References

AMT

Atmospheric Measurement Techniques

AMT

Atmos. Meas. Tech.

1867-8548

Copernicus Publications

Göttingen, Germany

10.5194/amt-8-3685-2015

Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

Chandra

https://orcid.org/0000-0002-8818-171X

¹ Zhang

https://orcid.org/0000-0001-9708-1561

¹ Kollias

² Matrosov

³ Szyrmer

Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, Miami, Florida, USA

Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Canada

Cooperative Institute for Research in Environmental Sciences, University of Colorado and NOAA/Earth System Research Laboratory, Boulder, Colorado, USA

14 09 2015

8 9 3685 3699

2015

This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/

This article is available from https://amt.copernicus.org/articles/8/3685/2015/amt-8-3685-2015.html

The full text article is available as a PDF file from https://amt.copernicus.org/articles/8/3685/2015/amt-8-3685-2015.pdf

The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong signal attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-band (35-GHz) ARM (Atmospheric Radiation Measurement) zenith radars (KAZR). A 1-dimensional, simple, steady state microphysical model is used to estimate impacts of microphysical processes and attenuation on the profiles of radar observables at 35-GHz and thus provide criteria for identifying situations when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for signal saturation and wet radome effects. The algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity–rain rate (Ze–R) relation. Observations collected by the KAZR, rain gauge, disdrometer and scanning precipitating radars during the DYNAMO/AMIE field campaign at the Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The differences in the rain accumulation from the proposed algorithm are quantified. The results indicate that the proposed algorithm has a potential for deriving continuous rain rate statistics in the tropics.

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