A Meteorological and Snow observational data set from Snoqualmie Pass (921 m), Washington Cascades, U.S.

We introduce a quality controlled observational atmospheric, snow, and soil data set from Snoqualmie Pass, Washington, U.S.A., to enable testing of hydrometeorological and snow process representations within a rain-snow transitional climate where existing observations are sparse and limited. Continuous meteorological forcing (including air temperature, total precipitation, wind speed, specific humidity, air pressure, short- and longwave irradiance) are provided at hourly intervals for a 24-year historical period (water years 1989-2012) and at half-hourly intervals for a more-recent period (water years 2013-2015), separated based on the availability of observations. Additional observations include 40-years of snow board new snow accumulation, multiple measurements of total snow depth, and manual snow pits, while more recent years include sub-daily surface temperature, snowpack drainage, soil moisture and temperature profiles, and eddy co-variance derived turbulent heat flux. This data set is ideal for testing hypotheses about energy balance, soil and snow processes in the rain-snow transition zone. Plots of live data can be found here: http://depts.washington.edu/mtnhydr/cgi/plot.cgi

Pamela Snow, Piano Recital, April 9, 1970

Concert Program for Pamela Snow, Piano Recital, April 9, 1970

Ice and Snow, Niagara Falls, U.S.A.

The description of the image reads "514-a-A fairy-land of ice and snow, Niagara Falls, U.S.A.".

An Empirical Comparison of SNoW and SVMs for Face Detection

Impressive claims have been made for the performance of the SNoW algorithm on face detection tasks by Yang et. al. [7]. In particular, by looking at both their results and those of Heisele et. al. [3], one could infer that the SNoW system performed substantially better than an SVM-based system, even when the SVM used a polynomial kernel and the SNoW system used a particularly simplistic 'primitive' linear representation. We evaluated the two approaches in a controlled experiment, looking directly at performance on a simple, fixed-sized test set, isolating out 'infrastructure' issues related to detecting faces at various scales in large images. We found that SNoW performed about as well as linear SVMs, and substantially worse than polynomial SVMs.

Snow white hen.

Cumple con los requisitos del currículo de Inglaterra, Gales y Escocia aportando los conocimientos básicos relacionados con el aprendizaje de la lectura y la escritura en niños de seis y siete años. El texto sirve de base para conocer e identificar los sonidos en las palabras. En esta historia, se trata la rima'en', y en ella vemos cómo la gallina huye del corral y pone los huevos en otro lugar.

The snow queen.

El objetivo de esta serie es desarrollar en los niños las habilidades para la lectura y la comprensión de textos, a lo largo de doce niveles y mediante la narración de una historia distinta en cada uno de los libros que la componen. Se refuerza el vocabulario relacionado con el contenido de la historia y se acompaña de distintas actividades. En ésta, se narra el cuento de la Reina de las Nieves, y se incluye en el nivel doce.

Snow White and the seven dwarfs.

La malvada Reina es muy vanidosa y está decidida a ser la mujer más hermosa sobre la tierra, pero su espejo mágico le desvela que la más bella es la princesa Blancanieves que trabaja de criada en el palacio. Pero nadie puede interponerse en su camino como descubre la hermosa Blancanieves.

Elmer in the snow.

Una mañana, Elmer el elefante mosaico, pregunta a un grupo de elefantes de que se quejan, y éstos le responden que tienen más frío que de costumbre. Elmer les contesta que en la selva no hace frío y para que comparen les lleva hasta las montañas heladas, donde comprueban lo que realmente es pasar frío, pero también se divierten retozando en la nieve y el hielo.

Village in the snow.

Material didáctico como guía de lectura, comprensión y reconocimiento de palabras. Para trabajar: patrones de ortografía comunes para cada fonema, para leer textos y familiarizarse con ritmo y expresión. Aplicación fonológica del vocabulario para deletrear palabras con precisión. Mrs Mary les cuenta a los niños una historia sobre una aldea en las montañas. Los niños van a la habitación de Biff y quieren una aventura. Biff recoge la llave mágica.

I wonder why mountains have snow on top : and other questions about mountains.

En esta colección se trata de responder a las preguntas que los jóvenes lectores se hacen sobre: las montañas y su formación, los volcanes, las plantas y animales que viven en ellas. También, de los deportes practicados en la montaña: montañismo, esquiar, ciclismo.

Snow : causes and effects.

En esta serie los jóvenes lectores se acercan a los diferentes tipos de clima que experimentamos en la Tierra. Además de tratar el tema de un fenómeno meteorológico en particular, se incluye información sobre el pronostico del tiempo y vemos, además, las formas en que las personas, los animales y las plantas modifican su comportamiento de acuerdo a determinadas condiciones meteorológicas.

Establishing Winter Origins of Migrating Lesser Snow Geese Using Stable Isotopes

Increases in Snow Goose (Chen caerulescens) populations and large-scale habitat changes in North America have contributed to the concentration of migratory waterfowl on fewer wetlands, reducing resource availability, and enhancing risks of disease transmission. Predicting wintering locations of migratory individuals is critical to guide wildlife population management and habitat restoration. We used stable carbon (δ13C), nitrogen (δ15N), and hydrogen (δ2H) isotope ratios in muscle tissue of wintering Snow Geese to discriminate four major wintering areas, the Playa Lake Region, Texas Gulf Coast, Louisiana Gulf Coast, and Arkansas, and infer the wintering locations of individuals collected later during the 2007 and 2008 spring migrations in the Rainwater Basin (RWB) of Nebraska. We predicted the wintering ground derivation of migrating Snow Geese using a likelihood-based approach. Our three-isotope analysis provided an efficient discrimination of the four wintering areas. The assignment model predicted that 53% [95% CI: 37-69] of our sample of Snow Geese from the RWB in 2007 had most likely originated in Louisiana, 38% [23-54] had wintered on Texas Gulf Coast, and 9% [0-20] in Arkansas; the assessment suggested that 89% [73-100] of our 2008 sample had most likely come from Texas Gulf Coast, 9% [0-27] from Louisiana Gulf Coast, and 2% [0-9] from Arkansas. Further segregation of wintering grounds and additional sampling of spring migrating Snow Geese would refine overall assignment and help explain interannual variations in migratory connectivity. The ability to distinguish origins of northbound geese can support the development of spatially-adaptive management strategies for the midcontinent Snow Goose population. Establishing migratory connectivity using isotope assignment techniques can be extended to other waterfowl species to determine critical habitat, evaluate population energy requirements, and inform waterfowl conservation and management strategies.

Effect of ENSO phase on large-scale snow water equivalent distribution in a GCM

Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only