Extreme reversals in successive winter season precipitation anomalies across the Western United States, 1895-2015

2017 ◽  
Vol 38 (3) ◽  
pp. 1520-1532 ◽  
Author(s):  
Michael L. Marston ◽  
Andrew W. Ellis
Keyword(s):  
United States ◽  
Winter Season ◽  
Western United States ◽  
Precipitation Anomalies

scholarly journals Verification of Surface Temperature Forecasts from the National Digital Forecast Database over the Western United States

2006 ◽  
Vol 21 (5) ◽  
pp. 869-892 ◽  
Author(s):  
David T. Myrick ◽  
John D. Horel
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Winter Season ◽  
Forecast Accuracy ◽  
Horizontal Resolution ◽  
Western United States ◽  
Lead Times ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Mean Square Errors

Abstract Experimental gridded forecasts of surface temperature issued by National Weather Service offices in the western United States during the 2003/04 winter season (18 November 2003–29 February 2004) are evaluated relative to surface observations and gridded analyses. The 5-km horizontal resolution gridded forecasts issued at 0000 UTC for forecast lead times at 12-h intervals from 12 to 168 h were obtained from the National Digital Forecast Database (NDFD). Forecast accuracy and skill are determined relative to observations at over 3000 locations archived by MesoWest. Forecast quality is also determined relative to Rapid Update Cycle (RUC) analyses at 20-km resolution that are interpolated to the 5-km NDFD grid as well as objective analyses obtained from the Advanced Regional Prediction System Data Assimilation System that rely upon the MesoWest observations and RUC analyses. For the West as a whole, the experimental temperature forecasts issued at 0000 UTC during the 2003/04 winter season exhibit skill at lead times of 12, 24, 36, and 48 h on the basis of several verification approaches. Subgrid-scale temperature variations and observational and analysis errors undoubtedly contribute some uncertainty regarding these results. Even though the “true” values appropriate to evaluate the forecast values on the NDFD grid are unknown, it is estimated that the root-mean-square errors of the NDFD temperature forecasts are on the order of 3°C at lead times shorter than 48 h and greater than 4°C at lead times longer than 120 h. However, such estimates are derived from only a small fraction of the NDFD grid boxes. Incremental improvements in forecast accuracy as a result of forecaster adjustments to the 0000 UTC temperature grids from 144- to 24-h lead times are estimated to be on the order of 13%.

scholarly journals Spatiotemporal Characteristics of Snowpack Density in the Mountainous Regions of the Western United States

2008 ◽  
Vol 9 (6) ◽  
pp. 1416-1426 ◽  
Author(s):  
Naoki Mizukami ◽  
Sanja Perica
Keyword(s):  
United States ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Western United States ◽  
Densification Rate ◽  
Snow Density ◽  
Mountainous Regions ◽  
Spatiotemporal Characteristics ◽  
Snow Water

Abstract Snow density is calculated as a ratio of snow water equivalent to snow depth. Until the late 1990s, there were no continuous simultaneous measurements of snow water equivalent and snow depth covering large areas. Because of that, spatiotemporal characteristics of snowpack density could not be well described. Since then, the Natural Resources Conservation Service (NRCS) has been collecting both types of data daily throughout the winter season at snowpack telemetry (SNOTEL) sites located in the mountainous areas of the western United States. This new dataset provided an opportunity to examine the spatiotemporal characteristics of snowpack density. The analysis of approximately seven years of data showed that at a given location and throughout the winter season, year-to-year snowpack density changes are significantly smaller than corresponding snow depth and snow water equivalent changes. As a result, reliable climatological estimates of snow density could be obtained from relatively short records. Snow density magnitudes and densification rates (i.e., rates at which snow densities change in time) were found to be location dependent. During early and midwinter, the densification rate is correlated with density. Starting in early or mid-March, however, snowpack density increases by approximately 2.0 kg m−3 day−1 regardless of location. Cluster analysis was used to obtain qualitative information on spatial patterns of snowpack density and densification rates. Four clusters were identified, each with a distinct density magnitude and densification rate. The most significant physiographic factor that discriminates between clusters was proximity to a large water body. Within individual mountain ranges, snowpack density characteristics were primarily dependent on elevation.

Influence of winter season climate variability on snow-precipitation ratio in the western United States

2015 ◽  
Vol 36 (9) ◽  
pp. 3175-3190 ◽  
Author(s):  
Mohammad Safeeq ◽  
Shraddhanand Shukla ◽  
Ivan Arismendi ◽  
Gordon E. Grant ◽  
Sarah L. Lewis ◽  
...  
Keyword(s):  
United States ◽  
Climate Variability ◽  
Winter Season ◽  
Western United States ◽  
Precipitation Ratio ◽  
Snow Precipitation

scholarly journals Climatology of Orographic Precipitation Gradients in the Contiguous Western United States

2020 ◽  
Vol 21 (8) ◽  
pp. 1723-1740
Author(s):  
Lucas Bohne ◽  
Courtenay Strong ◽  
W. James Steenburgh
Keyword(s):  
United States ◽  
Function Analysis ◽  
Precipitation Amount ◽  
Winter Season ◽  
Western United States ◽  
Orographic Precipitation ◽  
Spatial And Temporal Patterns ◽  
Case Examples ◽  
Modes Of Variability ◽  
States Experience

AbstractOrographic precipitation gradients (OPG) relating to the increase or decrease in precipitation amount with elevation are not well studied or analyzed except for case examples. A quality controlled daily OPG dataset for the western United States that is based on a linear regression framework of gauge precipitation observations and elevation for a 39-yr time period was created and analyzed to identify spatial and temporal patterns and variability in OPG and some of the drivers of variability on seasonal, annual, interannual, and climatological time scales. Most locations in the western United States experience positive OPG during most of the year, exhibiting an annual cycle with the highest magnitude of OPG in the winter season and lowest magnitude of OPG in the summer season. Coastal locations tend to have OPG with higher magnitude and larger variability in OPG than do interior locations during cool seasons. Empirical orthogonal function analysis identifies two principal components that account for 33% of the variability in a subset of the OPG dataset, and these modes of variability are related to precipitation amount and atmospheric circulation over the Pacific Ocean. Comparison of daily OPG with similarly calculated 3-day and monthly OPG identifies that OPG magnitudes are sensitive to the choice of length of the precipitation accumulation period.

HIBERNATION PECULIARITIES OF PLATYSAMIA GLOVERI STR. (SATURNIIDAE, LEPIDOPTERA)

1940 ◽  
Vol 72 (5) ◽  
pp. 89-90
Author(s):  
James B. Duncan
Keyword(s):  
United States ◽  
Winter Season ◽  
Rocky Mountain ◽  
Mountain Region ◽  
Western United States ◽  
Rocky Mountain Region ◽  
Varying Length

Recent observations of Platysamia gloveri Str. have brought out some interesting facts on the varying length of hibernation periods. The gloveri moth is restricted almost entirely to the Rocky Mountain Region of the western United States. This implies in general, therefore, the ability to withstand subzero weather throughout the lengthy winter season.

scholarly journals Sensitivity of Surface Analyses over the Western United States to RAWS Observations

2008 ◽  
Vol 23 (1) ◽  
pp. 145-158 ◽  
Author(s):  
David T. Myrick ◽  
John D. Horel
Keyword(s):  
United States ◽  
Wind Speed ◽  
Winter Season ◽  
Western United States ◽  
Cold Pool ◽  
Federal State ◽  
Advanced Regional Prediction System ◽  
Average Analysis ◽  
Regional Prediction ◽  
The Impact

Abstract Federal, state, and other wildland resource management agencies contribute to the collection of weather observations from over 1000 Remote Automated Weather Stations (RAWS) in the western United States. The impact of RAWS observations on surface objective analyses during the 2003/04 winter season was assessed using the Advanced Regional Prediction System (ARPS) Data Assimilation System (ADAS). A set of control analyses was created each day at 0000 and 1200 UTC using the Rapid Update Cycle (RUC) analyses as the background fields and assimilating approximately 3000 surface observations from MesoWest. Another set of analyses was generated by withholding all of the RAWS observations available at each time while 10 additional sets of analyses were created by randomly withholding comparable numbers of observations obtained from all sources. Random withholding of observations from the analyses provides a baseline estimate of the analysis quality. Relative to this baseline, removing the RAWS observations degrades temperature (wind speed) analyses by an additional 0.5°C (0.9 m s−1) when evaluated in terms of rmse over the entire season. RAWS temperature observations adjust the RUC background the most during the early morning hours and during winter season cold pool events in the western United States while wind speed observations have a greater impact during active weather periods. The average analysis area influenced by at least 1.0°C (2.5°C) by withholding each RAWS observation is on the order of 600 km2 (100 km2). The spatial influence of randomly withheld observations is much less.

scholarly journals A New Method to Characterize Changes in the Seasonal Cycle of Snowpack

2019 ◽  
Vol 58 (1) ◽  
pp. 131-143 ◽  
Author(s):  
Amato T. Evan
Keyword(s):  
United States ◽  
Annual Cycle ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
New Method ◽  
Western United States ◽  
Gaussian Shape ◽  
Annual Cycles ◽  
Snow Water ◽  
High Elevations

AbstractIn the western United States, water stored as mountain snowpack is a large percentage of the total water needed to meet the region’s demands, and it is likely that, as the planet continues to warm, mountain snowpack will decline. However, detecting such trends in the observational record is challenging because snowpack is highly variable in both space and time. Here, a method for characterizing mountain snowpack is developed that is based on fitting observed annual cycles of snow water equivalent (SWE) to a gamma-distribution probability density function. A new method for spatially interpolating the distribution’s fitting parameters to create a gridded climatology of SWE is also presented. Analysis of these data shows robust trends in the shape of the annual cycle of snowpack in the western United States. Over the 1982–2017 water years, the annual cycle of snowpack is becoming narrower and more Gaussian. A narrowing of the annual cycle corresponds to a shrinking of the length of the winter season, primarily because snowpack melting is commencing earlier in the water year. Because the annual cycle of snowpack at high elevations tends to be more skewed than at lower elevations, a more Gaussian shape suggests that snowpack is becoming more characteristic of that at lower elevations. Although no robust downward trends in annual-mean SWE are found, robust trends in the shape of the SWE annual cycle have implications for regional water resources.

Writing Time in Metaphors

2018 ◽  
Author(s):  
Jennifer J. Smith
Keyword(s):  
United States ◽  
The United States ◽  
Western United States ◽  
Entire System ◽  
Language And Culture ◽  
Space Race ◽  
Do So

Coherence of place often exists alongside irregularities in time in cycles, and chapter three turns to cycles linked by temporal markers. Ray Bradbury’s The Martian Chronicles (1950) follows a linear chronology and describes the exploration, conquest, and repopulation of Mars by humans. Conversely, Louise Erdrich’s Love Medicine (1984) jumps back and forth across time to narrate the lives of interconnected families in the western United States. Bradbury’s cycle invokes a confluence of historical forces—time as value-laden, work as a calling, and travel as necessitating standardized time—and contextualizes them in relation to anxieties about the space race. Erdrich’s cycle invokes broader, oppositional conceptions of time—as recursive and arbitrary and as causal and meaningful—to depict time as implicated in an entire system of measurement that made possible the destruction and exploitation of the Chippewa people. Both volumes understand the United States to be preoccupied with imperialist impulses. Even as they critique such projects, they also point to the tenacity with which individuals encounter these systems, and they do so by creating “interstitial temporalities,” which allow them to navigate time at the crossroads of language and culture.

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