Statistical Climate Model Downscaling for Impact Projections in the Midwest United States

School climate is an important construct for guiding violence prevention efforts in U.S. schools, but there has been less consideration of this concept in its neighboring country Mexico, which has a higher prevalence of violence. The U.S. Department of Education outlined a three-domain conceptualization of school climate (i.e., safe and supportive schools model) that includes engagement, safety, and the school environment. To examine the applicability of this school climate model in Mexico, the present study tested its measurement invariance across middle school students in the United States ( n = 15,099) and Mexico ( n = 2,211). Findings supported full invariance for engagement and modified-safety scales indicating that factor loadings and intercepts contributed almost equally to factor means, and scale scores were comparable across groups. Partial invariance was found for the environment scales. Results of a multigroup confirmatory factor analysis (MGCFA) consisting of all 13 school climate scales indicated significantly positive associations among all scales in the U.S. sample and among most scales in the Mexico sample. Implications of these findings are discussed.

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Investigation of the Summer Climate of the Contiguous United States and Mexico Using the Regional Atmospheric Modeling System (RAMS). Part II: Model Climate Variability

Journal of Climate ◽

10.1175/jcli4212.1 ◽

2007 ◽

Vol 20 (15) ◽

pp. 3866-3887 ◽

Cited By ~ 64

Author(s):

Christopher L. Castro ◽

Roger A. Pielke ◽

Jimmy O. Adegoke ◽

Siegfried D. Schubert ◽

Phillip J. Pegion

Keyword(s):

United States ◽

Climate Model ◽

Weather Prediction ◽

Regional Climate ◽

Summer Rainfall ◽

Atmospheric Modeling ◽

Regional Atmospheric Modeling System ◽

Prediction Mode ◽

Regional Atmospheric Modeling ◽

Seasonal Weather

Abstract Summer simulations over the contiguous United States and Mexico with the Regional Atmospheric Modeling System (RAMS) dynamically downscaling the NCEP–NCAR Reanalysis I for the period 1950–2002 (described in Part I of the study) are evaluated with respect to the three dominant modes of global SST. Two of these modes are associated with the statistically significant, naturally occurring interannual and interdecadal variability in the Pacific. The remaining mode corresponds to the recent warming of tropical sea surface temperatures. Time-evolving teleconnections associated with Pacific SSTs delay or accelerate the evolution of the North American monsoon. At the period of maximum teleconnectivity in late June and early July, there is an opposite relationship between precipitation in the core monsoon region and the central United States. Use of a regional climate model (RCM) is essential to capture this variability because of its representation of the diurnal cycle of convective rainfall. The RCM also captures the observed long-term changes in Mexican summer rainfall and suggests that these changes are due in part to the recent increase in eastern Pacific SST off the Mexican coast. To establish the physical linkage to remote SST forcing, additional RAMS seasonal weather prediction mode simulations were performed and these results are briefly discussed. In order for RCMs to be successful in a seasonal weather prediction mode for the summer season, it is required that the GCM provide a reasonable representation of the teleconnections and have a climatology that is comparable to a global atmospheric reanalysis.

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Genetic structure and variation in aggressiveness inFusarium virguliformein the Midwest United States

Canadian Journal of Plant Pathology ◽

10.1080/07060661.2012.664564 ◽

2012 ◽

Vol 34 (1) ◽

pp. 83-97 ◽

Cited By ~ 10

Author(s):

G. Y. C. Mbofung ◽

T. C. Harrington ◽

J. T. Steimel ◽

S. S. Navi ◽

X. B. Yang ◽

...

Keyword(s):

United States ◽

Genetic Structure ◽

Midwest United States

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A prognostic pollen emissions model for climate models (PECM1.0)

10.5194/gmd-2017-105 ◽

2017 ◽

Author(s):

Matthew C. Wozniak ◽

Allison Steiner

Keyword(s):

United States ◽

Land Cover ◽

Climate Models ◽

Climate Model ◽

Vegetation Type ◽

Global Climate ◽

The United States ◽

Global Climate Models ◽

Pollen Counts ◽

Surface Pollen

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

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Historical rainfall analysis and climate implications for agriculture in midwest United States

10.32469/10355/88139 ◽

2021 ◽

Author(s):

◽

Jane Marie Niemeyer

Keyword(s):

United States ◽

Historical Analysis ◽

The United States ◽

United States Department ◽

Department Of Agriculture ◽

Rainfall Events ◽

Rainfall Analysis ◽

Midwest United States ◽

Agriculture Soil ◽

Increasing Precipitation

A historical analysis of precipitation using 72 years of data from Midwest stations focuses on the implications of climate change for agricultural interests. The number of precipitation events, consecutive days of precipitation, and a Fourier transformation on precipitation are included. Although increased precipitation can be of benefit in agricultural production resulting in yield benefits in the Midwest, excessive rainfall events lead to runoff, which does not improve soil water content and plant available water. To examine the beneficial nature of rainfall events in the Midwest, rainfall retention is estimated using the United States Department of Agriculture Soil Conservation Service (USDA-NRCS/SCS) method. This method can be described briefly as an empirical formula estimating the soil's ability to store water and the amount of runoff. It was found that not only has rainfall increased but so have the number of rainfall days and the number of consecutive days of rainfall. To appricultural focus, spring and fall rainfall days were also found to increase implying that farmers may have fewer days to complete fieldwork in the current climate. With increasing precipitation, the potential for runoff also increases, losing valuable water needed for crops and contributing to lost nutrients in the soil.

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