Volume XL-8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 321-322, 2014
https://doi.org/10.5194/isprsarchives-XL-8-321-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 321-322, 2014
https://doi.org/10.5194/isprsarchives-XL-8-321-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

  28 Nov 2014

28 Nov 2014

Temporal changes in semivariogram of ocean surface latent heat flux under linear trend

M. K. Singh and P. Venkatachalam M. K. Singh and P. Venkatachalam
  • CSRE, IIT Bombay, Powai, Mumbai, 400076, India

Keywords: Temporal, Spatial, Statistics, Oceanography, Prediction

Abstract. One of the ways to study spatio-temporal variability of a process is to consider it as a temporal variation of a spatial process. Semivariogram is a measure of spatial variation in a process. If a process is undergoing a linear trend, then semivariogram parameters such as range, sill and nugget are bound to change. In this paper, a mathematical closed form of range, sill, and nugget and in turn semivariogram were expressed for a process under linear trend. The derived semivariogram was used to study the latent heat flux (LHF) over the Indian Ocean. LHF values depend on sea surface temperature (SST) and wind speed (WS) over ocean surface. Universal kriging (UK) was used to estimate the LHF with WS and SST as covariables. UK coefficients corresponding to covariables were found out for the years 2010, 2020, 2030, 2040 and 2050. In similar line, study has been attempted to see how empirical orthogonal function modes of a spatio-temporal process change with time under linear trend.