Determination of the spatial scaling relationship of rainfall extremes using radar data

Climate models and their future projections, are normally provided in coarse spatial resolutions which makes them an imprecise source of information for certain hydrological purposes. Finding the proficient means of downscaling such data is one of the open questions of climate research. Previous research has shown that, the rainfall extremes show self-similarity in time and that a relatively similar behavior exists in regard to the spatial scale as well (Veneziano et al 2002). This study aims at determining the spatial scaling relationship of the rainfall extremes by using fine grids of radar datasets and upscaling them. In an empirical manner by aggregating the radar rainfall cells in space and for different cell sizes with a = 1, 2, 3, …12 km and for different durations of d = 5 min, 15 min 30 min, 1 hr, 2 hr, 4 hr, …, 24 hr the Annual Maximum Series are extracted. Using the AMS of different spatial and temporal scales and applying the Koutsoyiannis et at. 1998 method for rainfall extreme value analysis, the probability distribution function is fitted. Assessing the changes of the PDF parameters with the scale, with a logarithmic transformation on both variables; ln(parameter) vs. ln(scale), can show the sought relationship. The preliminary results of the study show definable non-linear relationships for location and scale parameters of the GEV distribution and the eta parameter of the Koutsoyiannis et al. 1998 parametrization.

 

Koutsoyiannis, D. Kozonis, and A. Manetas, A mathematical framework for studying rainfall intensity-duration-frequency relationships, Journal of Hydrology, 206 (1-2), 118–135, doi:10.1016/S0022-1694(98)00097-3, 1998.

Veneziano, Daniele; Furcolo, Pierluigi (2002): Multifractality of rainfall and scaling of intensity-duration-frequency curves. In Water Resour. Res. 38 (12), 42-1-42-12. DOI: 10.1029/2001WR000372.