Sampling errors for satellite-derived tropical rainfall: Monte Carlo study using a space-time stochastic model


  • Thomas L. Bell,

  • A. Abdullah,

  • Russell L. Martin,

  • Gerald R. North


Estimates of monthly average rainfall based on satellite observations from a low Earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. We estimate the size of this error for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). We first examine in detail the statistical description of rainfall on scales from 1 to 103 km, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10% of the mean for rainfall averaged over a 500 × 500 km2 area.