Correcting bias in radar Z-R relationships due to uncertainty in point rain gauge networks

摘要

One of the key challenges in hydrology is to accurately measure and predict the spatial and temporal distribution of rainfall. Rain gauges measuring at point locations are often considered as the "ground truth" for grid based radar rainfall calibration. Usually, no consideration is given to the uncertainty in the measurement that varies depending on the number of rain gauges that fall within each grid cell. If this uncertainty in the rain gauge network measurements is ignored, the Z-R relationship used to convert reflectivity (Z) to rainfall (R) will be biased. We investigate the effects of point gauge rainfall uncertainty on parameter bias in the Z-R relationship. An error model is developed to compute point gauge rainfall uncertainty at the radar grid resolution. This error model has two components: (1) the error in the gauge measurement itself, and (2) the error introduced by the gauge not capturing the spatial variability within a radar pixel. The Simulation Extrapolation method (SIMEX) is used to determine the extent of parameter bias present in the rainfall-reflectivity relationship as a result of this uncertainty. When considering the point gauge rainfall uncertainty a 4% decrease in the average radar rainfall estimates is found. (C) 2014 Elsevier B.V. All rights reserved.