Snow measurement techniques for land-surface-atmosphere exchange studies in boreal landscapes

Summary  Snow has been studied widely in hydrology for many decades whereas recent meteorological interest in snow is caused by increased emphasis on high latitudes and wintertime in climate-change research as well as by the need to improve weather-forecast models during these conditions. Ground-based measurements of snow properties are needed both to improve understanding of surface-atmosphere exchange processes and to provide ground truth to new remote-sensing algorithms. This justifies a review of techniques to measure snow in combination with establishment of criteria for the suitability of the methods for process studies. This review assesses the state-of-art in ground-based snow-measurement techniques in the end of the 1990s in view of their accuracy, time resolution, possibility to automate, practicality and suitability in different terrain. Methods for snow-pack water equivalent, depth, density, growth, quality, liquid-water content and water leaving the snow pack are reviewed. Synoptic snow measurements in Fennoscandian countries are widely varying and there is no single standard on which process-related studies can build. A long-term, continuous monitoring of mass and energy properties of a snow cover requires a combination of point-measurement techniques. Areally representative values of snow properties can be achieved through a combination of automatically collected point data with repeated manual, areally covering measurements, remote-sensing data and digital elevation models, preferably in a GIS framework. Received August 27, 1999     

A case study of warm air advection over a melting snow surface

When relatively warm, moist air moves over a snow surface, sensible heat and moisture are extracted from its lower layers and used to melt the snow. The depth of the cooled layer depends on horizontal wind speeds and the presence of high vertical wind shear. The mechanism for air mass modification appears to be turbulent mixing.     

A 2D finite volume model for bebris flow and its application to events occurred in the Eastern Pyrenees

FLATModel is a 2D finite volume code that contains several original approaches to improve debris-flow simulation. Firstly, FLATModel incorporates a ＂stop-and-go＂ technique in each cell to allow continuous collapses and remobilizations of the debris-flow mass. Secondly, flow velocity and consequently yield stress is directly associated with the type of rheology to improve boundary accuracy. Thirdly, a simple approach for entrainment is also included in the model to analyse the effect of basal erosion of debris flows. FLATMODEL was tested at several events that occurred in the Eastern Pyrenees and simulation results indicated that the model can represent rather well the different characteristics observed in the field.     

Diurnal variation of deep cloud systems over the Indian region using INSAT-1B pixel data

Summary Among the various time scales of deep clouds, diurnal variation is found to be prominent over the tropics. The present study examines the diurnal variation in the number and area cover associated with the cloud systems over the tropical Indian region using INSAT-1B pixel data. Three periods, namely, April–May 1988, July–August 1988, and January–February 1989 are considered. The dependence of diurnal characteristics on the temperature threshold, life duration and size of cloud systems, and land-sea contrast has been explored. The diurnal characteristics of cloud systems living for more than a day have been studied for the first time. It is shown that cloud systems exhibit strong diurnal dependence at the coldest temperature threshold used (201 K). Also, the diurnal variation is more for larger cloud systems and for longer living systems. In general, more deep cloud activity is found from the satellite data during the pre-dawn and early morning hours. Precipitation is enhanced during morning to early noon hours. Further, using data from a recent field experiment, clear evidence of diurnal variation in precipitation over the Bay of Bengal is also presented. Received March 20, 2000/Revised October 3, 2000     

Enhancement of the method of summer precipitation forecasting

The physical-synoptic principles of the automated method of summer precipitation forecasting introduced into operational prognostic practice in 2006 by the decree of the Central Methodical Commission of the Federal Service for Hydrometeorology and Environmental Monitoring (Roshydromet) are presented. Beside that, improved modifications of this method, which are automatically updated, are shown. Validation of those updates based on observational data collected in 2004 has shown improvement of all major criteria of forecasts efficiency. The performed improvement is based on the more detailed quantitative realization of mechanism of various showers formation (including heavy rainfalls).     

Authigenic iron and titanium oxides in triassic red beds: (St. Bees Sandstone), Cumbria,Northern England

Authigenic iron and titanium oxides occur in three main textural varieties in the St. Bees Sandstone, a Triassic red bed succession in Cumbria. These are: (a) overgrowths of haematite, titaniferous haematite, anatase, and rutile which generally occur on detrital host grains of similar compositions. The overgrowths may occur as syntaxial rim cements or rhombohedral and prismatic projections and are always in optical continuity, (b) discrete crystals of anatase (including octahedrite) and haematite 10-40 μm in size occur in pore spaces, and (c) fine grained ( < 1 μm) pigmentary haematite occurs as grain coatings around detrital grains and in the interstitial matrix. The euhedral nature and pore-filling habit clearly indicate the authigenic origin of these iron- and titanium oxides. All three textural varieties are believed to have been precipitated from ground waters containing dissolved ferrous and titanium ions. These ions were derived from the intrastratal solution of detrital iron and titanium bearing grains including ferromagnesian silicates and iron-titanium oxides. The precipitation of iron oxides from migrating ground waters in the manner described here goes some way to explaining how thick, uniformly red successions can be formed.     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Possible representation for discovery observations of stellar flares

It is shown that the chronology of flare star discoveries in the Pleiades cluster and the Orion association can be described satisfactorily by various distribution functions (gamma, binomial, decreasing exponential, and delta) for the mean frequencies of stellar flares. However, it has been found that this is due to the uncertainty in the observationally derived distribution function for the mean frequency of stellar flares. The most likely function is that derived by Ambartsumian, which has a physical basis.Translated fromAstrofizika, Vol. 38, No. 1, pp. 25–32, January–March, 1995.