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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗
NASA NTRS2011

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was -1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching -3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗
NASA NTRSDate not supplied

Climatology of Global Precipitation Measurement Mission Precipitation Regimes and Implications for Global Estimates of Vertical Winds

The Global Precipitation Measurement (GPM) mission Validation Network (VN) framework leverages over 118 ground-based polarimetric Doppler radars to validate a large subset of precipitation measurements and retrievals from the GPM Dual-frequency Precipitation Radar (DPR). Recently, GPM DPR reflectivity profiles within the VN have been classified according to their convective regime using unsupervised machine learning techniques. The archetypal regimes are stratiform, convective, mixed stratiform-convective (e.g., transition regions), and “other” (e.g., peripheral regions of light precipitation). Subcategories within these four primary regimes vary according to the characteristic depth of included reflectivity profiles, resulting in 12 main GPM DPR precipitation profile categories. Polarimetry of ground-based Doppler radars in the VN offers additional insights into the types of precipitation, while pairs of radars positioned near each other enable retrieval of vertical winds via dual-Doppler analysis. Geometrically matched to the DPR reflectivity profiles in the GPM VN, these ground-based data and retrievals contribute more detailed characterization of the distinct kinematic and microphysical structures associated with each of the 12 DPR precipitation regimes. DPR reflectivity profiles linked with wind in the VN are restricted to GPM overpasses of proximal radar pairs that allow dual-Doppler analysis. Although a limited subset of DPR profiles in the VN are matched with vertical motion, agreement between the reflectivity structures paired with wind data and those of the greater DPR dataset in the VN suggest that estimates of vertical motion may be inferred in regions without ground-based measurements. We present a climatology of the 12 convective regimes identified within the DPR VN dataset as well as early efforts to estimate the kinematic and microphysical structures of precipitation profiles within the greater GPM DPR dataset by applying machine learning techniques. Precipitation data paired with global estimates of vertical winds from these efforts offer early insight to and support upcoming missions to retrieve convective mass flux, including the Investigation of Convective Updrafts (INCUS) in the Tropics and the global Atmosphere Observing System (AOS).

Precipitation↗
NASA NTRS1992

Nystagmus induced by electrical stimulation of the vestibular and prepositus hypoglossi nuclei in the monkey: evidence for site of induction of velocity storage

Electrical stimulation of the vestibular nuclei (VN) and prepositus hypoglossi nuclei (PPH) of alert cynomolgus monkeys evoked nystagmus and eye deviation while they were in darkness. At some sites in VN, nystagmus and after-nystagmus were induced with characteristics suggesting that velocity storage had been excited. We analyzed these responses and compared them to the slow component of optokinetic nystagmus (OKN) and to optokinetic after-nystagmus (OKAN). We then recorded unit activity in VN and determined which types of nystagmus would be evoked from the sites of recording. Nystagmus and eye deviations were also elicited by electrical stimulation of PPH, and we characterized the responses where unit activity was recorded in PPH. Horizontal slow phase velocity of the VN "storage" responses was contralateral to the side of stimulation. The rising time constants and peak steady-state velocities were similar to those of OKN, and the falling time constants of the after-nystagmus and of OKAN were approximately equal. Both the induced after-nystagmus and OKAN were habituated by stimulation of the VN. When horizontal after-nystagmus was evoked with animals on their sides, it developed yaw and pitch components that tended to shift the vector of the slow phase velocity toward the spatial vertical. Similar "cross-coupling" occurs for horizontal OKAN or for vestibular post-rotatory nystagmus elicited in tilted positions. Thus, the storage component of nystagmus induced by VN stimulation had the same characteristics as the slow component of OKN and the VOR. Positive stimulus sites for inducing nystagmus with typical storage components were located in rostral portions of VN. They lay in caudal ventral superior vestibular nucleus (SVN), dorsal portions of central medial vestibular nucleus (MVN) caudal to the abducens nuclei and in adjacent lateral vestibular nucleus (LVN). More complex stimulus responses, but with contralateral after-nystagmus, were induced from surrounding regions of ventral MVN and LVN, rostral descending vestibular nucleus and the marginal zone between MVN and PPH. Vestibular-only (VO), vestibular plus saccade (VPS) and tonic vestibular pause (TVP) units were identified by extracellular recording. Stimulation near type I lateral and vertical canal-related VO units elicited typical "storage" responses with after-nystagmus in 23 of 29 tracks (79%). Stimulus responses were more complex from the region of neurons with oculomotor-related signals, i.e., TVP or VPS cells, although after-nystagmus was also elicited from these sites. Effects of vestibular nerve and nucleus stimulation were compared.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
NASA NTRS2010

Methods and Results for a Global Precipitation Measurement (GPM) Validation Network Prototype

As one component of a ground validation system to meet requirements for the upcoming Global Precipitation Measurement (GPM) mission, a quasi-operational prototype a system to compare satellite- and ground-based radar measurements has been developed. This prototype, the GPM Validation Network (VN), acquires data from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite and from ground radar (GR) networks in the continental U.S. and participating international sites. PR data serve as a surrogate for similar observations from the Dual-frequency Precipitation Radar (DPR) to be present on GPM. Primary goals of the VN prototype are to understand and characterize the variability and bias of precipitation retrievals between the PR and GR in various precipitation regimes at large scales, and to improve precipitation retrieval algorithms for the GPM instruments. The current VN capabilities concentrate on comparisons of the base reflectivity observations between the PR and GR, and include support for rain rate comparisons. The VN algorithm resamples PR and GR reflectivity and other 2-D and 3-D data fields to irregular common volumes defined by the geometric intersection of the instrument observations, and performs statistical comparisons of PR and GR reflectivity and estimated rain rates. Algorithmic biases and uncertainties introduced by traditional data analysis techniques are minimized by not performing interpolation or extrapolation of data to a fixed grid. The core VN dataset consists of WSR-88D GR data and matching PR orbit subset data covering 21 sites in the southeastern U. S., from August, 2006 to the present. On average, about 3.5 overpass events per month for these WSR-88D sites meet VN criteria for significant precipitation, and have matching PR and GR data available. This large statistical sample has allowed the relative calibration accuracy and stability of the individual ground radars, and the quality of the PR reflectivity attenuation correction in convective and stratiform precipitation to be evaluated. We will present results of PR-GR reflectivity and rain rate bias comparisons for each OR site, and for different rain types, for the full data set and as time series. The capabilities of the statistical analysis and vertical cross section tools for display and analysis of individual site overpass event data will be described, and examples of the tools' outputs will be shown.

Morris, Kenneth R.↗
NASA NTRSDate not supplied

Exploring Controls on the Fluvial Breaching of Degraded Impact Craters

Many lakes on early Mars were hosted in degraded impact craters. Past work has suggested that landscape erosion and crater degradation were very active prior to the valley network (VN)-forming era on Mars. Rim relief reduction during degradation may have primed craters for subsequent inlet incision during the VN-forming era. However, not all old, rimless craters on Mars are breached, so extensive rim degradation could not have been the only control on VN inlet formation. In this study, we ask: Why were some, but not all, degraded craters breached during the VN-forming era? Here, we focus on testing whether there are any measurable distinctions between VN-breached and non-breached degraded Noachian craters.

E R Bamber↗
NASA NTRS1995

The Performance of the NAS HSPs in 1st Half of 1994

During the first six months of 1994, the NAS (National Airspace System) 16-CPU Y-MP C90 Von Neumann (VN) delivered an average throughput of 4.045 GFLOPS while the ACSF (Aeronautics Consolidated Supercomputer Facility) 8-CPU Y-MP C90 Eagle averaged 1.658 GFLOPS. The VN rate represents a machine efficiency of 26.3% whereas the Eagle rate corresponds to a machine efficiency of 21.6%. VN displayed a greater efficiency than Eagle primarily because the stronger workload demand for its CPU cycles allowed it to devote more time to user programs and less time to idle. An additional factor increasing VN efficiency was the ability of the UNICOS 8.0 Operating System to deliver a larger fraction of CPU time to user programs. Although measurements indicate increasing vector length for both workloads, insufficient vector lengths continue to hinder HSP (High Speed Processor) performance. To improve HSP performance, NAS should continue to encourage the HSP users to modify their codes to increase program vector length.

Bergeron, Robert J.↗
NASA NTRS2010

Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

Morris, Kenneth R.↗
NASA NTRS2010

Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

Morris, K. Robert↗
NASA NTRS2003

Premotor neurons encode torsional eye velocity during smooth-pursuit eye movements

Responses to horizontal and vertical ocular pursuit and head and body rotation in multiple planes were recorded in eye movement-sensitive neurons in the rostral vestibular nuclei (VN) of two rhesus monkeys. When tested during pursuit through primary eye position, the majority of the cells preferred either horizontal or vertical target motion. During pursuit of targets that moved horizontally at different vertical eccentricities or vertically at different horizontal eccentricities, eye angular velocity has been shown to include a torsional component the amplitude of which is proportional to half the gaze angle ("half-angle rule" of Listing's law). Approximately half of the neurons, the majority of which were characterized as "vertical" during pursuit through primary position, exhibited significant changes in their response gain and/or phase as a function of gaze eccentricity during pursuit, as if they were also sensitive to torsional eye velocity. Multiple linear regression analysis revealed a significant contribution of torsional eye movement sensitivity to the responsiveness of the cells. These findings suggest that many VN neurons encode three-dimensional angular velocity, rather than the two-dimensional derivative of eye position, during smooth-pursuit eye movements. Although no clear clustering of pursuit preferred-direction vectors along the semicircular canal axes was observed, the sensitivity of VN neurons to torsional eye movements might reflect a preservation of similar premotor coding of visual and vestibular-driven slow eye movements for both lateral-eyed and foveate species.

Non-NASA Center↗
NASA NTRS2009

Complementary Paired G4FETs as Voltage-Controlled NDR Device

It is possible to synthesize a voltage-controlled negative-differential-resistance (NDR) device or circuit by use of a pair of complementary G4FETs (four-gate field-effect transistors). [For more information about G4FETs, please see the immediately preceding article]. As shown in Figure 1, the present voltage-controlled NDR device or circuit is an updated version of a prior NDR device or circuit, known as a lambda diode, that contains a pair of complementary junction field-effect transistors (JFETs). (The lambda diode is so named because its current-versus- voltage plot bears some resemblance to an upper-case lambda.) The present version can be derived from the prior version by substituting G4FETs for the JFETs and connecting both JFET gates of each G4FET together. The front gate terminals of the G4FETs constitute additional terminals (that is, terminals not available in the older JFET version) to which one can apply control voltages VN and VP. Circuits in which NDR devices have been used include (1) Schmitt triggers and (2) oscillators containing inductance/ capacitance (LC) resonant circuits. Figure 2 depicts such circuits containing G4FET NDR devices like that of Figure 1. In the Schmitt trigger shown here, the G4FET NDR is loaded with an ordinary inversion-mode, p-channel, metal oxide/semiconductor field-effect transistor (inversion-mode PMOSFET), the VN terminal of the G4FET NDR device is used as an input terminal, and the input terminals of the PMOSFET and the G4FET NDR device are connected. VP can be used as an extra control voltage (that is, a control voltage not available in a typical prior Schmitt trigger) for adjusting the pinch-off voltage of the p-channel G4FET and thereby adjusting the trigger-voltage window. In the oscillator, a G4FET NDR device is loaded with a conventional LC tank circuit. As in other LC NDR oscillators, oscillation occurs because the NDR counteracts the resistance in the tank circuit. The advantage of this G4FET-NDR LC oscillator over a conventional LC NDR oscillator is that one can apply a time-varying signal to one of the extra control input terminals (VN or VP) to modulate the conductance of the NDR device and thereby amplitude-modulate the output signal.

Mojarradi, Mohammad↗
NASA NTRS2002

Vestibular convergence patterns in vestibular nuclei neurons of alert primates

Sensory signal convergence is a fundamental and important aspect of brain function. Such convergence may often involve complex multidimensional interactions as those proposed for the processing of otolith and semicircular canal (SCC) information for the detection of translational head movements and the effective discrimination from physically congruent gravity signals. In the present study, we have examined the responses of primate rostral vestibular nuclei (VN) neurons that do not exhibit any eye movement-related activity using 0.5-Hz translational and three-dimensional (3D) rotational motion. Three distinct neural populations were identified. Approximately one-fourth of the cells exclusively encoded rotational movements (canal-only neurons) and were unresponsive to translation. The canal-only central neurons encoded head rotation in SCC coordinates, exhibited little orthogonal canal convergence, and were characterized with significantly higher sensitivities to rotation as compared to primary SCC afferents. Another fourth of the neurons modulated their firing rates during translation (otolith-only cells). During rotations, these neurons only responded when the axis of rotation was earth-horizontal and the head was changing orientation relative to gravity. The remaining one-half of VN neurons were sensitive to both rotations and translations (otolith + canal neurons). Unlike primary otolith afferents, however, central neurons often exhibited significant spatiotemporal (noncosine) tuning properties and a wide variety of response dynamics to translation. To characterize the pattern of SCC inputs to otolith + canal neurons, their rotational maximum sensitivity vectors were computed using exclusively responses during earth-vertical axis rotations (EVA). Maximum sensitivity vectors were distributed throughout the 3D space, suggesting strong convergence from multiple SCCs. These neurons were also tested with earth-horizontal axis rotations (EHA), which would activate both vertical canals and otolith organs. However, the recorded responses could not be predicted from a linear combination of EVA rotational and translational responses. In contrast, one-third of the neurons responded similarly during EVA and EHA rotations, although a significant response modulation was present during translation. Thus this subpopulation of otolith + canal cells, which included neurons with either high- or low-pass dynamics to translation, appear to selectively ignore the component of otolith-selective activation that is due to changes in the orientation of the head relative to gravity. Thus contrary to primary otolith afferents and otolith-only central neurons that respond equivalently to tilts relative to gravity and translational movements, approximately one-third of the otolith + canal cells seem to encode a true estimate of the translational component of the imposed passive head and body movement.

Non-NASA Center↗
NASA NTRS1992

Neural basis for eye velocity generation in the vestibular nuclei of alert monkeys during off-vertical axis rotation

Activity of "vestibular only" (VO) and "vestibular plus saccade" (VPS) units was recorded in the rostral part of the medial vestibular nucleus and caudal part of the superior vestibular nucleus of alert rhesus monkeys. By estimating the "null axes" of recorded units (n = 79), the optimal plane of activation was approximately the mean plane of reciprocal semicircular canals, i.e., lateral canals, left anterior-right posterior (LARP) canals or right anterior-left posterior (RALP) canals. All units were excited by rotation in a direction that excited a corresponding ipsilateral semicircular canal. Thus, they all displayed a "type I" response. With the animal upright, there were rapid changes in firing rates of both VO and VPS units in response to steps of angular velocity about a vertical axis. The units were bidirectionally activated during vestibular nystagmus (VN), horizontal optokinetic nystagmus (OKN), optokinetic after-nystagmus (OKAN) and off-vertical axis rotation (OVAR). The rising and falling time constants of the responses to rotation indicated that they were closely linked to velocity storage. There were differences between VPS and VO neurons in that activity of VO units followed the expected time course in response to a stimulus even during periods of drowsiness, when eye velocity was reduced. Firing rates of VPS units, on the other hand, were significantly reduced in the drowsy state. Lateral canal-related units had average firing rates that were linearly related to the bias or steady state level of horizontal eye velocity during OVAR over a range of +/- 60 deg/s. These units could be further divided into two classes according to whether they were modulated during OVAR. Non-modulated units (n = 5) were VO types and all modulated units (n = 5) were VPS types. There was no significant difference between the bias level sensitivities relative to eye velocity of the units with and without modulation (P > 0.05). The modulated units had no sustained change in firing rate in response to static head tilts and their phases relative to head position varied from unit to unit. The phase did not appear to be linked to the modulation of horizontal eye velocity during OVAR. The sensitivities of unit activity to eye velocity were similar during all stimulus modalities despite the different gains of eye velocity vs stimulus velocity during VN, OKN and OVAR. Therefore, VO and VPS units are likely to carry an eye velocity signal related to velocity storage.(ABSTRACT TRUNCATED AT 400 WORDS).

Non-NASA Center↗
NASA NTRS2003

Precise Heater Controller with rf-Biased Josephson Junctions

Paramagnetic susceptibility thermometers used in fundamental physics experiments are capable of measuring temperature changes with a precision of a part in 2 x 10(exp 10). However, heater controllers are only able to control open-loop power dissipation to about a part in 10(exp 5). We used an array of rf-biased Josephson junctions to precisely control the electrical power dissipation in a heater resistor mounted on a thermally isolated cryogenic platform. Theoretically, this method is capable of controlling the electrical power dissipation to better than a part in 10(exp 12). However, this level has not yet been demonstrated experimentally. The experiment consists of a liquid helium cell that also functions as a high-resolution PdMn thermometer, with a heater resistor mounted on it. The cell is thermally connected to a temperature-controlled cooling stage via a weak thermal link. The heater resistor is electrically connected to the array of Josephson junctions using superconducting wire. An rf-biased array of capacitively shunted Josephson junctions drives the voltage across the heater. The quantized voltage across the resistor is Vn = nf(h/2e), where h is Planck's constant, f is the array biasing frequency, e is the charge of an electron, and n is the integer quantum state of the Josephson array. This results in an electrical power dissipation on the cell of Pn = (Vn)(sup 2/R), where R is the heater resistance. The change of the quantum state of the array changes the power dissipated in the heater, which in turn, results in the change of the cell temperature. This temperature change is compared to the expected values based on the known thermal standoff resistance of the cell from the cooling stage. We will present our initial experimental results and discuss future improvements. This work has been funded by the Fundamental Physics Discipline of the Microgravity Science Office of NASA, and supported by a no-cost equipment loan from Sandia National Laboratories.

Green, Colin J.↗
NASA NTRS2009

An Enhanced Global Precipitation Measurement (GPM) Validation Network Prototype

A Validation Network (VN) prototype is currently underway that compares data from the Precipitation Radar (PR) instrument on NASA's Tropical Rainfall Measuring Mission (TRMM) satellite to similar measurements from the U.S. national network of operational weather radars. This prototype is being conducted as part of the ground validation activities of NASA's Global Precipitation Measurement (GPM) mission. GPM will carry a Dual-frequency Precipitation Radar instrument (DPR) with similar characteristics to the TRMM PR. The purpose of the VN is to identify and resolve significant discrepancies between the U.S. national network of ground radar (GR) observations and satellite observations. The ultimate goal of such comparisons is to understand and resolve the first order variability and bias of precipitation retrievals in different meteorological/hydrological regimes at large scales. This paper presents a description of, and results from, an improved algorithm for volume matching and comparison of PR and ground radar observations.

Schwaller, Matthew R.↗
NASA NTRS2019

Overview, Update and Science of the GPM Validation Network Radar Database

A critical component of the Global Precipitation Measurement (GPM) Mission validation strategy involves use of dual-polarimetric (DP) ground-based radar (GR) products. Both operational and research DP radars across the U.S. and several international locations are used with coincident GPM dual-frequency precipitation radar (DPR) data in a significant expansion of the original TRMM-based “validation network architecture” (VN; Schwaller and Morris, 2011, J.Tech.). The VN radar databases consist of millions of geometrically matched DPR and GR precipitation volumes. Not only does it serve as a tool for validation of satellite-based precipitation retrieval algorithms and GR calibration but also a valuable resource for precipitation science and for complimenting future convective precipitation-related satellite missions.

Precipitation Science↗
NASA NTRSDate not supplied

The Multiplatform Precipitation Feature (MPF) Database: Synthesizing Satellite and Ground-Based Precipitation and Lightning Datasets for Convective Studies

NASA’s Lightning Imaging Sensor (LIS) and the Global Precipitation Measurement (GPM) mission have contributed a wealth of data toward global lightning and precipitation studies, respectively. Combining lightning and precipitation datasets leverages their unique insights into deep convective processes that inform about characteristics of convection and its intensity. Recent efforts to synthesize the LIS and GPM datasets prepare the opportunity for unprecedented large-scale, value-added multiplatform analyses of convection. This data synthesis proof-of-concept study elaborates on the creation of a database of reflectivity-based multiplatform precipitation features (MPFs) that capture a combination of information extracted from spatiotemporally coincident lightning and precipitation data within individual storm features. The space-based GPM Dual-frequency Precipitation Radar (DPR) provides a record of precipitation data, while the GPM Validation Network (VN) additionally incorporates ground-based polarimetric Doppler radar data to provide microphysical and kinematic context to DPR data. The LIS instrument onboard the International Space Station has contributed lightning observations since 2017. MPFs encapsulating information from these datasets are created from isolated regions of filtered, smoothed DPR reflectivity data to which ellipses are fit. Each MPF includes feature location, size, and eccentricity information as well as summary reflectivity characteristics. They also include summaries of precipitation microphysics and derived three-dimensional wind available from ground-based radar data. LIS data provides standard lightning characteristics such as flash count and density to each MPF as well as other informative metrics such as flash area and radiance. Each MPF file includes information about the original data from which the MPF and its characteristics were determined, allowing end-user reconstruction of the ellipse and deeper “level I” analysis of captured data. This database of VN-LIS MPFs enables broad statistical analysis of the relationships between the microphysical, kinematic, and electrical properties of convection. Preliminary results from a demonstration of the database will be described as well as ongoing efforts and avenues for future work.

Lightning↗
NASA NTRSDate not supplied

Leveraging the Multiplatform Precipitation Feature Database of Combined Ground Radar and Satellite Lightning Observations for Convective Studies

The Multiplatform Precipitation Feature (MPF) database combines coincident observations of lightning from space with satellite- and ground-based radar data in a storm-based, feature-defined framework. The concept for the MPF database stems from the motivation to extend the scale and scope of investigations into the complex connections between ice precipitation, updrafts, and lightning in thunderstorms. The earliest iteration of the MPF database incorporates NASA International Space Station Lightning Imaging Sensor (ISS LIS) observations alongside the NASA Global Precipitation Measurement (GPM) Mission Dual-frequency Precipitation Radar (DPR) and Validation Network (VN). Because of the specific role of the GPM VN in forming the first MPFs, this subset is referred to as the VNMPF database. The synthesis of these multi-scale and multi-resolution observations leveraged each platform’s unique insights into convective properties and processes, offering a more complete view of deep convection over the large viewing area afforded by satellite coverage. The VNMPF database established the feasibility and infrastructure to combine microphysical, kinematic, and lightning observations from multiple satellite- and ground-based platforms. Following this successful proof-of-concept, recent progress has expanded the MPF database to make use of coincident ISS LIS lightning observations and data from the operational Weather Surveillance Radar - 1988 Doppler (WSR-88D) network, where individual WSR-88D proximity facilitates vertical wind retrievals via dual-Doppler analysis. These database changes have expanded the scope of the dataset by removing the requirement for coincident GPM and ISS LIS overpasses. This increases the sample size dramatically and facilitates analysis of higher-resolution radar-derived properties. These advancements allow both storm-scale and unprecedented broad statistical analyses of deep convection from electrical, kinematic, and microphysical perspectives over the contiguous United States. This presentation outlines the construction of the new MPF database and introduces some preliminary analyses of the convection captured within it. Early results summarize relationships based on updraft characteristics ascertained from WSR-88D dual-Doppler three-dimensional wind retrievals, properties of ice microphysics gleaned from dual-polarization analyses, and electrical characteristics observed by the ISS LIS. The expanded scale and scope offered by more than five years of ISS LIS observations enable new insights into regional and seasonal variations in the microphysical, kinematic, and electrical relationships of convection. Analysis of the database highlights the potential for advancements in lightning meteorology made possible by combining large-scale spaceborne lightning detection and proven storm interrogation tools such as operational polarimetric Doppler radar.

Lightning↗