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At least 1,009 records · Page 56
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NASA NTRS2017

Single Object & Time Series Spectroscopy with JWST NIRCam

JWST will enable high signal-to-noise spectroscopic observations of the atmospheres of transiting planets with high sensitivity at wavelengths that are inaccessible with HST or other existing facilities. We plan to exploit this by measuring abundances, chemical compositions, cloud properties, and temperature-pressure parameters of a set of mostly warm (T 600 - 1200 K) and low mass (14 -200 Earth mass) planets in our guaranteed time program. These planets are expected to have significant molecular absorptions of H2O, CH4, CO2, CO, and other molecules that are key for determining these parameters and illuminating how and where the planets formed. We describe how we will use the NIRCam grisms to observe slitless transmission and emission spectra of these planets over 2.4 - 5.0 microns wavelength and how well these observations can measure our desired parameters. This will include how we set integration times, exposure parameters, and obtain simultaneous shorter wavelength images to track telescope pointing and stellar variability. We will illustrate this with specific examples showing model spectra, simulated observations, expected information retrieval results, completed Astronomer's Proposal Tools observing templates, target visibility, and other considerations.

NIRCam↗
NASA NTRS2017

Assessing the Altitude and Dispersion of Volcanic Plumes Using MISR Multi-angle Imaging from Space: Sixteen Years of Volcanic Activity in the Kamchatka Peninsula, Russia

Volcanic eruptions represent a significant source of atmospheric aerosols and can display local, regional and global effects, impacting earth systems and human populations. In order to assess the relative impacts of these events, accurate plume injection altitude measurements are needed. In this work, volcanic plumes generated from seven Kamchatka Peninsula volcanoes (Shiveluch, Kliuchevskoi, Bezymianny, Tolbachik, Kizimen, Karymsky and Zhupanovsky), were identified using over 16 years of Multi-angle Imaging SpectroRadimeter (MISR) measurements. Eighty-eight volcanic plumes were observed by MISR, capturing 3-25% of reported events at individual volcanoes. Retrievals were most successful where high intensity events persisted over a period of weeks to months. Compared with existing ground and airborne observations, and alternative satellite-based reports compiled by the Global Volcanism Program (GVP), MISR plume height retrievals showed general consistency; the comparison reports appear to be skewed towards the region of highest concentration observed in MISR-constrained vertical plume extent. The report observations display less discrepancy with MISR toward the end of the analysis period, with improvements in the suborbital data likely the result of the deployment of new instrumentation. Conversely, the general consistency of MISR plume heights with conventionally reported observations supports the use of MISR in the ongoing assessment of volcanic activity globally, especially where other types of volcanic plume observations are unavailable. Differences between the northern (Shiveluch, Kliuchevskoi, Bezymianny and Tolbachik) and southern (Kizimen, Karymsky and Zhupanovsky) volcanoes broadly correspond to the Central Kamchatka Depression (CKD) and Eastern Volcanic Front (EVF), respectively, geological sub-regions of Kamchatka distinguished by varying magma composition. For example, by comparison with reanalysis-model simulations of local meteorological conditions, CKD plumes generally were less constrained by mid-tropospheric (< 6 km) layers of vertical stability above the boundary layer, suggesting that these eruptions were more energetic than those in the EVF

Kamchatka↗
NASA NTRS1993

On the Problem of Measuring Interannual Wind Speed Variations Using SSMI Data

The first Special Sensor Microwave Imager (SSMI) was launched on the Defence Meteorological Satellite Program (DMSP) F8 spacecraft in July 1987, and wind speed was no longer retrieved after December 1991. A second SSMI was launched on DMSP F10 in December 1990. Interpretation of the 1987 - 1993 (or longer)SSMI wind speed time series is dependent upon the space and time characteristics of the differences between F8 and F10 SSMI measurements.

SSMI↗
NASA NTRSDate not supplied

A Study of Precipitation Mean Particle Size with the GPM Combined Radar-Radiometer Algorithm

The Global Precipitation Measurement (GPM) mission provides quantitative estimates of the mass-weighted mean diameter, Dm, a characteristic parameter of the precipitation particle size distribution (PSD). This study investigates the three-dimensional distribution of Dm retrieved by the GPM Combined Radar-Radiometer Algorithm (CORRA) using observations from GPM’s dual-frequency precipitation radar and microwave imager. We examine Dm in individual precipitation systems in different climate regimes and investigate a six-year global climatology. The vertical structure of Dm is demonstrated with cases of deep convection, frontal rain and snow, and stratocumulus light rain. The Dm values, detectable by GPM, range from appx 0.7 mm in stratocumulus precipitation to >3.5 mm in the ice layers of intense convection. Within the constraint of the 12-dBZ detectability threshold, the smallest climatological mean Dm (~ 0.8 mm) are found in the eastern oceans, and the largest values (~ 2 mm) occur above the melting levels in convection over land in summer. The standard deviation is generally < 0.45 mm below 6 km. Climate regimes are characterized with Dm annual/seasonal variations, its convective/stratiform components, and vertical variabilities (2-10 km). The US Central Plains and Argentina are associated with the largest Dm in a deep layer. Tropical Africa has larger Dm and standard deviation than Amazon. Large convective Dm occurs at high latitudes of Eurasia and North America in summer; the southern hemisphere high latitudes have shallower systems with smaller Dm. Oceanic storm tracks in both hemispheres have relatively large Dm, particularly for convective Dm in winter.

Mei Han↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
NASA NTRS2006

Aquarius: A Mission to Monitor Sea Surface Salinity from Space

Aquarius is a combination radiometer and scatterometer (radar) operating at L-band (1.413 GHz for the radiometer and 1.26 GHz for the scatterometer). The primary instrument for measuring salinity is the radiometer. The scatterometer will provide a correction for surface roughness (waves) which is one of the largest potential sources of error in the retrieval. Unique features of the sensor are the large reflector (2.5 meter offset fed reflector with three feeds), polarimetric operation, and the tight thermal control. The three feeds produce three beams arranged to image in pushbroom fashion looking to the side of the orbit away from the sun to avoid sunglint. Polarimetric operation is included to assist in correcting for Faraday rotation which can be important at L-band. The tight thermal control is necessary to meet stability requirements (less than 0.12K drift over 7 days) which have been imposed to assist in meeting the science requirements for the retrieval of surface salinity (0.2 psu). The sensor will be in a sun-synchronous orbit at about 650 km with equatorial crossings of 6ad6pm (ascending at 6 pm). The objective is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean. To accomplish this, the measurement goals are a spatial resolution of 100 km and retrieval accuracy of 0.2 psu globally on a monthly basis. Aquarius is being developed by NASA and is a partnership between JPL and the Goddard Space Flight Center. The SAC-D mission is being developed by CONAE and will include the spacecraft and several additional instruments, including visible and infrared cameras and a microwave radiometer to monitor rain and wind velocity over the oceans, and sea ice.

LeVine, D. M.↗
NASA NTRS1999

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Tao, Wei-Kuo↗
NASA NTRS2018

Validation of Ozone Profile Retrievals Derived from the OMPS LP Version 2.5 Algorithm Against Correlative Satellite Measurements

The Limb Profiler (LP) is a part of the Ozone Mapping and Profiler Suite launched on board of the Suomi NPP satellite in October 2011. The LP measures solar radiation scattered from the atmospheric limb in ultraviolet and visible spectral ranges between the surface and 80 km. These measurements of scattered solar radiances allow for the retrieval of ozone profiles from cloud tops up to 55 km. The LP started operational observations in April 2012. In this study we evaluate more than 5.5 years of ozone profile measurements from the OMPS LP processed with the new NASA GSFC version 2.5 retrieval algorithm. We provide a brief description of the key changes that had been implemented in this new algorithm, including a pointing correction, new cloud height detection, explicit aerosol correction and a reduction of the number of wavelengths used in the retrievals. The OMPS LP ozone retrievals have been compared with independent satellite profile measurements obtained from the Aura Microwave Limb Sounder (MLS), Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Odin Optical Spectrograph and InfraRed Imaging System (OSIRIS). We document observed biases and seasonal differences and evaluate the stability of the version 2.5 ozone record over 5.5 years. Our analysis indicates that the mean differences between LP and correlative measurements are well within required +/- 10% between 18 and 42 km. In the upper stratosphere and lower mesosphere (>43 km) LP tends to have a negative bias. We find larger biases in the lower stratosphere and upper troposphere, but LP ozone retrievals have significantly improved in version 2.5 compared to version 2 due to the implemented aerosol correction. In the northern high latitudes we observe larger biases between 20 and 32 km due to the remaining thermal sensitivity issue. Our analysis shows that LP ozone retrievals agree well with the correlative satellite observations in characterizing vertical, spatial and temporal ozone distribution associated with natural processes, like the seasonal cycle and quasi-biennial oscillations. We found a small positive drift approx. 0.5%/yr in the LP ozone record against MLS and OSIRIS that is more pronounced at altitudes above 35 km. This pattern in the relative drift is consistent with a possible 100m drift in the LP sensor pointing detected by one of our altitude-resolving methods.

Ozone Mapping↗
NASA NTRS2022

On the Effects of Cloud Water Content on Passive Microwave Snowfall Retrievals

The Bayesian passive microwave retrievals of snowfall often rely on mathematical matching of the observed vectors of brightness temperature with an a priori database of precipitation profiles and their corresponding brightness temperatures. Mathematical proximity does not necessarily lead to consistent retrievals due to limited information content of passive microwave observations. This paper defines imposter (genuine) vectors of brightness temperature as those that are mathematically close but physically inconsistent (consistent) and characterizes them through the Silhouette Coefficient (SC) analysis. The Neyman–Pearson (NP) hypothesis testing is used to separate the imposter and genuine brightness temperatures based on their associated values of cloud ice (IWP) and liquid water path (LWP), given by coincidences of CloudSat Profiling Radar (CPR) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI). The study determines thresholds for IWP and LWP that allow optimal identification of imposter brightness temperatures of non-snowing and snowing clouds, which can mislead the passive microwave retrieval algorithms to falsely detect or miss the snowfall events. It is demonstrated that emission signal of supercooled liquid water in snowing clouds can lead to improved passive microwave retrieval of snowfall and conditioning the retrievals to the cloud IWP and LWP can result in marginal correction of the snowfall detection probability; however, reduce the probability of false alarm by 6%–8% over sea ice and open oceans.

Snowfall↗
NASA NTRS2016

Aerosol Optical Depth as Observed by the Mars Science Laboratory REMS UV Photodiodes

Systematic observations taken by the REMS (Rover Environmental Monitoring Station) UV (ultraviolet) photodiodes on a daily basis throughout the landed Mars Science Laboratory mission provide a highly useful tool for characterizing aerosols above Gale Crater. Radiative transfer modeling is used to model the approximately 1.75 Mars Years of observations taken to date taking into account multiple scattering from aerosols and the extended field of view of the REMS UV photodiodes. The retrievals show in detail the annual cycle of aerosol optical depth, which is punctuated with numerous short timescale events of increased optical depth. Dust deposition onto the photodiodes is accounted for by comparison with aerosol optical depth derived from direct imaging of the Sun by Mastcam. The effect of dust on the photodiodes is noticeable, but does not dominate the signal. Cleaning of dust from the photodiodes was observed in the season around solar longitude (Ls) equal to 270 degrees, but not during other seasons. Systematic deviations in the residuals from the retrieval fit are indicative of changes in aerosol effective particle size, with larger particles present during periods of increased optical depth. This seasonal dependence of aerosol particle size is expected as dust activity injects larger particles into the air, while larger aerosols settle out of the atmosphere more quickly leading to a smaller average particle size over time.

Smith, Michael D.↗
NASA NTRS2020

Derivation of Shortwave Radiometric Adjustments for SNPP and NOAA-20 VIIRS for the NASA MODIS-VIIRS Continuity Cloud Products

Climate studies, including trend detection and other time series analyses, necessarily require stable, well-characterized and long-term data records. For satellite-based geophysical retrieval datasets, such data records often involve merging the observational records of multiple similar, though not identical, instruments. The National Aeronautics and Space Administration (NASA)cloud mask(CLDMSK) and cloud-top and optical properties(CLDPROP) products are designed to bridge the observational records of the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard NASA’s Aqua satellite and the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the joint NASA/National Oceanic and Atmospheric Administration(NOAA)Suomi National Polar-orbiting Partnership (SNPP)satellite and NOAA’s new generation of operational polar-orbiting weather platforms(NOAA-20+).Early implementations of the CLDPROP algorithms on Aqua MODIS and SNPP VIIRS suffered from large intersensor biases in cloud optical properties that were traced back to relative radiometric inconsistency in analogous shortwave channels on both imagers, with VIIRS generally observing brighter top-of-atmosphere spectral reflectance than MODIS (e.g., up to 5%brighter in the 0.67μm channel). Radiometric adjustment factors for the SNPP and NOAA-20 VIIRS shortwave channels used in the cloud optical property retrievals are derived from an extensive analysis of the overlapping observational records with Aqua MODIS, specifically for homogenous maritime liquid water cloud scenes for which the viewing/solar geometry of MODIS and VIIRS match. Application of these adjustment factors to the VIIRS L1B prior to ingestion into the CLDMSK and CLDPROP algorithms yields improved intersensor agreement, particularly for cloud optical properties

relative radiometry↗
NASA NTRS2011

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Dubovik, O↗
NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗
NASA NTRS2017

Challenges in Discerning Atmospheric Composition in Directly Imaged Planets

One of the justifications motivating efforts to detect and characterize young extrasolar giant planets has been to measure atmospheric composition for comparison with that of the primary star. If the enhancement of heavy elements in the atmospheres of extrasolar giant planets, like it is for their solar system analogs, is inversely proportional to mass, then it is likely that these worlds formed by core accretion. However in practice it has been very difficult to constrain metallicity because of the complex effect of clouds. Cloud opacity varies both vertically and, in some cases, horizontally through the atmosphere. Particle size and composition, both of which impact opacity, are difficult challenges both for forward modeling and retrieval studies. In my presentation I will discuss systematic efforts to improve cloud studies to enable more reliable determinations of atmospheric composition. These efforts are relevant both to discerning composition of directly imaged young planets from ground based telescopes and future space based missions, such as WFIRST and LUVOIR.

young extrasolar giant planets↗
NASA NTRS1997

Summary of Research Report Cooperative Agreement

Several areas of work related to commercialization of technology developed at NASA Ames Research Center (ARC) are discussed in this report. The areas are: (1) perform a feasibility study to develop a software commercialization center is at ARC; (2) perform preliminary work for formation of joint development of sensor technology for telemedicine applications; (3) development of a discovery interview process and staff training to assist the commercialization of technology developed at Ames, specifically aimed at working with researchers; (4) develop partners to further develop and commercialize image compression technology developed at AMES; (5) assist efforts to commercialize a software technology which imparts the ability to establish relevance-based retrieval in the handling of large repositories of information; (6) explore the development of cryocooler technology using pulse tube refrigeration; (7) assess interest in commercialization of a new method of measuring skin friction drag on wind tunnel models using liquid crystal material; (8) attempt to incorporate emerging technologies in the infrastructure of natural hazards mitigation; and (9) forming a nonprofit organization, "The Bootstrap Alliance", whose mission is to promote the use of digital technologies for collaborative problem solving. The results of these initiatives are discussed.

Source record↗
NASA NTRS1999

Variability of Convective Precipitation from TRMM Microwave Imager (TMI)

Tropical precipitation generally occurs in two distinguishable forms: convective and stratiform. The two different types of precipitation systems have considerably different vertical profiles of latent heat release that has a crucial role in driving the circulation of the atmosphere. Thus, it is very important to study the variability of convective and stratiform precipitation. This paper presents variability of convective precipitation estimated from TRMM Microwave Imager (TMI). The convective/stratiform precipitation areas are classified using a combined texture-based and polarization-based algorithm. Surface rainfall rates are retrieved using the Goddard Profiling algorithm (Gprof). We will examine the spatial and temporal variability of convective precipitation for 1998. In addition, convective precipitation computed from TMI will be compared with those from the space borne Precipitation Radar (PR) and the ground-based radars for several cases.

Hong, Ye↗