Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?

Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?
复制标题

液云微物理过程可以用于垂直指向云雷达校准吗?

DOI:
10.5194/amt-12-3151-2019
复制
发表时间:
2019
影响因子:
3.8
通讯作者:
E. Luke
E. Luke
中科院分区:
地球科学3区
文献类型:
--
作者:
M. Maahn;F. Hoffmann;M. Shupe;G. de Boer;S. Matrosov;E. Luke

文献摘要

参考文献

被引文献

相似文献

抽象的。测云雷达是观测云过程的独特仪器,但雷达校准的不确定性经常限制数据质量。到目前为止,还没有一种可靠的方法来评估过去云雷达数据集的校准。在这里,我们调查的微物理过程中的液体云,如云滴到毛毛雨滴的过渡的观测是否可以用来校准云雷达。具体而言,我们研究了雷达反射率因子与三个不受绝对雷达校准影响的变量之间的关系:雷达多普勒谱的偏斜度(γ),雷达平均多普勒速度(W)和液态水路径(LWP)。对于每个关系,我们评估雷达校准的潜力。对于γ和W,我们使用箱模型模拟来确定参考点的典型雷达反射率值。我们将新方法应用于2016年使用两台35 GHz Ka波段ARM天顶雷达(KAZR)在阿拉斯加北坡(NSA)和奥利克托克点(OLI)的大气辐射测量(ARM)站点进行的观测。对于具有足够数量的液态云观测的时期,我们发现液态云过程对于云雷达校准是足够鲁棒的,基于LWP的方法表现最好。我们估计,在2016年,NSA的雷达反射率约为1±1 dB,但很稳定。就公开进修学院而言,我们发现在维持准确校准方面存在严重问题,包括在2016年6月突然下降5至7分贝。
Abstract. Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single robust method exists for assessing the calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes in liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). For each relation, we evaluate the potential for radar calibration. For γ and W, we use box model simulations to determine typical radar reflectivity values for reference points. We apply the new methods to observations at the Atmospheric Radiation Measurement (ARM) sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that liquid cloud processes are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that, in 2016, the radar reflectivity at NSA was about 1±1 dB too low but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.
DOI: 10.1175/jas-d-16-0220.1
发表时间: 2017-06
影响因子: 3.1
作者:
F. Hoffmann;Y. Noh;S. Raasch
通讯作者: F. Hoffmann;Y. Noh;S. Raasch
DOI: 10.5194/gmd-10-1521-2017
发表时间: 2016-11
影响因子: 5.1
作者:
S. Unterstrasser;F. Hoffmann;Marion Lerch
通讯作者: S. Unterstrasser;F. Hoffmann;Marion Lerch
开发和评估冰云参数化,以利用现场飞机观测对雷达时刻进行正向建模
DOI: 10.1175/jtech-d-14-00112.1
发表时间: 2015
影响因子: 2.2
作者:
U. Löhnert;P. Kollias;R. C. Jackson;G. M. McFarquhar
通讯作者: G. M. McFarquhar