Article citationsMore>>

GorjiSefidmazgi, M., Sayemuzzaman, M., Homaifar, A., Jha, M.K. and Liess, S. (2014) Trend Analysis Using Non-Stationary Time Series Clustering Based on the Finite Element Method. Nonlinear Processes in Geophysics, 21, 605-615.
http://dx.doi.org/10.5194/npg-21-605-2014

has been cited by the following article:

• TITLE: Rainy/Non-Rainy Day Pattern Analysis for North Carolina

  AUTHORS: Akand W. Islam

  KEYWORDS: Mann-Kendall, Sen-Slope, Inverse Distance Weighing Interpolation, Trend Significance

  JOURNAL NAME: American Journal of Climate Change, Vol.4 No.1, March 3, 2015

  ABSTRACT: Trends in rainy/non-rainy days are investigated using the Mann-Kendall non-parametric test at 249 weather station sites of North Carolina, United States. Sen-Slope method has been applied to predict the trend magnitude. Inverse distance weighing interpolation technique is adopted to represent the spatial distribution of trend magnitude across the North Carolina. Quality controlled daily precipitation data sets from 1950 to 2009 have been used to analyze. The double-mass curve and autocorrelation were adopted to analyze the precipitation time series of each station to check the consistency and homogeneity. Standard Precipitation Index (SPI) has also been discussed for the study area. It is found in North Carolina that a number of rainy day trends are increasing both spatially and temporally. Eastern part of North Carolina shows the significant increasing rainy day trends. Trend significance has been checked at 1% and 5% significance level. Recent decades show the high SPI in both the extent of wetness and dryness.