scholarly journals Projected Changes in United States Regional Extreme Heat Days Derived From Bivariate Quantile Mapping of CMIP5 Simulations

2019 ◽  
Vol 124 (10) ◽  
pp. 5214-5232 ◽  
Author(s):  
J. T. Schoof ◽  
S. C. Pryor ◽  
T. W. Ford
Keyword(s):  
United States ◽  
Extreme Heat ◽  
Quantile Mapping ◽  
Projected Changes ◽  
Bivariate Quantile

Racial and Political Dynamics of an Approaching “Majority-Minority” United States

2018 ◽  
Vol 677 (1) ◽  
pp. 204-214 ◽  
Author(s):  
Maureen A. Craig ◽  
Julian M. Rucker ◽  
Jennifer A. Richeson
Keyword(s):  
United States ◽  
The United States ◽  
Future Research ◽  
White Americans ◽  
Psychological Mechanisms ◽  
Political Outcomes ◽  
Essential Questions ◽  
Social Scientific ◽  
Demographic Shifts ◽  
Projected Changes

Do demographic shifts in the racial composition of the United States promote positive changes in the nation’s racial dynamics? Change in response to the nation’s growing diversity is likely, but its direction and scope are less clear. This review integrates emerging social-scientific research that examines how Americans are responding to the projected changes in the racial/ethnic demographics of the United States. Specifically, we review recent empirical research that examines how exposure to information that the United States is becoming a “majority-minority” nation affects racial attitudes and several political outcomes (e.g., ideology, policy preferences), and the psychological mechanisms that give rise to those attitudes. We focus primarily on the reactions of members of the current dominant racial group (i.e., white Americans). We then consider important implications of these findings and propose essential questions for future research.

scholarly journals Heat Vulnerability and Heat Island Mitigation in the United States

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 558 ◽  
Author(s):  
Jungmin Lim ◽  
Mark Skidmore
Keyword(s):  
United States ◽  
Local Governments ◽  
Heat Waves ◽  
Fold Increase ◽  
The United States ◽  
Extreme Heat ◽  
Mitigation Measures ◽  
Heat Island ◽  
Weather Extremes ◽  
Heat Vulnerability

Heat waves are the deadliest type of natural hazard among all weather extremes in the United States. Given the observed and anticipated increase in heat risks associated with ongoing climate change, this study examines community vulnerability to extreme heat and the degree to which heat island mitigation (HIM) actions by state/local governments reduce heat-induced fatalities. The analysis uses all heat events that occurred over the 1996–2011 period for all United States counties to model heat vulnerability. Results show that: (1) Higher income reduces extreme heat vulnerability, while poverty intensifies it; (2) living in mobile homes or rental homes heightens susceptibility to extreme heat; (3) increased heat vulnerability due to the growth of the elderly population is predicted to result in a two-fold increase in heat-related fatalities by 2030; and (4) community heat island mitigation measures reduce heat intensities and thus heat-related fatalities. Findings also show that an additional locally implemented measure reduces the annual death rate by 15%. A falsification test rules out the possibility of spurious inference on the life-saving role of heat island mitigation measures. Overall, these findings inform efforts to protect the most vulnerable population subgroups and guide future policies to counteract the growing risk of deadly heat waves.

scholarly journals Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes

2017 ◽  
Vol 21 (6) ◽  
pp. 2649-2666 ◽  
Author(s):  
Matthew B. Switanek ◽  
Peter A. Troch ◽  
Christopher L. Castro ◽  
Armin Leuprecht ◽  
Hsin-I Chang ◽  
...  
Keyword(s):  
Error Correction ◽  
Bias Correction ◽  
Climate Model ◽  
Correction Method ◽  
Climate Change Signal ◽  
Quantile Mapping ◽  
Temperature And Precipitation ◽  
Distribution Mapping ◽  
Projected Changes ◽  
Time Invariant

Abstract. Commonly used bias correction methods such as quantile mapping (QM) assume the function of error correction values between modeled and observed distributions are stationary or time invariant. This article finds that this function of the error correction values cannot be assumed to be stationary. As a result, QM lacks justification to inflate/deflate various moments of the climate change signal. Previous adaptations of QM, most notably quantile delta mapping (QDM), have been developed that do not rely on this assumption of stationarity. Here, we outline a methodology called scaled distribution mapping (SDM), which is conceptually similar to QDM, but more explicitly accounts for the frequency of rain days and the likelihood of individual events. The SDM method is found to outperform QM, QDM, and detrended QM in its ability to better preserve raw climate model projected changes to meteorological variables such as temperature and precipitation.

Evaluation of Historical and Future Cool Season Precipitation over the Eastern United States and Western Atlantic Storm Track Using CMIP5 Models

2015 ◽  
Vol 28 (2) ◽  
pp. 451-467 ◽  
Author(s):  
Kelly Lombardo ◽  
Brian A. Colle ◽  
Zhenhai Zhang
Keyword(s):  
United States ◽  
Global Climate Model ◽  
Storm Track ◽  
Cmip5 Models ◽  
Eastern United States ◽  
Cool Season ◽  
Western Atlantic ◽  
Extreme Precipitation Events ◽  
Projected Changes ◽  
Precipitation Events

Abstract This study analyzed the contribution of cyclones to projected changes in cool season (1 November–31 March) precipitation over the eastern United States and western North Atlantic Ocean. First, global climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were compared to Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) precipitation analyses for the period 1979–2004. The CMIP5 ensemble mean realistically reproduced the historical distribution of regional precipitation with no discernable effect because of model spatial resolution. Subsequently, the projected changes in precipitation on cyclone and noncyclone days under the representative concentration pathway 8.5 (RCP8.5) scenario were quantified. While precipitation on both types of days was projected to increase, the increase on noncyclone days (23%) was greater than the increase on cyclone days (12%). The increase in precipitation on cyclone days occurred despite a decrease in the number of cyclone days. This increase can be attributed primarily to a shift toward more frequent extreme precipitation events coupled with a decline in light precipitation events.

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