by finite element （FE） analysis. The two possible stress origins, i.e., oblique plate convergence and ridge collision/indenter tectonics of Chile ridge against Peru-Chile trench, have been emphasized in the present study. Three types of boundary conditions for the three particular models have been applied to calculate stress fields. Models are assumed to be elastic and plane stress condition. Modeling results are presented in terms of four parameters, i. e., orientation of maximum horizontal stress （σHmax）, displacement vector, strain distribution, and maximum shear stress （ τmax ） contour line within the model. The results of the first model with oblique plate convergence show inconsistency between the geometric shape of the LOFZ and the distribution of the four parameters. Although more realistic results are obtained from the second model with normal ridge collision, there are few coincident in the LOFZ geometry and regional stress field. The third model with normal and oblique ridge collision is reasonable in understanding the origin of stress field and geometrical condition in the lithosphere of the LOFZ.     

The influence of seasonal snow on soil thermal and water dynamics under different vegetation covers in a permafrost region

Seasonal snow is one of the most important influences on the development and distribution of permafrost and the hydrothermal regime in surface soil. Alpine meadow, which constitutes the main land type in permafrost regions of the Qinghai-Tibet Plateau, was selected to study the influence of seasonal snow on the temperature and moisture in active soil layers under different vegetation coverage. Monitoring sites for soil moisture and temperature were constructed to observe the hydrothermal processes in active soil layers under different vegetation cover with seasonal snow cover variation for three years from 2010 to 2012. Differences in soil temperature and moisture in areas of diverse vegetation coverage with varying levels of snow cover were analyzed using active soil layer water and temperature indices. The results indicated that snow cover greatly influenced the hydrothermal dynamics of the active soil layer in alpine meadows. In the snow manipulation experiment with a snow depth greater than 15 cm, the snow cover postponed both the freeze-fall and thawrise onset times of soil temperature and moisture in alpine LC （lower vegetation coverage） meadows and of soil moisture in alpine HC （higher vegetation coverage） meadows; however, the opposite response occurred for soil temperatures of alpine HC meadows,where the entire melting period was extended by advancing the thaw-rise and delaying the freeze-fall onset time of the soil temperature. Snow cover resulted in a decreased amplitude and rate of variation in soil temperature, for both alpine HC meadows and alpine LC meadows, whereas the distinct influence of snow cover on the amplitude and rate of soil moisture variation occurred at different soil layers with different vegetation coverages. Snow cover increased the soil moisture of alpine grasslands during thawing periods. The results confirmed that the annual hydrothermal dynamics of active layers in permafrost were subject to the synergistic actions of both snow cover and vegetation coverage.     

Effects of snow cover on ground thermal regime: A case study in Heilongjiang Province of China

The important effects of snow cover to ground thermal regime has received much attention of scholars during the past few decades. In the most of previous research, the effects were usually evaluated through the numerical models and many important results are found. However, less examples and insufficient data based on field measurements are available to show natural cases. In the present work, a typical case study in Mohe and Beijicun meteorological stations, which both are located in the most northern tip of China, is given to show the effects of snow cover on the ground thermal regime. The spatial(the ground profile) and time series analysis in the extremely snowy winter of 2012–2013 in Heilongjiang Province are also performed by contrast with those in the winter of 2011–2012 based on the measured data collected by 63 meteorological stations. Our results illustrate the positive(warmer) effect of snow cover on the ground temperature(GT) on the daily basis, the highest difference between GT and daily mean air temperature(DGAT) is as high as 32.35℃. Moreover, by the lag time analysis method it is found that the response time of GT from 0 cm to 20 cm ground depth to the alternate change of snow depth has 10 days lag, while at 40 cm depth the response of DGAT is not significant. This result is different from the previous research by modeling, in which the response depth of ground to the alteration of snow depth is far more than 40 cm.     

An Innovative Approach to Predicting Scour Depth Around Foundations Under Combined Waves and Currents in Large-Scale Tests Based on Small-Scale Tests

This study presents an innovative theoretical approach to predicting the scour depth around a foundation in large-scale model tests based on small-scale model tests under combined waves and currents. In the present approach, the hydrodynamic parameters were designed based on the Froude similitude criteria. To avoid the cohesive behavior, we scaled the sediment size based on the settling velocity similarity, i.e., the suspended load similarity. Then, a series of different scale model tests was co...     

Distribution of borehole temperature at four high-altitude alpine glaciers in Central Asia

The distribution of borehole temperature at four high-altitude alpine glaciers was investigated. The result shows that the temperature ranges from -13.4℃ to -1.84℃, indicating the glaciers are cold throughout the boreholes. The negative gradient （i.e., the temperature decreasing with the increasing of depth） due to the advection of ice and climate warming, and the negative gradient moving downwards relates to climate warming, are probably responsible for the observed minimum temperature moving to lower depth in boreholes of the Gyabrag glacier and Miaoergou glacier compared to the previously investigated continental ice core borehole temperature in West China. The borehole temperature at 10m depth ranges from -8.0℃ in the Gyabrag glacier in the central Himalayas to -12.9℃ in the Tsabagarav glacier in the Altai range. The borehole temperature at 10 m depth is 3-4 degrees higher than the calculated mean annual air temperature on the surface of the glaciers and the higher 10 m depth temperature is mainly caused by the production of latent heat due to melt-water percolation and refreezing. The basal temperature is far below the melting point, indicating that the glaciers are frozen to bedrock. The very low temperature gradients near the bedrock suggest that the influence of geothermal flux and ice flow on basal temperature is very weak. The low temperature and small velocity of ice flow of glaciers are beneficial for preservation of the chemical and isotopic information in ice cores.     

The upper mixed layer during coastal upwelling events on the northern portugal shelf

The upper mixed layer (UML) depth obtained from temperature is very close to that from density:the maximum is about 15m. This indicates that temperature is a good indicator of mixed layer during measurements. When the surface heat flux is balanced by a cross-shore heat flux, the surface mixed layer depth obtained from the WM model (Weatherly and Martin, 1978),hPRT, is roughly the same as observed. The mixed layer depth calculated from the PWP model (Price, Weller and Pinkel, 1986) is close to the depth obtained from thermistor chain temperature data. The results show that both the WM model and PWP model can provide a good estimate of stratification in the study area during the cruise. The value of log( h/u3) is about 9.5 in the study area, which shows that the study area is strongly stratified in summer. Observations on the northern Portugal shelf reveal high variability in stability, giving rise to semi-diurnal, semi-monthly and diurnal oscillations, and long term variations. The fortnightly oscillatio     

Analysis of Wave Distributions Using the WAVEWATCH-III Model in the Arctic Ocean

In this work,we examined long-term wave distributions using a third-generation numerical wave model called WAVE-WATCH-III(WW3)(version 6.07).We also evaluated the influence of sea ice on wave simulation by using eight parametric switches.To select a suitable ice-wave parameterization,we validated the simulations from the WW3 model in March,May,September,and December 2017 against the measurements from the Jason-2 altimeter at latitudes of up to 60°N.Generally,all parameterizations ex-hibited slight differences,i.e.,about 0.6 m root mean square error(RMSE)of significant wave height(SWH)in May and September and about 0.9 m RMSE for the freezing months of March and December.The comparison of the results with the SWH from the European Centre for Medium-Range Weather Forecasts for December 2017 indicated that switch IC4_M1 performed most effec-tively(0.68 m RMSE)at high latitudes(60°-80°N).Given this finding,we analyzed the long-term wave distributions in 1999-2018 on the basis of switch IC4_M1.Although the seasonal variability of the simulated SWH was of two types,i.e.,‘U’and‘sin’modes,our results proved that fetch expansion prompted the wave growth.Moreover,the interannual variability of the specific regions in the‘U’mode was found to be correlated with the decade variability of wind in the Arctic Ocean.     

Precipitation type estimation and validation in China

The results from three methods aimed at improving precipitation type(e.g., rain, sleet, and snow) estimation are presented and compared in this paper. The methods include the threshold air temperature(AT), threshold wet bulb temperature(WBT) and Koistinen and Saltikoff(KSS) methods.Dot graphs are plotted to acquire the threshold air temperature or the threshold wet bulb temperature using daily averaged air temperature, wet bulb temperature and precipitation data at 643 stations from 1961 to 1979(precipitation types are not labeled in the database from 1980 to present) in China. The results indicate that the threshold AT or WBT methods are not able to differentiate rain, sleet and snow in the most regions in China; sleet is difficult to differentiate from other precipitation types based on the two threshold methods. Therefore, one threshold AT and WBT method was used in this study to differentiate rain and snow. Based on GaussianKriging interpolation of threshold air temperature(T0and wet bulb temperature(Tw), the T0 and Tw contour lines and contour surfaces are calculated for China.Finally, a comparison between the KSS, AT and WBT methods are provided in which the KSS method is calculated based on air temperature and relative humidity. The results suggest that the KSS method is more appropriate for water phase estimation than are the other methods; the maximum precision for rain and snow is 99% and 94%, respectively. The AT method performs better than the WBT method when the critical air temperature is 2°C.     

Thermodynamic properties of snow cover on sea ice during the austral summer in Prydz Bay,East Antarctica

The thermodynamic properties of snow cover on sea ice play a key role in the ice-ocean-atmosphere system and have been a focus of recent scientific research. In this study, we investigated the thermodynamic properties of snow cover on sea ice in the Nella Fjord, Prydz Bay, East Antarctica(69°20′S, 76°07′E), near the Chinese Antarctic Zhongshan Station. Our observations were carried out during the 29th Chinese National Antarctic Research Expedition. We found that the vertical temperature profile of snow cover changed considerably in response to changes in air temperature and solar radiation during the summer. Associated with the changes in the temperature profile were fluctuations in the temperature gradient within the upper 10 cm of the snow cover. Results of previous research have shown that the thermal conductivity of snow is strongly correlated with snow density. To calculate the thermal conductivity in this study, we measured densities in three snow pits. The calculated thermal conductivity ranged from 0.258–0.569 W?m-1?K-1. We present these datasets to show how involved parameters changed, and to contribute to a better understanding of melting processes in the snow cover on sea ice.     

Comparison of two wind algorithms of ENVISAT ASAR at high wind

Two wind algorithms of ENVISAT advanced synthetic aperture radar (ASAR), i. e. CMOD4 model from the European Space Agency (ESA) and CMOD IFR2 model from Quilfen et al., are compared in this paper. The wind direction is estimated from orientation of low and linear signatures in the ASAR imagery. The wind direction has inherently a 180° ambiguity since only a single ASAR image is used. The 180° ambiguity is eliminated by using the buoy data from the NOAA (National Oceanic and Atmospheric Administration) buoys moored in the Pacific. Wind speed is obtained with the two wind algorithms using both estimated wind direction and normalized radar cross section (NRCS). The retrieved wind results agree well with the data from Quikscat. The root mean square error (RMSE) of wind direction is 2.80? The RMSEs of wind speed from CMOD4 model and CMOD_IFR2 model are 1.09 m/s and 0.60 m/s, respectively. The results indicate that the CMOD_IFR2 model is slight better than CMOD4 model at high wind.     

Snowline and Snow Cover Monitoring at High Spatial Resolution in a Mountainous River Basin Based on a Timelapse Camera at a Daily Scale

Snowline change and snow cover distribution patterns are still poorly understood in steep alpine basins of the Qilian Mountainous region because fast changes in snow cover cannot be observed by current sensing methods due to their short time scale. To address this issue of daily snowline and snow cover observations, a groundbased EOS 7D camera and four infrared digital hunting video cameras(LTL5210A) were installed around the Hulugou river basin(HRB) in the Qilian Mountains along northeastern margin of the Tibetan Plateau(38°15'54 "N, 99°52'53" E) in September 2011.Pictures taken with the EOS 7D camera were georeferenced and the data from four LIL5210 A cameras and snow depth sensors were used to assist snow cover estimation. The results showed that the time-lapse photography can be very useful and precise for monitoring snowline and snow cover in mountainous regions. The snowline and snow cover evolution at this basin can be precisely captured at daily scale. In HRB snow cover is mainly established after October, and the maximum snow cover appeared during February and March. The consistent rise of the snowline and decrease in snow cover appeared after middle part of March. This melt process is strongly associated with air temperature increase.     

Joint inversion of magnetotelluric and fullwaveform seismic data based on alternating cross-gradient structural constraints

Magnetotelluric(MT)inversion and seismic inversion are important methods for the interpretation of subsurface exploration data,but separate inversion of MT and seismic produces ambiguous and non-unique results due to various factors.In order to achieve accurate results,the authors propose a joint inversion method of two-dimensional MT and seismic data in the frequency domain.The finite element method is used for numerical simulation of electromagnetic data in the forward modelling,and the Gauss-Newton method is used for the inversion.The 9-point-finite-difference method is used to solve the seismic wave field in the acoustic wave equation,and the inverse problem of seismic data is solved by full waveform inversion with a conjugate gradient,a simple and fast method.Cross gradient functions are used to provide constraint structure between resistivity and velocity parameters to carry out the joint inversion.The joint inversion algorithm is tested by double-rectangular model synthesis data,and the accuracy of the algorithm is verified.The results show that the joint inversion results are better than those from separate inversion.The algorithm is applied to a geophysical model of a metalliferous deposit in Jinchuan and is compared with the separate inversion results.It shows that the results obtained with joint inversion are much closer to the real model.     

The Altitudinal Belts of Subalpine Virgin Forest on Mt.Gongga Simulated by a Succession Model

How to accurately simulate the distribution of forest species based upon their biological attributes has been a traditional biogeographical issue.Forest gap models are very useful tools for examining the dynamics of forest succession and revealing the species structure of vegetation.In the present study,the GFSM（Gongga Forest Succession Model） was developed and applied to simulate the distribution,composition and succession process of forests in 100 m elevation intervals.The results indicate that the simulated results of the tree species,quantities of the different types of trees,tree age and differences in DBH（diameter at breast height） composition were in line with the actual situation from 1400 to 3700 MASL（meters above sea level） on the eastern slope of Mt.Gongga.Moreover,the dominant species in the simulated results were the same as those in the surveyed database.Thus,the GFSM model can best simulate the features of forest dynamics and structure in the natural conditions of Mt.Gongga.The work provides a new approach to studying the structure and distribution characteristics of mountain ecosystems in varied elevations.Moreover,the results of this study suggest that the biogeochemistry mechanism model should be combined with the forestsuccession model to facilitate the ecological model in simulating the physical and chemical processes involved.     

Influence of Environmental Conditions on the Sound Velocity Ratio of Seafloor Surficial Sediment

In this work, we investigated the influences of salinity, temperature, and hydrostatic pressure on the acoustics of seafloor surficial sediment by theoretically and experimentally analyzing the sound velocity ratio of the seafloor sediment to the bottom seawater in typical environmental conditions. Temperature-and pressure-controlled experiments were conducted to examine the characteristics of the sound velocity ratio, the results of which agree with the theoretical analysis using the effective density fluid model. Of the three environmental factors considered, the sound velocity ratio was found to be sensitive to temperature and pressure but not to salinity, with the sound velocity ratio decreasing with temperature and hydrostatic pressure. With respect to surficial sediments, pore water plays a key role in the sound velocity ratio of sediment influenced by different environmental factors. The sound velocities of different types of sediments(sandy, silty, and clayey) change similarly with temperature, but change slightly differently with hydrostatic pressure. The influence of environmental factors on the sound velocity ratio of seafloor sediment is independent of the detection frequency. The results show that the sound velocity ratio can change up to 0.0008 per ℃ when the temperature ranges from 2℃ to 25℃ and up to 0.00064 MPa-1 when the seawater depth pressure ranges from 0 MPa to 40 MPa.     

Mapping of an approximate neutral density surface with Ungridded data

A neutral density surface is a logical study frame for water-mass mixing since water parcels spread along such a surface without doing work against buoyancy restoring force. Mesoscale eddies are believed to stir and subsequently mix predominantly along such surfaces. Because of the nonlinear nature of the equation of state of seawater, the process of accurately mapping a neutral density surface necessarily involves lateral computation from one conductivity, temperature and depth （CTD） cast to the next in a logical sequence. By contrast, the depth of a potential density surface on any CTD cast is found solely from the data on this cast. The lateral calculation procedure causes a significant inconvenience. In a previous paper by present author published in this journal （You, 2006）, the mapping of neutral density surfaces with regularly gridded data such as Levitus data has been introduced. In this note, I present a new method to find the depth of a neutral density surface from a cast without having to specify an integration path in space. An appropriate reference point is required that is on the neutral density surface and thereafter the neutral density surface can be determined by using the CTD casts in any order. This method is only approximate and the likely errors can be estimated by plotting a scatter diagram of all the pressures and potential temperatures on the neutral density surfaces. The method assumes that the variations of potential temperature and pressure （with respect to the values at the reference point） on the neutral density surface are proportional It is important to select the most appropriate reference point in order to approximately satisfy this assumption, and in practice this is found by inspecting the θ-p plot of data on the surface. This may require that the algorithm be used twice. When the straight lines on the θ-p plot, drawn from the reference point to other points on the neutral density surface, enclose an area that is external to the cluster of θ-p points of the neutral density surface, errors will occur, and these errors can be quantified from this diagram. Examples showing the use of the method are presented for each of the world＇s main oceans.