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NASA NTRS2010

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products. 3

Wolff, David B.↗
NASA NTRS2010

Satellite (Timed, Aura, Aqua) and In Situ (Meteorological Rockets, Balloons) Measurement Comparability

Measurements using the inflatable falling sphere often are requested to provide density data in support of special sounding rocket launchings into the mesosphere and thermosphere. To insure density measurements within narrow time frames and close in space, the inflatable falling sphere is launched within minutes of the major test. Sphere measurements are reliable for the most part, however, availability of these rocket systems has become more difficult and, in fact, these instruments no longer are manufactured resulting in a reduction of the meager stockpile of instruments. Sphere measurements also are used to validate remotely measured temperatures and have the advantage of measuring small-scale atmospheric features. Even so, with the dearth of remaining falling spheres perhaps it is time to consider whether the remote measurements are mature enough to stand alone. Presented are two field studies, one in 2003 from Northern Sweden and one in 2010 from the vicinity of Kwajalein Atoll that compare temperature retrievals between satellite and in situ failing spheres. The major satellite instruments employed are SABER, MLS, and AIRS. The comparisons indicate that remotely measured temperatures mimic the sphere temperature measurements quite well. The data also confirm that satellite retrievals, while not always at the exact location required for individual studies, are adaptable enough and highly useful. Although the falling sphere will provide a measurement at a specific location and time, satellites only pass a given location daily or less often. This report reveals that averaged satellite measurements can provide temperatures and densities comparable to the falling sphere.

Schmidlin, F. J.↗
NASA NTRS2011

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

Wolff, David B.↗
NASA NTRS2011

Analysis of ALTAIR 1998 Meteor Radar Data

We describe a new analysis of a set of 32 UHF meteor radar traces recorded with the 422 MHz ALTAIR radar facility in November 1998. Emphasis is on the velocity measurements, and on inferences that can be drawn from them regarding the meteor masses and mass densities. We find that the velocity vs altitude data can be fitted as quadratic functions of the path integrals of the atmospheric densities vs distance, and deceleration rates derived from those fits all show the expected behavior of increasing with decreasing altitude. We also describe a computer model of the coupled processes of collisional heating, radiative cooling, evaporative cooling and ablation, and deceleration - for meteors composed of defined mixtures of mineral constituents. For each of the cases in the data set we ran the model starting with the measured initial velocity and trajectory inclination, and with various trial values of the quantity mPs 2 (the initial mass times the mass density squared), and then compared the computed deceleration vs altitude curves vs the measured ones. In this way we arrived at the best-fit values of the mPs 2 for each of the measured meteor traces. Then further, assuming various trial values of the density Ps, we compared the computed mass vs altitude curves with similar curves for the same set of meteors determined previously from the measured radar cross sections and an electrostatic scattering model. In this way we arrived at estimates of the best-fit mass densities Ps for each of the cases. Keywords meteor ALTAIR radar analysis 1 Introduction This paper describes a new analysis of a set of 422 MHz meteor scatter radar data recorded with the ALTAIR High-Power-Large-Aperture radar facility at Kwajalein Atoll on 18 November 1998. The exceptional accuracy/precision of the ALTAIR tracking data allow us to determine quite accurate meteor trajectories, velocities and deceleration rates. The measurements and velocity/deceleration data analysis are described in Sections II and III. The main point of this paper is to use these deceleration rate data, together with results from a computer model, to determine values of the quantities mPs 2 (the meteor mass times its material density squared); and further, by combining these m s 2 values with meteor mass estimates for the same set of meteors determined separately from measured radar scattering

Zinn, J.↗
NASA NTRS2012

Comparison of Temperature Measurements in the Middle Atmosphere by Satellite with Profiles Obtained by Meteorological Rockets

Measurements using the inflatable falling sphere technique have occasionally been used to obtain temperature results from density data and thereby provide comparison with temperature profiles obtained by satellite sounders in the mesosphere and stratosphere. To insure density measurements within narrow time frames and close in space, the inflatable falling sphere is launched within seconds of the nearly overhead satellite pass. Sphere measurements can be used to validate remotely measured temperatures but also have the advantage of measuring small-scale atmospheric features. Even so, with the dearth of remaining falling spheres available (the manufacture of these systems has been discontinued), it may be time to consider whether the remote measurements are mature enough to stand alone. Three field studies are considered, one in 2003 from Northern Sweden, and two in 2010 from the vicinity of Kwajalein Atoll in the South Pacific and from Barking Sands, Hawaii. All three sites are used to compare temperature retrievals between satellite and in situ falling spheres. The major satellite instruments employed are SABER, MLS, and AIRS. The comparisons indicate that remotely measured temperatures mimic the sphere temperature measurements quite well. The data also confirm that satellite retrievals, while not always at the exact location required for detailed studies in space and time, compare sufficiently well to be highly useful. Although the falling sphere will provide a measurement at a specific location and time, satellites only pass a given location daily or less frequently. This report reveals that averaged satellite measurements can provide temperatures and densities comparable to those obtained from the falling sphere, thereby providing a reliable measure of global temperature

Goldberg, Richard A.↗
NASA NTRS2010

Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

Fisher, Brad↗
NASA NTRS2013

National Report on the NASA Sounding Rocket and Balloon Programs

The U. S. National Aeronautics and Space Administration (NASA) Sounding Rockets and Balloon Programs conduct a total of 30 to 40 missions per year in support of the NASA scientific community and other users. The NASA Sounding Rockets Program supports the science community by integrating their experiments into the sounding rocket payloads, and providing both the rocket vehicle and launch operations services. Activities since 2011 have included two flights from Andoya Rocket Range, more than eight flights from White Sands Missile Range, approximately sixteen flights from Wallops Flight Facility, two flights from Poker Flat Research Range, and four flights from Kwajalein Atoll. Other activities included the final developmental flight of the Terrier-Improved Malemute launch vehicle, a test flight of the Talos-Terrier-Oriole launch vehicle, and a host of smaller activities to improve program support capabilities. Several operational missions have utilized the new Terrier-Malemute vehicle. The NASA Sounding Rockets Program is currently engaged in the development of a new sustainer motor known as the Peregrine. The Peregrine development effort will involve one static firing and three flight tests with a target completion data of August 2014. The NASA Balloon Program supported numerous scientific and developmental missions since its last report. The program conducted flights from the U.S., Sweden, Australia, and Antarctica utilizing standard and experimental vehicles. Of particular note are the successful test flights of the Wallops Arc Second Pointer (WASP), the successful demonstration of a medium-size Super Pressure Balloon (SPB), and most recently, three simultaneous missions aloft over Antarctica. NASA continues its successful incremental design qualification program and will support a science mission aboard WASP in late 2013 and a science mission aboard the SPB in early 2015. NASA has also embarked on an intra-agency collaboration to launch a rocket from a balloon to conduct supersonic decelerator tests. An overview of NASA's Sounding Rockets and Balloon Operations, Technology Development and Science support activities will be presented.

Eberspeaker, Philip↗
NASA NTRS2013

The NASA Meter Class Autonomous Telescope: Ascension Island

The Meter Class Autonomous Telescope (MCAT) is the newest optical sensor dedicated to NASA s mission to characterize the space debris environment. It is the successor to a series of optical telescopes developed and operated by the JSC Orbital Debris Program Office (ODPO) to monitor and assess the debris environment in (1) Low Earth Orbit (LEO), (2) Medium Earth Orbit (MEO), and (3) Geosynchronous Orbit (GEO), with emphasis on LEO and GEO altitudes. A joint NASA-Air Force Research Labs project, MCAT is a 1.3m optical telescope dedicated to debris research. Its optical path and sensor yield a large survey fence at the cutting edge of current detector performance. It has four primary operational observing modes, two of which were not computationally feasible a decade ago. Operations are supported by a sophisticated software suite that monitors clouds and weather conditions, and controls everything from data collection to dome rotation to processing tens of GB of imagery data nightly. With fainter detection limits, precision detection, acquisition and tracking of targets, multi-color photometry, precision astrometry, automated reacquisition capability, and the ability to process all data at the acquisition rate, MCAT is capable of producing and processing a volume and quality of data far in excess of any current (or prior) ODPO operations. This means higher fidelity population inputs and eliminating the multi-year backlog from acquisition-to-product typical of optical campaigns. All of this is possible given a suitable observing location. Originally planned for the island of Legan, part of the Kwajalein Atoll Islands, recent developments have led to a change in venue. Specifically, the Ground-based Electro-Optical Deep Space Surveillance, or GEODSS, System of telescopes is the United States major tracking system for deep space. This network consists of telescopes in Maui, Hawaii; Diego Garcia (Indian Ocean), and Socorro, New Mexico. A fourth optical telescope, though smaller in size, has been operating in conjunction with this effort until recently in M.ron, Spain. With the M.ron site closing, a significant gap in longitude exists between the New Mexico and Diego Garcia sites. This longitudinal gap is well covered by placing a telescope on Ascension Island (7degrees 58'20" S, 14degrees 24'4"W), in the Atlantic Ocean. Ascension Island offers the benefits of both location and weather. The near equatorial location affords the opportunity to access under-sampled low-inclination orbits and new GEO longitudes, while simultaneously filling in the GEODSS longitudinal gap. Ascension Island is a volcanic, desert island, receiving only 7" of rain per year on average. With consistent trade winds blowing from the SSE direction off Africa, the combination of an island location with consistent winds will create the smooth laminar flow sought after by all astronomical sites, which creates stable atmospheric ('seeing') conditions. Finally, this low population island has minimal lighting, resulting in very dark skies, ideal for an observatory.

Lederer, S. M.↗
NASA NTRS2013

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

TRMM↗
NASA NTRS2013

Nuclear Spectroscopic Telescope Array (NuSTAR) Mission

The Nuclear Spectroscopic Telescope Array (NuSTAR) is a National Aeronautics and Space Administration (NASA) Small Explorer mission that carried the first focusing hard X-ray (6-79 keV) telescope into orbit. It was launched on a Pegasus rocket into a low-inclination Earth orbit on June 13, 2012, from Reagan Test Site, Kwajalein Atoll. NuSTAR will carry out a two-year primary science mission. The NuSTAR observatory is composed of the X-ray instrument and the spacecraft. The NuSTAR spacecraft is three-axis stabilized with a single articulating solar array based on Orbital Sciences Corporation's LEOStar-2 design. The NuSTAR science instrument consists of two co-aligned grazing incidence optics focusing on to two shielded solid state CdZnTe pixel detectors. The instrument was launched in a compact, stowed configuration, and after launch, a 10-meter mast was deployed to achieve a focal length of 10.15 m. The NuSTAR instrument provides sub-arcminute imaging with excellent spectral resolution over a 12-arcminute field of view. The NuSTAR observatory will be operated out of the Mission Operations Center (MOC) at UC Berkeley. Most science targets will be viewed for a week or more. The science data will be transferred from the UC Berkeley MOC to a Science Operations Center (SOC) located at the California Institute of Technology (Caltech). In this paper, we will describe the mission architecture, the technical challenges during the development phase, and the post-launch activities.

Telescope↗
NASA NTRS2017

The Imaging X-Ray Polarimetry Explorer (IXPE): Overview

Mission background: Imaging x-ray polarimetry in 2–8 kiloelectronvolt band; NASA Astrophysics Small Explorer (SMEX) selected in 2017 January. Orbit: Pegasus-XL (airborne) launch in 2021, from Kwajalein; Equatorial circular orbit at greater than or approximately equal to 540 kilometers (620 kilometers, goal) altitude. Flight system: Spacecraft, payload structure, and integration by Ball Aerospace - Deployable payload boom from Orbital-ATK, under contract to Ball; X-ray Mirror Module Assemblies by NASA/MSFC; X-ray (polarization-sensitive) Instruments by IAPS/INAF (Istituto di Astrofisica e Planetologia Spaziali / Istituto Nazionale di Astrofisica) and INFN (Istituto Nazionale di Fisica Nucleare). Ground system: ASI (Agenzia Spaziale Italiana) Malindi ground station, with Singapore backup; Mission Operations Center at LASP (Laboratory for Atmospheric and Space Physics, University of Colorado); Science Operations Center at NASA/MSFC; Data archive at HEASARC (High Energy Astrophysics Science Archive Research Center), (NASA/GSFC), mirror at ASI Data Center. Science: Active galactic nuclei; Microquasars; Radio pulsars and pulsar wind nebulae; Supernova remnants; Magnetars; Accreting x-ray pulsars.

X-ray polarimetry space missio↗
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 NTRS2020

Development and Evaluation of the Raindrop Size Distribution Parameters for the NASA Global Precipitation Measurement Mission Ground Validation Program

The National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission ground validation program uses dual-polarization radar moments to estimate raindrop size distribution (DSD) parameters, the mass-weighted mean drop diameter Dmass, and normalized intercept parameter NW, to validate the GPM Core Observatory–derived DSD parameters. The disdrometer-based Dmass and NW are derived through empirical relationships between Dmass and differential reflectivity ZDR, and between NW, reflectivity ZH, and Dmass. This study employs large datasets collected from two-dimensional video disdrometers (2DVD) during six different field studies to derive the requisite empirical relationships. The uncertainty of the derived Dmass(ZDR) relationship is evaluated through comparisons of 2DVD-calculated and ZDR-estimated Dmass, where ZDR is calculated directly from 2DVD observations. Similarly, the uncertainty of the NW(ZH, Dmass) relationship is evaluated through 2DVD-calculated and Dmass and ZH-estimated NW, where Dmass and ZH are directly calculated from 2DVD observations. This study also presents the sensitivity of Dmass(ZDR) relationships to climate regime and to disdrometer type after developing three additional Dmass(ZDR) relationships from second-generation Particle Size Velocity (PARSIVEL2) disdrometer (P2) observations collected in the Pacific Northwest, in Iowa, and at Kwajalein Atoll in the tropical Pacific Ocean. The application of P2-derived Dmass(ZDR) relationship based on precipitation in the northwestern United States to P2 observations collected over the tropical ocean resulted in the highest error among comparisons of the three datasets.

Ali Tokay↗
NASA NTRS2023

NASA Sounding Rockets User Handbook

This Handbook describes the capabilities of the Sounding Rocket program, the design and technology applications used by that program, and the processes established to integrate the customer (principal investigator/program user/scientist/experimenter) into the mission team to ensure the highest probability of a successful project.

Sounding Rocket↗