Evaluating the hydro-estimator satellite rainfall algorithm over a mountainous region

YÜCEL İ. , Kuligowski R. J. , Gochis D. J.

INTERNATIONAL JOURNAL OF REMOTE SENSING, vol.32, no.22, pp.7315-7342, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 32 Issue: 22
  • Publication Date: 2011
  • Doi Number: 10.1080/01431161.2010.523028
  • Page Numbers: pp.7315-7342


This study investigates the performance of the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) operational rainfall estimation algorithm, called the hydro-estimator (HE), with and without its orographic correction method, in its depiction of the timing, intensity and duration of convective rainfall in general, and of the topography-rainfall relationship in particular. An event-based rainfall observation network in north-west Mexico, established as part of the North American monsoon experiment (NAME), provides gauge-based precipitation measurements with sufficient temporal and spatial sampling characteristics to examine the climatological structure of diurnal convective activity over north-west Mexico. In this study, rainfall estimates from the HE algorithm were evaluated against point observations collected from 49 rain gauges from August until the end of September in 2002 and from 79 gauges from August to September in 2003. While the HE with orographic correction to some extent captures the spatial distribution and timing of diurnal convective events, elevation-dependent biases exist, which are characterized by an underestimate in the occurrence of light precipitation at high elevations and an overestimate in the occurrence of precipitation at low elevations. The potential of the HE in providing high spatial and temporal resolution data is also evaluated using a hydrological model over the North American monsoon (NAM) region. The findings suggest that continued improvement to the HE orographic correction scheme is warranted in order to advance quantitative precipitation estimation in complex terrain regions and for use in hydrologic applications.