scholarly journals NOAA’s 1981–2010 U.S. Climate Normals: Monthly Precipitation, Snowfall, and Snow Depth

2013 ◽  
Vol 52 (11) ◽  
pp. 2377-2395 ◽  
Author(s):  
Imke Durre ◽  
Michael F. Squires ◽  
Russell S. Vose ◽  
Xungang Yin ◽  
Anthony Arguez ◽  
...  
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Great Plains ◽  
Snow Depth ◽  
State Of The Art ◽  
The United States ◽  
Climatic Data ◽  
Monthly Precipitation ◽  
National Climatic Data Center ◽  
The Caribbean

AbstractThe 1981–2010 “U.S. Climate Normals” released by the National Oceanic and Atmospheric Administration’s (NOAA) National Climatic Data Center include a suite of monthly, seasonal, and annual statistics that are based on precipitation, snowfall, and snow-depth measurements. This paper describes the procedures used to calculate the average totals, frequencies of occurrence, and percentiles that constitute these normals. All parameters were calculated from a single, state-of-the-art dataset of daily observations, taking care to produce normals that were as representative as possible of the full 1981–2010 period, even when the underlying data records were incomplete. In the resulting product, average precipitation totals are available at approximately 9300 stations across the United States and parts of the Caribbean Sea and Pacific Ocean islands. Snowfall and snow-depth statistics are provided for approximately 5300 of those stations, as compared with several hundred stations in the 1971–2000 normals. The 1981–2010 statistics exhibit the familiar climatological patterns across the contiguous United States. When compared with the same calculations for 1971–2000, the later period is characterized by a smaller number of days with snow on the ground and less total annual snowfall across much of the contiguous United States; wetter conditions over much of the Great Plains, Midwest, and northern California; and drier conditions over much of the Southeast and Pacific Northwest. These differences are a reflection of the removal of the 1970s and the addition of the 2000s to the 30-yr-normals period as part of this latest revision of the normals.

scholarly journals The Regional Snowfall Index

2014 ◽  
Vol 95 (12) ◽  
pp. 1835-1848 ◽  
Author(s):  
Michael F. Squires ◽  
Jay H. Lawrimore ◽  
Richard R. Heim ◽  
David A. Robinson ◽  
Mathieu R. Gerbush ◽  
...  
Keyword(s):  
United States ◽  
Data Center ◽  
Historical Perspective ◽  
The United States ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Impact Scale ◽  
Population Information ◽  
Regional Index ◽  
The Impact

This paper describes a new snowfall index that quantifies the impact of snowstorms within six climate regions in the United States. The regional snowfall index (RSI) is based on the spatial extent of snowfall accumulation, the amount of snowfall, and the juxtaposition of these elements with population. Including population information provides a measure of the societal susceptibility for each region. The RSI is an evolution of the Northeast snowfall impact scale (NESIS), which NOAA's National Climatic Data Center began producing operationally in 2006. While NESIS was developed for storms that had a major impact in the Northeast, it includes all snowfall during the lifetime of a storm across the United States and as such can be thought of as a quasi-national index that is calibrated to Northeast snowstorms. By contrast, the RSI is a regional index calibrated to specific regions using only the snow that falls within that region. This paper describes the methodology used to compute the RSI, which requires region-specific parameters and thresholds, and its application within six climate regions in the eastern two-thirds of the nation. The process used to select the region-specific parameters and thresholds is explained. The new index has been calculated for over 580 snowstorms that occurred between 1900 and 2013 providing a century-scale historical perspective for these snowstorms. The RSI is computed for category 1 or greater storms in near–real time, usually a day after the storm has ended.

Trends in Snow Cover and Related Quantities at Weather Stations in the Conterminous United States

2015 ◽  
Vol 28 (19) ◽  
pp. 7518-7528 ◽  
Author(s):  
Noah Knowles
Keyword(s):  
United States ◽  
Correlation Analysis ◽  
Snow Cover ◽  
Canonical Correlation Analysis ◽  
Great Plains ◽  
Canonical Correlation ◽  
Snow Depth ◽  
The United States ◽  
Eastern Half ◽  
Precipitation Trends

Abstract Trend tests, linear regression, and canonical correlation analysis were used to quantify changes in National Weather Service Cooperative Observer (COOP) snow depth data and derived quantities, precipitation, snowfall, and temperature over the study period 1950–2010. Despite widespread warming, historical trends in snowfall and snow depth are generally mixed owing to competing influences of trends in precipitation. Trends toward later snow-cover onset in the western half of the conterminous United States and earlier onset in the eastern half and a widespread trend toward earlier final meltoff of snow cover combined to produce trends toward shorter snow seasons in the eastern half of the United States and in the west and longer snow seasons in the Great Plains and southern Rockies. The annual total number of days with snow cover exhibited a widespread decline. Monthly trend patterns show the dominant influence of temperature trends on occurrence of snow cover in the warmer snow-season months and a combination of temperature and precipitation trends in the colder months. A canonical correlation analysis indicated that most trends presented here took hold in the 1970s, consistent with the temporal pattern of global warming during the study period.

scholarly journals Race Characterization of Puccinia striiformis f. sp. tritici, the Cause of Wheat Stripe Rust, in Saskatchewan and Southern Alberta, Canada and Virulence Comparison with Races from the United States

Plant Disease ◽  
2016 ◽  
Vol 100 (8) ◽  
pp. 1744-1753 ◽  
Author(s):  
G. S. Brar ◽  
H. R. Kutcher
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Stripe Rust ◽  
Great Plains ◽  
Puccinia Striiformis ◽  
The United States ◽  
Wheat Stripe Rust ◽  
The Pacific ◽  
Southern Alberta ◽  
Virulence Frequency

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, has been common across Saskatchewan, Canada since 2000. Fifty-nine isolates of P. striiformis f. sp. tritici, the majority of which were collected between 2011 and 2013 from Saskatchewan and southern Alberta, were analyzed for virulence frequency and diversity and compared with isolates characterized in the Pacific Northwest and Great Plains regions of the United States. In all, 31 wheat differentials, including 20 near-isogenic lines and 1 triticale variety, differentiated 59 P. striiformis f. sp. tritici isolates into 33 races, of which one race, C-PST-1, represented 31% of the isolates. None of the races were virulent on Yr5, Yr15, or YrSP. Virulence frequency ranged from 65 to 98% on YrA, Yr2, Yr8, Yr9, Yr27, Yr29, Yr32, YrSu, ‘Heines VII’, and ‘Nord Deprez’. Race C-PST-6 was virulent on the greatest number of the differentials (n = 25) and C-PST-18 on the fewest (n = 14). Discriminant analysis of principal components and multivariate cluster analyses detected three and four major groups, respectively, which differed from each other in terms of virulence spectrum and year of collection. The diversity of the P. striiformis f. sp. tritici population in southern Alberta was greater than in Saskatchewan, which indicated that, although P. striiformis f. sp. tritici is primarily windborne over great distances and does not usually overwinter, there are detectable differences in virulence between these regions of western Canada. Comparative analyses of virulence frequency of Saskatchewan or southern Alberta isolates with isolates representing races from the Great Plains and the Pacific Northwest of the United States indicated greater similarity of Saskatchewan races to the Great Plains despite strong correlations with both parts of the United States. This suggests that the P. striiformis f. sp. tritici population in Saskatchewan is a mixture of inoculum from both parts of the United States.

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.

scholarly journals Comparison of Virulence and Isozyme Phenotypes of Pgt-QCCJ and Great Plains Races of Puccinia graminis f. sp. tritici

1997 ◽  
Vol 87 (9) ◽  
pp. 910-914 ◽  
Author(s):  
A. P. Roelfs ◽  
B. McCallum ◽  
D. V. McVey ◽  
J. V. Groth
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Great Plains ◽  
Stem Rust ◽  
The United States ◽  
Northern Great Plains ◽  
Puccinia Graminis ◽  
The Pacific ◽  
Sexual Recombination ◽  
Winter Wheat Cultivars

Stem rust race Pgt-QCCJ was first found in the Great Plains of the United States in 1989, collected primarily from barley. This race became a major part of the Puccinia graminis f. sp. tritici population, even though it is virulent to only a few hard red winter wheat cultivars in the central Great Plains and to barley in the northern Great Plains. It threatens barley production in the northern Great Plains of the United States and Canada due to virulence to Rpg-1. Six differences in virulence and two in isozyme banding patterns from the most similar stem rust races make it unlikely that QCCJ arose as a mutant. Thus, QCCJ likely arose through sexual or parasexual recombination. Sexual recombination in the Great Plains is unlikely, as it has not been detected in many years. Avirulence to ‘McNair 70l’ is only known from the Pacific Northwest of the United States and adjacent Canada. The rust population in this area is of sexual origin, and the pattern of virulence/avirulence and isozyme banding for QCCJ occurs there. Pgt-QCCJ likely originated in the Pacific Northwest during or before 1989 and was wind-transported into the Great Plains.

scholarly journals Effects of Daily Temperature Highs on Development of Phakopsora pachyrhizi on Soybean

2012 ◽  
Vol 102 (8) ◽  
pp. 761-768 ◽  
Author(s):  
M. R. Bonde ◽  
S. E. Nester ◽  
D. K. Berner
Keyword(s):  
United States ◽  
Southeastern United States ◽  
The United States ◽  
Daily Temperature ◽  
Soybean Rust ◽  
Limiting Factor ◽  
Climatic Data ◽  
Phakopsora Pachyrhizi ◽  
Diurnal Temperature ◽  
National Climatic Data Center

Although considerable information exists regarding the importance of moisture in the development of soybean rust, little is known about the influence of temperature. The purpose of our study was to determine whether temperature might be a significant limiting factor in the development of soybean rust in the southeastern United States. Soybean plants infected with Phakopsora pachyrhizi were incubated in temperature-controlled growth chambers simulating day and night diurnal temperature patterns representative of the southeastern United States during the growing season. At 3-day intervals beginning 12 days after inoculation, urediniospores were collected from each plant and counted. The highest numbers of urediniospores were produced when day temperatures peaked at 21 or 25°C and night temperatures dipped to 8 or 12°C. When day temperatures peaked at 29, 33, or 37°C for a minimum of 1 h/day, urediniospore production was reduced to 36, 19, and 0%, respectively, compared with urediniospore production at the optimum diurnal temperature conditions. Essentially, no lesions developed when the daily temperature high was 37°C or above. Temperature data obtained from the National Climatic Data Center showed that temperature highs during July and August in several southeastern states were too high for significant urediniospore production on 55 to 77% of days. The inhibition of temperature highs on soybean rust development in southeastern states not only limits disease locally but also has implications pertaining to spread of soybean rust into and development of disease in the major soybean-producing regions of the Midwestern and northern states. We concluded from our results that temperature highs common to southeastern states are a factor in the delay or absence of soybean rust in much of the United States.

scholarly journals A New Homogenized Climate Division Precipitation Dataset for Analysis of Climate Variability and Climate Change

2011 ◽  
Vol 50 (6) ◽  
pp. 1187-1199 ◽  
Author(s):  
D. Brent McRoberts ◽  
John W. Nielsen-Gammon
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Weighted Average ◽  
The United States ◽  
Climatic Data ◽  
Monthly Precipitation ◽  
Precipitation Trend ◽  
Climate Trends ◽  
Climate Division ◽  
National Climatic Data Center

AbstractA new homogeneous climate division monthly precipitation dataset [based on full network estimated precipitation (FNEP)] was created as an alternative to the National Climatic Data Center (NCDC) climate division dataset. These alternative climate division monthly precipitation values were estimated using an equal-weighted average of Cooperative Observer Program stations that contained serially complete time series. Missing station observations were estimated by a procedure that was optimized through testing on U.S. Historical Climate Network stations. Inhomogeneities in the NCDC dataset arise from two principal causes. The pre-1931 estimation of NCDC climate division monthly precipitation from statewide averages led to a significant time series discontinuity in several climate divisions. From 1931 to the present, NCDC climate division averages have been calculated from a subset of available station data within each climate division, and temporal changes in the location of available stations have caused artificial changes in the time series. The FNEP climate division dataset is recommended over the NCDC dataset for studies involving climate trends or long-term climate variability. According to the FNEP data, the 1895–2009 linear precipitation trend is positive across most of the United States, and trends exceed 10% per century across the southern plains and the Corn Belt. Remaining inhomogeneities from changes in gauge technology and station location may be responsible for an artificial trend of 1%–3% per century.

scholarly journals Precipitation Deficit Flash Droughts over the United States

2016 ◽  
Vol 17 (4) ◽  
pp. 1169-1184 ◽  
Author(s):  
Kingtse C. Mo ◽  
Dennis P. Lettenmaier
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Heat Wave ◽  
Great Plains ◽  
Land Surface ◽  
The United States ◽  
Southern Great Plains ◽  
Physical Mechanisms ◽  
The Pacific ◽  
Surface Models

Abstract Flash drought refers to relatively short periods of warm surface temperature and anomalously low and rapid decreasing soil moisture (SM). Based on the physical mechanisms associated with flash droughts, these events are classified into two categories: heat wave and precipitation P deficit flash droughts. In previous work, the authors have defined heat wave flash droughts as resulting from the confluence of severe warm air temperature Tair, which increases evapotranspiration (ET), and anomalously low and decreasing SM. Here, a second type of flash drought caused by precipitation deficits is explored. The authors term these events P-deficit flash droughts, which they associate with lack of P. Precipitation deficits cause ET to decrease and temperature to increase. The P-deficit flash droughts are analyzed based on observations of P, Tair, and SM and ET reconstructed using land surface models for the period 1916–2013. The authors find that P-deficit flash droughts are more common than heat wave flash droughts. They are about twice as likely to occur as heat wave flash droughts over the conterminous United States. They are most prevalent over the southern United States with maxima over the southern Great Plains and the Southwest, in contrast to heat wave flash droughts that are mostly likely to occur over the Midwest and the Pacific Northwest, where the vegetation cover is dense.

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