Variations in glacier volume and snow cover and their impact on lake storage in the Paiku Co Basin,in the Central Himalayas

Glaciers and snow cover are important constituents of the surface of the Tibetan Plateau. The responses of these phenomena to global environmental changes are sensitive, rapid and intensive due to the high altitudes and arid cold climate of the Tibetan Plateau. Based on multisource remote sensing data, including Landsat images, MOD10A2 snow product, ICESat, Cryosat-2 altimetry data and long-term ground climate observations, we analysed the dynamic changes of glaciers, snow melting and lake in the Paiku Co basin using extraction methods for glaciers and lake, the degree-day model and the ice and lake volume method. The interaction among the climate, ice-snow and the hydrological elements in Paiku Co is revealed. From 2000 to 2018, the basin tended to be drier, and rainfall decreased at a rate of −3.07 mm/a. The seasonal temperature difference in the basin increased, the maximum temperature increased at a rate of 0.02°C/a and the minimum temperature decreased at a rate of −0.06°C/a, which accelerated the melting from glaciers and snow at rates of 0.55 × 10⁷ m³/a and 0.29 × 10⁷ m³/a, respectively. The rate of contribution to the lake from rainfall, snow and glacier melted water was 55.6, 27.7 and 16.7%, respectively. In the past 18 years, the warmer and drier climate has caused the lake to shrink. The water level of the lake continued to decline at a rate of −0.02 m/a, and the lake water volume decreased by 4.85 × 10⁸ m³ at a rate of −0.27 × 10⁸ m³/a from 2000 to 2018. This evaluation is important for understanding how the snow and ice melting in the central Himalayas affect the regional water cycle.     

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.     

Properties of Galaxies in the Second Byurakan Survey. II. Characteristic Features of a Separate Sample of Galaxies

Some features of a sample of galaxies from the Second Byurakan Survey are discussed. Most of them are small galaxies with star formation. It is shown that different types of galaxies are in the Survey, with high, medium, and low levels of excitation and continua ranging from blue to relatively red. Many of the galaxies have absorption lines in their spectra; their continua are formed by stars in later spectral classes.     

AN INTEGRATED APPROACH TO AIR MASS CLASSIFICATION IN THE NORTH CENTRAL UNITED STATES

Both subjective and objective schemes for air mass classification offer advantages to climatological studies. An integrated approach is developed and applied to 850 mb level data in the north central United States. Each air mass type was initially delimited by a subjective analysis. Final limits were then determined with an objective technique that separates temperature curves into normal components based on interpretation from the subjective method. Continental air was most frequent in all seasons except summer. The methodology also allows estimation of classification error.     

Discrimination of sedimentary facies by association analysis

The ability of association analysis to discriminate sedimentary facies was tested on Purdy's modal analyses of modern sediments of the Great Bahama Bank. Purdy's data set has served in the past as a standard reference for evaluating various multivariate classification algorithms. In order to adapt Purdy's data to association analysis, the percent abundance of the 12 constituents was converted to binary form by dichotomizing each variable on its mean value. The results obtained by association analysis are virtually identical to those obtained by Purdy and other authors. The same four main sedimentary facies were discriminated; 86% of the samples were identically classified (97% when misclassified borderline cases are counted as matches); the total partition variance of the classification is only negligibly greater (4%); and the grouping of the variables yielded the same four groups. The rank order of the three division-attributes responsible for the sample classification is fines, oolites, and corals. Association analysis has been employed by other authors to differentiate meaningful facies groups in studies of ancient reef carbonates, modern reef sediments, and heavy minerals in stream sediments. In all these studies, the results were found to be compatible with those obtained by using the continuous quantitative measurements, indicating that qualitative binary data may often be sufficient for the purpose of facies discrimination in many branches of geology and that association analysis is an effective method for this purpose.     

Estimation of snow water equivalent using microwave radiometry over Arctic first‐year sea ice

The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea‐ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10‐day period over 20 first‐year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first‐year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd.     

One hundred years of mountain hydrology in Switzerland by the WSL

In 1903 the Swiss Federal Research Institute WSL started its first forest hydrology measurements with the aim to deliver a sound scientific basis for the implementation of new forest legislation introduced in Switzerland in 1876. This legislation was triggered by several large floods that occurred in Switzerland, for which a major cause was widely seen as the poor condition of forests at that time. Consequently, hydrologic research at WSL first focused on the influence of forests on floods. In the second half of the 20th century, other hydrological issues such as water quality, snow hydrology and sediment transport complemented the hydrologic research at WSL. Some recent results of this work are presented in three papers joining this introductory paper to mark the 100th anniversary of hydrologic research at WSL. Copyright © 2006 John Wiley & Sons, Ltd.     

Ice‐cover variability on shallow lakes at high latitudes: model simulations and observations

A one‐dimensional thermodynamic model for simulating lake‐ice phenology is presented and evaluated. The model can be driven with observed daily or hourly atmospheric forcing of air temperature, relative humidity, wind speed, cloud amount and snowfall. In addition to computing the energy balance components, key model output includes the temperature profile at an arbitrary number of levels within the ice/snow (or the water temperature if there is no ice) and ice thickness (clear ice and snow‐ice) on a daily basis, as well as freeze‐up and break‐up dates. The lake‐ice model is used to simulate ice‐growth processes on shallow lakes in arctic, sub‐arctic, and high‐boreal forest environments. Model output is compared with field and remote sensing observations gathered over several ice seasons. Simulated ice thickness, including snow‐ice formation, compares favourably with field measurements. Ice‐on and ice‐off dates are also well simulated when compared with field and satellite observations, with a mean absolute difference of 2 days. Model simulations and observations illustrate the key role that snow cover plays on the seasonal evolution of ice thickness and the timing of spring break‐up. It is also shown that lake morphometry, depth in particular, is a determinant of ice‐off dates for shallow lakes at high latitudes. Copyright © 2003 John Wiley & Sons, Ltd.     

Wavelet analysis of inter‐annual variability in the runoff regimes of glacial and nival stream catchments,Bow Lake,Alberta

Continuous wavelet analyses of hourly time series of air temperature, stream discharge, and precipitation are used to compare the seasonal and inter‐annual variability in hydrological regimes of the two principal streams feeding Bow Lake, Banff National Park, Alberta: the glacial stream draining the Wapta Icefields, and the snowmelt‐fed Bow River. The goal is to understand how water sources and flow routing differ between the two catchments. Wavelet spectra and cross‐wavelet spectra were determined for air temperature and discharge from the two streams for summers (June–September) 1997–2000, and for rainfall and discharge for the summers of 1999 and 2000. The diurnal signal of the glacial runoff was orders of magnitude higher in 1998 than in other years, indicating that significant ice exposure and the development of channelized glacial drainage occurred as a result of the 1997–98 El Niño conditions. Early retreat of the snowpack in 1997 and 1998 led to a significant summer‐long input of melt runoff from a small area of ice cover in the Bow River catchment; but such inputs were not apparent in 1999 and 2000, when snow cover was more extensive. Rainfall had a stronger influence on runoff and followed quicker flow paths in the Bow River catchment than in the glacial catchment. Snowpack thickness and catchment size were the primary controls on the phase relationship between temperature and discharge at diurnal time scales. Wavelet analysis is a fast and effective means to characterize runoff, temperature, and precipitation regimes and their interrelationships and inter‐annual variability. The technique is effective at identifying inter‐annual and seasonal changes in the relative contributions of different water sources to runoff, and changes in the time required for routing of diurnal meltwater pulses through a catchment. However, it is less effective at identifying changes/differences in the type of the flow routing (e.g. overland flow versus through flow) between or within catchments. Copyright © 2003 John Wiley & Sons, Ltd.     

Modelling the effect of low soil temperatures on transpiration by Scots pine

For ecosystem modelling of the Boreal forest it is important to include processes associated with low soil temperature during spring‐early summer, as these affect the tree water uptake. The COUP model, a physically based SVAT model, was tested with 2 years of soil and snow physical measurements and sap flow measurements in a 70‐year‐old Scots pine stand in the boreal zone of northern Sweden. During the first year the extent and duration of soil frost was manipulated in the field. The model was successful in reproducing the timing of the soil warming after the snowmelt and frost thaw. A delayed soil warming, into the growing season, severely reduced the transpiration. We demonstrated the potential for considerable overestimation of transpiration by the model if the reduction of the trees' capacity to transpire due to low soil temperatures is not taken into account. We also demonstrated that the accumulated effect of aboveground conditions could be included when simulating the relationship between soil temperature and tree water uptake. This improved the estimated transpiration for the control plot and when soil warming was delayed into the growing season. The study illustrates the need of including antecedent conditions on root growth in the model in order to catch these effects on transpiration. The COUP model is a promising tool for predicting transpiration in high‐latitude stands. Copyright © 2006 John Wiley & Sons, Ltd.