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At least 487 records · Page 27
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NASA NTRS2020

An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation

To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1°×1° daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1°×1° grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

Aerosol↗
NASA NTRSDate not supplied

The PACE-MAPP Polarized Ocean Bio-optical Model

The MAPP polarimeter retrieval algorithm, originally developed for the airborne NASA GISS Research Scanning Polarimeter, is being adapted to the PACE observing system to allow for a simultaneous retrieval of aerosol, thin cirrus, and ocean products using both PACE polarimeters and the OCI shortwave infrared channels. Here, we describe the polarized ocean bio-optical model we have developed for PACE-MAPP, which is designed to use a combination of homogenous and coated spheres to more accurately model the absorption and backscattering properties of algal and non-algal particles, and which also includes absorption by colored dissolved organic matter. We first use Lorenz-Mie computations to create lookup tables to accurately and efficiently characterize the optical properties of homogeneous and coated spheres embedded in water for PACE. We then use these lookup tables to develop a bio-optical model that consists of an external mixture of homogeneous (non-algal) and coated (algal) spheres. Lastly, we use the bio-optical model in forward radiative transfer computations to perform inversions of MODIS remote sensing reflectance for a variety of ocean regions. We explore the sensitivity of these inversions to ocean constituent inherent optical properties.

James Allen↗
NASA NTRS2021

Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

Since early 2000, NASA's Multi-angle Imaging SpectroRadiometer (MISR) instrument has been performing remote sensing retrievals of aerosol optical properties from the polar-orbiting Terra spacecraft. A noteworthy aspect of MISR observations over the ocean is that, for much of the Earth, some of the multi-angle views have contributions from solar reflection by the ocean surface (glint, or glitter), while others do not. Aerosol retrieval algorithms often discard these glint-influenced observations because they can overwhelm the signal and are difficult to predict without knowledge of the (wind-speed-driven) ocean surface roughness. However, theoretical studies have shown that multi-angle observations of a location at geometries with and without reflected sun glint can be a rich source of information, sufficient to support simultaneous retrieval of both the aerosol state and the wind speed at the ocean surface. We are in the early stages of creating such an algorithm. In this paper, we describe our assessment of the appropriate level of parameterization for simultaneous aerosol and ocean surface property retrievals using sun glint. For this purpose, we use generalized nonlinear retrieval analysis (GENRA), an information content assessment (ICA) technique employing Bayesian inference, and simulations from the Ahmad–Fraser iterative radiative transfer code. We find that four parameters are suitable: aerosol optical depth (τ), particle size distribution (expressed as the fine mode fraction f of small particles in a bimodal size distribution), surface wind speed (w), and relative humidity (r, to define the aerosol water content and complex refractive index). None of these parameters define ocean optical properties, as we found that the aerosol state could be retrieved with the nine MISR near-infrared views alone, where the ocean body is strongly absorbing in the open ocean. We also found that retrieval capability varies with observation geometry and that as τ increases so does the ability to determine aerosol intensive optical properties (r and f, while it decreases for w). Increases in w decrease the ability to determine the true value of that parameter but have minimal impact on retrieval of aerosol properties. We explored the benefit of excluding the two most extreme MISR view angles for which radiative transfer with the plane-parallel approximation is less certain, but we found no advantage in doing so. Finally, the impact of treating wind speed as a scalar parameter, rather than as a two-parameter directional wind, was tested. While the simpler scalar model does contribute to overall aerosol uncertainty, it is not sufficiently large to justify the addition of another dimension to parameter space. An algorithm designed upon these principles is in development. It will be used to perform an atmospheric correction with MISR for coincident ocean color (OC) observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on the NASA Terra spacecraft. Unlike MISR, MODIS is a single-view-angle instrument, but it has a more complete set of spectral channels ideal for determination of optical ocean properties. The atmospheric correction of MODIS OC data can therefore benefit from MISR aerosol retrievals. Furthermore, higher-spatial-resolution data from coincident MISR observations may also improve glint screening.

Kirk Knobelspiesse↗
NASA NTRS2011

Utilization of Ancillary Data Sets for Conceptual SMAP Mission Algorithm Development and Product Generation

The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors, including its availability and ease of use, its inherent error and resulting impact on the overall soil moisture or freeze/thaw retrieval accuracy, and its compatibility with similar choices made by the SMOS mission. All decisions regarding SMAP ancillary data sources would be fully documented by the SMAP Project and made available to the user community.

freeze/thaw↗
NASA NTRS2003

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

During the three years of finding, we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Wentz, Frank J.↗
NASA NTRS2003

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

During the three years of fundin& we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Lawrence, Richard J.↗
NASA NTRS2012

Comparisons of Aquarius Measurements over Oceans with Radiative Transfer Models at L-Band

The Aquarius/SAC-D spacecraft includes three L-band (1.4 GHz) radiometers dedicated to measuring sea surface salinity. It was launched in June 2011 by NASA and CONAE (Argentine space agency). We report detailed comparisons of Aquarius measurements with radiative transfer model predictions. These comparisons are used as part of the initial assessment of Aquarius data and to estimate the radiometer calibration bias and stability. Comparisons are also being performed to assess the performance of models used in the retrieval algorithm for correcting the effect of various sources of geophysical "noise" (e.g. Faraday rotation, surface roughness). Such corrections are critical in bringing the error in retrieved salinity down to the required 0.2 practical salinity unit on monthly global maps at 150 km by 150 km resolution.

Dinnat, E.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-29194-DND

The Stratospheric Aerosol and Gas Experiment (SAGE) III instrument was deployed on the International Space Station (ISS) in early March 2017. SAGE III/ISS is the latest in the NASA lineage of solar occultation satellite instruments designed to monitor the vertical distribution of aerosol, ozone and other trace gases in the upper atmosphere. Originally built in the early 2000s, the SAGE III/ISS instrument required extensive testing and refurbishment prior to deliver to ISS, including the replacement of the neutral density filter that has been associated with some instrument response issues during the METEOR/3M mission. In particular, METEOR/3M measurements of the oxygen A-band absorption feature near 762 nm that were to be utilized to retrieve profiles of temperature and pressure were adversely affected by this instrument issue. Preliminary examination of the SAGE III/ISS oxygen A-band spectra indicate that the measurements are of higher fidelity than from the METEOR/3M instrument, which may permit successful retrieval of science quality temperature and pressure products. In this paper, we will provide an overview of the temperature and pressure retrieval algorithm, present preliminary analyses of the SAGE III/ISS oxygen A-band measurements, and an initial assessment of the quality of the temperature and pressure retrievals.

Michael Pitts↗
DOE OSTI2020

A three-dimensional reconstruction algorithm for scanning transmission electron microscopy data from thick samples

Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal series of four-dimensional scanning transmission electron microscopy (4D-STEM) data and transcends the prevalent structure retrieval algorithm assumption of a very thin specimen homogenous along the optic axis. We demonstrate this approach by reconstructing the different layers of a lead iridate (Pb$_2$Ir$_2$O$_7$) and yttrium-stabilized zirconia (Y$_{0.095}$Zr$_{0.905}$O$_2$) heterostructure from data acquired with the specimen in a single plan-view orientation, with the epitaxial layers stacked along the beam direction.

Brown, Hamish G↗
NASA NTRSDate not supplied

Atmospheric Infrared Sounder Version 7 Near-Real-Time Product and Imagery Released by NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of data processing, archive, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. The GES DISC provides service to both AIRS routine and Near Real-Time (NRT) products. The AIRS NRT products are an important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). In collaboration with AIRS Project, the GES DISC has just released products from the Version 7 algorithm. The new version algorithm provides significant improvements over the previous version. The most substantial advances are: improved consistency between day and night water vapor; improved total column ozone and temperature; improved infrared-only (IR-only) retrievals, especially in high latitude regions; an improved Stochastic Cloud Clearing Neural Network used as a first guess at the initial value in the iterative retrieval process; and removal of ambiguity in surface classification in the IR-only retrieval algorithm. In addition, the GES DISC produces AIRS NRT imagery. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The data products used to generate this imagery include atmospheric temperature, humidity, precipitation, cloud, Dust Score, CO, and SO2. In this presentation, we will demonstrate visualization of the AIRS NRT imagery from the new Version 7, and demonstrate some improvements over the previous version. Progress on improving the AIRS NRT imagery, a collaboration project with the AIRS Applications Development Team at NASA Jet Propulsion Laboratory (JPL), will also be presented.

Feng Ding↗
NASA NTRS1992

Vertical resolution and accuracy of atmospheric infrared sounding spectrometers

A theoretical analysis is performed to evaluate the accuracy and vertical resolution of atmospheric profiles obtained with the HIRS/2, GOES I/M, and HIS instruments. In addition, a linear simultaneous retrieval algorithm is used with aircraft observations to validate the theoretical predictions. Both theoretical and observational results clearly indicate that the accuracy and vertical resolution of the retrieval profile would be improved by high spectral resolution and broad spectral coverage of infrared radiance measurements. The HIS is found to possess the equivalent of 11 pieces of temperature- and 9 pieces of water vapor-independent precise measurements. The characteristics for temperature include a vertical resolution of 1-6 km with an accuracy of 1 K and for water vapor a vertical resolution of 0.5-3.0 km with an accuracy of 3 K in dewpoint temperature. The HIS is a factor of 2-3 times better in vertical resolution and a factor of 2 times better in accuracy than the GOES I/M and HIRS/2 filter radiometers.

Huang, Hung-Lung↗
NASA NTRS1993

Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. II - Emission-source and generalized weighting-function properties of a time-dependent cloud-radiation model

The foremost physical aspects of microphysical-radiative interactions that control the formation and modulation of frequency-dependent passive microwave TB over a continental cold-rain precipitation system are explained within the framework of the essential ingredients of a physically based precipitation-retrieval algorithm. The analysis is based on a modeling study in which a 3D cloud model has provided the objective basis for generating an extensive set of microphysical profiles that describe numerous precipitation features in the course of the evolution of a continental hail storm. A summary of the various components of the algorithm, as well as the surface rain rates, is given. The algorithm employs the cloud model to provide a consistent and objectively generated source of detailed microphysical information as the underpinnings to an inversion-based perturbative retrieval scheme.

Mugnai, Alberto↗
NASA NTRS2000

Profiling of Atmospheric Water Vapor from the SSM/T-2 Radiometric Measurements

An advantage of using the millimeter-wave measurements for water vapor profiling is the ability to probe beyond a moderate cloud cover. Such a capability has been demonstrated from an airborne MIR (Millimeter-wave Imaging Radiometer) flight over the Pacific Ocean during an intense observation period of TOGA/COARE (Tropical Ocean Global Atmosphere/ Couple Ocean Atmospheric Response Experiment) in early 1993. A Cloud Lidar System (CLS) and MODIS Airborne Simulator (MAS) were on board the same aircraft to identify the presence of clouds and cloud type. The retrieval algorithm not only provides output of a water vapor profile, but also the cloud liquid water and approximate cloud altitude required to satisfy convergence of the retrieval. The validity of these cloud parameters has not been verified previously. In this document, these cloud parameters are compared with those derived from concurrent measurements from the CLS and AMPR (Advanced Microwave Precipitation Radiometer).

Wang, J. R.↗
NASA NTRS2006

SAGE III solar ozone measurements: Initial results

Results from two retrieval algorithms, o3-aer and o3-mlr , used for SAGE III solar occultation ozone measurements in the stratosphere and upper troposphere are compared. The main differences between these two retrieved (version 3.0) ozone are found at altitudes above 40 km and below 15 km. Compared to correlative measurements, the SAGE II type ozone retrievals (o3-aer) provide better precisions above 40 km and do not induce artificial hemispheric differences in upper stratospheric ozone. The multiple linear regression technique (o3_mlr), however, can yield slightly more accurate ozone (by a few percent) in the lower stratosphere and upper troposphere. By using SAGE III (version 3.0) ozone from both algorithms and in their preferred regions, the agreement between SAGE III and correlative measurements is shown to be approx.5% down to 17 km. Below 17 km SAGE III ozone values are systematically higher, by 10% at 13 km, and a small hemispheric difference (a few percent) appears. Compared to SAGE III and HALOE, SAGE II ozone has the best accuracy in the lowest few kilometers of the stratosphere. Estimated precision in SAGE III ozone is about 5% or better between 20 and 40 km and approx.10% at 50 km. The precision below 20 km is difficult to evaluate because of limited coincidences between SAGE III and sondes. SAGE III ozone values are systematically slightly larger (2-3%) than those from SAGE II but the profile shapes are remarkably similar for altitudes above 15 km. There is no evidence of any relative drift or time dependent differences between these two instruments for altitudes above 15-20 km.

Wang, Hsiang-Jui↗
NASA NTRS2016

A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

Chen, Zhong↗
NASA NTRS2005

Processing GPS Occultation Data To Characterize Atmosphere

GOAS [Global Positioning System (GPS) Occultation Analysis System] is a computer program that accepts signal-occultation data from GPS receivers aboard low-Earth-orbiting satellites and processes the data to characterize the terrestrial atmosphere and, in somewhat less comprehensive fashion, the ionosphere. GOAS is very robust and can be run in an unattended semi-operational processing mode. It features sophisticated retrieval algorithms that utilize the amplitudes and phases of the GPS signals. It incorporates a module that, using an assumed atmospheric refractivity profile, simulates the effects of the retrieval processing system, including the GPS receiver. GOAS utilizes the GIPSY software for precise determination of orbits as needed for calibration. The GOAS output for the Earth s troposphere and mid-to-lower stratosphere consists of high-resolution (<1 km) profiles of density, temperature, pressure, atmospheric refractivity, bending angles of signals, and water-vapor content versus altitude from the Earth s surface to an altitude of 30 km. The GOAS output for the ionosphere consists of electron-density profiles from an altitude of about 50 km to the altitude of a satellite, plus parameters related to the rapidly varying structure of the electron density, particularly in the E layer of the ionosphere.

Hajj, George↗
NASA NTRS2019

A Fast Vector Radiative Transfer Model for the Atmosphere-Ocean Coupled System

To infer atmospheric and oceanic constituent properties from polarimetric observations, an efficient and accurate retrieval algorithm is desirable. In-line radiative transfer calculations are indispensable if a large state vector, including both atmospheric profiles and surface properties, is used to improve retrieval accuracy. However, in-line radiative transfer calculations are usually not computationally efficient for remote sensing applications. Therefore, there is a pressing need to develop an accurate and fast vector radiative transfer model (RTM) to fully utilize satellite polarimetric observations. This paper reports on a fast vector RTM, referred to as TAMU-VRTM, in support of polarimetric remote sensing, which is capable of simulating the Stokes vector values observed at the top of the atmosphere and at the surface by fully considering absorption, scattering, and emission in the atmosphere and ocean. Gaseous absorption is parameterized with respect to gas concentration, temperature, and pressure, by using a regression method applicable to an inhomogeneous atmospheric path. An efficient two-component approach combining the small angle approximation and the adding-doubling method is utilized to solve the vector radiative transfer equation (RTE). The thermal emission component of the RTE solution is obtained by an efficient doubling process. The air-sea interface is treated as a wind-ruffled rough surface in the model to mimic a realistic ocean surface. Several oceanic optical property models are introduced to model ocean inherent optical properties. To demonstrate the applicability of the TAMUVRTM, simulations are compared with satellite observations, and results from other vector radiative transfer methods including benchmarks.

radiative transfer in coupled atmosphere-ocean sys↗
NASA NTRS1995

A Bayesian approach to microwave precipitation profile retrieval

A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. A multivariate lognormal prior probability distribution contains the covariance information about hydrometeor distribution that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrieval method is tested with data from the Advanced Microwave Precipitation Radiometer (10, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify the retrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many of the retrieval errors are traced to problems with the cloud model microphysical information, and future improvements to the algorithm are suggested.

Evans, K. Franklin↗