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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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NASA NTRS2003

AstroBioLab: A Mobile Biotic and Soil Analysis Laboratory

The Jet Propulsion Laboratory, Scripps Institution of Oceanography, and NASA Ames Research Center are currently developing a mobile Astrobiology Laboratory (AstroBioLab) for a series of field campaigns using the Chilean Atacama Desert as a Martian surface analog site. The Astrobiology Science and Technology for Exploring Planets (ASTEP) program funded AstroBioLab is designed around the Mars Organic Detector (MOD) instrument and the Mars Oxidant Instrument (MOI) which provide complementary data sets. Using this suite of Mars Instrument Development Program (MIDP) and Planetary Instrument Definition and Development Program (PIDDP) derived in situ instruments, which provide state-of-the-art organic compound detection (attomolar sensitivity) and depth profiling of oxidation chemistry, we measure and correlate the interplay of organic compounds, inorganic oxidants, UV irradiation and water abundance. This mobile laboratory studies the proposition that intense UV irradiation coupled with low levels of liquid water generates metastable oxidizing species that can consume moderate amounts of seeded organic compounds. Results from the initial spring 2003 field campaign will be presented.

J L Bada↗
NASA NTRS2014

High-Speed On-Board Data Processing for Science Instruments

A new development of on-board data processing platform has been in progress at NASA Langley Research Center since April, 2012, and the overall review of such work is presented in this paper. The project is called High-Speed On-Board Data Processing for Science Instruments (HOPS) and focuses on a high-speed scalable data processing platform for three particular National Research Council's Decadal Survey missions such as Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS), Aerosol-Cloud-Ecosystems (ACE), and Doppler Aerosol Wind Lidar (DAWN) 3-D Winds. HOPS utilizes advanced general purpose computing with Field Programmable Gate Array (FPGA) based algorithm implementation techniques. The significance of HOPS is to enable high speed on-board data processing for current and future science missions with its reconfigurable and scalable data processing platform. A single HOPS processing board is expected to provide approximately 66 times faster data processing speed for ASCENDS, more than 70% reduction in both power and weight, and about two orders of cost reduction compared to the state-of-the-art (SOA) on-board data processing system. Such benchmark predictions are based on the data when HOPS was originally proposed in August, 2011. The details of these improvement measures are also presented. The two facets of HOPS development are identifying the most computationally intensive algorithm segments of each mission and implementing them in a FPGA-based data processing board. A general introduction of such facets is also the purpose of this paper.

Beyon, Jeffrey Y.↗
NASA NTRSDate not supplied

Overview of Lightning Science at NASA Marshall Space Flight Center

NASA Marshall Space Flight Center (MSFC) is a recognized world leader in the science of lightning. To date, MSFC has led three space-based global lightning observing missions and has helped lead multiple suborbital field campaigns involving lightning observations. Recently, the MSFC Lightning Team is closing out the recently completed International Space Station Lightning Imaging Sensor (ISS LIS) mission, including developing a nearly three-decade global climatology of lightning from space. This work also includes integrating lightning observations with data from NASA precipitation missions. The Team is also busy analyzing data from a recent airborne field campaign that observed dozens of terrestrial gamma-ray flashes (TGFs) from intense tropical thunderstorms. Lightning Team members are also leaders in validation of the Geostationary Lightning Mapper (GLM) operated by NOAA, and in developing lightning safety applications and studying the relationship between lightning and wildfires. The Lightning Team also studies chemical production by lightning and contributes to the National Climate Assessment (NCA). Finally, the Lightning Team is busy developing the next generation of spaceborne lightning sensors to broaden our understanding of the relationships between lightning, weather, climate, and atmospheric composition.

Timothy Lang↗
NASA NTRS1992

Science applications of the Mars Observer gamma ray spectrometer

The Mars Observer gamma ray spectrometer will return data related to the elemental composition of Mars. The instrument has both a gamma ray spectrometer and several neutron detectors. The gamma ray spectrometer will return a spectrum nominally every 20 s from Mars permitting a map of the elemental abundances to be made. The gamma rays are emitted from nuclei involved in radioactive decay, from nuclei formed by capture of a thermal neutron, and from nuclei put in an excited state by a fast-neutron interaction. The gamma rays come from an average depth of the order of a few tens of centimeters. The spectrum will show sharp emission lines whose intensity determines the concentration of the element and whose energy identifies the element. The neutron detectors, using the fact that the orbital velocity of the Mars Observer spacecraft is similar to the velocity of thermal neutrons, determine both the thermal and epithermal neutron flux. By combining the results from both techniques it is possible to map the depth dependence of hydrogen in the upper meter as well. These data permit a variety of Martian geoscience problems to be addressed including the crust and mantle composition, weathering processes, volcanism, and the volatile reservoirs and processes.

Boynton, W. V.↗
NASA NTRS2016

An Efficient Ray-Tracing Method for Determining Terrain Intercepts in EDL Simulations

The calculation of a ray's intercept from an arbitrary point in space to a prescribed surface is a common task in computer simulations. The arbitrary point often represents an object that is moving according to the simulation, while the prescribed surface is fixed in a defined frame. For detailed simulations, this surface becomes complex, taking the form of real-world objects such as mountains, craters or valleys which require more advanced methods to accurately calculate a ray's intercept location. Incorporation of these complex surfaces has commonly been implemented in graphics systems that utilize highly optimized graphics processing units to analyze such features. This paper proposes a simplified method that does not require computationally intensive graphics solutions, but rather an optimized ray-tracing method for an assumed terrain dataset. This approach was developed for the Mars Science Laboratory mission which landed on the complex terrain of Gale Crater. First, this paper begins with a discussion of the simulation used to implement the model and the applicability of finding surface intercepts with respect to atmosphere modeling, altitude determination, radar modeling, and contact forces influencing vehicle dynamics. Next, the derivation and assumptions of the intercept finding method are presented. Key assumptions are noted making the routines specific to only certain types of surface data sets that are equidistantly spaced in longitude and latitude. The derivation of the method relies on ray-tracing, requiring discussion on the formulation of the ray with respect to the terrain datasets. Further discussion includes techniques for ray initialization in order to optimize the intercept search. Then, the model implementation for various new applications in the simulation are demonstrated. Finally, a validation of the accuracy is presented along with the corresponding data sets used in the validation. A performance summary of the method will be shown using the analysis from the Mars Science Laboratory's terminal descent sensing model. Alternate uses will also be shown for determining horizon maps and orbiter set times.

Shidner, Jeremy D.↗
NASA NTRSDate not supplied

EXCLAIM: The EXperiment for Cryogenic Large-Aperture Intensity Mapping

The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) will constrain star formation over cosmic time by carrying out a blind and complete census of redshifted carbon monoxide (CO) and ionized carbon ([CII]) emission in cross-correlation with galaxy survey data in redshift windows from the present to z=3.5 with a fully cryogenic, balloon-borne telescope. EXCLAIM will carry out extragalactic and Galactic surveys in a conventional balloon flight planned for 2023. EXCLAIM will be the first instrument to deploy µ-Spec silicon integrated spectrometers with a spectral resolving power R=512 covering 420-540 GHz. We summarize the design, science goals, and status of EXCLAIM.

Thomas Essinger-Hileman↗
NASA NTRS2011

The Primordial Inflation Explorer (PIXIE): A Nulling Polarimeter for Cosmic Microwave Background Observations

The Primordial Inflation Explorer (PIXIE) is a concept for an Explorer-class mission to measure the gravity-wave signature of primordial inflation through its distinctive imprint on the linear polarization of the cosmic microwave background. The instrument consists of a polarizing Michelson interferometer configured as a nulling polarimeter to measure the difference spectrum between orthogonal linear polarizations from two co-aligned beams. Either input can view the sky or a temperature-controlled absolute reference blackbody calibrator. Rhe proposed instrument can map the absolute intensity and linear polarization (Stokes I, Q, and U parameters) over the full sky in 400 spectral channels spanning 2.5 decades in frequency from 30 GHz to 6 THz (1 cm to 50 micron wavelength). Multi-moded optics provide background-limited sensitivity using only 4 detectors, while the highly symmetric design and multiple signal modulations provide robust rejection of potential systematic errors. The principal science goal is the detection and characterization of linear polarization from an inflationary epoch in the early universe, with tensor-to-scalar ratio r < 10..3 at 5 standard deviations. The rich PIXIE data set can also constrain physical processes ranging from Big Bang cosmology to the nature of the first stars to physical conditions within the interstellar medium of the Galaxy.

Kogut, Alan J.↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2000

Ion Mass Spectrometer for Sporadic-E Rocket Experiments

NASA grant NAG5-5086 provided funding for the William B. Hanson Center for Space Sciences at the University of Texas at Dallas (UTD) to design, fabricate, calibrate, and ultimately fly two ion mass spectrometer instruments on a pair of sounding rocket payloads. Drs. R.A. Heelis and G.D. Earle from UTD were co-investigators on the project. The principal investigator for both rocket experiments was Dr. Robert Pfaff of the Goddard Space Flight Center. The overall project title was "Rocket/Radar Investigation of Lower Ionospheric Electrodynamics Associated with Intense Mid-Latitude Sporadic-E Layers". This report describes the overall objectives of the project, summarizes the instrument design and flight experiment details, and presents representative data obtained during the flights.

Heelis, R. A.↗
NASA NTRS1996

The fragmentation of 510 MeV/nucleon iron-56 in polyethylene. I. Fragment fluence spectra

The fragmentation of 510 MeV/nucleon iron ions in several thicknesses of polyethylene has been measured. Non-interacting primary beam particles and fragments have been identified and their LETs calculated by measuring ionization energy loss in a stack of silicon detectors. Fluences, normalized to the incident beam intensity and corrected for detector effects, are presented for each fragment charge and target. Histograms of fluence as a function of LET are also presented. Some implications of these data for measurements of the biological effects of heavy ions are discussed.

NASA Center HQS↗
NASA NTRS1984

New Zealand SIR-B science investigations

It is proposed that shuttle imaging radar (SIR) data be used to study unusual geological features of New Zealand. Particular attention is planned for geological faults. SIR-B imagery is to be compared with LANDSAT multispectral imagery. Three other investigations which are to use SIR data are discussed. An ocean eddy is to be studied from a correlation of SIR-B and advanced very high resolution radiometer imagery. Timber volume is to be assessed by determining the age and size of pine forests from SIR-B data. Soil moisture is to be investigated by comparing SIR-B data with simultaneous gravimetric data. Land cover in a region already subjected to intensive investigation using LANDSAT and aircraft scanner data is to be discriminated by SIR-B data.

Collins, M. A.↗
NASA NTRS2015

The Two-Column Aerosol Project: Phase I - Overview and Impact of Elevated Aerosol Layers on Aerosol Optical Depth

The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study designed to provide a comprehensive data set that can be used to investigate a number of important climate science questions, including those related to aerosol mixing state and aerosol radiative forcing. The study was designed to sample the atmosphere be tween and within two atmospheric columns; one fixed near the coast of North America (over Cape Cod, MA) and a second moveable column over the Atlantic Ocean several hundred kilometers from the coast. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was deployed at the base of the Cape Cod column, and the ARM Aerial Facility was utilized for the summer and winter intensive observation periods. One important finding from TCAP is that four of six nearly cloud-free flight days had aerosol layers aloft in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA high-spectral resolution lidar (HSRL-2).These layer s contributed up to 60 of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. In addition, while there was a great deal of spatial and day-to-day variability in the aerosol chemical composition and optical properties, no systematic differences between the two columns were observed.

aerosols↗
NASA NTRS2001

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Ichoku, Charles↗
NASA NTRS2016

Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications

Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.

Stefanov, William L.↗
NASA NTRS2005

Generating Mosaics of Astronomical Images

"Montage" is the name of a service of the National Virtual Observatory (NVO), and of software being developed to implement the service via the World Wide Web. Montage generates science-grade custom mosaics of astronomical images on demand from input files that comply with the Flexible Image Transport System (FITS) standard and contain image data registered on projections that comply with the World Coordinate System (WCS) standards. "Science-grade" in this context signifies that terrestrial and instrumental features are removed from images in a way that can be described quantitatively. "Custom" refers to user-specified parameters of projection, coordinates, size, rotation, and spatial sampling. The greatest value of Montage is expected to lie in its ability to analyze images at multiple wavelengths, delivering them on a common projection, coordinate system, and spatial sampling, and thereby enabling further analysis as though they were part of a single, multi-wavelength image. Montage will be deployed as a computation-intensive service through existing astronomy portals and other Web sites. It will be integrated into the emerging NVO architecture and will be executed on the TeraGrid. The Montage software will also be portable and publicly available.

Bergou, Attila↗
NASA NTRS2016

Evaluation of the Validated Soil Moisture Product from the SMAP Radiometer

NASA's Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAP's radiometer-derived soil moisture product (L2_SM_P) provides soil moisture estimates posted on a 36 km fixed Earth grid using brightness temperature observations from descending (6 am) passes and ancillary data. A beta quality version of L2_SM_P was released to the public in September, 2015, with the fully validated L2_SM_P soil moisture data expected to be released in May, 2016. Additional improvements (including optimization of retrieval algorithm parameters and upscaling approaches) and methodology expansions (including increasing the number of core sites, model-based intercomparisons, and results from several intensive field campaigns) are anticipated in moving from accuracy assessment of the beta quality data to an evaluation of the fully validated L2_SM_P data product.

Ocean Salinity↗
NASA NTRS2013

NASA's Genesis and Rapid Intensification Processes (GRIP) Field Experiment

In August–September 2010, NASA, NOAA, and the National Science Foundation (NSF) conducted separate but closely coordinated hurricane field campaigns, bringing to bear a combined seven aircraft with both new and mature observing technologies. NASA's Genesis and Rapid Intensification Processes (GRIP) experiment, the subject of this article, along with NOAA's Intensity Forecasting Experiment (IFEX) and NSF's Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) experiment, obtained unprecedented observations of the formation and intensification of tropical cyclones. The major goal of GRIP was to better understand the physical processes that control hurricane formation and intensity change, specifically the relative roles of environmental and inner-core processes. A key focus of GRIP was the application of new technologies to address this important scientific goal, including the first ever use of the unmanned Global Hawk aircraft for hurricane science operations. NASA and NOAA conducted coordinated flights to thoroughly sample the rapid intensification (RI) of Hurricanes Earl and Karl. The tri-agency aircraft teamed up to perform coordinated flights for the genesis of Hurricane Karl and Tropical Storm Matthew and the non-redevelopment of the remnants of Tropical Storm Gaston. The combined GRIP–IFEX–PREDICT datasets, along with remote sensing data from a variety of satellite platforms [Geostationary Operational Environmental Satellite (GOES), Tropical Rainfall Measuring Mission (TRMM), Aqua, Terra, CloudSat, and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)], will contribute to advancing understanding of hurricane formation and intensification. This article summarizes the GRIP experiment, the missions flown, and some preliminary findings.

hurricane↗