scholarly journals Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiaohui Zheng ◽  
Qiguang Wang ◽  
Lihua Zhou ◽  
Qing Sun ◽  
Qi Li
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Climate Models ◽  
Coastal Areas ◽  
Snow Accumulation ◽  
Western United States ◽  
Lead Times ◽  
Wet Season ◽  
Mountain Areas ◽  
Southeastern Pacific

This study used long-term in situ rainfall, snow, and streamflow data to explore the predictive contributions of snowmelt and rainfall to streamflow in six watersheds over the Western United States. Analysis showed that peak snow accumulation, snow-free day, and snowmelt slope all had strong correlation with peak streamflow, particularly in inland basins. Further analysis revealed that the variation of snow accumulation anomaly had strong lead correlation with the variation of streamflow anomaly. Over the entire Western United States, inner mountain areas had lead times of 4–10 pentads. However, in coastal areas, nearly all sites had lead times of less than one pentad. The relative contributions of rainfall and snowmelt to streamflow in different watersheds were calculated based on the snow lead time. The geographic distribution of annual relative contributions revealed that interior areas were dominated by snowmelt contribution, whereas the rainfall contribution dominated coastal areas. In the wet season, the snowmelt contribution increased in the western Pacific Northwest, whereas the rainfall contribution increased in the southeastern Pacific Northwest, southern Upper Colorado, and northern Rio Grande regions. The derived results demonstrated the predictive contributions of snowmelt and rainfall to streamflow. These findings could be considered a reference both for seasonal predictions of streamflow and for prevention of hydrological disasters. Furthermore, they will be helpful in the evaluation and improvement of hydrological and climate models.

scholarly journals Cool season precipitation projections for California and the Western United States in NA-CORDEX models

2021 ◽  
Author(s):  
Kelly Mahoney ◽  
James D. Scott ◽  
Michael Alexander ◽  
Rachel McCrary ◽  
Mimi Hughes ◽  
...  
Keyword(s):  
United States ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Western United States ◽  
Monthly Precipitation ◽  
Wet Season ◽  
Cool Season ◽  
Projected Change

AbstractUnderstanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

Identification of Resistance to Powdery Mildew in Publicly Available Male Hop Germplasm

2018 ◽  
Vol 19 (3) ◽  
pp. 258-264
Author(s):  
David H. Gent ◽  
Briana J. Claassen ◽  
Megan C. Twomey ◽  
Sierra N. Wolfenbarger
Keyword(s):  
United States ◽  
Powdery Mildew ◽  
Pacific Northwest ◽  
Western United States ◽  
R Genes ◽  
Sources Of Resistance ◽  
Department Of Agriculture ◽  
Breeding Programs ◽  
The Pacific ◽  
The U.S

Powdery mildew (caused by Podosphaera macularis) is one of the most important diseases of hop in the western United States. Strains of the fungus virulent on cultivars possessing the resistance factor termed R6 and the cultivar Cascade have become widespread in the Pacific Northwestern United States, the primary hop producing region in the country, rendering most cultivars grown susceptible to the disease at some level. In an effort to identify potential sources of resistance in extant germplasm, 136 male accessions of hop contained in the U.S. Department of Agriculture collection were screened under controlled conditions. Iterative inoculations with three isolates of P. macularis with varying race identified 23 (16.9%) accessions with apparent resistance to all known races of the pathogen present in the Pacific Northwest. Of the 23 accessions, 12 were resistant when inoculated with three additional isolates obtained from Europe that possess novel virulences. The nature of resistance in these individuals is unclear but does not appear to be based on known R genes. Identification of possible novel sources of resistance to powdery mildew will be useful to hop breeding programs in the western United States and elsewhere.

scholarly journals Seasonal Precipitation Influences Streamflow Vulnerability to the 2015 Drought in the Western United States

2019 ◽  
Vol 20 (7) ◽  
pp. 1261-1274
Author(s):  
Christopher P. Konrad
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Summer Precipitation ◽  
Western United States ◽  
Order Model ◽  
First Order ◽  
The Pacific ◽  
Critical Issues ◽  
Desert Southwest ◽  
Normative Models

Abstract Streamflow was exceptionally low in the spring and summer of 2015 across much of the western United States because of a regional drought that exploited the sensitivity of both snow- and rain-dominant rivers. Streamflow during 2015 was examined at 324 gauges in the region to assess its response to the amount, form, and seasonal timing of precipitation and the viability of using spatially aggregated, normative models to assess streamflow vulnerability to drought. Seasonal rain and spring snowmelt had the strongest effects on runoff during the same season, but their effects persisted into subsequent seasons as well. Below-normal runoff in the spring of 2015 was pervasive across the region, while distinct seasonal responses were evident in different hydroclimatic settings: January–March (winter) runoff was above normal in most snow-dominant rivers and runoff in all seasons was above normal for much of the desert Southwest. Summer precipitation contributed to summer runoff in both the Pacific Northwest and desert Southwest. A first-order model that presumes runoff is a constant fraction of precipitation (the precipitation elasticity of runoff, E = 1) could be used for assessing and forecasting runoff responses to precipitation deficits across the region, but runoff generally is more vulnerable to drought (E > 1) than predicted by a first-order model. Uncertainty in spring and summer precipitation forecasts remain critical issues for forecasting and predicting summer streamflow vulnerability to drought across much of the western United States.

scholarly journals The contribution of marine organics to the air quality of the western United States

2010 ◽  
Vol 10 (15) ◽  
pp. 7415-7423 ◽  
Author(s):  
B. Gantt ◽  
N. Meskhidze ◽  
A. G. Carlton
Keyword(s):  
United States ◽  
Air Quality ◽  
San Francisco ◽  
Atmospheric Chemistry ◽  
Environmental Protection Agency ◽  
Regional Scale ◽  
The United States ◽  
Coastal Areas ◽  
Western United States ◽  
The Us

Abstract. The contribution of marine organic emissions to the air quality in coastal areas of the western United States is studied using the latest version of the US Environmental Protection Agency (EPA) regional-scale Community Multiscale Air Quality (CMAQv4.7) modeling system. Emissions of marine isoprene, monoterpenes, and primary organic matter (POM) from the ocean are implemented into the model to provide a comprehensive view of the connection between ocean biology and atmospheric chemistry and air pollution. Model simulations show that marine organics can increase the concentration of PM2.5 by 0.1–0.3 μg m−3 (up to 5%) in some coastal cities such as San Francisco, CA. This increase in the PM2.5 concentration is primarily attributed to the POM emissions, with small contributions from the marine isoprene and monoterpenes. When marine organic emissions are included, organic carbon (OC) concentrations over the remote ocean are increased by up to 50% (25% in coastal areas), values consistent with recent observational findings. This study is the first to quantify the air quality impacts from marine POM and monoterpenes for the United States, and it highlights the need for inclusion of marine organic emissions in air quality models.

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 Will Future Climate Favor More Erratic Wildfires in the Western United States?

2013 ◽  
Vol 52 (11) ◽  
pp. 2410-2417 ◽  
Author(s):  
Lifeng Luo ◽  
Ying Tang ◽  
Shiyuan Zhong ◽  
Xindi Bian ◽  
Warren E. Heilman
Keyword(s):  
United States ◽  
Climate Models ◽  
Regional Climate ◽  
Fire Behavior ◽  
Regional Climate Models ◽  
Future Climate ◽  
Lower Atmosphere ◽  
Western United States ◽  
Mountainous Regions ◽  
Increased Risk

AbstractWildfires that occurred over the western United States during August 2012 were fewer in number but larger in size when compared with all other Augusts in the twenty-first century. This unique characteristic, along with the tremendous property damage and potential loss of life that occur with large wildfires with erratic behavior, raised the question of whether future climate will favor rapid wildfire growth so that similar wildfire activity may become more frequent as climate changes. This study addresses this question by examining differences in the climatological distribution of the Haines index (HI) between the current and projected future climate over the western United States. The HI, ranging from 2 to 6, was designed to characterize dry, unstable air in the lower atmosphere that may contribute to erratic or extreme fire behavior. A shift in HI distribution from low values (2 and 3) to higher values (5 and 6) would indicate an increased risk for rapid wildfire growth and spread. Distributions of Haines index are calculated from simulations of current (1971–2000) and future (2041–70) climate using multiple regional climate models in the North American Regional Climate Change Assessment Program. Despite some differences among the projections, the simulations indicate that there may be not only more days but also more consecutive days with HI ≥ 5 during August in the future. This result suggests that future atmospheric environments will be more conducive to erratic wildfires in the mountainous regions of the western United States.

scholarly journals Holocene climate and oceanography of the coastal Western United States and California Current System

2021 ◽  
Author(s):  
Hannah M. Palmer ◽  
Veronica Padilla Vriesman ◽  
Caitlin M. Livsey ◽  
Carina R. Fish ◽  
Tessa M. Hill
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Fire History ◽  
Variable Interval ◽  
Sea Surface ◽  
Western United States ◽  
Human Populations ◽  
Holocene Climate ◽  
California Current System ◽  
The Holocene

Abstract. To understand and contextualize modern climate change, we must improve our understanding of climatic and oceanographic changes in the Holocene (11.75 ka–present). Climate records of the Holocene can be utilized as a “baseline” from which to compare modern climate and can also provide insights into how environments and ecosystems experience and recover from environmental change. However, individual studies on Holocene climate in the literature tend to focus on a distinct geographic location, a specific proxy record, or a certain aspect of climate (e.g., upwelling or precipitation), resulting in localized, record-specific trends rather than a comprehensive view of climate variability through the Holocene. Here we synthesize the major oceanographic and terrestrial changes that have occurred in the Western United States (bounded by 30° N to 52° N and 115° W to 130° W) through the most recent 11.75 ka and explore the impacts of these changes on marine and terrestrial ecosystems and human populations. This three-tiered systematic review combines interpretations from over 100 published studies, codes and geospatially analyzes temperature, hydroclimate, and fire history from over 50 published studies, and interprets nine representative time series through the Holocene. We find that the early Holocene is characterized by warming relative to pre-Holocene conditions, including warm sea surface conditions, a warm and dry Pacific Northwest, a warm and wet Southwest, and overall spatial and temporal stability. In the mid Holocene, these patterns reverse; this interval is characterized by cool sea surface temperatures, a cool and wet Pacific Northwest and warm and dry Southwest. The late Holocene is the most variable interval, both spatially and temporally, and a novel spatial trend appears in terrestrial climate with warmer coastal areas and cooler inland areas. Human communities interacted with the environment throughout the entire Holocene, as evidenced in archeological and paleoenvironmental records, yet the recent era of colonization (1850–present) represents an unprecedented environmental interval in many records. Overall, our analysis shows linkages between terrestrial and oceanographic conditions, distinct environmental phases through time, and emphasizes the importance of local factors in controlling climate through the dynamic Holocene.

scholarly journals Long-range climate forecasting and its use for water management in the Pacific Northwest region of North America

2000 ◽  
Vol 2 (3) ◽  
pp. 163-182 ◽  
Author(s):  
Alan F. Hamlet ◽  
Dennis P. Lettenmaier
Keyword(s):  
Pacific Northwest ◽  
Time Scales ◽  
Climate Models ◽  
Climate Model ◽  
Lead Times ◽  
Climate Forecasting ◽  
The Pacific ◽  
Climate Forecasts ◽  
Resampling Method ◽  
Streamflow Forecasts

Ongoing research by the Climate Impacts Group at the University of Washington focuses on the use of recent advances in climate research to improve streamflow forecasts at seasonal-to-interannual, decadal, and longer time scales. Seasonal-to-interannual climate forecasting capabilities have advanced significantly in the past several years, primarily because of improvements in the understanding of, and an ability to forecast, El Niño/Southern Oscillation (ENSO) at seasonal/interannual time scales, and because of better understanding of longer time scale climate phenomena like the Pacific Decadal Oscillation (PDO). These phenomena exert strong controls on climate variability along the Pacific Coast of North America. The streamflow forecasting techniques we have developed for Pacific Northwest (PNW) rivers are based on climate forecasts that facilitate longer lead times (as much as a year) than the methods that are traditionally used for water management (maximum forecast lead times of a few months). At interannual time scales, the simplest of these techniques involves resampling meteorological data from previous years identified to be in similar climate categories as are forecast for the coming year. These data are then used to drive a hydrology model, which produces an ensemble of streamflow forecasts that are analogous to those that result from the well-known Extended Streamflow Prediction (ESP) method. This technique is a relatively simple, but effective, way of incorporating long-lead climate information into streamflow forecasts. It faithfully captures the history of observed climate variability. Its main limitation is that the sample size of observed events for some climate categories is small because of the length of the historic record. Furthermore, it is unable to capture important aspects of global change, which may interact with shorter term variations through changes in climate phenomena like ENSO and PDO. An alternative to the resampling method is to use nested regional climate models to produce the long-lead climate forecasts. Success using this approach has been hindered to some degree by the bias that is inherent in climate models, even when downscaled using regional nested modeling approaches. Adjustment or correction for this bias is central to the use of climate model output for hydrologic forecasting purposes. Approaches for dealing with climate model bias in the context of global and meso-scale are presently an area of active research. We illustrate an experimental application of the nested climate modeling approach for the Columbia River Basin, and compare it with the simpler resampling method. At much longer time scales, changes in Columbia River flows that might be associated with global climate change are of considerable concern in the PNW, given recent Endangered Species Act listing of certain salmonid species, and the increase in water demand that is expected to follow increases in human population in the region. Many of the same general challenges associated with the spatial downscaling of climate forecasts are present in these long-range investigations. Additional uncertainties exist in the ability of climate models to predict the effects of changing greenhouse gas concentrations. These uncertainties tend to dominate the results, and lead us to use relatively simplemethods of downscaling seasonal temperature and precipitation to interpret the implications of alternative climate scenarios on PNW water resources.

Characterizing Predictability of Precipitation Means and Extremes over the Conterminous United States, 1949–2010*

2016 ◽  
Vol 29 (7) ◽  
pp. 2621-2633 ◽  
Author(s):  
Mingkai Jiang ◽  
Benjamin S. Felzer ◽  
Dork Sahagian
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
West Coast ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
The United States ◽  
Monthly Precipitation ◽  
The West ◽  
Precipitation Seasonality

Abstract The proper understanding of precipitation variability, seasonality, and predictability are important for effective environmental management. Precipitation and its associated extremes vary in magnitude and duration both spatially and temporally, making it one of the most challenging climate parameters to predict on the basis of global and regional climate models. Using information theory, an improved understanding of precipitation predictability in the conterminous United States over the period of 1949–2010 is sought based on a gridded monthly precipitation dataset. Predictability is defined as the recurrent likelihood of patterns described by the metrics of magnitude variability and seasonality. It is shown that monthly mean precipitation and duration-based dry and wet extremes are generally highly variable in the east compared to those in the west, while the reversed spatial pattern is observed for intensity-based wetness indices except along the Pacific Northwest coast. It is thus inferred that, over much of the U.S. landscape, variations of monthly mean precipitation are driven by the variations in precipitation occurrences rather than the intensity of infrequent heavy rainfall. It is further demonstrated that precipitation seasonality for means and extremes is homogeneously invariant within the United States, with the exceptions of the West Coast, Florida, and parts of the Midwest, where stronger seasonality is identified. A proportionally higher role of variability in regulating precipitation predictability is demonstrated. Seasonality surpasses variability only in parts of the West Coast. The quantified patterns of predictability for precipitation means and extremes have direct applications to those phenomena influenced by climate periodicity, such as biodiversity and ecosystem management.

Sign in / Sign up

Export Citation Format

Share Document