Optimizing observations of drizzle onset with millimeter-wavelength
Claudia Acquistapace1, Stefan Kneifel1, Ulrich Löhnert1, Pavlos Kollias2,1, Maximilian Maahn3,4, and Matthias Bauer-Pfundstein51University of Cologne, Pohligstr. 3, 50969 Köln, Germany 2Stony Brook University, Stony Brook, NY 11794-5000, USA 3Cooperative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO 80309, USA 4Earth System Research Laboratory, National Oceanographic and Atmospheric Administration, 325 Broadway, Boulder, CO 80305, USA 5METEK Meteorologische Messtechnik GmbH, Fritz-Straßmann-Straße 4, 25337 Elmshorn, Germany
Received: 25 Sep 2016 – Accepted for review: 28 Oct 2016 – Discussion started: 07 Nov 2016
Abstract. Cloud Doppler radars are increasingly used to study cloud and precipitation microphysical processes. Typical bulk cloud properties such as liquid or ice content are usually derived using the first three standard moments of the radar Doppler spectrum. Recent studies demonstrated the value of higher moments for the reduction of retrieval uncertainties and for providing additional insights into microphysical processes. Large effort has been undertaken e.g. within the Atmospheric Radiation Measurement (ARM) program to ensure high quality of radar Doppler spectra. However, a systematic approach concerning the accuracy of higher moments estimates and their sensitivity to basic radar system settings such as spectral resolution, integration time, and beam width is still missing.
In this study we present an approach how to optimize radar settings for radar Doppler spectra moments in the specific context of drizzle detection. The process of drizzle development has shown to be particularly sensitive to higher radar moments such as skewness. We collected radar raw data (IQ time series) from consecutive zenith pointing observations for two liquid cloud cases observed at the cloud observatory JOYCE in Germany. The IQ data allowed us to process Doppler spectra and derive their moments using different spectral resolutions and integration times during identical time intervals. This enabled us to study the sensitivity of the spatio-temporal structure of the derived moments to the different radar settings. The observed signatures were further investigated using a radar Doppler forward model which allowed us to compare observed and simulated sensitivities and also to study the impact of additional hardware-dependent parameters such as antenna beam width.
For the observed cloud with drizzle onset we found that longer integration times mainly modify spectral width (Sw) and skewness (Sk) leaving other moments mostly unaffected. An integration time of 2 s seems to be an optimal compromise: both observations and simulations revealed that a 10 s integration time – as it is widely used for European cloud radars – leads to a significantly turbulence induced increase of Sw and reduction of Sk compared to 2 s integration time. This can lead to significantly different microphysical interpretations with respect to drizzle water content and effective radius. A change from 2 s to even shorter integration times (0.4 s) has much smaller effects on Sw and Sk. We also find that spectral resolution has a small impact on the moment estimations, and thus on the microphysical interpretation of the drizzle signal. Even the coarsest spectral resolution studied of 0.08 ms−1 seems to be appropriate for calculation moments of drizzling clouds. Moreover, simulations provided additional insight into the microphysical interpretation of the skewness signatures observed: in low (high) turbulence condition, only drizzle larger than 20 μm (40 μm) can generate Sk values above the Sk noise level (in our case 0.4). Higher Sk values are also obtained in simulations when smaller beam widths are adopted.
Acquistapace, C., Kneifel, S., Löhnert, U., Kollias, P., Maahn, M., and Bauer-Pfundstein, M.: Optimizing observations of drizzle onset with millimeter-wavelength
radars, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-315, in review, 2016.