Amitai E, Nystuen JA, Liao L, Meneghini R, Morin E. Uniting space, ground, and underwater measurements for improved estimates of rain rate. IEEE Geoscience and Remote Sensing Letters [Internet]. 2004;1 :35–38. Publisher's VersionAbstract
Global precipitation is monitored from a variety of platforms including spaceborne, ground-, and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.
Morin E, Krajewski WF, Goodrich DC, Gao X, Sorooshian S. Estimating Rainfall Intensities from Weather Radar Data: The Scale-Dependency Problem. Journal of Hydrometeorology [Internet]. 2003;4 :782–797. Publisher's VersionAbstract
Meteorological radar is a remote sensing system that provides rainfall estimations at high spatial and temporal resolutions. The radar-based rainfall intensities (R) are calculated from the observed radar reflectivities (Z). Often, rain gauge rainfall observations are used in combination with the radar data to find the optimal parameters in the Z–R transformation equation. The scale dependency of the power-law Z–R parameters when estimated from radar reflectivity and rain gauge intensity data is explored herein. The multiplicative (a) and exponent (b) parameters are said to be “scale dependent” if applying the observed and calculated rainfall intensities to objective function at different scale results in different “optimal” parameters. Radar and gauge data were analyzed from convective storms over a midsize, semiarid, and well-equipped watershed. Using the root-mean-square difference (rmsd) objective function, a significant scale dependency was observed. Increased time- and space scales resulted in a considerable increase of the a parameter and decrease of the b parameter. Two sources of uncertainties related to scale dependency were examined: 1) observational uncertainties, which were studied both experimentally and with simplified models that allow representation of observation errors; and 2) model uncertainties. It was found that observational errors are mainly (but not only) associated with positive bias of the b parameter that is reduced with integration, at least for small scales. Model errors also result in scale dependency, but the trend is less systematic, as in the case of observational errors. It is concluded that identification of optimal scale for Z–R relationship determination requires further knowledge of reflectivity and rain-intensity error structure.
Morin E, Georgakakos KP, Shamir U, Enzel Y. Investigating the effect of catchment characteristics on the response time scale using a distributed model and weather radar information. Weather Radar Information and Distributed Hydrological Modelling (Proceedings of symposium I-IS03 held during IUOG2003 at Sapporo. July 2003). [Internet]. 2003 :177–185. Publisher's Version
Morin E, Georgakakos KP, Shamir U, Garti R, Enzel Y. Objective, observations-based, automatic estimation of the catchment response timescale. Water Resources Research [Internet]. 2002;38 :1212. Publisher's VersionAbstract
A new characteristic timescale of a catchment is presented, the response timescale (RTS). It is a range of averaging time intervals which, when applied to catchment rainfall, yield smoothed time series that best approximate that of the resultant runoff. In determining the RTS, nothing is assumed about the nature of the rainfall-runoff transformation. In addition, this new measure is shown to be robust against measurement errors. An objective, automatic, observations-based algorithm is described that introduces the concept of peaks density for the estimation of RTS. Estimation is exemplified for single and multiple rainfall-runoff events through application to small catchments in Panama and Israel. In all cases, relatively stable values of response timescale are obtained. It is concluded that at least for the case studies, the response timescale is an intrinsic characteristic of the catchment and it is generally expected to be different from the catchment lag time and time of concentration. INDEX
Morin E, Enzel Y, Shamir U, Garti R. The characteristic time scale for basin hydrological response using radar data. Journal of Hydrology [Internet]. 2001;252 :85–99. Publisher's VersionAbstract
The transformation of rainfall into runoff at a basin outlet is the combined effect of many hydrological processes, which occur at a wide range of spatial and temporal scales. However, determining the scale of the combined hydrological response of the basin is still problematic and concepts for its definition are yet to be identified. In this paper high-resolution meteorological radar data are used for the determination of a characteristic temporal scale for the hydrological response of the basin - the 'response time scale' (Ts*). Ts* is defined as the time scale at which the pattern of the time-averaged radar rainfall hietograph is most similar to the pattern of the measured outlet runoff hydrograph. The existence of such similarity at a relatively stable time scale for a specific basin indicates that it is an intrinsic property of the basin and is related to its hydrological response. The identification of the response time scale is carried out by analysis of observations only, without assuming a specific rainfall-runoff model. Ts* is examined in four small basins (10-100 km2) in Israel. The spatial scale is assumed as the entire basin. For all analyzed basins a stable response time scale is identified. Relatively short time scales are found for the urban and arid basins (15-30 min), while for the rural basins longer time scale are identified (90-180 min). The issues of relationship between the response time scale and basin properties and modeling at the response time scale have yet to be determined. ?? 2001 Elsevier Science B.V. All rights reserved.
Dayan U, Ziv B, Margalit A, Morin E, Sharon D. A severe autumn storm over the Middle-East: Synoptic and mesoscale convection analysis. Theoretical and Applied Climatology [Internet]. 2001;69 :103–122. Publisher's VersionAbstract
At times, a pronounced trough of low barometric pressure extends from equatorial Africa northward, over the Red Sea and the eastern Mediterranean countries, i.e., the Red Sea Trough. The associated weather is usually hot and dry, and consequently the atmosphere becomes conditionally unstable. In cases in which additional moisture is supplied and dynamic conditions become supportive, as the case analyzed here, intense thunderstorms occur, with extreme rain rates, hail and floods. The storm herein analyzed caused extensive damage both in casualties and property and evolved in two main consecutive phases: In the first a Mesoscale Convective System that moved from Sinai northward over Israel dominated, and in the second deep convection was organized mainly along a cold front. Data analysis indicates several synoptic-scale factors that had a supportive effect on the storm formation and intensification: Conditional instability established by the Red Sea trough, mid-level moisture transport from Northern Africa, and upper-level divergence imparted by both polar and subtropical jet streams over the Middle-East. Mesoscale features were further investigated by means of a hydro-meteorological observational analysis with high spatio-temporal resolution using raingauge and radar data, and satellite imagery. It is shown that local factors, particularly topographic effects, play a major role in the evolution, intensity and spatial organization of the convective activity. Our findings support results of a numerical study of another autumn rainstorm associated with the Red Sea trough. In the present case we identify an additional contributing factor, i.e., a mid-latitude upper-level trough that further intensified the storm as it was approaching the Middle-East.