Long-Term Trend Analysis of Precipitation and Air Temperature for Kentucky, United States

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.

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

“…Parametric and nonparametric approaches are commonly used for identifying trends in hydrological and meteorological variables across the world (Ficklin et al 2013;Chattopadhyay and Jha 2016;Chattopadhyay and Edwards 2016). The Mann-Kendall (MK) and modified MannKendall (MMK) tests belong to the family of nonparametric tests.…”

“…Numerous studies have employed the MK (Chattopadhyay and Edwards 2016;Tosunoglu and Kisi 2016) and MMK (Giuntoli et al 2013;Kibria et al 2016). These are possibly the most widely used nonparametric tests for trend detection in hydrological and climatological studies (Mitof and Pravalie 2014;Jones et al 2015).…”

Spatial and Temporal Changes in Temperature, Precipitation, and Streamflow in the Miyun Reservoir Basin of China

“…The missing data were reconstructed by calculating the average value of their neighboring stations [15,25]. Considering relocation and instrument changes of meteorological stations, which may lead to implausible or biased conclusions, the double-mass curve method was adopted to detect the homogeneity of the meteorological data for each station in this study [15,[26][27][28]. After these procedures, 17 rain gauges and nine meteorological stations were retained for the subsequent trend analysis.…”

“…The serial correlation analysis method presented by Yue et al [36] was used to test the presence of serial correlation proposed. Lag-1 serial correlation test was analyzed according to proposal from von Storch [38] and was adopted widely to eliminate the effect of serial correlation [27,28,39,40]. In this study, a trend-free pre-whitening (TFPW) method was used as follows:…”

Yozgat’ın Aylık Toplam Yağış ve Aylık Ortalama Hava Sıcaklıklarının Trend Analizi

“…Addisu et al, (2015) [24] found that MK trend test gave the maximum and minimum temperature analysis resulted in a general increasing trend whereas, rainfall amount resulted in a general decreasing trend in Ethiopia. Chattopadhyay and Edwards (2016) [25] analysed the long-term trends in annual precipitation and mean annual air temperature (for the period 1950-2010) for the state of Kentucky.…”