Stratiform and convective precipitation observed by multiple radars during the DYNAMO/AMIE experiment

Min Deng, Pavlos Kollias, Zhe Feng, Chidong Zhang, Charles N. Long, Heike Kalesse, Arunchandra Chandra, Vickal V. Kumar, Alain Protat

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this study, methods of convective/stratiform precipitation classification and surface rain-rate estimation based on the Atmospheric Radiation Measurement Program (ARM) cloud radar measurements were developed and evaluated. Simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two scanning precipitation radars [NCAR S-band/Ka-band Dual Polarization, Dual Wavelength Doppler Radar (S-PolKa) and Texas A&M University Shared Mobile Atmospheric Research and Teaching Radar (SMART-R)], and surface precipitation during the Dynamics of the Madden-Julian Oscillation/ARM MJOInvestigation Experiment (DYNAMO/AMIE) field campaign were used. The motivation of this study is to apply the unique long-term ARM cloud radar observations without accompanying precipitation radars to the study of cloud life cycle and precipitation features under different weather and climate regimes. The resulting convective/stratiform classification from KAZR was evaluated against precipitation radars. Precipitation occurrence and classified convective/stratiform rain fractions from KAZR compared favorably to the collocated SMART-R and S-PolKa observations. Both KAZR and S-PolKa radars observed about 5% precipitation occurrence. The convective (stratiform) precipitation fraction is about 18% (82%). Collocated disdrometer observations of two days showed an increased number concentration of small and large raindrops in convective rain relative to dominant small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also showed distinct structures for convective and stratiform rain. These evidences indicate that the method produces physically consistent results for the two types of rain. A new KAZR-based, two-parameter [the gradient of accumulative radar reflectivity Ze (GAZ) below 1 km and near-surface Ze] rain-rate estimation procedure was developed for both convective and stratiform rain. This estimate was compared with the exponential Z-R (reflectivity-rain rate) relation. The relative difference between the estimated and surface-measured rainfall rates showed that the two-parameter relation can improve rainfall estimation relative to the Z-R relation.

Original languageEnglish (US)
Pages (from-to)2503-2523
Number of pages21
JournalJournal of Applied Meteorology and Climatology
Volume53
Issue number11
DOIs
StatePublished - 2014

Keywords

  • Algorithms
  • Instrumentation/sensors
  • Radars/Radar observations
  • Remote sensing
  • Surface observations

ASJC Scopus subject areas

  • Atmospheric Science

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