Empirical Mode Decomposition (EMD) is used to examine the relationship between precipitation and surface temperature from six regions. Three regions are defined by physiography: world, ocean, and land. The other three regions are defined by averaged precipitation: dry, normal and wet. Monthly averaged daily precipitation rate from the Global Precipitation Climatology Project are compared with average monthly surface air temperature anomalies from the Goddard Institute for Space Studies using EMD. The EMD process produces component time series referred to as intrinsic mode functions (IMFs). Theses IMFs are ordered by frequency from high to low. Eight IMFs were produced for each the time series. The first three IMFs corresponded to seasonal, semi-annual and annual variations, respectively. IMF 4 to 6 corresponded to a biennial, pentennial and decadal climate signals, respectively. IMF 7 was related to the broad 20-30 year period, with the trend being revealed in IMF 8. The time series spanned the period from January 1980 to December 2015 at monthly intervals. Temperature and precipitation time series from six sampling regions were analyzed for evidence of correlation. Results from the analysis reveal the following: (1) The EMD process reveals both linear and non-linear trends. The trends are not entirely consistent between regions though they are highly correlated. (2) Apparent wave-to-wave interactions between high and low frequency components appear to be observed in the IMF 1 and 2. These distortions appear to correspond to the troughs and peaks in the decadal cycle captured in IMF 6 and may related to the solar cycle. (3) The correlation between precipitation and temperature increases with increasing IMF number.