Abstract
Variation in quantities such as precipitation and temperature is often assessed by detecting and characterizing trends in available meteorological data. The objective of this study was to determine the long-term trends in annual precipitation and mean annual air temperature for the state of Kentucky. Non-parametric statistical tests were applied to homogenized and (as needed) pre-whitened annual series of precipitation and mean air temperature during 1950–2010. Significant trends in annual precipitation were detected (both positive, averaging 4.1 mm/year) for only two of the 60 precipitation-homogenous weather stations (Calloway and Carlisle counties in rural western Kentucky). Only three of the 42 temperature-homogenous stations demonstrated trends (all positive, averaging 0.01 °C/year) in mean annual temperature: Calloway County, Allen County in southern-central Kentucky, and urbanized Jefferson County in northern-central Kentucky. In view of the locations of the stations demonstrating positive trends, similar work in adjacent states will be required to better understand the processes responsible for those trends and to properly place them in their larger context, if any.
Highlights
Precipitation and air temperature are two of the most important variables in the fields of climate sciences and hydrology
The findings clearly indicate that, according to the dataset and methods used in this study, annual rainfall depths in Kentucky generally exhibit no statistically significant trends with respect to time
The data and analysis in the present study indicate that, broadly speaking, mean annual temperatures in Kentucky have not demonstrated a statistically significant trend with regard to time
Summary
Precipitation and air temperature are two of the most important variables in the fields of climate sciences and hydrology. The implications of changes in precipitation and temperature make it crucial for water resource planners to accurately assess their behavior and impacts on related hydrologic variables. Relationship between Climate Data and Hydrologic Studies. With hydrologic simulation models operated with data projections from climate models, have recently been undertaken to assess the potential hydrologic impacts of changing climate [1,2,3,4,5,6]. Ficklin et al [1] applied a hydrologic model to the Upper Colorado River Basin and combined it with forecast data from 16 Global Climate Models (GCMs), finding a temporal shift in most hydrologic outputs with a significant decline in snowmelt projected by the end of the 21st century
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