Master of Science, The Ohio State University, 2015, Atmospheric Sciences

Seasonal U.S. climate division data (1895-2014) of temperatures and precipitation in seven chosen divisions are analyzed for trends and patterns of variability and for factors contributing the most to the variability of temperature in each season and division. The divisions are chosen to represent regions of the U.S. that conform to particular patterns of variability of the Palmer Drought Severity Index (PDSI) in summer. Rotated principal component analysis (RPCA) of atmospheric and oceanic teleconnection indices, annual atmospheric CO2 concentrations, and time series of cloud cover and divisionally-averaged precipitation removes intercorrelations between these variables in each region. The orthogonal factors produced from RPCA are used in stepwise multiple linear regression (SMLR) to determine the explainable variance in seasonally-averaged daily maximum and minimum temperatures (Tmax, Tmin) and diurnal temperature range (DTR). Simple linear regression is used to determine rates of change in divisionally-averaged DTR, Tmax, and Tmin in each region and season. The major temperature trends found are accelerated warming of Tmin in most regions and seasons, no decline in spring DTR nationally, and similarities among the four interior/central regions. These regions are characterized by statistically significant long-term (1895-2013) and short-term (1960-2013) decreases in DTR and increases in Tmin, with long-term decreases in annually-averaged Tmax and in summer and autumn seasonally-averaged Tmax. The Northwest, Northeast coastal, and Desert Southwest regions experienced long-term increases in DTR and significant increases in both Tmax and Tmin. Variance within time series of seasonally-averaged temperatures is generally greater during warmer periods. Inconsistency in seasonal precipitation in most regions may be increasing in each region's wet season. Cloud cover is the factor explaining the most variability in DTR overall among all four seasons in Central Ohio (Ohio (open full item for complete abstract)

Committee: Jay Hobgood (Advisor); Alvaro Montenegro (Committee Member); Jeffery Rogers (Other) Subjects: Atmospheric Sciences; Climate Change; Earth

Master of Science, The Ohio State University, 2015, Atmospheric Sciences

Long-term (1895-2012) soil moisture proxy data are collected and analyzed for its spatial and temporal variability across the United States in conjunction with air temperature and diurnal temperature range (DTR) variations over the same period. Palmer Drought Severity Index (PDSI) summer data were subjected to a Rotated Principle Component Analysis (RPCA) that identified 10 regions (components) having unique patterns of PDSI spatial and temporal variability. Four of those regions (RPC1: Ohio River Valley; RPC2: upper Midwest and eastern Northern Plains; RPC3: southeastern United States; RPC5: Southern Plains) are analyzed further with regard to DTR variations. In conjunction to the summer PDSI time series scores produced by the RPCA, mean DTR, T-max, and T-min (maximum and minimum temperatures) were obtained using GHCNM station data within each of the regions of interest and analyzed for trends. The twelve wettest and driest summers were also identified for each of the 4 regions based on the rank of their PDSI time series scores. The average temperature/DTR for each of these cases (wet or dry) were then compared. Soil moisture in the Ohio River Valley (RPC1) has an increasing trend throughout the 20th-21st centuries. T-max shows a downtrend of 0.5°C while T-min has increased ~ 0.7°C producing a downward trend in DTR throughout the period of record. The upper Midwest and eastern Northern Plains (RPC2) produced similar behavior as the Ohio River Valley with more moist soil conditions at the end of the 20th and early 21st century. DTR trends downward in this region due to a very clear upward trend in T-min coupled with a negligible downtrend in T-max. PDSI in the southeastern United States (RPC3) does not have a strong trend but does show a slight increase. T-max produces a trivial, but slight increasing trend while T-min shows a stronger increase in temperatures. This outcome produces a decreasing trend in DTR. Soil moisture in the Southern Plains (RPC5) shows an o (open full item for complete abstract)

Committee: Jeffery Rogers Dr. (Advisor); Jay Stanley Hobgood Dr. (Committee Member); Jialin Lin Dr. (Committee Member) Subjects: Atmospheric Sciences; Climate Change; Meteorology

MA, Kent State University, 2009, College of Arts and Sciences / Department of Geography

The Great Lakes Region of the United States is an area of great climatic diversity. Research analyzing diurnal temperature range (DTR) has noted that in late autumn and early winter an abrupt decrease in the mean temperature range for stations near the Great Lakes occurs. Reasons for this rapid change are likely related to cloud cover amounts and frequencies of specific weather-types. In this thesis, temporal trends and correlations of several weather variables were conducted to assist in the explanation of the rapid change in the region's climate. This variability was then correlated to the teleconnection phases of PNA (Pacific/North American) and NAO (North Atlantic Oscillation). Through statistical and spatial analysis of 54 first order weather stations it was found that the timing and magnitude of breakpoints in DTR, cloud cover, and MP (moist polar weather-type) were the most significantly related. The breakpoint for DTR decrease and cloud cover (CC) increase occurs in early November in the east and late October in the west, generally seen with increased MP frequency as well. DTR breakpoint occurs on the same day, typically in late October to early November, or a few days after CC while MP is typically a few weeks after DTR. Changes in the magnitude of the breakpoint, relative to teleconnection phase, were much more significant than the timing of the breakpoint. PNA phase demonstrated greater and stronger influence on the western Great Lakes Region while NAO on the eastern and strong lake-effect areas.

Committee: Scott Sheridan PhD (Advisor); Thomas Schmidlin PhD (Committee Member); Donna Witter PhD (Committee Member) Subjects: Atmosphere; Earth; Geography