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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Climatological Processing of Radar Data for the TRMM Ground Validation Program

The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November, 1997. The main purpose of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented. The primary goal of TRMM GV is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies for the following primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, research analysts at NASA Goddard Space Flight Center (GSFC) generate standardized TRMM GV products using quality-controlled ground-based radar data from the four primary GV sites as input. This presentation will provide an overview of the TRMM GV climatological processing system. A description of the data flow between the primary GV sites, NASA GSFC, and the TRMM Science and Data Information System (TSDIS) will be presented. The radar quality control algorithm, which features eight adjustable height and reflectivity parameters, and its effect on monthly rainfall maps will be described. The methodology used to create monthly, gauge-adjusted rainfall products for each primary site will also be summarized. The standardized monthly rainfall products are developed in discrete, modular steps with distinct intermediate products. These developmental steps include: (1) extracting radar data over the locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) automated quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z-R relationships from the quality-controlled merged data over monthly time scales. A summary of recently reprocessed official GV rainfall products available for TRMM science users will be presented. Updated basic standardized product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for each primary GV site will be also displayed.

Kulie, Mark↗
NASA NTRS1999

ER-2 Observations of Precipitation Systems During TRMM-LBA

The NASA ER-2 performed numerous flights over precipitation systems in Rondonia, Brazil. The ER-2 carried a payload including the ER-2 Doppler Radar (EDOP), the Advanced Microwave Precipitation Radiometer (AMPR), the Lightning Instrument Package, and other instruments. This presentation will overview the types of data sets collected during TRMM-LBA with particular emphasis on EDOP measurements. Numerous cases of convection ranging from weak to very intense, were overflown by the ER-2. Two TRMM overpasses were coincident with ER-2 flights which allowed for intercomparisons between the Precipitation Radiometer (PR), EDOP, and the S-POL and TOGA ground-based radars. Preliminary results from this comparison will be presented as well as initial selection of case studies and efforts involving vertical motions in convection.

Heymsfield, Gerald↗
NASA NTRSDate not supplied

Sensing Small Uncrewed Aerial Vehicles with Distributed Radars for Advanced Air Mobility Surveillance

In the context of Advanced and Urban Air Mobility major attention is being reserved to the development of sensing strategies for small Uncrewed Aerial Vehicles (sUAVs) to enable their safe operations in and around urban areas. Such strategies should rely on non-cooperative distributed sensors to strengthen the surveillance solution towards the unreliability of Global Navigation Satellite System (GNSS) positioning information, which is typical for low-altitude-flying platforms in urban regions, and increase the monitored airspace volume. To this aim, this paper proposes a fusion solution for a network of distributed ground-based radars, which can be exploited to not only increase the coverage over large airspace volumes but also improve the overall detectability and traceability of sUAVs by leveraging on multiple views over the same area. The solution exploits a centralized fusion scheme in which measurements collected by each radar are shared with a Fusion Center where Kalman Filtering is exploited to build a unique, fused track. Tests conducted on experimental data collected using two sUAVs as flying targets and three distributed radars showed that the proposed solution can produce an increase in coverage from about 20 % (single radar configuration) to about 80 % of the targets’ flight path, as well as a finer accuracy yielding meter and meter-per-second root mean square error values on position and velocity components.

Federica Vitiello↗
NASA NTRS2019

Haystack Ultra-Wideband Satellite Imaging Radar Measurements of the Orbital Debris Environment: 2014-2017

Since the founding of the NASA Orbital Debris Program Office (ODPO) in 1979, the knowledge that orbital debris poses a risk to operational satellites and human spaceflight has been publically available. Services that rely on satellite-based technology such as communications, internet, navigation, and weather forecasting, to name a few, are ubiquitous in modern society. The International Space Station (ISS) has been continuously inhabited by a crew of up to six astronauts since November 2000 and makes, on average, approximately one debris avoidance maneuver per year to avoid objects that are large enough to be tracked by ground-based radars. This places an increased need for understanding the current status of the debris environment (measurements), for the ability to predict the future environment (modeling), and for understanding risk factors for debris creating events (mitigation). For NASA, the measurements, modeling, and mitigation aspects of orbital debris are led by the NASA ODPO at the Johnson Space Center (JSC) in Houston, Texas.This report summarizes radar measurement data from the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR) operated by the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) and provided to the NASA ODPO. The time period covered by this report includes data collected during the U.S. government fiscal year (FY) 2014 through FY2017. The U.S. government FY begins on 1 October and lasts through 30 September of a given year (i.e., FY2014 lasts from 1 October 1 2013 through 30 September 30 2014). At this report’s release, processed data was unavailable from the Haystack Auxiliary Radar (HAX) due to errors in the calibration data for the radar and limited transmit power; a decision was made by NASA not to collect low-power HAX radar data. This is being resolved by NASA and MIT/LL and data collected during this time period will be released in a separate report.

DRADIS↗
NASA NTRS2013

Reduction of Non-uniform Beam Filling Effects by Vertical Decorrelation: Theory and Simulations

Algorithms for estimating precipitation rates from spaceborne radar observations of apparent radar reflectivity depend on attenuation correction procedures. The algorithm suite for the Ku-band precipitation radar aboard the Tropical Rainfall Measuring Mission satellite is one such example. The well-known problem of nonuniform beam filling is a source of error in the estimates, especially in regions where intense deep convection occurs. The error is caused by unresolved horizontal variability in precipitation characteristics such as specific attenuation, rain rate, and effective reflectivity factor. This paper proposes the use of vertical decorrelation for correcting the nonuniform beam filling error developed under the assumption of a perfect vertical correlation. Empirical tests conducted using ground-based radar observations in the current simulation study show that decorrelation effects are evident in tilted convective cells. However, the problem of obtaining reasonable estimates of a governing parameter from the satellite data remains unresolved.

radar reflectivity↗
NASA NTRS1999

The First Year of TRMM and its Connection to a Global Precipitation Measuring System

This presentation will focus primarily on the advances in our understanding of tropical rain systems needed to interpret the TRMM data. Global averages, as well as case studies from TRMM radar (PR), the TRMM Microwave Imager (TMI) and Visible and Infrared Sensor (VIRS) will be presented. Comparisons and contrasts among the different sensors will be drawn. The relationship between excessive cold clouds and lightning will be illustrated. Comparisons between rainfall products show fairly good agreement outside the deep tropics. The deep tropics will be examined in greater detail to highlight differences and possible sources of discrepancies. Results will also be compared to previous rainfall climatologies generated from the SSM/I instrument. Finally, the paper will focus upon the relationship between the estimates made from the TRMM sensor and those made from ground based radars and preliminary conclusions as well as steps being taken to continue improving our understanding will be presented.

Kummerow, Christian↗
NASA NTRS2025

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗
NASA NTRS2000

Evolution and Mean Properties of Convective Systems in Southwestern Amazonia During TRMM-LBA

During the wet season TRMM field campaign in Rondonia, Brazil, a variety of convective systems were sampled by radar, sounding, and geostationary satellite for a 60 day period in early 1999. Local variations in the local wind and humidity field have been attributed in part by this study to synoptic scale phenomena, most conspicuously the establishment of stationary frontal systems penetrating into the tropics. These baroclinic systems induced periodic episodes low level moist, westerly flow across Rondonia during the experiment. This flow feature may be an important component of the South American climate system by playing a role in maintaining the South Atlantic Convergence Zone, which was active during these local westerly wind events. It is therefore important to understand the differences in mesoscale properties of convective systems between the westerly wind periods and intervening easterly wind periods. Differences in shear and moisture characteristics (Halverson et al. 2000, this meeting) are compared to structural and life-cycle characteristics of convective systems in Rondonia. Data from ground based radar and geostationary satellite provide a view of the evolution of the vertical structure and horizontal morphology of several large mesoscale convective systems in each regime. Preliminary statistics on the diurnal variation of precipitation intensity, areal coverage, and cloud top area are presented. Results suggest that long-lived, shallow convective systems with a large stratiform component of precipitation are characteristic of the westerly wind periods. A goal of this study is to establish a basis for which to parameterize the mesoscale effects of convection on large scale features of the South American climate system.

Rickenbach, Thomas M.↗
NASA NTRS1993

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

Turner, B. J.↗
NASA NTRS2002

A Downscaling Analysis of the Urban Influence on Rainfall: TRMM Satellite Component AMS Conference on Satellite Meteorology and Oceanography

A recent publication by Shepherd et al. (2002) demonstrated the feasibility of using TRMM precipitation radar (PR) estimates to identify precipitation anomalies caused by urbanization. The approach is particularly useful for investigating this global process because TRMM data span large portions of the globe and comprise an extended temporal dataset. Recent literature suggests that urbanized regions of Houston, Texas may be influencing lightning and precipitation formation over and downwind of the city. Possible mechanisms include: (1) enhanced convergence through interactions between the sea breeze, Galveston bay breeze, and urban heat island circulations, (2) enhanced convergence due to increased surface roughness over the city and/or destabilization of the boundary layer by the UHI, or (3) enhanced cloud condensation nuclei due to urban and industrial aerosol sources. In this study, a downscaling analysis of spatial and temporal trends in rainfall around the Houston Area is being conducted. The downscaling analysis concept involves identifying and quantifying urban rainfall anomalies at progressively smaller spatial and temporal scales using the TRMM satellite, ground-based radar, and a dense network of rain gauges. The goal is to test the hypothesis that the Houston urban district and regions in the climatological downwind region of the city exhibit enhanced rainfall amounts relative to the climatological upwind regions. TRMM was launched in 1997 and currently operates in a low-inclination (35 deg), non-sun-synchronous orbit at an altitude of 402 km (350 km prior to August 2001). The satellite analysis follows the methodologies described in Shepherd et al. (2002). Nearly five years of TRMM PR-derived mean monthly rainfall estimates are utilized to produce annual and warm season isohyetal analyses around Houston. Early results indicate that rainfall rates (mm/h) for the entire period are largest within 100 km northeast and east of Houston (e.g. the "hypothesized downwind region"). The mean rainfall rate over the Houston urban center is 30.5% larger than the upwind control region. The mean rainfall rate in the downwind region is 34.4% larger than the upwind region. An analysis of a parameter called the urban rainfall ratio (URR) illustrates that 65% (88%) of the satellite-derived rainfall rates in the downwind (upwind control) region are greater (less) than the mean background rainfall rate of the entire study region. When the data is stratified by summer months from 1998 to 2001 (June-August), even greater influence over and downwind of the urban area is observed in the statistics. This result is consistent with published reports of urban-generated rainfall being more prevalent in the warm season. The research demonstrates that the evolving TRMM satellite climatology is a credible way to detect mesoscale precipitation signatures that may be linked to urbanization. Early results also corroborate recent findings on Houston-induced convection/drainfall anomalies. Burian and Shepherd will report on other aspects of the downscaling analysis in future forums, but early rain gauge results are consistent with the satellite-based observations.

Shepherd, J. Marshall↗
DOE OSTI2024

Use of Satellite, Surface Observations and Numerical Weather Prediction Model Data to Improve Cloud Base Height and Cloud Base Vertical Velocity Estimation

Cloud base height (CBH) and cloud base vertical velocity (CBVV) are important variables that impact the overall climate in a region as they influence the formulation, longevity, and evolution of clouds. Retrieval of both parameters have long used ground instrumentation (e.g., Doppler lidar (DL), ground base radar); however, retrieving CBH from satellites is particularly challenging given that space-based instruments only observe cloud tops. In this manuscript, CBH is retrieved using a multi-linear regression equation, while CBVV used a random forests model. Both retrievals combine satellite and numerical weather prediction data. The satellite data used are the Visible Infrared Imaging Radiometer Suite imagery, while measurements of CBH and CBVV include DL and radiosonde data at the Southern Great Plains (SGP) Atmospheric Radiation Measurement observatory. Data from 83 summer days (May-August) in 2018–2021 featuring cumulus clouds forced by solar heating were examined and used to train the models, with years 2022–2023 used for validation. Various spatial domains were defined with one large (2.4° longitude by 2.0° latitude) SGP domain being split into smaller sections (smallest being 0.99° and 0.61° longitude and latitude respectably). CBH and CBVV values obtained from the DL as compared to the models show root mean square errors between 150 and 200 m, with CBVV values between 0.45 and 1 ms -1 . Finally, it was found that the CBH formulation performs well over all domains, while the CBVV retrievals become less accurate due to more turbulence being introduced into the observations as the number of DL stations decreases in the smaller domains.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Shallow cloud variability in Houston, Texas, during the ESCAPE and TRACER field experiments

Shallow convection plays an important role in Earth's climate system by regulating the vertical transport of heat, moisture, and momentum in the lower troposphere. Aerosols, large-scale meteorology, and low-level convergence influence the spatiotemporal variability in shallow convection, and the coastal urban area of Houston, Texas, is an ideal laboratory to investigate these complex interactions. Here, geostationary satellite and ground-based radar observations from June to September 2022 during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) field campaigns are used to characterize the spatial coverage, vertical extent, and precipitation fraction of shallow convective clouds. The fused operational remote sensing datasets over a 250 km × 250 km domain are evaluated against profiling observations. The domain-wide diurnal shallow cloud fractions are used to identify four distinct modes of shallow convection. In all clusters, the domain-wide cloud fractions are consistently higher than the domain-wide precipitation fractions, and shallow cloud fractions are higher over water than they are over land, while the shallow precipitation fractions show the opposite behavior. In the two modes with minimal deep cloud activity, shallow cloud frequency is highest over ocean in the early morning, and there is a transition to higher shallow cloud frequency over land by the afternoon in one cluster or to high shallow cloud frequencies everywhere by the afternoon in the other. Lastly, we find regions with higher shallow cloud top heights and a large region along the coastline where shallow clouds are more likely to precipitate.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

A new method for in situ electron temperature determinations from plasma wave phenomena

A discrepancy has been reported between the values of the electron temperature t sub e deduced from satellite electrostatic probe measurements and ground based radar backscatter measurements. This discrepancy (radar backscatter temperature less than the probe temperature) is not present when the probe experiment is flown on a rocket to lower altitudes but reappears when the rocket probe attains higher altitudes. There is a need for an independent radio wave method for making in-situ t sub e measurements in order to help resolve this problem. A new method of determining t sub e from the satellite resonant phenomena is presented. It is based on the splitting (observed at high latitudes) of the diffuse resonance which occurs at the frequency f sub d1 between f sub h and 2 f sub h. The advantage of this method over the other methods involving ionospheric resonances is the simplicity of the required calculations. There is, however, the limitation of plasma conditions where the f sub d1 resonance can be observed and the limitation to mid-to-high latitudes where the splitting is observed.

Oya, H.↗