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4D Weather Cubes and defense applications
Published in Adedeji B. Badiru, Cassie B. Barlow, Defense Innovation Handbook, 2018
Jaclyn E. Schmidt, Jarred L. Burley, Brannon J. Elmore, Steven T. Fiorino, Kevin J. Keefer, Noah R. Van Zandt
A first-order validation was performed on rain fields against base reflectivity from the lowest elevation angle or 0.5-degree tilt of NEXRAD radar. Reflectivity values (Z) were converted to rain rates (mm/hr) through Marshall-Palmer distribution relationships. Due to rain droplet sizes being on the order of microns, radar reflectivity is measured in decibels of reflectivity (dBZ), a logarithmic method that differentiates between precipitation sizes (i.e., drizzle, hail). NEXRAD rain rates were averaged per half-degree grid point for a one-to-one comparison with Weather Cube rain placement and rates. Due to the limitations of operating radar systems, rain fields were analyzed only for areas of NEXRAD coverage, as seen in Figure 14.4. The overall locations of rain fields within the Weather Cubes for both case studies were comparable to that of NEXRAD coverage, but the rain rates differed greatly from the values reported by the KTLX radar.
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Published in Eric W. Harmsen, Megh R. Goyal, Flood Assessment, 2017
In order to address the need to obtain more rainfall estimates for basin analysis, in 1997 National Weather Service (NWS) put into operation the WSR-88D Next Generation Radar (NEXRAD) in the United States of America (USA). NEXRAD radar enhances coverage with a 1 degree × 1 km base resolution. Since 1999, NEXRAD has been used by the NWS to estimate rainfall in Puerto Rico. The NEXRAD facility is located near the City of Cayey at 860 m above mean sea level and at approximately 120 km from Mayagüez. The radar measures reflectivity in decibel (dBZ) and uses empirically derived Z-R relationships to transform reflectivity to rain rate. The Marshall and Palmer [63] equation is the default Z-R relationship employed by the WSR-88D and is described by the following empirical power law: () Z=aRb
Radar Polarimetry for Rain Estimation
Published in Ni-Bin Chang, Yang Hong, Multiscale Hydrologic Remote Sensing, 2012
As for radar measurements, rain echo has distinctive characteristics (Schuur et al. 2003; Ryzhkov et al. 2005b). There is a wide range of ZH values. Generally, heavy rain has a ZH larger than 40 dBZ, and light rain has a ZH of 25 dBZ or below. A storm core of heavy rain normally has a large ZH value. Sometimes, hail can be found within the storm core. In that case, the ZH value would be larger than that for rain, usually larger than 50 dBZ. ZDR is generally between 0 and 5 dB, depending on the intensity of rain. Its value is small (close to 0 dB) for light rain. With an increasing concentration of large raindrops, the ZDR value increases. For melting hail, ZDR normally has a large value, which might be larger than 5 dB. Rain signal generally has a ρhv close to 1 (>0.98). If other species (such as snow/hail) are mixed with rain, ρhv would decrease. Nonrain echo generally has a smaller ρhv than rain. For example, the ρhv of biological scatterers or ground clutters is mostly <0.85. The contamination of nonrain scatterers would cause ρhv to decrease. In addition, the ρhv value for rain signals with a low signal-to-noise (SNR) is lower than that for a high SNR. Practically, a threshold of 0.95 is sometimes applied to ρhv to roughly identify the rain signal. The KDP value is dependent on the radar frequency. Given the same DSD, higher frequencies would cause a larger measurement of KDP. For the S-band radar echo of rain, KDP is normally 0–3° km−1. Snow and hail have a lower KDP due to their lower dielectric constants and more random orientation, as compared with raindrops. Dry hail (or dry snow) has a smaller KDP than melting hail (or wet snow), typically –0.5–0.5° km−1. Other scatterers such as birds or clutters generally yield a very noisy KDP. Further understanding of polarimetric radar measurements can be found in the literature (Straka et al. 2000; Schuur et al. 2003), which gives detailed descriptions of the polarimetric characteristics of different scatterers.
Hail suppression effectiveness for different cloud condensation nucleus (CCN) populations in continental and maritime environments
Published in Aerosol Science and Technology, 2023
For each unseeded experiment from 2.4.1, one seeding experiment was performed with the following characteristics. Cloud seeding was performed within a parallelepiped shape, which occupied three grid points in the horizontal and vertical directions, forming a volume of 13.5 km−3. The location of the parallelepiped center was in the grid point where radar reflectivity had a maximum value, air temperature was approximately 0 °C, and vertical velocity of air had positive values. The AgI agent was uniformly distributed within the seeding area and released continuously within 90 s (15 time steps). The seeding rate was 1.61466 × 10−12 kg m−3 s−1 at each grid point within the seeding volume. Cloud seeding started at the moment when the maximum radar reflectivity value reached 5 dBZ (approximately 5 min of the time integration). This early seeding was conducted because convective clouds have few natural ice crystals that would compete with the AgI particles during the early stage of cloud life. The total released seeding material was approximately 1.96 kg.
A case study of cold-seasonthundersnow in Beijing
Published in Atmospheric and Oceanic Science Letters, 2019
Reguang JIAO, Bin CHEN, Ammara HABIB, Guangyu SHI
Radar echo animation showed that for the echo moving from west to east and slightly northward, the maximum echo intensity was 35 dBZ at 0000 LST 10 November, and the average echo intensity was 20 dBZ (Figure 4(c)). Since the scattering of ice crystals is much weaker than that of water droplets, the 20-dBZ echo intensity indicated that the strong-echo area may have had both solid and liquid droplets. The sounding at GXT at 2000 LST 9 November showed that at 758 hPa the temperature was 1°C, and that water droplets possibly existed at the top of the inverse layer. A cross section of the volume scan data showed an echo mainly above 1.5 km, an echo top up to 10 km, and a strong echo center at the height of 5 km. Therefore, it can be inferred that the heavy snowfall was due to the upward movement of the southwesterly flow above the inversion layer with the release of unstable energy.
Evaluation of the WDM6 scheme in the simulation of number concentrations and drop size distributions of warm-rain hydrometeors: comparisons with the observations and other schemes
Published in Atmospheric and Oceanic Science Letters, 2019
Jiaxu GUO, Hengchi LEI, Di CHEN, Jiefan YANG
A flight trial was conducted on 22 May 2017 in Hebei Province, China, with five periods of observation mainly concentrated in the area of 2–7 km in height and −20°C to 10°C in temperature. Three airborne DSD probes (a cloud droplet probe (CDP), cloud imaging probe (CIP) and high-volume precipitation spectrometer (HVPS)), along with an aircraft-integrated meteorological measurement system (AIMMS-20) recording environmental information such as geolocation, height, temperature, etc., were used during the flight trial. Details of the instruments are shown in Table 1. The locations of the second and fourth periods of observation are presented in Figure 1(a and b), marked by the red boxes along with the radar composite reflectivity. The second period of observation was regarded as the observation of a convective cloud (CC), since the radar composite reflectivity was over 30 dBZ in most parts, with the maximum exceeding 35 dBZ, which could be taken as the threshold of a convective echo. The fourth period of observation, with a uniform reflectivity of 20 dBZ, was regarded as the observation of a stratiform cloud (SC).