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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 307 records · Page 17
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NASA NTRSDate not supplied

Spaceborne Passive-Microwave and Visible/IR Observations of Severe Weather: Leveraging Multiple Perspectives for Detection, Validation, and Climatologies

Severe weather phenomena not only are responsible for damages to property, infrastructure, and agriculture, they are also difficult to measure in-situ and have been associated with large errors and uncertainties in precipitation estimation that pose challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Severe convection exhibits distinct signatures in remote-sensing datasets, where it is manifested as textured or overshooting cloud tops in visible/IR imagery, or resulting a prominent brightness temperature depression in passive-microwave imagery. These distinct deep convective signatures in spaceborne datasets have been leveraged to analyze severe thunderstorms, create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data may be inconsistent or unavailable. Visible/IR and passive-microwave instruments are powerful tools for detecting severe thunderstorms, however, these datasets exhibit key limitations when examined individually: passive-microwave channels have large footprint and exhibit non-uniform beam filling. The visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. We investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair passive microwave, IR, and visible signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis to characterize potentially severe convective storms observed by Aqua MODIS and AMSR-E. We will discuss how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically.

Sarah D. Bang↗
NASA NTRSDate not supplied

Oceanic Validation of IMERG Version 7 with the GPM Validation Network

- To validate Version 7 of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) over tropical and high-latitude oceans using the GPM Validation Network (VN). - To trace errors from the Level-3 IMERG V07 product back through to the input Level-2 Goddard Profiling Algorithm (GPROF) V07 product for the GPM Microwave Imager (GMI).

GPM↗
NASA NTRSDate not supplied

A Census of Severe Weather as Observed From Aqua: Visible/IR and Passive-Microwave Perspectives of Severe Convection

Severe weather phenomena represent the extreme upper end of the spectrum of convection and precipitation and tend to be highly localized and relatively rare compared to the rest of the distribution, but they can cause damage and loss disproportionate to their scale and frequency. Fortunately, severe convection exhibits distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Leveraging these signatures individually has become a long-established practice to detect, analyze and establish climatologies of severe thunderstorms, especially in instances where traditional ground-based data may be unavailable. Spaceborne visible/IR and passive-microwave approaches are not without their pitfalls, however: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis in six different geographical regimes throughout the Aqua domain. We present a census of potentially severe convective storms and their environments as seen by multiple instruments simultaneously, investigating how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically. Using statistical machine learning analysis, we aim to quantify the optimal MODIS and AMSR-E parameter sets for discriminating severe from non-severe storm cells and assess what improvement (if any) in detection results from combining the IR, visible, and microwave datasets.

Sarah Bang↗
NASA NTRS2024

Classifying Microwave Radiometer Observations Over the Netherlands Into Dry, Shallow-, and Non-Shallow Precipitation Using A Random Forest Model

Spaceborne microwave radiometers represent an important component of the Global Precipitation Measurement (GPM) mission due to their frequent sampling of rain systems. Microwave radiometers measure microwave radiation (brightness temperatures, Tb), which can be converted into precipitation estimates with appropriate assumptions. However, detecting shallow precipitation systems using space-borne radiometers is challenging, especially over land, as their weak signals are hard to differentiate from those associated with dry conditions. This study uses a random forest model (RF) to classify microwave radiometer observations as dry, shallow, or nonshallow over the Netherlands - a region with varying surface conditions and frequent occurrence of shallow precipitation. The RF is trained on five years of data (2016-2020) and tested with two independent years (2015, 2021). The observations are classified using ground-based weather radar echo top heights. Various RF models are assessed, such as using only GPM’s Microwave Imager (GMI) Tb values as input features or including spatially aligned ERA-5 2-meter temperature and freezing level reanalysis and/or Dual Precipitation Radar (DPR) observations. Independent of the input features, the model performs best in summer and worst in winter. The model classifies observations from high-frequency channels (≥85 GHz) with lower Tb-values as non-shallow, higher values as dry, and those in between as shallow. Misclassified footprints exhibit radiometric characteristics corresponding to their assigned class. Case studies reveal dry observations misclassified as shallow are associated with lower Tb-values, likely resulting from the presence of ice particles in non-precipitating clouds. Shallow footprints misclassified as dry are likely related to the absence of ice particles.

Linda Bogerd↗
NASA NTRSDate not supplied

A Long-Term GOES Satellite Overshooting Cloud Top and Anvil Cloud Climatology Over South America

The modern-era GOES satellite series began in 1994 with the GOES-8 satellite, and was augmented in 2018 with higher spatial resolution and more frequent imaging when GOES-16 became operational. GOES imagery has provided forecasters and researchers new perspectives into cloud top patterns associated with severe convection, and the ability to better forecast convection in regions without adequate ground-based weather radar coverage. While much attention has been given to convection over North America, convection over South America can be equally, if not more, intense and frequent. Recent studies have demonstrated that overshooting cloud tops (OT) and surrounding anvil clouds can be detected within infrared satellite imagery. Relative storm updraft intensity metrics such as the tropopause-relative infrared brightness temperature, the prominence of an OT relative to its surrounding anvil, and cloud top height can also be derived using automated methods combined with reanalysis data. These automated OT detection and intensity estimation methods have recently been applied to all GOES images collected over South America, in combination with the MERRA-2 reanalysis, from 1995 to 2022 at NASA Langley within a project supported by the NASA Applied Sciences Disasters program. Innovative aggregation methods have merged these products into daily, monthly, annual, and multi-annual composites, with hourly time bins, at ~4 km pixel spacing to enable researchers a new opportunity to study South American convective processes throughout the diurnal cycle. These products have recently become publicly available from NASA. This presentation will overview this new dataset, and novel insights into South American convection depicted by the data.

Kristopher Bedka↗
NASA NTRSDate not supplied

Challenges in Remote-Sensing of Hail: Examining the Performance and Biases of Satellite Hail Retrievals Using Aqua MODIS Visible/IR and AMSR-E Passive-Microwave Observations

Hail poses threats to myriad aspects of human life and society, infrastructure, and agriculture. Scientifically, hail can often cause large errors in precipitation retrieval and estimation, posing challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Fortunately, hailstorms exhibit distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Approaches that leverage these signatures, however, are not without their pitfalls,: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. Large horizontal areas of smaller scatterers may also meaningfully lower the brightness temperatures, especially if they are able to occupy large portions of the footprint. Radiative transfer simulations show that low frequencies such as 19- and 37-GHz can be scattered to extremely low brightness temperatures by high concentrations of smaller (graupel-sized) ice scatterers, especially in larger features that are more likely to occupy the footprint, which may cause climatologies to overestimate the frequency severe hail. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together, pairing AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis over CONUS, and then explore the performance and challenges of the algorithm when we expand outside the United States into six different geographical regimes throughout the Aqua domain.

Sarah D Bang↗
NASA NTRS2003

Enhanced Weather Radar (EWxR) System

An airborne weather radar system, the Enhanced Weather Radar (EWxR), with enhanced on-board weather radar data processing was developed and tested. The system features additional weather data that is uplinked from ground-based sources, specialized data processing, and limited automatic radar control to search for hazardous weather. National Weather Service (NWS) ground-based Next Generation Radar (NEXRAD) information is used by the EWxR system to augment the on-board weather radar information. The system will simultaneously display NEXRAD and on-board weather radar information in a split-view format. The on-board weather radar includes an automated or hands-free storm-finding feature that optimizes the radar returns by automatically adjusting the tilt and range settings for the current altitude above the terrain and searches for storm cells near the atmospheric 0-degree isotherm. A rule-based decision aid was developed to automatically characterize cells as hazardous, possibly-hazardous, or non-hazardous based upon attributes of that cell. Cell attributes are determined based on data from the on-board radar and from ground-based radars. A flight path impact prediction algorithm was developed to help pilots to avoid hazardous weather along their flight plan and their mission. During development the system was tested on the NASA B757 aircraft and final tests were conducted on the Rockwell Collins Sabreliner.

Kronfeld, Kevin M.↗
NASA NTRS1999

Intercomparison of Various Algorithms in Determining Convective and Stratiform Precipitation

The paper presents the intercomparison of various algorithms in determining the convective and stratiform precipitation in tropical convection. The latent heat released from precipitation is the driving mechanism for the general circulation of the atmosphere and exhibits different vertical profile in convective and stratiform regimes of the tropical convection. The primary goal of this paper is to evaluate the performance of the operational convective/stratiform algorithm that is employed by the NASA Tropical Rainfall Measuring Mission (TRMM) ground validation program. The operational algorithm is based on the texture of radar reflectivity field at constant altitude. The TRMM ground validation program continuously monitors the tropical convection through ground based radar and rain gauge network at selected sites around the tropics and generates the rainfall products including the convective/stratiform rainfall map that can readily be used by the TRMM satellite program. An evaluation and improvement of these rainfall products requires additional measurements that can be available through field campaigns. The data used in this study was collected during the second phase of the Texas Florida Underflights (TEFLUN-B) field campaign in East Central Florida, a primary site of the TRMM ground validation program. The TEFLUN-B field campaign was conducted in August and September 1998 in support of the NASA Tropical Rainfall Measuring Mission (TRMM) satellite observations. An objective of the TEFLUN-B field campaign was to obtain the ground based precipitation measurements of Florida convection at different temporal and spatial scales. The field campaign had various components of precipitation measurements including dual wavelength precipitation profiler, various types of disdrometers and rain gauges, collocated about 40 km southwest of Melbourne NEXRAD radar. In this study, we examine the profiler based reflectivity and Doppler velocity and the disdrometer based drop size distribution observations to evaluate the operational scanning radar (i.e. NEXRAD) based convective/stratiform algorithm.

Tokay, Ali↗
NASA NTRS1985

Radar wind profilers

Continuous, automated measurement of tropospheric wind profiles with UHF and VHF Doppler radars has been demonstrated. Ground-based networks of these radars will be available as part of a global wind measurement system, and remote single stations could be built to further complement a spaceborne measurement device. A number of ground-based wind profilers will be in place by the time a space system is tested so the global wind measurement system should be designed with these ground-based profilers providing part of the picture.

Strauch, R. G.↗
NASA NTRS2023

High-Resolution Snowstorm Measurements and Retrievals Using Cross-Platform Multi-Frequency and Polarimetric Radars

Many studies have provided microphysical retrievals using radars of different frequencies, platforms, and methodologies. However, little is known about the consistency of retrievals derived from different radar platforms (i.e., airborne or spaceborne vs. groundbased) and their methodologies. This study is the first to directly compare snow mean volume diameter (Dm) retrievals from both nadir-pointing airborne multi-frequency radars and ground-based polarimetric range-height indicator (RHI) radar scans along a coincident airborne flight track. Compared to typical airborne/spaceborne/ground validation studies which at best provide O(1 km) resolution, these two platforms together provide directly collocated, high-resolution O(10m) retrievals. Dm retrieval values were over all both largest and smallest when using two separate dual-wavelength methods from aircraft measurements. A Triple-frequency analysis suggests the possibility that snow aggregates were generally composed of needles. The results shown here can be used as a benchmark for comparing retrieval methodologies.

Edwin L. Dunnavan↗
NASA NTRS1971

Remote detection of turbulence in clear air.

Various concepts for remote detection of turbulence in the clear air are reviewed. It is concluded that there is at present no technique available for operational use to remotely detect and measure turbulence in the clear air. Several techniques with good potentials for future application currently being studied include a laser Doppler radar method for airborne and ground-based use and an approach utilizing ground-based ultrasensitive microwave Doppler radars.

Mcgowan, W. A.↗