One of areas where big data are collected is in environmental and climate studies. The Global Circulation Models or Regional Circulation Models can generate huge amount of data in space and time. Data collected through remote sensing or sensor networks are also huge. All these data are correlated spatially and temporally. One therefore has to deal with the huge covariance matrix in the traditional likelihood-based inferences or Bayesian inferences.