An Extended Radar Relative Calibration Adjustment (eRCA) Technique for Higher Frequency Radars and RHI Scans

Abstract

Abstract. This study extends the relative calibration adjustment technique for calibration of weather radars to higher frequency radars, as well as range-height indicator scans. The calibration of weather radars represents one of the most dominant sources of error for their use in a variety of fields including quantitative precipitation estimation and model comparisons. While most weather radars are routinely calibrated, the frequency of calibration is often less than required resulting in miscalibrated time periods. While full absolute calibration techniques often require the radar to be taken offline for a period of time, there have been online calibration techniques discussed in the literature. The relative calibration adjustment (RCA) technique uses the statistics of the ground clutter surrounding the radar as a monitoring source for the stability of calibration but has only been demonstrated to work at S- and C-Band for plan-position indicator scans at a constant elevation. In this work the RCA technique is modified to work with higher frequency radars, including Ka-band cloud radars. At higher frequencies the properties of clutter can be much more variable. This work introduces an extended clutter selection procedure that incorporates the temporal stability of clutter and helps to improve the operational stability of RCA for relatively higher frequency radars. The technique is also extended to utilize range-height scans from radars where the elevation is varied rather than the azimuth. These types of scans are often utilized with research radars to examine the vertical structure of clouds. The newly extended technique (eRCA) is applied to four DOE-ARM weather radars ranging in frequency from C- to Ka- band. Cross comparisons of three co-located radars with frequencies C, X, and Ka at the ARM CACTI site show the technique can determine changes in calibration. Using an X-band radar at the ARM Eastern North Atlantic site, we show how the technique can be modified to be more resilient to clutter fields that show an increased variability, in this case due to sea clutter. The results show that this technique is promising for a-posteriori data calibration and monitoring.

Dependencies of Simulated Convective Cell and System Growth Biases on Atmospheric Instability and Model Resolution

“…This region is moistened by the northerly South American low-level jet (Salio et al, 2002(Salio et al, , 2007Sasaki et al, 2022Sasaki et al, , 2024Vera et al, 2006) under the influence of synoptic troughs (Piersante et al, 2021;Rocque & Rasmussen, 2022) and a surface low pressure in the lee of the Andes (Seluchi et al, 2003) that build convective instability beneath inversions and steep lapse rates caused by westerly flow over the Andes (Rasmussen & Houze, 2011, 2016Ribeiro & Bosart, 2018;Schumacher et al, 2021). This meteorological setup interacts with the mountainous terrain to produce frequent deep convection initiation (Nelson et al, 2021(Nelson et al, , 2022Marquis et al, 2021Marquis et al, , 2023, rapid growth (Mulholland et al, 2018;Feng et al, 2022), and organization (Mulholland et al, 2019;Trapp et al, 2020;Singh et al, 2022) (Varble et al, 2021), the CSAPR2 collected plan projection indicator (PPI) volume scans every 15 minutes with elevation varying from 0.5° and 33° (Hardin et al, 2018). CSAPR2 did not collect PPI volumes from 27 December 2018 to 20 January 2019, 9 February to 23 February 2019, and after 3 March 2019 due to operational interruptions.…”