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RhI is Wurtzite structured and crystallizes in the hexagonal P6_3mc space group. The structure is three-dimensional. Rh is bonded to four equivalent I atoms to form corner-sharing RhI4 tetrahedra. There are three shorter (2.60 Å) and one longer (2.64 Å) Rh–I bond lengths. I is bonded to four equivalent Rh atoms to form corner-sharing IRh4 tetrahedra.
This dataset contains streamwise velocity retrieved from the Range Height Indicator (RHI) scans done by the UC Davis scanning Lidar. The quality control of the radial wind speed is performed following the algorithm of Beck & Kuhn (2017). Instantaneous realizations characterized by wind misalignment greater than 60 degrees (based on the closest VAD scan in time) are discarded.
Abstract. This study extends the relative calibration adjustment technique for calibration of weather radars to higher-frequency radars as well as range–height indicator (RHI) 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 (PPI) 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 Department of Energy Atmospheric Radiation Measurement (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 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) site show that the technique can determine changes in calibration. Using an X-band radar at the ARM Eastern North Atlantic (ENA) site, we show how the technique can be modified to be more resilient to clutter fields that show increased variability, in this case due to sea clutter. The results show that this technique is promising for a posteriori data calibration and monitoring.
This is the X-SAPR RHI scan data processed using Corrected Moments in Antenna Coordinates 2.0.
X-Band Scanning ARM Cloud Radar (XSACR) Along-Wind RHI Scan Corrected
X-Band Scanning ARM Cloud Radar (XSACR) Cross-Wind RHI Scan Corrected
X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals) Corrected
X-Band Scanning ARM Cloud Radar (XSACR) Boundary Layer RHI Scan Corrected
The spatial distribution of relative humidity with respect to ice (RHI) in the boreal wintertime tropical tropopause layer (TTL, is asymptotically Equal to 14-18 km) over the Pacific is examined with the measurements provided by the NASA Airborne Tropical TRopopause EXperiment. We also compare the measured RHI distributions with results from a transport and microphysical model driven by meteorological analysis fields. Notable features in the distribution of RHI versus temperature and longitude include (1) the common occurrence of RHI values near ice saturation over the western Pacific in the lower to middle TTL; (2) low RHI values in the lower TTL over the central and eastern Pacific; (3) common occurrence of RHI values following a constant mixing ratio in the middle to upper TTL (temperatures between 190 and 200 K); (4) RHI values typically near ice saturation in the coldest airmasses sampled; and (5) RHI values typically near 100% across the TTL temperature range in air parcels with ozone mixing ratios less than 50 ppbv. We suggest that the typically saturated air in the lower TTL over the western Pacific is likely driven by a combination of the frequent occurrence of deep convection and the predominance of rising motion in this region. The nearly constant water vapor mixing ratios in the middle to upper TTL likely result from the combination of slow ascent (resulting in long residence times) and wave-driven temperature variability. The numerical simulations generally reproduce the observed RHI distribution features, and sensitivity tests further emphasize the strong influence of convective input and vertical motions on TTL relative humidity.
The distribution of relative humidity with respect to ice (RHI) in the Boreal wintertime Tropical Tropopause Layer (TTL - about 14-19 km) over the Pacific is examined with the extensive dataset of measurements from the NASA Airborne Tropical TRopopause EXperiment (ATTREX). Multiple deployments of the Global Hawk during ATTREX provided hundreds of vertical profiles spanning the Pacific with accurate measurements of temperature, pressure, water vapor concentration, ozone concentration, and cloud properties. We also compare the measured RHI distributions with results from a transport and microphysical model driven by meteorological analysis fields. Notable features in the distribution of RHI versus temperature and longitude include (1) the common occurrence of RHI values near ice saturation over the western Pacific in the lower TTL (temperatures greater than 200 K) and in airmasses with low ozone concentrations indicating recent detrainment from deep convection; (2) low RHI values in the lower TTL over the eastern Pacific where deep convection is infrequent; (3) RHI values following a constant H2O mixing ratio in the upper TTL (temperatures below about 195 degrees Kelvin), particularly for samples with ozone mixing ratios greater than about 50-100 parts-per-billion-volume indicating mixtures of tropospheric and stratospheric air, and (4) RHI values typically near ice saturation in the coldest airmasses sampled (temperatures less than about 190 degrees Kelvin). We find that the typically saturated air in the lower TTL over the western Pacific is largely driven by the frequent occurrence of deep convection in this region. The nearly-constant water vapor mixing ratios in the upper TTL result from the combination of slow ascent (resulting in long residence times) and wave-driven temperature variability on a range of time scales (resulting in most air parcels having experienced low temperature and dehydration).
This paper describes a resonant-holographic-interferometry (RHI) technique for nonintrusive flow diagnostics, that relies on the index of refraction variation close to a spectral line. This technique makes it possible to obtain interferograms that are species-selective along with quantitative full-field information for the species under study. The application of the RHI technique to flow fields is analyzed together with measurements of flow parameters such as velocity, pressure, and temperature. The advantages of RHI technique over other nonintrusive diagnostic techniques, such as LIF and planar LIF, are discussed.
The aim of this project is to improve the initial conditions of large eddy simulations (LES) of deep convective storms by assimilating scanning radar reflectivity and radial velocity data as well as local environmental observations. Accomplishing this goal often results in more accurate numerical forecasts of clouds and precipitation than if the background initial meteorological conditions are solely relied upon for convection initiation and intensification, as is typical of most operational and research models. Conducted in a storm-scale LES framework, these more accurate numerical analyses can serve as tool to better understand and parameterize land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development of convection. Our work examined the sensitivity of the numerical representation of cloud-scale wind and microphysical structures to: i) the assimilation of radiosonde observations characterizing the near-storm inflow, ii) the assimilation of radar data of varying resolution for model simulations with grid spacings of 1-km and 0.25-km, and iii) to the assimilation of three-dimensional plan-projection-indicator (PPI) and range-height indicator (RHI) radar volumes. Few studies have explored deep convective storm analyses and forecasts produced by assimilation of radar observations to cloud-scale LES. Furthermore, to our knowledge, no storm-scale DA study has explored the value of assimilating high-resolution sector RHI volumes to determine if they can improve the retrieval of the vertical kinematic and microphysical storm structure aloft over the use of traditionally utilized PPI scans.
One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.
Occurrence frequency and dynamical conditions of ice supersaturation (ISS, where relative humidity with respect to ice (RHi) greater than 100%) are examined in the upper troposphere around convective activity. Comparisons are conducted between in situ airborne observations and the Weather Research and Forecasting model simulations using four double-moment microphysical schemes at temperatures less than or or equal to -40degdegC. All four schemes capture both clear-sky and in-cloud ISS conditions. However, the clear-sky (in-cloud) ISS conditions are completely (significantly) limited to the RHi thresholds of the Cooper parameterization. In all of the simulations, ISS occurrence frequencies are higher by approximately 3-4 orders of magnitude at higher updraft speeds (greater than 1 m s(exp -1) than those at the lower updraft speeds when ice water content (IWC) greater than 0.01 gm(exp -3), while observations show smaller differences up to approximately 1-2 orders of magnitude. The simulated ISS also occurs less frequently at weaker updrafts and downdrafts than observed. These results indicate that the simulations have a greater dependence on stronger updrafts to maintain/generate ISS at higher IWC. At lower IWC (less than or equal or 0.01 gm(exp -3), simulations unexpectedly show lower ISS frequencies at stronger updrafts. Overall, the Thompson aerosol-aware scheme has the closest magnitudes and frequencies of ISS greater than 20% to the observations, and the modified Morrison has the closest correlations between ISS frequencies and vertical velocity at higher IWC and number density. The Cooper parameterization often generates excessive ice crystals and therefore suppresses the frequency and magnitude of ISS, indicating that it should be initiated at higher ISS (e.g.,lees than or equal to 25%).
Stratiform and convective rain are associated with different microphysical processes and generally produce drop-size distributions (DSDs) with different characteristics. Previous studies using data from (a) a tropical coastal location, (b) a mid-latitude continental location with semi-arid climate, and (c) a sub-tropical continental location, found that the two rain types could be separated in the NW–Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. In this paper, we investigate the same separation technique using data and observations from a mid-latitude coastal region. Three-minute DSDs from disdrometer measurements are used for the NW- versus Dm-based classification and are compared with simultaneous observations from an S-band polarimetric radar 38 km away from the disdrometer site. Specifically, RHI (range-height indicator) scans over the disdrometer were used for confirmation. Results show that there was no need to modify the separation criteria from previous studies. Three-minute DSDs from the same location were used as input to scattering calculations to derive retrieval equations for NW and Dm for the S-band radar using an improved technique and applied to the RHI scans to identify convective and stratiform rain regions. Two events are shown as illustrative examples.
Cartesian Cloud Cover Gridding Product for X-Band Scanning ARM Cloud Radar with calibrated input, RHI scan mode at CACTI, MOSAIC, COMBLE, etc.
Cartesian Cloud Cover Gridding Product for Ka-Band Scanning ARM Cloud Radar from calibrated input, RHI scan mode at CACTI, MOSAIC, COMBLE, etc.
Attenuation Corrected reflectivity add to calibrated Ka-Band Scanning ARM Cloud Radar (KASACR) CF-Radial RHI scan