KAZR Hydrometeor and Insect Masks

The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.Ka波段ARM天顶指向雷达（Ka-band ARM zenith pointing radar，简称KAZR）灵敏度极高，可探测云粒子与单个昆虫。尽管利用Ka波段雷达探测昆虫对于推动雷达昆虫学（radar entomology）的发展具有重要意义且极具价值，但这种高灵敏度也会对雷达气象学（radar meteorology）研究造成干扰——昆虫可能会被误判为云团或降水粒子。例如，自ARM云主动遥感（ARM Active Remote Sensing of Clouds，简称ARSCL）增值产品问世以来，将昆虫误判为云团的问题就一直存在（Clothiaux等人，2000）。研究团队基于云粒子与昆虫的雷达散射特性，开发出一款可在KAZR的同极化与交叉极化多普勒速度谱中识别云团、雨滴、冰粒与昆虫的算法。该算法可在KAZR原生时间-高度分辨率下生成有效掩膜，用以标记水成物粒子与昆虫的时空位置。其中，水成物粒子掩膜包含二进制信息（如是否存在水成物粒子），而昆虫掩膜则包含昆虫活动的代理指标——多普勒速度谱中探测到的昆虫数量越多，该指标数值越高。该算法基于KAZR中等灵敏度模式（medium sensitivity mode，简称MD）的观测数据开发，并已应用于美国南部大平原（Southern Great Plains，简称SGP）中心站点2018年与2019年5月至10月两个夏季的KAZR观测数据。未来，该数据集将扩展纳入其他KAZR运行模式的数据，以及来自ARM其他野外站点的观测资料。该算法与数据集的详细信息可参见：Williams C.R.、Johnson K.L.、Giangrande S.E.、Hardin J.C.、Oktem R.与Romps D.M.，2021：《利用垂直指向偏振雷达多普勒速度谱识别昆虫、云团与降水》，《大气测量技术》，2021年2月6日投稿。链接：https://amt.copernicus.org/preprints/amt-2021-27/#discussion。如需了解ARSCL增值产品的更多信息，请参见Clothiaux E.E.、Ackerman T.P.、Mace G.G.、Moran K.P.、Marchand R.T.、Miller M.A.与Martner B.E.，2000；《应用气象学杂志》，39卷，645-665页。