Precipitation of Ge nanoparticles from GeO2 glasses in transmission electron microscope

We show, using spatially resolved energy loss spectroscopy in a transmission electron microscopy (TEM), that GeO2 and GeO2-SiO2 glasses are extremely sensitive to high energy electrons. Ge nanoparticles can be precipitated in GeO2 glasses efficiently by the high-energy electron beam of a TEM. This is relevant to TEM characterization of luminescent Ge nanoparticles in silicate glasses, which may produce artificial results. (C) 2005 American Institute of Physics.

Dendroclimatic reconstructions of temperature, precipitation, and pressure patterns over the western and central USA, 1602-1961 [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Verified reconstructions of seasonal temperature, precipitation and sea-level pressure over North America and the North Pacific have been derived from 65 arid-site tree-ring chronologies in the North American West. Significant reconstructions were obtained for temperature for wide areas in the West and mid-continent. Precipitation reconstructions were significant only in the West, and pressure was reconstructed over wide areas of the North Pacific Ocean and the North American continent.

400 years of precipitation variability in central and southern California reconstructed from tree-rings [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Precipitation variability at 31 stations hanging from San Diego to San Francisco and from the coast to the Sierras was characterized ...

Surface temperature and precipitation variations in the western U.S. and their relation to large scale circulation indices [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): An analysis of the principal components of surface temperature and precipitation in the western U.S. is presented. Data consist of monthly mean temperature and total precipitation for 66 climate divisions west of the Continental Divide, for the years 1931-1984. The analysis is repeated for three separate combinations of months - the water year (Oct - Sept), the cool season (Oct - Mar) and the warm season (Apr - Sept). Inspection of monthly precipitation climatology indicates that selection of these combinations of months results in very few awkward splittings of the natural precipitation seasons found in the West.

A mechanism for the link between solar-irradiance variations and regional precipitation

Although the mechanisms of climatic fluctuations are not completely understood, changes in global solar irradiance show a link with regional precipitation. A proposed mechanism for this linkage begins with absorption of varying amounts of solar energy by tropical oceans, which may aid in development of ocean temperature anomalies. These anomalies are then transported by major ocean currents to locations where the stored energy is released into the atmosphere, altering pressure and moisture patterns that can ultimately affect regional precipitation. Correlation coefficients between annual averages of monthly differences in empirically modeled solar-irradiance variations and annual state-divisional precipitation values in the United States for 1950 to 1988 were computed with lag times of 0 to 7 years. The highest correlations (R=0.65) occur in the Pacific Northwest with a lag time of 4 years, which is about equal to the travel time of water within the Pacific Gyre from the western tropical Pacific Ocean to the Gulf of Alaska. With positive correlations, droughts coincide with periods of negative irradiance differences (dry, high-pressure development), and wet periods coincide with periods of positive differences (moist, low-pressure development).

ENSO and precipitation variability over Mexico during the last 90 years

Latin America has been shown to be susceptible to climatic anomalies during El Niño/Southern Oscillation (ENSO) events (eg, Aceituno 1988; Ropelewshi and Halpert 1987; Kiladis and Diaz 1989). While these studies have emphasized ENSO-related rainfall and temperature anomalies over Central and South America, less work has been done on the climatic effects of ENSO over the Mexican region. In this study we are investigating interannual and intraseasonal fluctuation in temperature and precipitation over the southwestern United States and Mexico since the turn of the century. We are particularly interested in the effects of ENSO on the interannual variability over this region. This report focuses on the association between ENSO and interannual variability of precipitation over Mexico.

A stochastic model of temporal variations in monthly temperature, precipitation, snowfall, and resulting snowpack

We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.