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.

The annual course of precipitation over much of the United States: observed versus GCM simulation

General Circulation Models (GCMs) may be useful in estimating the ecological impacts of global climatic change. We analyzed seasonal weather patterns over the conterminous United States and determined that regional patterns of rainfall seasonality appear to control the distributions of the Nation's major biomes. These regional patterns were compared to the output from three GCMs for validation. The models appear to simulate the appropriate seasonal climates in the northern tier of states. However, the spatial extent of these regions is distorted. None of the models accurately portrayed rainfall seasonalities in the southern tier of states, where biomes are primarily influenced by the Bermuda High.

Uncovering North American temperature and precipitation patterns associated with the Southern Oscillation

The extreme phases of the Southern Oscillation (SO) have been linked to fairly persistent classes of circulation anomalies over the North Pacific and parts of North America. It has been more difficult to uncover correspondingly consistent patterns of surface temperature and precipitation over much of the continent. The few regions that appear to have consistent SO-related patterns of temperature and precipitation anomalies are identified and discussed. Also discussed are regions that appear to have strong SO-related surface anomalies whose sign varies from episode to episode.

The influence of seasonal precipitation and temperature variations on runoff in California and southwestern Oregon

EXTRACT (SEE PDF FOR FULL ABSTRACT): There is considerable seasonal-to-interannual variability in the runoff of major watersheds in the Sierra Nevada, Coastal, and Cascade ranges of California and southwestern Oregon. This variability is reflected in both the amount and timing of runoff. This study examines that variability using long historical streamflow records and seasonal mean temperature and precipitation. ... Precipitation is the only significant predictor for both amount and timing of runoff in the low elevation basins. As elevation increases, the models rely more and more on temperature to explain amount and timing of runoff.

"Cool" vs. "warm" winter precipitation and its effect on streamflow in California

Precipitation is a difficult variable to understand and predict. In this study, monthly precipitation in California is divided into two classes according to the monthly temperature to better diagnose the atmospheric circulation that causes precipitation, and to illustrate how temperature compounds the precipitation to runoff process.

ENSO influences on atmospheric circulation and precipitation in the western United States

EXTRACT (SEE PDF FOR FULL ABSTRACT): The influence of ENSO on atmospheric circulation and precipitation over the western United States is presented from two perspectives. First, ENSO-associated circulation patterns over the North Pacific/North America sector were identified using an REOF (rotated empirical orthogonal function) analysis of the 700-mb height field and compositing these for extreme phases of the Southern Oscillation Index. ... Second, we examine the variability of precipitation during the warm and cool phases of ENSO for different locations in the western United States.

Semiempirical down-scaling of GCM output to the local scale for temperature, precipitation, and runoff

EXTRACT (SEE PDF FOR FULL ABSTRACT): An empirically derived multiple linear regression model is used to relate a local-scale dependent variable (either temperature, precipitation, or surface runoff) measured at individual gauging stations to six large-scale independent variables (temperature, precipitation, surface runoff, height to the 500-mbar pressure surface, and the zonal and meridional gradient across this surface). ...The area investigated is the western United States. ... The calibration data set is from 1948 through 1988 and includes data from 268 joint temperature and precipitation stations, 152 streamflow stations (which are converted to runoff data), and 24 gridded 500-mbar pressure height nodes.

Climatology of the seasonal precipitation maximum in the western United States

The western United States is characterized by heterogeneous patterns of seasonal precipitation regimes due to the hierarchy of climatic controls that operate at different spatial scales. A climatology of intermonthly precipitation changes, using data from more than 4,000 stations including high-elevation sites, illustrate how different climatic controls explain the spatial distribution of the seasonal precipitation maximum. These results indicate that smaller-scale climatic controls must be considered along with larger-scale ones to explain patterns of spatial climate heterogeneity over mountainous areas. The results also offer important implications for scholars interested in assessing spatial climatic variations of the western United States at different timescales.

Decadal hydroclimatic variability in the western coastal United States: temporal and spatial variations in precipitation, streamflow, and lake level

EXTRACT (SEE PDF FOR FULL ABSTRACT): We have analyzed streamflow variations recorded at 15 USGS gauging stations in California during the past 90 years or so. The anomalies (departures from the 1960-1990 mean discharge) of streamflow on annual-to-decadal time scales are strongly correlated with precipitation anomalies in each drainage basin. ... Although causes of the decadal climate (precipitation) variability are not known with certainty, the use of streamflow records may help us understand the relative strengths of moisture sources and shift of the jet stream in atmospheric circulation.

Long-term response of Torrey pine to coastal climate: precipitation, temperature, and fog

EXTRACT (SEE PDF FOR FULL ABSTRACT): Torrey pine (Pinus torreyana Parry ex Carr.) has one of the most limited geographical ranges and population size in the Pinus genus; it is present only on Santa Rosa Island and on the coast between San Diego and Del Mar, where our research was conducted. A 168-year chronology (1827-1994) was developed using 28 increment cores extracted from 15 living and 2 dead stranding trees at Torrey Pines State Reserve, San Diego, California. ... The spatial correlation with western North America winter and spring precipitation, as well as with published tree-ring chronologies, indicates a connection with the American Southwest. Global correlation maps with winter sea level pressure and sea surface temperature are consistent with the hypothesis that San Diego precipitation is affected by a southerly displaced North Pacific storm track and by warmer water farther south, both leading to higher transport of lower latitude moisture.