Abstract

Abstract. Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are 1) radar calibration, 2) ground clutter, 3) wet radome attenuation, 4) rain induced attenuation, 5) vertical profile of reflectivity, 6) non-uniform beam filling, and 7) variations in rain drop size distribution (DSD). This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1–2 km), where 4), 5), and 6) only play a minor role. A 3-day rainfall event (25–27 August 2010) that produced more than 50 mm of precipitation in De Bilt, The Netherlands is analyzed using radar, rain gauge, and disdrometer data. Without any correction it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB of underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z-R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall-Palmer Z-R relation. Correcting for all of these effects has a large positive impact on the radar derived precipitation estimates and yields a good match between radar QPE and gauge measurements, with a difference of 5 to 8 %. This shows the potential of radar as a tool for rainfall estimation, especially at close ranges, but also underlines the importance of applying radar correction methods as individual errors can have a large detrimental impact on the QPE performance of the radar.

Keywords:
Disdrometer Radar Quantitative precipitation estimation Clutter Precipitation Attenuation Remote sensing Weather radar Rain gauge Environmental science Radome Calibration Meteorology Terrain Radar horizon Storm Geology Continuous-wave radar Radar imaging Computer science Antenna (radio) Mathematics Geography Physics Optics Statistics Telecommunications

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Topics

Precipitation Measurement and Analysis
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Meteorological Phenomena and Simulations
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Ocean Waves and Remote Sensing
Physical Sciences →  Earth and Planetary Sciences →  Oceanography

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