ARS | Publication request: LOW TEMPERATURE SEM OF PRECIPITATED AND METAMORPHOSED SNOW CRYSTALS COLLECTED AND TRANSPORTED FROM REMOTE SITES

Submitted to: Hitachi Instrument News
Publication Type: Trade Journal
Publication Acceptance Date: June 12, 1996
Publication Date: June 3, 2001
Citation: WERGIN, W.P., RANGO, A., ERBE, E.F., MURPHY, C.A. LOW TEMPERATURE SEM OF PRECIPITATED AND METAMORPHOSED SNOW CRYSTALS COLLECTED AND TRANSPORTED FROM REMOTE SITES. HITACHI INSTRUMENT NEWS. 2001. P. 11-24.

Technical Abstract: Procedures were developed to sample, store, ship and process precipitated and metamorphosed snow crystals, collectively known as "snowflakes," from remote sites to a laboratory where they could be observed and photographed using low temperature scanning electron microscopy (LTSEM). Snow samples were collected during 1994-96 from West Virginia, Colorado, and Alaska and sent to Beltsville, MD, for observation. The samples consisted of freshly precipitated snowflakes and snow collected from pits excavated in winter snowfields measuring up to 1.5m in depth. The snow crystals were mounted on copper plates, plunged into lN2, transferred to a storage dewar and shipped to the laboratory. Observations easily recorded in stereo format (three dimension) revealed detailed surface features on the precipitated crystals consisting of rime, graupel and skeletal features. Samples from snowpacks preserved the metamorphosed crystals which had unique structural features and bonding patterns resulting from temperature and vapor pressure gradients. In late spring, the surface of a snowpack in an alpine region exhibited a reddish hue. Undisturbed surfaces from these snowpacks were sampled to observe the snow crystals and the organisms responsible for the coloration. Etching the surface of samples from these sites exposed the presence of numerous cells believed to be algae. Study results indicate LTSEM can be used to provide detailed information about the surface features of precipitated and metamorphosed snow crystals sampled at remote locations. The technique can also be used to increase understanding of ecology snow. The results have application to research activities attempting to forecast the water quantity in winter snowpack and the amount reaching reservoirs and available for agriculture and hydroelectric power.