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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Radar Reflectivity Simulated by a 2-D Spectra Bin Model: Sensitivity of Cloud-aerosol Interaction

The Goddard Cumulus Ensemble (GCE) model with bin spectra microphysics is used to simulate mesoscale convective systems.The model uses explicit bins to represent size spectra of cloud nuclei, water drops, ice crystals, snow and graupel. Each hydrometeorite category is described by 33 mass bins. The simulations provide a unique data set of simulated raindrop size distribution in a realistic dynamic frame. Calculations of radar parameters using simulated drop size distribution serve as an evaluation of numerical model performance. In addition, the GCE bin spectra modes is a very useful tool to study uncertainties related to radar observations; all the environmental parameters are precisely known. In this presentation, we concentrate on the discussion of Z-R (ZDR-R) relation in the simulated systems. Due to computational limitations, the spectra bin model has been run in two dimensions with 31 stretched vertical layers and 1026 horizontal grid points (1 km resolution). Two different cases, one in midlatitude continent, the other in tropical ocean, have been simulated. The continental case is a strong convection which lasted for two hours. The oceanic case is a persistent system with more than 10 hours' life span. It is shown that the simulated Z-R (ZDR-R) relations generally agree with observations using radar and rain gauge data. The spatial and temporal variations of Z-R relation in different locations are also analyzed. Impact of aerosols on cloud formation and raindrop size distribution was studied. Both clean (low CCN) and dirty (high CCN) cases are simulated. The Z-R relation is shown to vary considerable in the initial CCN concentrations.

Li, Kiaowen↗
NASA NTRS1971

NASA-tricot - A lightweight radar reflective, knitted fabric

Fabric knitted on conventional knitting machines uses commercially available yarns, has high aerodynamic drag capability, and is relatively inexpensive. The two yarn components used are 15-denier nylon monofilament and aluminized Mylar tape.

Matthews, F. R.↗
NASA NTRS1990

Radar reflectivity of Titan

The low dielectric constant of the liquid hydrocarbon and ethane-methane surface mixture of Titan has as a direct consequence a set of unique microwave-reflection properties which were sought out at 3.5-cm wavelength, using a 70-m transmitting antenna in conjunction with the VLA as a receiving instrument. The statistically significant echoes obtained indicate that Titan is not covered with a deep global ocean of ethane. A global ocean as shallow as about 200 m would have exhibited reflectivities smaller by an order of magnitude, and below the experiment's detection limit.

Muhleman, Duane O.↗
NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗
NASA NTRS2011

Producing Science-Ready Radar Datasets for the Retrieval of Forest Structure Parameters from Backscatter: Correcting for Terrain Topography and Changes in Vegetation Reflectivity

Radar backscatter data contain both geometric and radiometric distortions due to underlying topography and the radar viewing geometry. Our objective is to develop a radiometric correction algorithm specific to the UAVSAR system configuration that would improve retrieval of forest structure parameters. UAVSAR is an airborne Lband radar capable of repeat?pass interferometry producing images with a spatial resolution of 5m. It is characterized by an electronically steerable antenna to compensate for aircraft attitude. Thus, the computation of viewing angles (i.e. look, incidence and projection) must include aircraft attitude angles (i.e. yaw, pitch and roll) in addition to the antenna steering angle. In this presentation, we address two components of radiometric correction: area projection and vegetation reflectivity. The first correction is applied by normalization of the radar backscatter by the local ground area illuminated by the radar beam. The second is a correction due to changes in vegetation reflectivity with viewing geometry.

polarimetry↗
NASA NTRS1986

Global radar units on Venus derived from statistical analysis of Pioneer Venus Orbiter radar data

The classification of surface radar units on Venus using an unsupervised cluster analysis of Pioneer Venus radar reflectivity and root-mean-square (rms)-slope data is described. The advantages of the unsupervised analysis are discussed. F tests are utilized to evaluate the numerical significance of the clusters. The derived rms-slope data and reflectivity for 15 radar units are presented. The relations between radar data bases and elevation are studied. The lowlands, rolling plains, highlands, and mountainous surface of Venus are examined. The geology of Venus landing sites and radar properties, and the surface radar reflectivity images and earth-based images are compared. The spatial relations between classification units are calculated. It is concluded that the unsupervised analysis data correlate well with Head et al. (1985b) data and produce more detailed classification images.

Davis, P. A.↗
NASA NTRS1989

A composite study of Florida thunderstorms, using radar, cloud-to-ground lightning, and surface winds

Two thunderstorms occurring in Florida during the summer of 1987 are studied in order to determine the location of cloud-to-ground (CG) lightning in terms of surface winds and radar reflectivity. Composites of radar, CG lightning locations, and surface winds during the development, mature, and dissipation stages of the storms are presented and analyzed. The relationship between lightning and radar reflectivity is examined. It is noted that the main CG lightning activity region is on the upshear side of the storm in the reflectivity gradient where upward motion is between the convergent gust front and reflectivity center, and lightning avoids areas of maximum reflectivity.

Watson, Andrew I.↗
NASA NTRS2002

Use of Collocated KWAJEX Satellite, Aircraft, and Ground Measurements for Understanding Ambiguities in TRMM Radiometer Rain Profile Algorithm

Coordinated ground, aircraft, and satellite observations are analyzed from the 1999 TRMM Kwajalein Atoll field experiment (KWAJEX) to better understand the relationships between cloud microphysical processes and microwave radiation intensities in the context of physical evaluation of the Level 2 TRMM radiometer rain profile algorithm and uncertainties with its assumed microphysics-radiation relationships. This talk focuses on the results of a multi-dataset analysis based on measurements from KWAJEX surface, air, and satellite platforms to test the hypothesis that uncertainties in the passive microwave radiometer algorithm (TMI 2a12 in the nomenclature of TRMM) are systematically coupled and correlated with the magnitudes of deviation of the assumed 3-dimensional microphysical properties from observed microphysical properties. Re-stated, this study focuses on identifying the weaknesses in the operational TRMM 2a12 radiometer algorithm based on observed microphysics and radiation data in terms of over-simplifications used in its theoretical microphysical underpinnings. The analysis makes use of a common transform coordinate system derived from the measuring capabilities of the aircraft radiometer used to survey the experimental study area, i.e., the 4-channel AMPR radiometer flown on the NASA DC-8 aircraft. Normalized emission and scattering indices derived from radiometer brightness temperatures at the four measuring frequencies enable a 2-dimensional coordinate system that facilities compositing of Kwajalein S-band ground radar reflectivities, ARMAR Ku-band aircraft radar reflectivities, TMI spacecraft radiometer brightness temperatures, PR Ku-band spacecraft radar reflectivities, bulk microphysical parameters derived from the aircraft-mounted cloud microphysics laser probes (including liquid/ice water contents, effective liquid/ice hydrometeor radii, and effective liquid/ice hydrometeor variances), and rainrates derived from any of the individual ground, aircraft, or satellite algorithms applied to the radar or radiometer measurements, or their combination. The results support the study's underlying hypothesis, particularly in context of ice phase processes, in that the cloud regions where the 2a12 algorithm's microphysical database most misrepresents the microphysical conditions as determined by the laser probes, are where retrieved surface rainrates are most erroneous relative to other reference rainrates as determined by ground and aircraft radar. In reaching these conclusions, TMI and PR brightness temperatures and reflectivities have been synthesized from the aircraft AMPR and ARMAR measurements with the analysis conducted in a composite framework to eliminate measurement noise associated with the case study approach and single element volumes obfuscated by heterogeneous beam filling effects. In diagnosing the performance of the 2a12 algorithm, weaknesses have been found in the cloud-radiation database used to provide microphysical guidance to the algorithm for upper cloud ice microphysics. It is also necessary to adjust a fractional convective rainfall factor within the algorithm somewhat arbitrarily to achieve satisfactory algorithm accuracy.

Smith, Eric A.↗
NASA NTRS2013

Modified Hitschfeld-Bordan Equations for Attenuation-Corrected Radar Rain Reflectivity: Application to Nonuniform Beamfilling at Off-Nadir Incidence

As shown by Takahashi et al., multiple path attenuation estimates over the field of view of an airborne or spaceborne weather radar are feasible for off-nadir incidence angles. This follows from the fact that the surface reference technique, which provides path attenuation estimates, can be applied to each radar range gate that intersects the surface. This study builds on this result by showing that three of the modified Hitschfeld-Bordan estimates for the attenuation-corrected radar reflectivity factor can be generalized to the case where multiple path attenuation estimates are available, thereby providing a correction to the effects of nonuniform beamfilling. A simple simulation is presented showing some strengths and weaknesses of the approach.

nonuniform beamfilling↗
NASA NTRS2006

Electric Fields, Cloud Microphysics, and Reflectivity in Anvils of Florida Thunderstorms

A coordinated aircraft - radar project that investigated the electric fields, cloud microphysics and radar reflectivity of thunderstorm anvils near Kennedy Space Center is described. Measurements from two cases illustrate the extensive nature of the microphysics and electric field observations. As the aircraft flew from the edges of anvils into the interior, electric fields very frequently increased abruptly from approx.1 to >10 kV/m even though the particle concentrations and radar reflectivity increased smoothly. The abrupt increase in field usually occurred when the aircraft entered regions with a reflectivity of 10 to 15 dBZ. It is suggested that the abrupt increase in electric field may be because the charge advection from the storm core did not occur across the entire breadth of the anvil and was not constant in time. Screening layers were not detected near the edges of the anvils. Some long-lived anvils showed subsequent enhancement of electric field and reflectivity and growth of particles, which if localized, might be a factor in explaining the abrupt change of field in some cases. Comparisons of electric field magnitude with particle concentration or reflectivity for a combined data set that included all anvil measurements showed a threshold behavior. When the average reflectivity, such as in a 3-km cube, was less than approximately 5 dBZ, the electric field magnitude was <3 kV/m. Based on these findings, the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) is now being used by NASA, the Air Force and Federal Aviation Administration in new Lightning Launch Commit Criteria as a diagnostic for high electric fields in anvils.

Dye, J. E.↗
NASA NTRS2007

Electric Fields, Cloud Microphysics, and Reflectivity in Anvils of Florida Thunderstorms

A coordinated aircraft - radar project that investigated the electric fields, cloud microphysics and radar reflectivity of thunderstorm anvils near Kennedy Space Center is described. Measurements from two cases illustrate the extensive nature of the microphysics and electric field observations. As the aircraft flew from the edges of anvils into the interior, electric fields very frequently increased abruptly from approximately 1 to more than 10 kV m(exp -1) even though the particle concentration and radar reflectivity increased smoothly. The abrupt increase in field usually occurred when the aircraft entered regions with a reflectivity of 10 to 15 dBZ. It is suggested that the abrupt increase in electric field may be because the charge advection from the storm core did not occur across the entire breadth of the anvil and was not constant in time. Screening layers were not detected near the edges of the anvils. Some long-lived anvils showed subsequent enhancement of electric field and reflectivity and growth of particles, which if localized, might be a factor in explaining the abrupt change of field in some cases. Comparisons of electric field magnitude with particle concentration or reflectivity for a combined data set that included all anvil measurements showed a threshold behavior. When the average reflectivity, such as in a 3-km cube, was less than approximately 5 dBZ, the electric field magnitude was les than kV m(exp -1). Based on these findings, the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) is now being used by NASA, the Air Force and Federal Aviation Administration in new Lightning Launch Commit Criteria as a diagnostic for high electric fields in anvils.

Dye, J. E.↗
NASA NTRS2021

Development and Analysis of a Thick Cloud Layers Database for Lightning Launch Commit Criteria Improvement

Lightning can pose a potential threat to space launch vehicles. In response to this, rules were created called the Lightning Launch Commit Criteria (LLCC) that help weather personnel evaluate the potential for natural and rocket-triggered lightning. One of the ten LLCC with the least research is called the Thick Cloud Layers rule. To further understand electrification of thick cloud layers and potentially improve the Thick Cloud Layers rule, a database of thick cloud layers that occurred over the Eastern Range was created. This database is then used to create an algorithm for identifying and differentiating thick cloud layers from other cloud types based on radar characteristics, temperature levels in reference to cloud height, and the surface electric field. By analyzing and identifying thick cloud events, this project could help narrow down when thick clouds are occurring and potentially minimize unnecessary launch delays. Events that caused LLCC violations involving the Thick Cloud Layers rule were analyzed by hand using Level-2 NEXRAD radar data from the National Weather Service WSR-88D radar in Melbourne with the program GR2Analyst. Cases that were found to be isolated and not involved with convection were recorded (date, start/end time, location) in a database. Radar data associated with these cases was collected and gridded using Python radar packages. Once gridded, I calculated and recorded for each radar scan the following radar reflectivity driven parameters within an 11x11 km bin centered on each 1 square km grid point: the mean reflectivity colder than 0 degrees Celsius, Maximum Radar Reflectivity (MRR) colder than 0 degrees Celsius, Volume Averaged Height Integrated Radar Reflectivity (VAHIRR), Hydrometeor Identification (HID), the difference between the maximum and mean reflectivity, the cloud depth colder than 0 degrees Celsius, the overall cloud depth, the cloud top, and the cloud bottom. Soundings for each event were used to determine cloud temperature levels, and where the cloud is in relation to the freezing level. Electric field mill data collected over the Eastern Range was used to determine surface electric fields below each cloud. All parameters were analyzed in depth for several thick cloud cases to gain an understanding of typical thick cloud characteristics. Cases of thick clouds and other isolated cloud types were also recorded for training purposes to see if enough differences exist between cloud types to differentiate them with an algorithm. Each case along with its corresponding characteristics was recorded in a database, and this database was used to compare differing cloud types, as well as train the algorithm to detect thick clouds.

Lightning↗
NASA NTRS1983

Slant path attenuation and cross-polarization prediction

The accuracy with which slant-path attenuation and cross-polarization are predicted using differential reflectivity (ZDR) radar data is discussed. Consideration is given to the use of generalized relationships between radar reflectivity (Z), ZDR, and rainfall rate (R); and between R, attenuation, and cross-polarization (XPD) on a slant path. The forward-scatter matrix which is used to calculate the slant path attenuation and XPD is described. It is shown that the use of a double exponential drop size distribution and forward-scatter matrices improves the accuracy of the prediction of slant-path attenuation and XPD. Data obtained with the VPI & SU S-band radar, using slow switching between orthorzonal polarizations is presented. The results are illustrated in graphs.

Pratt, T.↗