Several methods have been proposed to train microwave radiometers to retrieve precipitation rates estimated by a radar which observed the same location at the same time. These radar-trained passive-microwave algorithms differ in the quantities that are estimated: some estimate the vertically-integrated liquid water, while others estimate the near-surface precipitation. Since it is no more or le...

Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolu...

In a recent study (Haddad and Park, 2009), a method was proposed to use co-located simultaneous observations by the space-borne Tropical Rainfall Measuring Mission (TRMM) precipitation radar and microwave imager to train the microwave radiometer to retrieve vertical profiles of precipitation in the absence of radar observations. This radartrained passive-microwave approach was developed for mid...

Representation of the canopy hydrological processes has been challenging in land surface modeling due to the subgrid heterogeneity in both precipitation and surface characteristics. The Shuttleworth dynamic– statistical method is widely used to represent the impact of the precipitation subgrid variability on canopy hydrological processes but shows unwanted sensitivity to temporal resolution whe...

The spatial and temporal variability of convection during the North American Monsoon Experiment (NAME) was examined via analysis of three-dimensional polarimetric radar data. Terrain bands were defined as the Gulf of California (over water) and elevations of 0–500 m above mean sea level (MSL; coastal plain), 500–1500 m MSL, and .1500 m MSL. Convective rainfall over the Gulf typically featured t...

abstract obtaining reliable precipitation observations is important for hydrological simulations and weather forecasting. radar data can provide insight in the spatial variation of precipitation and can also detect large areas of rain and estimate rainfall rates. weather radar systems nearly always operate in s-, c- or x-band. since x-band systems require smaller antennas than those at c- or s-...

Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium’s limitedarea ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (B...

This study tested multiple hydrologic mechanisms to explain snowpack dynamics in extreme rain-on-snow floods, which occur widely in the temperate and polar regions. We examined 26, 10 day large storm events over the period 1992–2012 in the H.J. Andrews Experimental Forest in western Oregon, using statistical analyses (regression, ANOVA, and wavelet coherence) of hourly snowmelt lysimeter, air a...

Numerical experiments were carried out using the Tel-Aviv University 2-D cloud model to investigate the effects of increased concentrations of Cloud Condensation Nuclei (CCN), giant CCN (GCCN) and Ice Nuclei (IN) on the development of precipitation and cloud structure in mixedphase sub-tropical convective clouds. In order to differentiate between the contribution of the aerosols and the meteoro...