Observing the response of the land surface to climate variability by time series analysis of satellite observations

Abstract

Satellite observations of the terrestrial biosphere cover a period of time sufficiently extended to allow the calculation of a reliable climatology. The latter is particularly relevant for studies of vegetation response to climate variability. Observations from space of the land surface are hampered by clouds at shorter wavelength and affected by water in the atmosphere in the microwave range. Both polar orbiting and geostationary satellites have a revisit frequency high enough to allow for some redundancy relative to the processes being observed, so that time series where a fraction of observations are removed and the resulting gaps filled are still very useful to monitor land surface processes. We applied the Harmonic ANalysis of Time Series (HANTS) to identify and remove anomalous observations (outliers) and to fill the resulting gaps. The HANTS algorithm has been widely used to reconstruct time series of Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Land Surface Temperature (LST) as well as the Polarization Difference Brightness Temperature (PDBT) during the past 30 years to remove random noise or eliminate cloud/snow contamination. Several studies in North and Southern Africa, South America, Europe, China and India captured the response of the land surface to climate forcing, modulated by water availability across a range of temporal scales from hourly to decennial. These studies are reviewed to illustrate how the analysis of time series of different land surface properties reveal processes and interactions.