Submitted to: Scanning
Publication Type: Proceedings
Publication Acceptance Date: April 10, 1996
Publication Date: N/A
Interpretive Summary: One third of the water used for irrigation and the growth of agricultural crops is provided by snow. Predicting the amount of water present in winter snowpack is an essential forecast activity needed to estimate the amount of water that reaches reservoirs and agricultural fields. However, currently used methods for calculating the amount of water in snow are inaccurate; therefore, multimillion dollar losses in agricultural efficiency result each year. To improve the accuracy of the predictions, ARS investigators have developed a new method for examining snow in an instrument called a scanning electron microscope. In the present study, samples of aging snow were removed from snowpacks and placed on holders that could be transferred to a laboratory for examination. Photographs of the aging snow revealed that time and temperature influenced the basic shapes and sizes of the crystals. Because this new technique yielded accurate measurement of snow particles, it will be used by scientists to improve computerized modeling systems that predict the amount of water in snowpack. These predictive systems will in turn benefit farmers who require irrigation water.
Low temperature scanning electron microscopy was used to observe metamorphosed snow crystals commonly known as "snowflakes". Snow was collected from sites in Maryland, West Virginia, Colorado and Alaska. The samples consisted snow that was collected from snowpits measuring up to 1m in depth. The samples were frozen in LN2 and then transferred either to a cryosystem mounted on an SEM or to a storage dewar. Low temperature scanning electron microscopic observations revealed that snowpacks that had been exposed to temperature gradients contained crystals with unique structural features and bonding patterns that resulted from variations in temperature and pressure. This study indicates that low temperature scanning electron microscopy is a feasible technique for observing snow that was sampled at remote locations and for determining the shapes and sizes of metamorphosed snow crystals. The results assist research activities that forecast water in the winter snowpack and predict the amount that will be available for agriculture and hydroelectric power.