Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: David Gochis x
  • Journal of Applied Meteorology and Climatology x
  • User-accessible content x
Clear All Modify Search
Sergey Y. Matrosov, Robert Cifelli, and David Gochis


The utility of X-band polarimetric radar to provide rainfall estimations with high spatial and temporal resolution in heavy convective precipitation in the presence of hail is explored. A case study involving observations of strong convective cells with a transportable polarimetric X-band radar near Boulder, Colorado, is presented. These cells produced rain–hail mixtures with a significant liquid fraction, causing local flash floods and debris flow in an environmentally sensitive burn area that had been previously affected by wildfire. It is demonstrated that the specific differential phase shift (K DP)–based rainfall estimator provided liquid accumulations that were in relatively good agreement with a network of high-density rain gauges and experimental disdrometers. This estimator was also able to capture the significant variability of accumulated rainfall in a relatively small area of interest, and the corresponding results were not significantly affected by hail. Hail presence, however, was a likely reason for significant overestimation of rainfall retrievals for X-band radar approaches that are based on radar-reflectivity Ze measurements that have been corrected for attenuation in rain. Even greater overestimations were observed with the S-band radar of the weather-service network. In part because of larger range distances, these radar data could not correctly reproduce the spatial variability of rainfall in the burn area.

Full access
Giuseppe Mascaro, Enrique R. Vivoni, David J. Gochis, Christopher J. Watts, and Julio C. Rodriguez


In this study a temporal statistical downscaling scheme of rainfall is calibrated using observations from 2007 to 2010 at eight sites located along a 14-km topographic transect of 784 m in elevation in northwest Mexico. For this purpose, the rainfall statistical properties over a wide range of temporal scales (3 months–1 min) for the summer (July–September) and winter (November–March) seasons are first analyzed. Rainfall accumulation is found not to be significantly correlated with elevation in either season, and a strong diurnal cycle is found to be present only in summer, peaking in the late afternoon. Winter rainfall events are highly correlated between individual stations across the transect even at short aggregation times (<30 min), and summer storms are more localized in space and time. Spectral and scale invariance analyses showed the presence of three (two) scaling regimes in summer (winter), which are associated with typical meteorological phenomena of the corresponding time scales (frontal systems and relatively isolated convective systems). These analyses formed the basis for calibrating a temporal downscaling model to disaggregate daily precipitation to hourly resolution in the summer season, based on scale invariance and multifractal theory. In this downscaling scheme, a modulation function was used to reproduce the time heterogeneity introduced by the diurnal cycle. The model showed adequate performances in reproducing the small-scale observed precipitation variability. Results of this work are useful for the interpretation of storm-generation mechanisms in the region, and for creating hourly rainfall time series from daily rainfall data, obtained from observations or simulated by climate, meteorological, or other statistical models.

Full access