Search NASA⌕ Search

SEARCH · Search NASA

Results for “airborne instruments”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The Slope Imaging Multi-Polarization Photon-Counting Lidar: Development and Performance Results

The Slope Imaging Multi-polarization Photon-counting Lidar is an airborne instrument developed to demonstrate laser altimetry measurement methods that will enable more efficient observations of topography and surface properties from space. The instrument was developed through the NASA Earth Science Technology Office Instrument Incubator Program with a focus on cryosphere remote sensing. The SIMPL transmitter is an 11 KHz, 1064 nm, plane-polarized micropulse laser transmitter that is frequency doubled to 532 nm and split into four push-broom beams. The receiver employs single-photon, polarimetric ranging at 532 and 1064 nm using Single Photon Counting Modules in order to achieve simultaneous sampling of surface elevation, slope, roughness and depolarizing scattering properties, the latter used to differentiate surface types. Data acquired over ice-covered Lake Erie in February, 2009 are documenting SIMPL s measurement performance and capabilities, demonstrating differentiation of open water and several ice cover types. ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.

Dabney, Phillip↗
NASA NTRS2011

Flight Planning in the Cloud

This new interface will enable Principal Investigators (PIs), as well as UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) members to do their own flight planning and time estimation without having to request flight lines through the science coordinator. It uses an all-in-one Google Maps interface, a JPL hosted database, and PI flight requirements to design an airborne flight plan. The application will enable users to see their own flight plan being constructed interactively through a map interface, and then the flight planning software will generate all the files necessary for the flight. Afterward, the UAVSAR team can then complete the flight request, including calendaring and supplying requisite flight request files in the expected format for processing by NASA s airborne science program. Some of the main features of the interface include drawing flight lines on the map, nudging them, adding them to the current flight plan, and reordering them. The user can also search and select takeoff, landing, and intermediate airports. As the flight plan is constructed, all of its components are constantly being saved to the database, and the estimated flight times are updated. Another feature is the ability to import flight lines from previously saved flight plans. One of the main motivations was to make this Web application as simple and intuitive as possible, while also being dynamic and robust. This Web application can easily be extended to support other airborne instruments.

Flores, Sarah L.↗
NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗
NASA NTRS2015

Scanning L-Band Active Passive (SLAP) - Recent Results from an Airborne Simulator for SMAP

Scanning L-band Active Passive (SLAP) is a recently-developed NASA airborne instrument specially tailored to simulate the new Soil Moisture Active Passive (SMAP) satellite instrument suite. SLAP conducted its first test flights in December, 2013 and participated in its first science campaign-the IPHEX ground validation campaign of the GPM mission-in May, 2014. This paper will present results from additional test flights and science observations scheduled for 2015.

instruments↗
NASA NTRS2016

Derivation of Cumulus Cloud Dimensions and Shape from the Airborne Measurements by the Research Scanning Polarimeter

The Research Scanning Polarimeter (RSP) is an airborne instrument, whose measurements have been extensively used for retrievals of microphysical properties of clouds. In this study we show that for cumulus clouds the information content of the RSP data can be extended by adding the macroscopic parameters of the cloud, such as its geometric shape, dimensions, and height above the ground. This extension is possible by virtue of the high angular resolution and high frequency of the RSP measurements, which allow for geometric constraint of the cloud's 2D cross section between a number of tangent lines of view. The retrieval method is tested on realistic 3D radiative transfer simulations and applied to actual RSP data.

Remote sensing↗
NASA NTRS2016

Coastal High-resolution Observations and Remote Sensing of Ecosystems (C-HORSE)

Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.

Coasts↗
NASA NTRS2016

Space-Based Remote Imaging Spectroscopy of the Aliso Canyon CH4 Superemitter

The Aliso Canyon gas storage facility near Porter Ranch, California, produced a large accidental CH4 release from October 2015 to February 2016. The Hyperion imaging spectrometer on board the EO-1 satellite successfully detected this event, achieving the first orbital attribution of CH4 to a single anthropogenic superemitter. Hyperion measured shortwave infrared signatures of CH4 near 2.3 microns at 0.01 micron spectral resolution and 30 meter spatial resolution. It detected the plume on three overpasses, mapping its magnitude and morphology. These orbital observations were consistent with measurements by airborne instruments. We evaluate Hyperion instrument performance, draw implications for future orbital instruments, and extrapolate the potential for a global survey of CH4 superemitters.

Thompson, D. R.↗
NASA NTRS2017

The 2013 FLEX-US Airborne Campaign at the Parker Tract Loblolly Pine Plantation in North Carolina, USA

The first European Space Agency (ESA) and NASA collaboration in an airborne campaign to support ESA's FLuorescence EXplorer (FLEX) mission was conducted in North Carolina, USA during September-October 2013 (FLEX-US 2013) at the Parker Tract Loblolly Pine (LP) Plantation (Plymouth, NC, USA). This campaign combined two unique airborne instrument packages to obtain simultaneous observations of solar-induced fluorescence (SIF), LiDAR-based canopy structural information, visible through shortwave infrared (VSWIR) reflectance spectra, and surface temperature, to advance vegetation studies of carbon cycle dynamics and ecosystem health. We obtained statistically significant results for fluorescence, canopy temperature, and tower fluxes from data collected at four times of day over two consecutive autumn days across an age class chronosequence. Both the red fluorescence (F685) and far-red fluorescence (F740) radiances had highest values at mid-day, but their fluorescence yields exhibited different diurnal responses across LP age classes. The diurnal trends for F685 varied with forest canopy temperature difference (canopy minus air), having a stronger daily amplitude change for young vs. old canopies. The Photochemical Reflectance Index (PRI) was positively correlated with this temperature variable over the diurnal cycle. Tower measurements from mature loblolly stand showed the red/far-red fluorescence ratio was linearly related to canopy light use efficiency (LUE) over the diurnal cycle, but performed even better for the combined morning/afternoon (without midday) observations. This study demonstrates the importance of diurnal observations for interpretation of fluorescence dynamics, the need for red fluorescence to understand canopy physiological processes, and the benefits of combining fluorescence, reflectance, and structure information to clarify canopy function versus structure characteristics for a coniferous forest.

chlorophyll fluorescence; diurnal responses; red S↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRS2018

General Aviation Citizen Science Study to Help Tackle Remote Sensing of Harmful Algal Blooms (HABs)

We present a new, low-cost approach, based on volunteer pilots conducting high-resolution aerial imaging, to help document the onset, growth, and outbreak of harmful algal blooms (HABs) and related water quality issues in central and western Lake Erie. In this model study, volunteer private pilots acting as citizen scientists frequently flew over 200 mi of Lake Erie coastline, its islands, and freshwater estuaries, taking high-quality aerial photographs and videos. The photographs were taken in the nadir (vertical) position in red, green, and blue (RGB) and near-infrared (NIR) every 5 s with rugged, commercially available built-in Global Positioning System (GPS) cameras. The high-definition (HD) videos in 1080p format were taken continuously in an oblique forward direction. The unobstructed, georeferenced, high-resolution images, and HD videos can provide an early warning of ensuing HAB events to coastal communities and freshwater resource managers. The scientists and academic researchers can use the data to compliment a collection of in situ water measurements, matching satellite imagery, and help develop advanced airborne instrumentation, and validation of their algorithms. This data may help develop empirical models, which may lead to the next steps in predicting a HAB event as some watershed observed events changed the water quality such as particle size, sedimentation, color, mineralogy, and turbidity delivered to the Lake site. This paper shows the efficacy and scalability of citizen science (CS) aerial imaging as a complimentary tool for rapid emergency response in HABs monitoring, land and vegetation management, and scientific studies. This study can serve as a model for monitoring/management of freshwater and marine aquatic systems.

Ansari, Rafat R.↗
NASA NTRS2018

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Model-Relevant Observations and the Beneficiary Modeling Efforts in the Realm of the EVS-2 Project ORACLES

Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.

Redemann, Jens↗
NASA NTRS2018

Developing a Standard for Earth Observation Data Preservation Content - A Path to Future Usability

For datasets to be usable, many pieces of information in addition to the data themselves are essential. During the active parts of the lifecycle of dataset generating projects, the needed information is usually accessible through individuals familiar with the various aspects of the projects. However, the utility of datasets tends to outlive the lives of projects, by several decades in many cases. Thus it is essential to capture all the relevant information about the datasets, data, metadata and associate knowledge that is sufficient to read, understand, interpret and reuse the datasets, while the projects are still active. The capture and preservation should be such that the data are usable when no consultation is available from the original project participants. Identification of specific categories of content through an international standard is beneficial to the user communities of the future, so that projects involving Earth observations and generating data products can consistently plan for preservation and future usability of the project outcomes. While there are existing standards that address archival and preservation in general, there are no existing international standards or specifications today to address what content should be preserved. The standard, ISO 19165-1, titled "Geographic Information - Preservation of digital data and metadata Part 1: Fundamentals" considers geographic information preservation in general. It acknowledges that "specific content items needed to preserve the full provenance and context of the data and associated metadata depend on the needs of the designated community and types of datasets (e.g., maps, remotely sensed data from satellites and airborne instruments, physical samples). Follow-up parts to this standard may be developed detailing content items appropriate to individual disciplines." NASA proposed an extension to this standard, titled "Geographic information -- Preservation of digital data and metadata -- Part 2: Content specifications for Earth observation data and derived digital products." The development of this extension is in progress with participation by an international team representing nine countries. The purpose of this paper is to introduce this standard and report on its status.

Remote Sensing; Data Systems; Open Data;↗
NASA NTRS2018

The Importance of User Feedback in Sustaining Trusted Repositories

The NASA Earth Observation System Data and Information System (EOSDIS) has been operating since 1994 and is serving a global user community with well-managed Earth science data in a variety of scientific disciplines. EOSDIS processes, archives and distributes data and information products resulting from spaceborne and airborne instruments as well as in situ measurements from field campaigns. The Earth Science Data and Information System (ESDIS) Project at the NASA Goddard Space Flight Center manages EOSDIS with its 12 Distributed Active Archive Centers (DAACs) located across the United States. During the entire life of EOSDIS, the ESDIS Project and the DAACs have deployed many different mechanisms for user feedback, which have proven extremely valuable to their evolution and performance in their service to user communities. Some of the inputs from our user groups have resulted in fundamental changes in the architecture, design and operations of EOSDIS, while others have provided novel ideas for incremental changes. The EOSDIS DAACs have User Working Groups (UWGs) that represent broad user communities in the Earth science disciplines served by the DAACs. The UWGs meet periodically to assess and provide feedback on dataset and service priorities. As regular users of the data and services of the DAAC and experts in the scientific disciplines, the UWG members provide valuable inputs for planning and prioritizing the services, as well as addition of new datasets, for the benefit of the community. The EOSDIS is evaluated annually through an independently administered survey of its users resulting in the American Customer Satisfaction Index (ACSI). The survey provides an ACSI score as well as free-text suggestions from users, which are also helpful in making specific system improvements. In addition, each of the DAACs has a user services group that address on-going requests for help and other comments from users. The ESDIS Project has established a mechanism through the "earthdata" website (http://earthdata.nasa.gov) for users to provide feedback of any kind and these questions/comments are routed to the appropriate individuals in the Project or the DAACs. These various forms of receiving user feedback and responding to them continue to be extremely valuable in evolving and sustaining our Earth Science repository.

Behnke, Jeanne↗
NASA NTRS2019

Tri-Frequency Synthetic Aperture Radar for the Measurements of Snow Water Equivalent

SWESARR (Snow Water Equivalent Synthetic Aperture Radar and Radiometer) is an airborne instrument developed at the NASA Goddard Space Flight Center for the retrieval of Snow Water Equivalent. SWESARR was specifically designed to measure co-located active and passive signals using a high resolution and multi-frequency Synthetic Aperture Radar (SAR) and a multifrequency radiometer. SWESARR’s Synthetic Aperture Radar (SAR) system is made up of three independent radar units that operate in the X, Ku-Low, and Ku-High bands with bandwidths up to 200 MHz, and acquires data in two polarizations (dual-polarization radar). The difference in sensitivity of the backscatter signals to snow microstructure, in conjunctions with radiometer measurements, permits an accurate estimation of the snow water equivalent (SWE).

Rincon, Rafael↗
NASA NTRS2020

Revisiting the Effectiveness Of HCHO/NO2 Ratios for Inferring Ozone Sensitivity to Its Precursors Using High Resolution Airborne Remote Sensing Observations in A High Ozone Episode During the KORUS-AQ Campaign

The nonlinear chemical processes involved in ozone production (P(O3)) have necessitated using proxy indicators to convey information about the primary dependence of P(O3) on volatile organic compounds (VOCs) or nitrogen oxides (NOx). In particular, the ratio of remotely sensed columns of formaldehyde (HCHO) to nitrogen dioxide (NO2) has been widely used for studying O3 sensitivity. Previous studies found that the errors in retrievals and the incoherent relationship between the column and the near-surface concentrations are a barrier in applying the ratio in a robust way. In addition to these obstacles, we provide calculational-observational evidence, using an ensemble of 0-D photochemical box models constrained by DC-8 aircraft measurements on an ozone event during the Korea-United States Air Quality (KORUS-AQ) campaign over Seoul, to demonstrate the chemical feedback of NO2 on the formation of HCHO is a controlling factor for the transition line between NOx-sensitive and NOx-saturated regimes. A fixed value (~2.7) of the ratio of the chemical loss of NOx (LNOx) to the chemical loss of HO2+RO2 (LROx) perceptibly differentiates the regimes. Following this value, data points with a ratio of HCHO/NO2 less than 1 can be safely classified as NOx-saturated regime, whereas points with ratios between 1 and 4 fall into one or the other regime. We attribute this mainly to the HCHO-NO2 chemical relationship causing the transition line to occur at larger (smaller) HCHO/NO2 ratios in VOC-rich (VOC-poor) environments. We then redefine the transition line to LNOx/LROx~2.7 that accounts for the HCHO-NO2 chemical relationship leading to HCHO = 3.7 × (NO2 – 1.14 × 1016 molec.cm-2). Although the revised formula is locally calibrated (i.e., requires for readjustment for other regions), its mathematical format removes the need for having a wide range of thresholds used in HCHO/NO2 ratios that is a result of the chemical feedback. Therefore, to be able to properly take the chemical feedback into consideration, the use of HCHO = a × (NO2 – b) formula should be preferred to the ratio in future works. We then use the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument to study O3 sensitivity in Seoul. The unprecedented spatial (250 × 250 m2) and temporal (~every 2 h) resolutions of HCHO and NO2 observations form the sensor enhance our understanding of P(O3) in Seoul; rather than providing a crude label for the entire city, more in-depth variabilities in chemical regimes are observed that should be able to inform mitigation strategies correspondingly.

KORUS-AQ; formaldehyde; NOx; VOC; OMI; GeoTASO; oz↗
NASA NTRS2021

Characteristics of the RFI Environment at L-band as Observed from SMAP

This manuscript presents some characteristics of RFI sources as they were observed by the SMAP L-band radiometer. Knowledge of the nature of RFI can help improve design of future detection algorithms. For example, observations with airborne instruments demonstrating the pulse-like nature of RFI in the protected L-band spectrum at 1.413 GHz (attributed to air-traffic control radar) informed the design of the Aquarius radiometer and its RFI detection algorithm. The experience of Aquarius and SMOS in space led to the advanced detection system on SMAP. The fully polarimetric SMAP radiometer with spectral and time domain processing, provides sophisticated detection but also the opportunity to look at the temporal and spectral characteristics of the L-band RFI globally. The examples and categorization presented are based on a global sample but over a limited time. They are not meant to be complete. Rather, they are intended to provide insight into the time-frequency characteristics of RFI with the goal that knowledge of the characteristics can help improve detection in future missions.

Yan Soldo↗
NASA NTRS1995

AVIRIS User's Guide

This paper serves as a brief overview of the AVIRIS instrument (Airborne Visible/Infrared Imaging Spectrometer) and its role in the field of imaging spectrometry. Mission planning and flight operations are discussed, and recommendations are given regarding the deployment of ground truth experiments.

AVIRIS↗
NASA NTRSDate not supplied

Polarimeter + Lidar Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved Na product to in situ Na data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11 separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter Na agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged Na. We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged Na and the lidar + polarimeter vertically resolved Na are of similar magnitude and represent a significant improvement upon current remote sensing estimates of Na.

Aerosol number concentration↗