2007
DOI: 10.1029/2006jd008206
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Radar‐based quantitative precipitation estimation over Mediterranean and dry climate regimes

Abstract: [1] Quantitative precipitation estimation based on meteorological radar data potentially provides continuous, high-resolution, large-coverage data that are essential for meteorological and hydrologic analyses. While intense scientific efforts have focused on precipitation estimation in temperate climatic regimes, relatively few studies examined radar-based estimates in dry climatic regions. The paper examines radar-based rain depth estimation for rainfall periods (a series of successive rainy days) in Israel, … Show more

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Cited by 73 publications
(58 citation statements)
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“…Large, if not the largest problem in comparing satellite rainfall with the rainfall measured by gauges, is the scale difference between the two types of measurements, i.e., large spatial scale in the case of satellite rainfall products and small, in the case of rain gauges. A rain gauge measurement represents rainfall estimate at the local scale, limited to~200 m 2 coverage (Morin and Gabella 2007), while the satellite-pixel rainfall is a regional rainfall estimate with spatial coverage in order of tenths of km 2 (e.g., CMORPH 8 ) or even hundreds of km 2 (CMORPH 25 or TRMM). For example, in pixel 3, six rain gauges represent in total rainfall area of~1200 m 2 , while satellite rainfall estimated within a pixel represents an area of 729 km 2 .…”
Section: Discussionmentioning
confidence: 99%
“…Large, if not the largest problem in comparing satellite rainfall with the rainfall measured by gauges, is the scale difference between the two types of measurements, i.e., large spatial scale in the case of satellite rainfall products and small, in the case of rain gauges. A rain gauge measurement represents rainfall estimate at the local scale, limited to~200 m 2 coverage (Morin and Gabella 2007), while the satellite-pixel rainfall is a regional rainfall estimate with spatial coverage in order of tenths of km 2 (e.g., CMORPH 8 ) or even hundreds of km 2 (CMORPH 25 or TRMM). For example, in pixel 3, six rain gauges represent in total rainfall area of~1200 m 2 , while satellite rainfall estimated within a pixel represents an area of 729 km 2 .…”
Section: Discussionmentioning
confidence: 99%
“…Daily rainfall data from 26 rain gauges within 100 km distance from the radar were used for the radar-gauge adjustment and another 13 rain gauges in the surroundings of the Dalya and Taninim catchments were used for validation (Peleg and Morin, 2012). Rainfall data were initially calculated using the weather radar reflectivity data by applying a fixed reflectivity-rainfall power law relationship and then readjusted for each year using the weighted regression method (Gabella et al, 2001;Morin and Gabella, 2007). The model was constructed for four and five sub-basins for the upper Dalya and upper Taninim catchments, respectively.…”
Section: Sca-sma Hydrological Modelmentioning
confidence: 99%
“…Rain gauge measurements can be very accurate, but maintenance and calibration problems often result in poor data quality (e.g., Habib and Krajewski 2002;Morin and Gabella 2007;Villarini et al 2008). The lack of dense networks often requires the use of geostatistical methods to estimate areal precipitation, which, in most cases, have considerable deficiencies (Brandes et al 1999;Habib and Krajewski 2002;Morin and Gabella 2007;Villarini et al 2008).…”
Section: Introductionmentioning
confidence: 99%
“…The lack of dense networks often requires the use of geostatistical methods to estimate areal precipitation, which, in most cases, have considerable deficiencies (Brandes et al 1999;Habib and Krajewski 2002;Morin and Gabella 2007;Villarini et al 2008). Weather radars appear to be the best operational tool for precipitation estimation (Doswell et al 1996;Krajewski and Smith 2002;Morin et al 2005) because of their high spatiotemporal resolution and coverage. However, their precipitation measurements are affected by several factors, such as a varying Z-R relationship, topography blockage, evaporation of rain falling from relatively higher altitudes, and, for radars with nondual polarization, overestimation of precipitation due to the bright band (Crosson et al 1996;Fulton 1999;Krajewski and Smith 2002;Morin et al 2005).…”
Section: Introductionmentioning
confidence: 99%