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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
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NASA NTRSDate not supplied

Evolution of Drop Size Distributions during Hurricane Harvey and Their Effects on Rain Intensity

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017, before exiting the state as a tropical storm on August 29, 2017. Left in its wake was historic flooding over southeast Texas with some locations measuring more than 60 inches of rain. The Houston NEXRAD radar (KHGX) maintained operations for the entirety of the event and is utilized in this study to better understand the evolution of the drop size distribution (DSD) in the lower (liquid) portions of the storm and how changes in the DSD were tied to observed and measured changes in rain intensities. From the KHGX dual-polarimetric radar data several DSD parameters were retrieved, including three different rain rate retrievals, as well as the mass-weighted mean-drop diameter Dm, and the normalized intercept parameter NW of the gamma distribution. Two of the rain retrievals are popular hybrid approaches, where reflectivity, differential and specific differential phase are used. The other is an attenuation-based retrieval. In a previous study, it was found that both hybrid retrievals significantly underestimated the rainfall during the heaviest rain periods, while the attenuation-based retrieval, with proper adjustment, agreed quite well with a large network of gauges from the Harris County Flood Warning System. Using Dm and NW as proxies for drop size and concentration, respectively, we will show that the heaviest rain intensities were associated in areas of the storm where there was a large concentration of large drops present. It is envisaged that results of this study can be used to develop a near-real-time tuning of the attenuation-based retrieval, thus providing timely, and possibly life-saving warnings during inundating rainfall.

David B. Wolff↗
NASA NTRS1996

Correction of WindScat Scatterometric Measurements by Combining with AMSR Radiometric Data

The Seawinds scatterometer on the advanced Earth observing satellite-2 (ADEOS-2) will determine surface wind vectors by measuring the radar cross section. Multiple measurements will be made at different points in a wind-vector cell. When dense clouds and rain are present, the signal will be attenuated, thereby giving erroneous results for the wind. This report describes algorithms to use with the advanced mechanically scanned radiometer (AMSR) scanning radiometer on ADEOS-2 to correct for the attenuation. One can determine attenuation from a radiometer measurement based on the excess brightness temperature measured. This is the difference between the total measured brightness temperature and the contribution from surface emission. A major problem that the algorithm must address is determining the surface contribution. Two basic approaches were developed for this, one using the scattering coefficient measured along with the brightness temperature, and the other using the brightness temperature alone. For both methods, best results will occur if the wind from the preceding wind-vector cell can be used as an input to the algorithm. In the method based on the scattering coefficient, we need the wind direction from the preceding cell. In the method using brightness temperature alone, we need the wind speed from the preceding cell. If neither is available, the algorithm can work, but the corrections will be less accurate. Both correction methods require iterative solutions. Simulations show that the algorithms make significant improvements in the measured scattering coefficient and thus is the retrieved wind vector. For stratiform rains, the errors without correction can be quite large, so the correction makes a major improvement. For systems of separated convective cells, the initial error is smaller and the correction, although about the same percentage, has a smaller effect.

Song, S.↗
NASA NTRS1975

A 20 Ghz Depolarization Experiment Using the ATS-6 Satellite

A depolarization experiment using the 20 GHz downlink from the ATS-6 satellite was described. The following subjects were covered: (1) an operational summary of the experiment, (2) a description of the equipment used with emphasis on improvements made to the signal processing receiver used with the ATS-5 satellite, (3) data on depolarization and attenuation in one snow storm and two rain storms at 45 deg elevation, (4) data on low angle propagation, (5) conclusions about depolarization on satellite paths, and (6) recommendations for the depolarization portion of the CTS experiment.

Bostian, C. W.↗
NASA NTRS1980

Infrared scanner concept verification test report

The test results from a concept verification test conducted to assess the use of an infrared scanner as a remote temperature sensing device for the space shuttle program are presented. The temperature and geometric resolution limits, atmospheric attenuation effects including conditions with fog and rain, and the problem of surface emissivity variations are included. It is concluded that the basic concept of using an infrared scanner to determine near freezing surface temperatures is feasible. The major problem identified is concerned with infrared reflections which result in significant errors if not controlled. Action taken to manage these errors result in design and operational constraints to control the viewing angle and surface emissivity.

Bachtel, F. D.↗
NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗
NASA NTRS2024

Precipitation -17 O-Excess Altered During Tropical Convection: Evidence From Monsoon Cold Surges in Singapore

Despite the recent recognition of -17 O-excess as a promising new tracer for hydrological processes, our knowledge of the control mechanisms underlying -17 O-excess in tropical regions remains limited. To understand how microphysical processes during tropical convection affect precipitation isotope ratios, particularly -17 O-excess, in Singapore, we collected precipitation samples at minute intervals from six rain events associated with cold surges during the Northeast Monsoon seasons and analyzed their triple oxygen isotopes. Our results show that precipitation δ -18 O decreases in the convective zones and then gradually increases in the stratiform zones, while d-excess exhibits an inverse trend. This correlation between δ -18 O and d-excess indicates that rain evaporation plays a crucial role in regulating precipitation isotopes. Moreover, the rain events with a higher upstream rainout amount have lower δ -18 O and higher -17 O-excess values, suggesting that precipitation δ -18 O and -17 O-excess likely reflect the integrated upstream convective activity. Microphysical processes associated with upstream convection, such as rain evaporation and vapor recycling, are potential mechanisms that increase -17 O-excess values along moisture transport pathways for a rain event, and hence, undermine the effectiveness of -17 O-excess as a tracer of moisture source humidity. Contrary to the negative correlation observed in monthly precipitation, there is generally a positive correlation between d-excess and -17 O-excess at the event scale. However, this correlation weakens as convective rain intensifies, suggesting that stronger convection can attenuate the positive correlation between d-excess and -17 O-excess. Therefore, it is crucial to consider how tropical convection alters -17 O-excess when utilizing this tracer to interpret atmospheric dynamics and hydrological processes.

tropical weather systems↗
NASA NTRS2019

Assessing Dual-Polarization Radar Estimates of Extreme Rainfall During Hurricane Harvey

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value ofa50.015 andb50.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

David Billings Wolff↗
NASA NTRS1996

Stochastic Filtering of Rain Profiles Using Radar, Surface-Referenced Radar, or Combined Radar-Radiometer Measurements

This paper describes a computationally efficient nearly optimal Bayesian algorithm to estimate rain (and drop size distribution) profiles, given a radar reflectivity profile at a single attenuating wavelength. In addition to estimating the averages of all the mutually ambiguous combinations of rain parameters that can produce the data observed, the approach also calculates the n-ns uncertainty in its estimates (this uncertainty thus quantifies "the amount of ambiguity" in the "solution"). The paper also describes a more general approach that can make estimates based on a radar reflectivity profile together with an approximate measurement of the path-integrated attenuation, or a radar reflectivity profile and a set of passive microwave brightness temperatures. This more general "combined" algorithm is currently being adapted for the Tropical Rainfall Measuring Mission.

Haddad, Ziad S.↗
NASA NTRS2019

Assessing Dual-Polarization Radar Estimates of Extreme Rainfall During Hurricane Harvey

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017 before exiting the state as a tropical storm on August 29, 2017. Left in its wake was historic flooding, with some locations measuring more than 60 inches of rain over a five-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar data set to retrieve daily and event-total precipitation estimates for the period August 25-29, 2017. The KHGX precipitation estimates were then compared to the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed Drop Size Distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α=0.015 and β=0.600 and β=0.625 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

David B Wolff↗
NASA NTRS1986

Some comments on passive microwave measurement of rain

It is argued that because microwave radiation interacts much more strongly with hydrometeors than with cloud particles, microwave measurements from space offer a significant chance of making global precipitation estimates. Over oceans, passive microwave measurements are essentially attenuation measurements that can be very closely related to the rain rate independently of the details of the drop-size distribution. Over land, scattering of microwave radiation by the hydrometeors, especially in the ice phase, can be used to estimate rainfall. In scattering, the details of the drop-size distribution are very important and it is therefore more difficult to achieve a high degree of accuracy. The SSM/I (Special Sensor Microwave Imager), a passive microwave imaging sensor that will be launched soon, will have dual-polarized channels at 85.5 GHz that will be very sensitive to scattering by frozen hydrometeors. Other sensors being considered for the future space missions would extend the ability to estimate rain rates from space. The ideal spaceborne precipitation-measurement system would use the complementary strengths of passive microwave, radar, and visible/infrared measurements.

Wilheit, Thomas T.↗
NASA NTRS2016

Deployment and Performance of the NASA D3R During the GPM OLYMPEx Field Campaign

The NASA D3R was successfully deployed and operated throughout the NASA OLYMPEx field campaign. A differential phase based attenuation correction technique has been implemented for D3R observations. Hydrometeor classification has been demonstrated for five distinct classes using Ku-band observations of both convection and stratiform rain. The stratiform rain hydrometeor classification is compared against LDR observations and shows good agreement in identification of mixed-phase hydrometeors in the melting layer.

Sea measurements↗
DOE OSTI2020

Estimating total attenuation using Rayleigh targets at cloud top: applications in multilayer and mixed-phase clouds observed by ground-based multifrequency radars

At millimeter wavelengths, attenuation by hydrometeors, such as liquid droplets or large snowflakes, is generally not negligible. When using multifrequency ground-based radar measurements, it is common practice to use the Rayleigh targets at cloud top as a reference in order to derive attenuation-corrected reflectivities and meaningful dual-frequency ratios (DFRs). By capitalizing on this idea, this study describes a new quality-controlled approach that aims at identifying regions of cloud where particle growth is negligible. The core of the method is the identification of a “Rayleigh plateau”, i.e., a large enough region near cloud top where the vertical gradient of DFR remains small. By analyzing co-located Ka–W band radar and microwave radiometer (MWR) observations taken at two European sites under various meteorological conditions, it is shown how the resulting estimates of differential path-integrated attenuation (ΔPIA) can be used to characterize hydrometeor properties. When the ΔPIA is predominantly produced by cloud liquid droplets, this technique alone can provide accurate estimates of the liquid water path. When combined with MWR observations, this methodology paves the way towards profiling the cloud liquid water, quality-flagging the MWR retrieval for rain and drizzle contamination, and/or estimating the snow differential attenuation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Special Effects: Antenna Wetting, Short Distance Diversity and Depolarization

The Advanced Communication Technology Satellite (ACTS) communications system operates in the Ka frequency band. ACTS uses multiple, hopping, narrow beams and very small aperture terminal (VSAT) technology to establish a system availability of 99.5% for bit-error-rates of 5 x 10(exp -7) Or better over the continental United States. In order maintain this minimum system availability in all US rain zones, ACTS uses an adaptive rain fade compensation protocol to reduce the impact of signal attenuation resulting from propagation effects. The purpose of this paper is to present the results of system and sub-system characterizations considering the statistical effects of system variances due to antenna wetting and depolarization effects. In addition the availability enhancements using short distance diversity in a sub-tropical rain zone are investigated.

Acosta, Roberto J.↗
NASA NTRS1991

Polarization radar measurements in rain at 5 and 9 GHz

Potential techniques for measuring rainfall rate R and rainwater content W at 9 and 5 GHz are explored. An investigation is made of a previous technique to use the polarization propagation differential phase shift with increasing distance from the radar Phi(H-V) to estimate and remove the effects of specific and polarization differential attenuation from Z(H) and Z(DR), respectively. It is shown that in rain this technique is sensitive to variations in the drop-size distribution. It is confirmed that Phi(H-V) can be used to extend the distance over which useful measurements of Z(H) and Z(DR) can be obtained. While residual errors introduced by attenuation and the 'noise' from the correction scheme itself eclipse the potential of many possible techniques for quantitative rainfall measurements at these frequencies, the attenuation recovery scheme is argued to be adequate for obtaining useful polarization microphysical measurements, particularly above the melting level, even after encounters with rain.

Jameson, A. R.↗
NASA NTRS2009

The UAH/NSSTC Advanced Radar for Meteorological and Operational Research (ARMOR)

The past four years have seen a marked enhancement in meteorological-radar infrastructure and radar-research capability at the University of Alabama-Huntsville (UAH) and National Space Science and Technology Center (NSSTC; a collaborative center supported by UAH, NASA-MSFC and USRA). This enhancement is due in part to the development of the ARMOR C-band dual-polarimetric radar facility (amongst other mobile radar facilities also discussed in this conference). The ARMOR radar, located at Huntsville International Airport, originated as a unique collaboration between university, government and broadcast meteorologists (the very first of its kind relative to concurrent operational, research and broadcast applications of dual-polarimetry). Contributions from each of these entities resulted in the upgrade of a surplus National Weather Service WSR-74C radar to a research-grade C-band polarimetric radar. The initial upgrade of the radar took place in late 2004 with WHNT-TV purchase and installation of a SIGMET (now Vaisala) Antenna Mounted Receiver (AMR), RVP8/RCP8 radar processor/antenna controller, new radome, and a new dual-polarimetric antenna feed. The AMR enabled simultaneous transmit and receive (STSR) capability and hence collection of dual-polarimetric moments. During the initial part of the AMR upgrade the original WSR74C antenna reflector and 250 kW magnetron-transmitter were used. In early 2005, a new 350 kW magnetron transmitter was purchased from Baron Services and installed. In October of 2006 a new high performance parabolic antenna and dual-pol feed (Seavey) were installed together with a new Orbit pedestal. ARMOR Radar control and data delivery are facilitated through the use of T-1 lines that run from the airport to both NSSTC and WHNT-TV in Huntsville. Under current operating protocols radar scanning and product development are completed at NSSTC, though meteorologists at WHNT-TV can also control the radar if desired. In its default scanning configuration the radar is operated 24/7 in an STSR polarimetric rain scan mode alternating with a surveillance scan on a 5-minute cycle; scans separated by 2.5 minutes. Every 2.5 minutes the raw data arrive at NSSTC where they are corrected in real time for attenuation and differential attenuation (using a constrained ZDR/Z-PHI approach) and new products are generated (e.g., rain maps, hydrometeor identification etc.). The raw and derived products are archived at NSSTC and also redistributed locally in real time over the network within NSSTC to the National Weather Service Forecast Office in Huntsville (collocated with NSSTC) for operational use. During periods of interesting weather the radar is often operated in full, sector, or RHI volume modes from NSSTC and coincident with UAH mobile radar or NWS NEXRAD radar platforms as needed.

Petersen, Walter A.↗
NASA NTRS1993

General probability-matched relations between radar reflectivity and rain rate

An improved method for transforming radar-observed reflectivities Ze into rain rate R is presented. The method is based on a formulation of a Ze-R function constrained such that (1) the radar-retrieved pdf of R and all of its moments are identical to those determined from the gauges over a sufficiently large domain, and (2) the fraction of the time that it is raining above a low but still has an accurately measurable rain intensity is identical for both the radar and for simultaneous measurements of collocated gauges on average. Data measured by a 1.65-deg beamwidth C-band radar and 22 gauges located in the vicinity of Darwin, Australia, are used. The resultant Ze-R functions show a strong range dependence, especially for the rain regimes characterized by strong reflectivity gradients and substantial attenuation. The application of these novel Ze-R functions to the radar data produces excellent matches to the gauge measurements without any systematic bias.

Rosenfeld, Daniel↗
NASA NTRS2019

Path Attenuation Estimates for the DPR

The algorithm for the Surface Reference Technique (SRT) has been updated from version V6A to version V6X. The modified algorithm is designed to process dual-frequency radar data which are now available over the full swath. Comparisons between V6A and V6X show that the dual-wavelength version of the SRT (DSRT) eliminates some of the overestimates of path attenuation in the outer swath that occurred in the earlier version of the algorithm when dual-frequency data was unavailable in the outer swath. However, the DSRT is not reliable in cases of light rain rates where only the Ku-band channel detects rain, nor is it reliable in high rain rate cases where the Ka-band surface signal is lost through attenuation. A modified hybrid algorithm is planned for version 7 that can combine the best features of single- and dual-frequency path attenuation methods.

Meneghini, Robert↗