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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Electrically-Active Convection in Tropical Easterly Waves and Implications for Tropical Cyclogenesis in the Atlantic and East Pacific

In this study, we investigate the characteristics of tropical easterly wave convection and the possible implications of convective structure on tropical cyclogenesis and intensification over the Atlantic Ocean and East Pacific using data from the Tropical Rainfall Measurement Mission Microwave Imager, Precipitation Radar (PR), and Lightning Imaging Sensor as well as infrared (IR) brightness temperature data from the NASA global-merged IR brightness temperature dataset. Easterly waves were partitioned into northerly, southerly, trough, and ridge phases based on the 700-hPa meridional wind from the NCEP-NCAR reanalysis dataset. Waves were subsequently divided according to whether they did or did not develop tropical cyclones (i.e., developing and nondeveloping, respectively), and developing waves were further subdivided according to development location. Finally, composites as a function of wave phase and category were created using the various datasets. Results suggest that the convective characteristics that best distinguish developing from nondeveloping waves vary according to where developing waves spawn tropical cyclones. For waves that developed a cyclone in the Atlantic basin, coverage by IR brightness temperatures .240 K and .210 K provide the best distinction between developing and nondeveloping waves. In contrast, several variables provide a significant distinction between nondeveloping waves and waves that develop cyclones over the East Pacific as these waves near their genesis location including IR threshold coverage, lightning flash rates, and low-level (<4.5 km) PR reflectivity. Results of this study may be used to help develop thresholds to better distinguish developing from nondeveloping waves and serve as another aid for tropical cyclogenesis forecasting.

Leppert, Kenneth D., II↗
NASA NTRS2012

Global Precipitation Measurement (GPM) Safety Inhibit Timeline Tool

The Global Precipitation Measurement (GPM) Observatory is a joint mission under the partnership by National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA), Japan. The NASA Goddard Space Flight Center (GSFC) has the lead management responsibility for NASA on GPM. The GPM program will measure precipitation on a global basis with sufficient quality, Earth coverage, and sampling to improve prediction of the Earth's climate, weather, and specific components of the global water cycle. As part of the development process, NASA built the spacecraft (built in-house at GSFC) and provided one instrument (GPM Microwave Imager (GMI) developed by Ball Aerospace) JAXA provided the launch vehicle (H2-A by MHI) and provided one instrument (Dual-Frequency Precipitation Radar (DPR) developed by NTSpace). Each instrument developer provided a safety assessment which was incorporated into the NASA GPM Safety Hazard Assessment. Inhibit design was reviewed for hazardous subsystems which included the High Gain Antenna System (HGAS) deployment, solar array deployment, transmitter turn on, propulsion system release, GMI deployment, and DPR radar turn on. The safety inhibits for these listed hazards are controlled by software. GPM developed a "pathfinder" approach for reviewing software that controls the electrical inhibits. This is one of the first GSFC in-house programs that extensively used software controls. The GPM safety team developed a methodology to document software safety as part of the standard hazard report. As part of this process a new tool "safety inhibit time line" was created for management of inhibits and their controls during spacecraft buildup and testing during 1& Tat GSFC and at the Range in Japan. In addition to understanding inhibits and controls during 1& T the tool allows the safety analyst to better communicate with others the changes in inhibit states with each phase of hardware and software testing. The tool was very useful for communicating compliance with safety requirements especially when working with a foreign partner.

Dion, Shirley↗
NASA NTRS2011

APR-2 Tropical Cyclone Observations

The Second Generation Airborne Precipitation Radar (APR-2) participated in the Genesis and Rapid Intensification Processes (GRIP) experiment in August and September of 2010, collecting a large volume of data in several tropical systems, including Hurricanes Earl and Karl. Additional measurements of tropical cyclone have been made by APR-2 in experiments prior to GRIP (namely, CAMEX-4, NAMMA, TC4); Table 1 lists all the APR-2 tropical cyclone observations. The APR-2 observations consist of the vertical structure of rain reflectivity at 13.4 and 35.6 GHz, and at both co-polarization and crosspolarization, as well as vertical Doppler measurements and crosswind measurements. APR-2 normally flies on the NASA DC-8 aircraft, as in GRIP, collecting data with a downward looking, cross-track scanning geometry. The scan limits are 25 degrees on either side of the aircraft, resulting in a roughly 10-km swath, depending on the aircraft altitude. Details of the APR-2 observation geometry and performance can be found in Sadowy et al. (2003).The multiparameter nature of the APR-2 measurements makes the collection of tropical cyclone measurements valuable for detailed studies of the processes, microphysics and dynamics of tropical cyclones, as well as weaker systems that are associated with tropical cyclone formation. In this paper, we give a brief overview of how the APR-2 data are processed. We also discuss use of the APR-2 cross-track winds to estimate various quantities of interest in in studies of storm intensification. Finally, we show examples of the standard products and derived information.

radar↗
NASA NTRS2016

Global Precipitation Measurement (GPM) Spacecraft Lithium Ion Battery Micro-Cycling Investigation

The Global Precipitation Measurement (GPM) spacecraft was jointly developed by NASA and JAXA. It is a Low Earth Orbit (LEO) spacecraft launched on February 27, 2014. The power system is a Direct Energy Transfer (DET) system designed to support 1950 watts orbit average power. The batteries use SONY 18650HC cells and consist of three 8s by 84p batteries operated in parallel as a single battery. During instrument integration with the spacecraft, large current transients were observed in the battery. Investigation into the matter traced the cause to the Dual-Frequency Precipitation Radar (DPR) phased array radar which generates cyclical high rate current transients on the spacecraft power bus. The power system electronics interaction with these transients resulted in the current transients in the battery. An accelerated test program was developed to bound the effect, and to assess the impact to the mission.

Lithium Ion Battery Performance↗
NASA NTRS2018

Satellite Observations to Monitor Subarctic Rain-On-Snow Events

Rain-on-snow (ROS) events have been the focus of numerous studies in the past five years. Their characteristics(frequency, extent, and duration) represent a new and relevant climate indicator. However, monitoring ROS occurrences remotely using satellite observations is deemed challenging. The ROS events can be sporadic, of very different intensities, and the outcome of the rain water uncertain (either it freezes in the snow cover or runs off). Using passive and active microwave remote sensing observations, our study proposes new approaches to monitor the occurrence of ROS events.Specifically, we utilize observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), and Global Precipitation Measurements (GPM) Microwave Imager (GMI), and GPM Dual-frequency Precipitation Radar (DPR). We compare our ROS detection against weather stations and recently published algorithms using a different set of microwave frequencies.

Brucker, Ludovic↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13135-DND

Aircraft Icing - Aircraft structures act as ice nuclei in supercooled clouds - ice collects, weight increases, plane falls - Pilots need to know where and when icing can occur - PIREPS are first order: sparse, aircraft dependent, location uncertain - Model analyses and forecasts: freezing levels, cloud expectations - radar => precipitation - All combined in NCAR/FAA/NOAA/NASA program to provide Current Icing Product (CIP) & Forecast Icing product (FIP) analyses to pilots (CONUS) - some inadequacies remain - NWP uncertainties, intensity, altitude of icing, etc. - Operational satellites can add valuable information - indirectly: input of cloud properties to CIP & NWP - directly: determination of icing threat from real time satellite data

William L Smith↗
NASA NTRSDate not supplied

Detecting Hail from Space: Using a Multi-Frequency Passive-Microwave Retrieval to Analyze the Global Climatology and Diurnal Cycle of Severe Hail

Severe hail poses myriad threats to society, causing extensive damage to infrastructure and agriculture. As hail is severe, relatively infrequent, and highly localized, it is difficult to measure in-situ and if left unresolved in models and precipitation retrievals, hail can cause large errors and uncertainties. The difficulty in measuring hail in situ and the inconsistency of surface-based hail reporting drive the motivation to use spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We leverage the scattering signatures of severe hail in spaceborne passive-microwave datasets paired with surface hail reports to construct a multi-frequency hail retrieval using Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We use this retrieval to construct global passive-microwave climatologies of severe hail using the TRMM, GPM, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. We also leverage the sensors in inclined orbits to assess the diurnal variability of severe hail globally and the effect the diurnal cycle has on the detection of hail by sensors in sun-synchronous orbit. The goal is to construct a robust, multi-decade multi-satellite climatology of hail. As part of the NASA Disasters Applied Sciences program, we assess these climatologies against other satellite severe weather datasets and use these climatologies in collaboration with stakeholders and end-users to help them assess risk, and improve the prediction, preparation, and response to severe storms around the world.

Sarah D Bang↗
NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗
NASA NTRSDate not supplied

Detecting Hail from Space: Algorithms, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global climatologies of severe hail using several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the late 1980’s using the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We developed a passive-microwave algorithm that corresponds tightly to radar reflectivity and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗
NASA NTRSDate not supplied

Remote Sensing of Hail from Space: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗
NASA NTRSDate not supplied

Spaceborne Remote Sensing of Hail: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗
NASA NTRSDate not supplied

Diurnal Cycles of Intense Thunderstorms As Seen By Satellites

Spaceborne sensors cannot directly measure aspects of severe weather occurring at ground-level. Tools from Geostationary Earth Orbit (GEO) and Low Earth Orbit (LEO) can be related to storm intensity and likelihood of severe weather. Visible and Infrared (GEO and LEO) measure cloud-top properties and horizontal structure. Some properties have empirical correlations with severe weather occurrence. Precipitation Radar (LEO) measures vertical profile of reflectivity related to particle size and concentration, but attenuates (2.2-cm and shorter wavelengths) well above the surface in intense thunderstorms. Lightning mappers (GEO and LEO) measure lightning flash rates and flash properties, which relate to updraft properties including size and vigor. SAR and optical sensors can detect damage paths on the surface after a storm has passed. (Depends on the vegetation type and maturity.)

Daniel J Cecil↗
DOE OSTI2023

Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP-SAIL)

The Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP) project was conducted to help improve the understanding of precipitation formation in orographically influenced terrain. Special focus is put on the two processes of riming and secondary ice production and their external drivers. Two instruments, a polarimetric W-band simultaneous transmission simultaneous reception (STSR) Doppler cloud radar manufactured by Radiometer Physics GmbH (RPG, instrument type RPG-FMCW-94-DP), from now on named LIMRAD94, and the video in situ snowfall sensor (VISSS), were deployed at the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) site in Gothic, Colorado between November 2022 and June 2023 during the second SAIL winter. Note that the exact dates of data availability differ between the instruments. Both instruments arrived at Gothic on November 2, 2022, 09:20 local time. VISSS, described by Maahn et al., is equipped with two camera systems with telecentric lenses. The two cameras are at a 90° angle to each other. This configuration allows for size-independent measurements by capturing images of hydrometeors from two sides at a high frame rate of 250 Hz. With a minimum detection size of 200 μm, VISSS provides valuable insights into particle size, number, shape, complexity, and fall velocity. The VISSS was deployed on the grassland next to the ARM facility with the amazing help of the ARM employees on site. The setup started on November 2, 2022, and was finished on November 5, 2022, without major problems. VISSS measurements were started on November 6, 2022. LIMRAD94 was installed on a scaffolding platform near Orehouse (Gothic) on November 9, 2022, with the great help of RMBL staff. LIMRAD94 was mounted on a cold temperature scanner prototype. After a short test of the setup on November 9, 2022, the digital control of the scanner elevation stopped working for (at that time) unknown reasons. All attempts to resolve the problem failed. This malfunction made it impossible to operate LIMRAD94 in scanning mode. The scanner was then manually moved to zenith pointing mode and between November 10 and November 15, 2022, vertical observations for polarimetric calibration were performed. On November 15, 2022, after the polarimetric calibration was applied, the scanner was manually moved to 40° elevation with azimuthal view towards the Ka-band ARM Zenith Radar (KAZR) and measurements were continued at constant elevation. Investigation of the scanner malfunction on February 6, 2023, by Benn Schmatz revealed a disengagement between the cogwheel of the elevation motor and the cogwheel moving the scanner in elevation. This mechanical issue was temporarily solved by re-engaging the cogwheels. This made the scanner operational again for about four weeks, until mechanical force disengaged the cogwheels again on March 15, 2023. This repeated scanner failure remained undetected for about three weeks until April 8, 2023; during this time the scanner was stuck at 72° elevation. However, the radar software continued to produce data files falsely indicating that the scanner was still operational. After the scanner failure was noticed, scanning was stopped again, and we returned to constant elevation measurements. On May 15, 2023, the cogwheels of the elevation motor were secured with additional screws sent by the manufacturer. At some point in May, the cogwheels of the azimuth motor were also disengaged by mechanical force, which still allowed for range height indicator (RHI) but no plan position indicator (PPI) scans in the last weeks of the campaign. The azimuth motor was repaired in Germany after the end of the campaign. Throughout the campaign, RMBL and ARM staff kept the radar and the VISSS free of snow.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Radar observations of precipitation growth and evolution within the anvil region of a MCS

Doppler radar observations of the growth and evolution of precipitation (reflectivity factor) and associated mesoscale motions within the anvil region of an evolving mesoscale convective system (MCS) are presented. This MCS was observed during the Cooperative Huntsville Meteorological Experiment conducted over northern Alabama and central Tennessee during June and July, 1986. During the latter stages of the approximate eight-hour lifetime of this MCS, an extensive region of stratiform precipitation was observed. Attention is given to the initial appearance and subsequent evolution of precipitation within the stratiform region of the MCS, and the relation to the mesoscale flows that are seen within the system.

Knupp, Kevin R.↗
DOE OSTI2020

Mind the gap – Part 1: Accurately locating warm marine boundary layer clouds and precipitation using spaceborne radars

Abstract. Ground-based radar observations show that, over the eastern North Atlantic, 50 % of warm marine boundary layer (WMBL) hydrometeors occur below 1.2 km and have reflectivities of <-17 dBZ, thus making their detection from space susceptible to the extent of surface clutter and radar sensitivity. Surface clutter limits the ability of the CloudSat cloud profiling radar (CPR) to observe the true cloud base in ~52 % of the cloudy columns it detects and true virga base in ~80 %, meaning the CloudSat CPR often provides an incomplete view of even the clouds it does detect. Using forward simulations, we determine that a 250 m resolution radar would most accurately capture the boundaries of WMBL clouds and precipitation; that being said, because of sensitivity limitations, such a radar would suffer from cloud cover biases similar to those of the CloudSat CPR. Observations and forward simulations indicate that the CloudSat CPR fails to detect 29 %–43 % of the cloudy columns detected by ground-based sensors. Out of all configurations tested, the 7 dB more sensitive EarthCARE CPR performs best (only missing 9.0 % of cloudy columns) indicating that improving radar sensitivity is more important than decreasing the vertical extent of surface clutter for measuring cloud cover. However, because 50 % of WMBL systems are thinner than 400 m, they tend to be artificially stretched by long sensitive radar pulses, hence the EarthCARE CPR overestimation of cloud top height and hydrometeor fraction. Thus, it is recommended that the next generation of space-borne radars targeting WMBL science should operate interlaced pulse modes including both a highly sensitive long-pulse mode and a less sensitive but clutter-limiting short-pulse mode.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal components and the brightness temperature principal components of the classes. Because the classes are stratified by the sea surface temperature and the echo-top-height estimator, the number of classes that are considered for retrieval is significantly smaller than the total number of classes, making the algorithm computationally efficient. The radiometer-only algorithm is applied to TMI observations, and precipitation estimates are compared with combined TRMM precipitation radar (PR) TMI reference estimates. The TMI-only algorithm, supported by the empirically derived database, produces estimates that are more consistent with the reference values than the precipitation estimates from the version-6 TRMM facility TMI algorithm. Cloud-resolving model simulations are used to assign a latent heating profile to each precipitation profile in the empirically derived database, making it possible to estimate latent heating using the radiometer-only algorithm. Although the evaluation of latent heating estimates in this study is preliminary, because realistic conditional probability distribution functions are attached to latent heating structures in the algorithm s database, a generally positive impact on latent heating estimation from passive microwave observations is expected.

Grecu, Mircea↗
NASA NTRS1985

Airborne Doppler radar velocity measurements of precipitation seen in ocean surface reflection

The use of airborne or spaceborne radars to observe precipitation simultaneously directly and in reflection could provide significant new opportunities for measuring the properties of the precipitation, wind field, and ocean surface. Atlas and Meneghini (1983) have proposed that the difference between direct and reflected precipitation echo intensities observed with a nadir-directed beam is a measure of two-way attenuation and thus of path average rain rate, taking into account an employment of direct and reflected echoes from very near the ocean surface to normalize for ocean surface scatter. In the present paper, some key meteorological and oceanographic research applications are illustrated, giving particular attention to airborne Doppler radar velocity measurements of the precipitation.

Atlas, D.↗
NASA NTRS2019

A Radar Investigation of Precipitation Properties During Discrepancies Between GOES-16 GLM and LMA Observed Flash Rates in the Skyline Alabama Supercell of 22 April 2017

Conclusions: GLM (Geostationary Lightning Mapper) flash rates were 2 to 5 times lower than LMA (Lightning Mapping Array) in an Alabama supercell that was tracked using a combination of GLM flash initiation density and VIL (Vertically Integrated Liquid); Since most lightning was initiating at 8-9 kilometers (and not at low levels) according to LMA, flash height does not appear to be a primary factor in low GLM flash rates; When (LMA-GLM) flash rate differences were largest, the LMA observed flash areas were relatively small (and vice versa); Flash size may be a primary factor in low GLM flash rates due to detectability and/or flash clustering issues with small flashes within the coarse 8 kilometers by 8 kilometers resolution; High cloud liquid water droplet concentrations were inferred indirectly from riming necessary for large radar MESH (Maximum Expected Size of Hail), VIL and hail/graupel volumes. High cloud water droplet concentrations in supercells may decrease GLM detection efficiency due to optical extinction of near IR (near Infrared) emitted by lightning as it moves through cloud; Despite large flash rate differences, GLM & LMA lightning jumps during robust supercell generally agreed with each other and radar trends in HID (Radar Reflectivity and Hydrometeor Identification), MESH and VIL.However, more LMA jumps (than GLM) in developing supercell and more GLM jumps (than LMA) in weak to decaying supercell. Future work: improve GLM tracking.

GLM↗