Tuesday, 14 January 2020
Hall B (Boston Convention and Exhibition Center)
Changes in atmospheric demand can significantly impact the vulnerability of ecosystems to drought. Transition zones between arid and humid climates are particularly vulnerable to these changes. The United States Great Plains is a major agricultural region and lies within this sensitive transition zone, making it critically important to understand potential to changes in aridity. The Aridity Index (AI) is defined as the ratio of precipitation to potential evapotranspiration (PET), where PET represents the atmospheric demand for moisture. AI can be used as a tool to determine where the transition zones from humid to arid climates exists. Gradients in AI can shift depending upon changes in precipitation and atmospheric demand, thus we build upon past work by exploring changes to AI within the North American Regional Reanalysis (NARR) and Oklahoma Mesonet. Further, the individual components of aridity, precipitation and PET, were also analyzed to better understand which variable contributed to historic changes in AI at annual and monthly time scales. Contrary to past findings, the AI gradient within the NARR became weaker with time across the Great Plains at an annual time scale, with precipitation and PET being equally influential in driving this trend. However, monthly trends in AI were much more variable and highly sensitive to precipitation trends. Knowledge of these trends could inform agricultural practices and drought management in the Great Plains at the seasonal to sub-seasonal scale.
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