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NASA NTRS1986

Aircraft and satellite passive microwave observations of the Bering Sea ice cover during MIZEX West

Passive microwave measurements of the Bering Sea were made with the NASA CV-990 airborne laboratory during February. Microwave data were obtained with imaging and dual-polarized, fixed-beam radiometers in a range of frequencies from 10 to 183 GHz. The high resolution imagery at 92 GHz provides a particularly good description of the marginal ice zone delineating regions of open water, ice compactness, and ice-edge structure. Analysis of the fixed-beam data shows that spectral differences increase with a decrease in ice thickness. Polarization at 18 and 37 GHz distinguishes among new, young, and first-year ice types.

Cavalieri, D. J.↗

NASA NTRSDate not supplied

Assessment of Cloud Fraction Derived from a New Geostationary Satellite Cloud Retrieval Algorithm for CERES and Progress Towards Cross-platform Continuity

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has produced long-term records of top-of-atmosphere (TOA) and surface irradiances for detecting changes in the Earth’s radiation budget and advancing understanding of how clouds contribute to those changes. Accurate characterization of the spatial and temporal distributions of clouds are a critical component for producing CERES datasets. The CERES Cloud Working Group (CWG) derives cloud properties from both geostationary (GEO) and low-Earth orbit (LEO) satellite sensors in order to provide complete global coverage at hourly temporal resolution. However, the use of multiple sensors to provide this spatiotemporal coverage throughout a long-term record presents some challenges, because the various sensors generally have different spectral band characteristics (e.g., spectral band width and response) and spatial resolution. These differences can result in spatial artifacts at the coverage boundary between two sensors or temporal artifacts when one sensor replaces another in the record. For the upcoming Edition 5 release of CERES products, the CWG is developing cloud retrieval algorithms which utilize only spectral bands common to most modern passive satellite radiometers and account for differences in spectral width and response. The goal with this approach is to provide global cloud properties for CERES with greater cross-platform consistency than the previous Edition 4 products and thus mitigate artifacts which are evident at the interface of two sensors. This study focuses on retrieval of total cloud fraction from various GEO sensors, and we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations to assess the accuracy of total cloud fraction derived from the various sensors. The Edition 5 cloud mask algorithm depends on estimates of cloud-free TOA spectral radiances to differentiate clear and cloudy conditions, and CALIOP is used to assess the accuracy of those estimates when cloud-free conditions are indeed observed.

CALIOP↗

NASA NTRS1993

Spectral evidence for stirring scales and two-dimensional turbulence in the auroral ionosphere

Electric field power spectra from two auroral sounding rocket flights show evidence of a distinct scale size regime for injection of energy into the auroral oval. The signature of this process is a broad plateau in the spectrum, with power law dependences at both shorter and longer scale sizes. We argue that the spectral properties at high k are dominated by processes occurring near the edges of inverted-V electron precipitation regions (auroral arcs). We see no compelling reason to conclude that a linear local plasma instability is occurring but rather, that nonlinear mixing and forward cascade yield the observed velocity field. The spectra of simultaneously observed density irregularities are quite different from those of the electric field, implying that the plasma density does not behave as a passive scalar in the auroral zone during active conditions. At low-k values we show that the rocket spectra are consistent with the power spectra of magnetospheric electric fields measured by the DE, AE-C, and Hilat stallites.

Earle, G. D.↗

NASA NTRSDate not supplied

Assessment of Retrieved GMI Emissivity Over Land, Snow and Sea Ice in the GEOS System

Measurements from microwave sounders and imagers provide a valuable source of information including atmospheric temperature and water vapor in Numerical Weather Prediction (NWP) systems that assimilate these observations directly over water surfaces (oceans and other large water bodies). In a recent decadal survey, targeted observables in the Planetary Boundary Layer (PBL) were cited as a key need for future observations (NASEM, 2018). Microwave observations which sense in the PBL are currently available, however, utilizing surface-sensitive microwave observations for atmospheric data assimilation remains a challenge over land, snow and sea ice. This is in part due to the inability of surface emissivity models used by NWP data assimilation systems to simulate observations with sufficient accuracy. The GEOS-ADAS (Todling and el Akkraoui, 2018) which utilizes the Community Radiative Transfer Model (CRTM) (Han, 2006; Chen 2009) is no exception. The ECMWF system has retrieved instantaneous surface emissivity from surface-sensitive channels for SSMI/S and MHS radiance observations, and apply these estimates to the closest channels higher in frequency (Baordo and Geer 2016) in the calculation of simulated radiances. This approach currently is also being tested in the GEOS-ADAS for AMSU-A and ATMS radiances (Zhu et al. 2021). No or minimal emissivity spectral variability has been assumed in the above-mentioned studies. Recently, work by Munchak et al., 2020 (hereby referred to as M2020) provided a new database for emissivity over land, snow and sea ice retrieved from the NASA Global Precipitation Mission (GPM). Compared with Tool to Estimate Land Surface Emissivities at Microwave (TELSEM2; Wang et al., 2017), M2020 provides emissivities for more frequencies(i.e., 10.7 GHz V/H). Moreover, this database is unique in that it utilizes both active and passive data to retrieve surface emissivity and normalized radar cross section. While the emissivity values may be useful for other sensors, they are most applicable to the GPM Microwave Imager (GMI). In this work the GEOS-ADAS is modified to utilize emissivity values from Munchak et al, 2020 in place of values used by CRTM. Presently, only GMI radiances over ocean are used in the operational GEOS-ADAS. This study will focus on the GMI radiances over land, snow, and ice, as a first attempt to evaluate GMI radiances over these non-water surface types. Two cases are then presented, one with one week of observation minus background departures using the modified GEOS-ADAS, and one utilizing the original GEOS-ADAS. It should be noted that the surface emissivity models in CRTM are not state of the art and are scheduled to be replaced by the Community Surface Emissivity Module (CSEM; Chen and Weng, 2016). Simulations using default CRTM emissivity values are used merely as reference comparing against M2020, and is not a thorough comparison against other more state of the art modules such as CSEM.

GMI↗

NASA NTRS1991

Tropospheric Emission Spectrometer for the Earth Observing System

A Tropospheric Emission Spectrometer (TES) for the Earth Observing System (EOS) series of polar-orbiting platforms is described. TES is aimed at studying tropospheric chemistry, in particular, the exchange of gases between the surface and the atmosphere, urban and regional pollution, acid rain precursors, sources and sinks of greenhouse gases, and the interchange of gases between the troposphere and the stratosphere. TES is a high-resolution (0.025/cm) infrared Fourier transform spectrometer operating in the passive thermal-emission mode in a very wide spectral range (600 to 4350/cm; 2.3 to 16.7 microns). TES has 32 spatial pixels in each of four optically conjugated linear detector arrays, each optimized for a different spectral region.

Glavich, Thomas A.↗

NASA NTRS2016

Multistatic Aerosol Cloud Lidar in Space: A Theoretical Perspective

Accurate aerosol and cloud retrievals from space remain quite challenging and typically involve solving a severely ill-posed inverse scattering problem. In this Perspective, we formulate in general terms an aerosol and aerosol-cloud interaction space mission concept intended to provide detailed horizontal and vertical profiles of aerosol physical characteristics as well as identify mutually induced changes in the properties of aerosols and clouds. We argue that a natural and feasible way of addressing the ill-posedness of the inverse scattering problem while having an exquisite vertical-profiling capability is to fly a multistatic (including bistatic) lidar system. We analyze theoretically the capabilities of a formation-flying constellation of a primary satellite equipped with a conventional monostatic (backscattering) lidar and one or more additional platforms each hosting a receiver of the scattered laser light. If successfully implemented, this concept would combine the measurement capabilities of a passive multi-angle multi-spectral polarimeter with the vertical profiling capability of a lidar; address the ill-posedness of the inverse problem caused by the highly limited information content of monostatic lidar measurements; address the ill-posedness of the inverse problem caused by vertical integration and surface reflection in passive photopolarimetric measurements; relax polarization accuracy requirements; eliminate the need for exquisite radiative-transfer modeling of the atmosphere-surface system in data analyses; yield the day-and-night observation capability; provide direct characterization of ground-level aerosols as atmospheric pollutants; and yield direct measurements of polarized bidirectional surface reflectance. We demonstrate, in particular, that supplementing the conventional backscattering lidar with just one additional receiver flown in formation at a scattering angle close to 170deg can dramatically increase the information content of the measurements. Although the specific subject of this Perspective is the multistatic lidar concept, all our conclusions equally apply to a multistatic radar system intended to study from space the global distribution of cloud and precipitation characteristics.

aerosols↗

NASA NTRSDate not supplied

PLANNING FOR VEG-05 TOMATO CROP PRODUCTION ON THE INTERNATIONAL SPACE STATION

Growing fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the astronaut dietary experience as we move toward longer-duration missions. Tending plants may also serve as a countermeasure for crew psychological stresses associated with spaceflight. However, requirements to support consistent growth of a variety of nutritious crops under spaceflight environmental conditions remain unclear. This study explores the potential to grow crops for consumption on the International Space Station (ISS) using the Veggie vegetable-production system. Mizuna mustard was grown during VEG-04 studies in 2019, and human and plant data from those tests continue to be analyzed. Tomato plants will be grown for the VEG-05 experiment, and preflight definition studies are underway to ascertain the best hardware and operations for growing this fruiting crop. The variety of tomato selected for this study is ‘Red Robin’, a compact cherry tomato. Plants will be grown under two different red: blue lighting treatments using the Veggie units on ISS, and the impact of spectral quality on plant growth and yield, nutrient content, organoleptic acceptability, and microbial composition of the tomatoes will be assessed. Preliminary testing with this crop helped to identify responses to different analog types of growth hardware including both plant pillows and Passive Orbital Nutrient Delivery System (PONDS) units, and current testing is focusing on flight-like versions of this hardware. Challenges with fertilizer salts leaching out into the plant wicks and burning the stems of tomato were observed in earlier tests, so amended fertilizer and wick configurations have been developed. Crew procedures including plant thinning, watering, height adjustment with respect to lighting, and pollination are being validated. VEG-05 will be the first test of tomato fruit production on ISS. Lessons learned during preparation and implementation of the VEG-04 mizuna test for watering, and a separate ISS investigation with peppers (PH-04) in the Advanced Plant Habitat (APH) in terms of fertilizer, plant wicks, and pollination, will be adapted for this experiment. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call.

Veggie↗

NASA NTRSDate not supplied

Planning for VEG-05 Tomato Crop Production on the International Space Station

Veggie↗

NASA NTRS2011

CIRS-lite, a Fourier Transform Spectrometer for Low-Cost Planetary Missions

Passive spectroscopic remote sensing of planetary atmospheres and surfaces in the thermal infrared is a powerful tool for obtaining information about surface and atmospheric temperatures, composition, and dynamics (via the thermal wind equation). Due to its broad spectral coverage, the Fourier transform spectrometer (FTS) is particularly suited to the exploration and discovery of molecular species. NASA's Goddard Space Flight Center (GSFC) developed the CIRS (Composite Infrared Spectrometer) FTS for the NASA/ESA Cassini mission to the Saturnian system. CIRS observes Saturn, Titan, icy moons such as Enceladus, and the rings in thermal self-emission over the spectral range of 7 to 1000 ell11. CIRS has given us important new insights into stratospheric composition and jets on Jupiter and Saturn, the cryo-geyser and thermal stripes on Enceladus, and the winter polar vortex on Titan. CIRS has a mass of 43 kg, contrasted with the earlier GSFC FTS, pre-Voyager IRIS (14 kg). Future low-cost planetary missions will have very tight constraints on science payload mass, thus we must endeavor to return to IRIS-level mass while maintaining CIRS-level science capabilities ("do more with less"). CIRS-lite achieves this by pursuing: a) more sensitive infrared detectors (high Tc superconductor) to enable smaller optics. b) changed long wavelength limit from 1000 to 300 microns to reduce diffraction by smaller optics. c) CVD (chemical vapor deposition) diamond beam-splitter for broad spectral coverage. d) single FTS architecture instead of a dual FTS architecture. e) novel materials, such as single crystal silicon for the input telescope primary.

Brasunas, J.↗

NASA NTRS1979

Theory and experiment for passive microwave remote sensing of snowpacks

Both the theory and experiment for the passive remote sensing of snow with microwave radiometers have been studied. The volume scattering effects of snow are accounted for by incorporating Mie scattering theory into a radiative transfer model. The theory is applied to the interpretation of experimental data obtained from various snow measurements. The spectral and angular dependences of the brightness temperatures are illustrated and show good agreement between the theory and experiment. Brightness temperatures as a function of snow depths are also interpreted and discussed. It is observed that as the snow depth increases, the brightness temperature increases when the subsurface is an aluminum plate due to the fact that the plate is cold and snow absorption induces a brightening effect and the brightness temperature decreases when the subsurface is soil due to the fact that snow scattering induces darkening effects.

Kong, J. A.↗

NASA NTRS2013

Contemplating Synergistic Algorithms for the NASA ACE Mission

ACE is a proposed Tier 2 NASA Decadal Survey mission that will focus on clouds, aerosols, and precipitation as well as ocean ecosystems. The primary objective of the clouds component of this mission is to advance our ability to predict changes to the Earth's hydrological cycle and energy balance in response to climate forcings by generating observational constraints on future science questions, especially those associated with the effects of aerosol on clouds and precipitation. ACE will continue and extend the measurement heritage that began with the A-Train and that will continue through Earthcare. ACE planning efforts have identified several data streams that can contribute significantly to characterizing the properties of clouds and precipitation and the physical processes that force these properties. These include dual frequency Doppler radar, high spectral resolution lidar, polarimetric visible imagers, passive microwave and submillimeter wave radiometry. While all these data streams are technologically feasible, their total cost is substantial and likely prohibitive. It is, therefore, necessary to critically evaluate their contributions to the ACE science goals. We have begun developing algorithms to explore this trade space. Specifically, we will describe our early exploratory algorithms that take as input the set of potential ACE-like data streams and evaluate critically to what extent each data stream influences the error in a specific cloud quantity retrieval.

precipitation↗

NASA NTRS1980

Some adaptive filtering techniques applied to the passive remote sensing problem

A review is made of recursive statistical regression techniques incorporating past or past and future observations through smoothing and Kalman filtering, respectively; with results for the cases of the Tiros-N/MSU and Nimbus-6/Scams remote sensing satellite experiments. In response to the lack of a satisfactory model for the medium sounded, which is presently a major limitation on retrieval technique performance, a novel, global approach is proposed which casts the retrieval problem into the framework of adaptive filtering. A numerical implementation of such an adaptive system is presented, with a multilayer, semi-spectral general circulation model for the atmosphere being used to fine-tune the sensor as well as the dynamical equations of a Kalman filter. It is shown that the assimilation of radiometric data becomes a straightforward subproblem.

Toldalagi, P. M.↗

NASA NTRS1990

Numerical modeling of passive microwave O2 observations over precipitation

Radiometric observations at 118 GHz are compared to a planar-stratified numerical radiative transfer model, in order to study the microwave scattering and emission properties of precipitation cells. Agreement between observed and computed brightness perturbations is shown to be within 10 percent over the radiometrically opaque, mature regions of the cell. Transparent-channel cell top reflectivities of up to 50 percent in the convective core region and 6 percent in the anvil region are determined, using perturbed and nonscattering weighting functions. A parameterized rain cell model is used in a content analysis of 118 GHz precipitation cell spectra. The dominant 118-GHz spectral modes are found to contain useful data on the cell top altitude; they are applicable for detection of transparent anvil regions.

Gasiewski, A. J.↗

NASA NTRS2002

Geolocation Assessment Algorithm for CALIPSO Using Coastline Detection

Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) is a joint satellite mission between NASA and the French space agency CNES. The investigation will gather long-term, global cloud and aerosol optical and physical properties to improve climate models. The CALIPSO spacecraft is scheduled to launch in 2004 into a 98.2 inclination, 705 km circular orbit approximately 3 minutes behind the Aqua spacecraft. The payload consists of a two-wavelength polarization-sensitive lidar, and two passive imagers operating in the visible (0.645 mm) and infrared (8.7 - 12.0 mm) spectral regions. The imagers are nadir viewing and co-aligned with the lidar. Earth viewing measurements are geolocated to the Earth fixed coordinate system using satellite ephemeris, Earth rotation and geoid, and instrument pointing data. The coastline detection algorithm will assess the accuracy of the CALIPSO geolocation process by analyzing Wide Field Camera (WFC) visible ocean land boundaries. Processing space-time coincident MODIS and WFC scenes with the coastline algorithm will help verify the co-registration requirement with Moderate Resolution Imaging Spectrometer (MODIS) data. This paper quantifies the accuracy of the coastline geolocation assessment algorithm.

Currey, J. Chris↗

NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗

NASA NTRS2012

James Webb Space Telescope: Large Deployable Cryogenic Telescope in Space

The James Webb Space Telescope (JWST) is an infrared space telescope designed to explore four major science themes: first light and reionization, the assembly of galaxies, the birth of stars and protoplanetary systems, and planetary systems and origins of life. JWST is a segmented architecture telescope with an aperture of 6.6 m. It will operate at cryogenic temperature (40 K), achieved via passive cooling, in an orbit about the Earth-Sun second Lagrange point (L2). Passive cooling is facilitated by means of a large sunshield that provides thermal isolation and protection from direct illumination from the Sun. The large size of the telescope and spacecraft systems require that they are stowed for launch in a configuration that fits the Ariane 5 fairing, and then deployed after launch. Routine wavefront sensing and control measurements are used to achieve phasing of the segmented primary mirror and initial alignment of the telescope. A suite of instruments will provide the capability to observe over a spectral range from 0.6- to 27-micron wavelengths with imaging and spectroscopic configurations. An overview is presented of the architecture and selected optical design features of JWST are described

Lightsey, Paul A.↗

NASA NTRS2017

Assessment of the Impact of Spatial Heterogeneity on Microwave Satellite Soil Moisture Periodic Error

An accurate temporal and spatial characterization of errors is required for the efficient processing, evaluation, and assimilation of remotely-sensed surface soil moisture retrievals. However, empirical evidence exists that passive microwave soil moisture retrievals are prone to periodic artifacts which may complicate their application in data assimilation systems (which commonly treat observational errors as being temporally white). In this paper, the link between such temporally-periodic errors and spatial land surface heterogeneity is examined. Both the synthetic experiment and site-specified cases reveal that, when combined with strong spatial heterogeneity, temporal periodicity in satellite sampling patterns (associated with exact repeat intervals of the polar-orbiting satellites) can lead to spurious high frequency spectral peaks in soil moisture retrievals. In addition, the global distribution of the most prominent and consistent 8-day spectral peak in the Advanced Microwave Scanning Radiometer - Earth Observing System soil moisture retrievals is revealed via a peak detection method. Three spatial heterogeneity indicators - based on microwave brightness temperature, land cover types, and long-term averaged vegetation index - are proposed to characterize the degree to which the variability of land surface is capable of inducing periodic error into satellite-based soil moisture retrievals. Regions demonstrating 8-day periodic errors are generally consistent with those exhibiting relatively higher heterogeneity indicators. This implies a causal relationship between spatial land surface heterogeneity and temporal periodic error in remotely-sensed surface soil moisture retrievals.

Fangni Lei↗

NASA NTRS1996

Calibration of the Microwave Limb Sounder on the Upper Atmosphere Research Satellite

The Microwave Limb Sounder (MLS) is a three-radiometer, passive, limb emission instrument onboard the Upper Atmosphere Research Satellite (UARS). Radiometric, spectral and field-of-view calibrations of the MLS instrument are described in this paper. In-orbit noise performance, gain stability, spectral baseline and dynamic range are described, as well as use of in-flight data for validation and refinement of prelaunch calibrations. Estimated systematic scaling uncertainties (3 sigma) on calibrated limb radiances from prelaunch calibrations are 2.6% in bands 1 through 3, 3.4% in band 4, and 6% in band 5. The observed systematic errors in band 6 are about 15%, consistent with prelaunch calibration uncertainties. Random uncertainties on individual limb radiance measurements are very close to the levels predicted from measured radiometer noise temperature, with negligible contribution from noise and drifts on the regular in-flight gain calibration measurements.

Jarnot, R. F.↗