H24C-05:
A Precipitation Satellite Downscaling & Re-Calibration Routine for TRMM 3B42 and GPM Data Applied to the Tropical Andes
Abstract:
With the imminent release of GPM it is essential for the hydrological user community to improve the spatial resolution of satellite precipitation products (SPPs), also retrospectively of historical time-series. Despite the growing number of applications, to date SPPs have two major weaknesses. Firstly, geosynchronous infrared (IR) SPPs, relying exclusively on cloud elevation/ IR temperature, fail to replicate ground rainfall rates especially for convective rainfall. Secondly, composite SPPs like TRMM include microwave and active radar to overcome this, but the coarse spatial resolution (0.25°) from infrequent orbital sampling often fails to: a) characterize precipitation patterns (especially extremes) in complex topography regions, and b) allow for gauge comparisons with adequate spatial support. This is problematic for satellite-gauge merging and subsequent hydrological modelling applications.We therefore present a new re-calibration and downscaling routine that is applicable to 0.25°/ 3-hrly TRMM 3B42 and Level 3 GPM time-series to generate 1 km estimates. 16 years of instantaneous TRMM radar (TPR) images were evaluated against a unique dataset of over 100 10-min rain gauges from the tropical Andes (Colombia & Ecuador) to develop a spatially distributed error surface. Long-term statistics on occurrence frequency, convective/ stratiform fraction and extreme precipitation probability (Gamma & Generalized Pareto distributions) were computed from TPR at the 1 km scale as well as from TPR and 3B42 at the 0.25° scale. To downscale from 0.25° to 1 km a stochastic generator was used to restrict precipitation occurrence to a fraction of the 1 km pixels within the 0.25° gridcell at every time-step. Regression modelling established a relationship between probability distributions at the 0.25° scale and rainfall amounts were assigned to the retained 1 km pixels by quantile-matching to the gridcell. The approach inherently provides mass conservation of the downscaled pixels at the 0.25° gridcell scale. Validation was performed at 1 km pixel scale with synchronous instantaneous TPR images when available and by pixel-gauge comparison considering original error surfaces. The method is designed to be directly applicable to the standard Level 3 gridded time-series GPM product once this becomes available.