Quantifying short and long-term weather pattern impacts on aridity trends in eastern Texas using autoregressive time series modeling and randomization
Journal of Decision Making and Healthcare, Volume 1, Issue 2, December 2024, Pages: 104–111
ROBERT KENNEDY SMITH
Department of Computer Science, Georgetown University, Washington DC, 20057, USA
DER-CHEN CHANG
Department of Mathematics and Statistics, Georgetown University, Washington DC, 20057, USA
Graduate Institute of Business Administration, College of Management, Fu Jen Catholic University, New Taipei City 242, Taiwan, ROC
Abstract
Climate model projections agree that warming air temperatures will exceed increases in the dewpoint temperature, causing lower relative humidities and increased soil moisture deficits across the U.S. South. Increased reference evapotranspiration (ET0) is projected to be greater than the enhanced rainfall associated with anthropogenic climate change in almost all areas of the contiguous U.S., leading to expanding aridity. Meanwhile, there is also model agreement that precipitation will fall at heavier rates under warmer conditions, leading to additional runoff, and thus less water absorption, even under drier overall conditions. Although it could be tempting to assume that projected changes in soil moisture will be a result of future average conditions (the average monthly amount of water absorbed by the soil minus the average monthly amount that evaporates), this does not account for evolving weather patterns, multiday extreme events, and other anthropogenic influences such as urban heat islands. This brief analysis quantifies how climate change has impacted these factors in the recent past in the U.S. State of Texas, providing a preliminary measurement of the weather pattern-related impacts of human-induced climate change.
Cite this Article as
Robert Kennedy Smith and Der-Chen Chang, Quantifying short-and long term weather pattern impacts on aridity trends in eastern Texas using autoregressive time series modeling and randomization, Journal of Decision Making and Healthcare, 1(2), 104–111, 2024