scholarly journals Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Niloufar Nouri ◽  
Naresh Devineni ◽  
Valerie Were ◽  
Reza Khanbilvardi
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Southern Oscillation ◽  
The United States ◽  
Anthropogenic Factors ◽  
Climate Variables ◽  
Term Trend ◽  
Cyclical Variability ◽  
Long Term Trend

AbstractThe annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

scholarly journals Bayesian probabilistic forecasting with large-scale educational trend data: a case study using NAEP

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
David Kaplan ◽  
Mingya Huang
Keyword(s):  
United States ◽  
Large Scale ◽  
Population Level ◽  
The United States ◽  
The State ◽  
Probabilistic Forecasting ◽  
Term Trend ◽  
Trend Data ◽  
Long Term Trend

AbstractOf critical importance to education policy is monitoring trends in education outcomes over time. In the United States, the National Assessment of Educational Progress (NAEP) has provided long-term trend data since 1970; at the state/jurisdiction level, NAEP has provided long-term trend data since 1996. In addition to the national NAEP, all 50 states and United States jurisdictions participate in the state NAEP assessment. Thus, NAEP provides important monitoring and forecasting information regarding population-level academic performance of relevance to national and international goals. However, an inspection of NAEP trend reports shows that relatively simple trend plots are provided; and although these plots are important for communicating general trend information, we argue that much more useful information can be obtained by adopting a Bayesian probabilistic forecasting point of view. The purpose of this paper is to provide a Bayesian probabilistic forecasting workflow that can be used with large-scale assessment trend data generally, and to demonstrate that workflow with an application to the state NAEP assessments.

DIPHTHERIA IN THE UNITED STATES, 1959-1960

PEDIATRICS ◽  
1962 ◽  
Vol 30 (2) ◽  
pp. 194-205
Author(s):  
Theodore C. Doege ◽  
Clark W. Heath ◽  
Ida L. Sherman
Keyword(s):  
United States ◽  
Communicable Disease ◽  
Case Fatality ◽  
The United States ◽  
Surveillance Data ◽  
Term Trend ◽  
The Past ◽  
Primary Series ◽  
Long Term Trend

Diphtheria attack rates and cases, and to a much lesser extent case-fatality rates, have fallen steadily within the United States during the past 25 years. However, during 1959 and 1960 there was a halt in this long-term trend. Epidemiologic data on 868 clinical cases of diphtheria occurring in 1959 and 873 cases in 1960 were submitted to the Communicable Disease Center by 45 states. The cases and several major outbreaks tended to concentrate in the southern and southwestern states. Attack rates and deaths were highest for children under 10 years, and attack rates were more than five times greater for nonwhite children. Analysis of 1960 immunization data shows that 72% of the patients had received no immunizations. Fifty-five per cent of carriers, but only 18% of persons with bacteriologically confirmed cases, had received a primary series. Only 1 person of 58 fatal cases occurring in 1960 had received a primary series. Certain problems for future investigation, disclosed by the surveillance data, are discussed.

scholarly journals Long-term trend and correlation between vegetation greenness and climate variables in Asia based on satellite data

2018 ◽  
Vol 618 ◽  
pp. 1089-1095 ◽  
Author(s):  
Munkhnasan Lamchin ◽  
Woo-Kyun Lee ◽  
Seong Woo Jeon ◽  
Sonam Wangyel Wang ◽  
Chul Hee Lim ◽  
...  
Keyword(s):  
Satellite Data ◽  
Climate Variables ◽  
Term Trend ◽  
Vegetation Greenness ◽  
Long Term Trend

“Trump’s First Year in Asia: Accelerating a Long-term Trend”

2018 ◽  
Vol 25 (2) ◽  
pp. 198-220 ◽  
Author(s):  
David C. Kang
Keyword(s):  
East Asia ◽  
The United States ◽  
First Year ◽  
Foreseeable Future ◽  
Real Possibility ◽  
Term Trend ◽  
Trade War ◽  
The Impact ◽  
Long Term Trend

What has been the impact of Donald J. Trump’s presidency on the place of the United States in East Asia? Trump already has shown a proclivity for upending the mainstream American consensus about grand strategy to East Asia, with the real possibility of a trade war with China or a shooting war with North Korea on the horizon. However, this article will place President Trump’s first year in office into a larger context of long-term decline of U.S. leadership and influence in East Asia, arguing that this trend has been underway for quite some time, and that Trump has not altered fundamentally this trajectory. Some of Trump’s actions may accelerate a decline in U.S. leadership, but by no means was Trump the first nor will he be the last U.S. president to deal with a swiftly changing East Asia. The region has been changing rapidly for decades, and there are no indications that this will stop anytime soon. However, continuing and gradual U.S. withdrawal from leadership does not mean less American-East Asia interaction. East Asia will remain the most important trading and investment region for the U.S. for the foreseeable future.

scholarly journals On the Maximum Observed Wind Speed in a Randomly Sampled Hurricane

2010 ◽  
Vol 23 (5) ◽  
pp. 1262-1265 ◽  
Author(s):  
Andrew R. Solow
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Ocean Warming ◽  
Hurricane Intensity ◽  
Term Trend ◽  
Long Term Trend ◽  
Observational Record

Abstract There is considerable interest in detecting a long-term trend in hurricane intensity possibly related to large-scale ocean warming. This effort is complicated by the paucity of wind speed measurements for hurricanes occurring in the early part of the observational record. Here, results are presented regarding the maximum observed wind speed in a sparsely randomly sampled hurricane based on a model of the evolution of wind speed over the lifetime of a hurricane.

Multidecadal Trends and Interannual Variability of Rainfall as Observed from Five Lowland Stations at Mt. Kilimanjaro, Tanzania

2017 ◽  
Vol 18 (2) ◽  
pp. 349-361 ◽  
Author(s):  
Insa Otte ◽  
Florian Detsch ◽  
Ephraim Mwangomo ◽  
Andreas Hemp ◽  
Tim Appelhans ◽  
...  
Keyword(s):  
Sugar Cane ◽  
Southern Oscillation ◽  
Global Climate ◽  
Cover Time ◽  
Term Trend ◽  
Positive Indian Ocean Dipole ◽  
Kilimanjaro Region ◽  
Long Term Trend

Abstract Future rainfall dynamics in the Kilimanjaro region will mainly be influenced by both global climate and local land-cover change. An increase in rainfall is expected, but rising temperatures are also predicted for the ecosystem. In situ rainfall of five stations is analyzed to determine seasonal variability and multidecadal trends in the lowlands and lower elevations of the Kilimanjaro region. Monthly rainfall totals are obtained from the Tanzanian Meteorological Agency, from two mission stations, and from a sugar cane plantation. The datasets of the two mission stations cover time spans of 64 and 62 years, starting in 1940 and 1942, while rainfall data obtained from the Tanzanian Meteorological Agency and from the sugar cane plantation start in 1973 and 1974 and thus cover 40–41 years. In one out of five stations, a significant weak negative linear long-term trend in rainfall is observable, which is also evident in the other locations but is not significant. However, humid and dry decades are evident and seasonality has changed, especially during the long rains between March and May. El Niño–Southern Oscillation (ENSO) in combination with positive Indian Ocean dipole (IOD) leads to enhanced rainfall during the year of ENSO onset and the following year. During La Niña years, rainfall increases in the following year, while during the onset year rainfall patterns are more diverse. Positive IOD leads to enhanced rainfall amounts.

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