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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

TRMM .25 deg x .25 deg Gridded Precipitation Text Product

Since the launch of the Tropical Rainfall Measuring Mission (TRMM), the Precipitation Measurement Missions science team has endeavored to provide TRMM precipitation retrievals in a variety of formats that are more easily usable by the broad science community than the standard Hierarchical Data Format (HDF) in which TRMM data is produced and archived. At the request of users, the Precipitation Processing System (PPS) has developed a .25 x .25 gridded product in an easily used ASCII text format. The entire TRMM mission data has been made available in this format. The paper provides the details of this new precipitation product that is designated with the TRMM designator 3G68.25. The format is packaged into daily files. It provides hourly precipitation information from the TRMM microwave imager (TMI), precipitation radar (PR), and TMI/PR combined rain retrievals. A major advantage of this approach is the inclusion only of rain data, compression when a particular grid has no rain from the PR or combined, and its direct ASCII text format. For those interested only in rain retrievals and whether rain is convection or stratiform, these products provide a huge reduction in the data volume inherent in the standard TRMM products. This paper provides examples of the 3G68 data products and their uses. It also provides information about C tools that can be used to aggregate daily files into larger time samples. In addition, it describes the possibilities inherent in the spatial sampling which allows resampling into coarser spatial sampling. The paper concludes with information about downloading the gridded text data products.

Stocker, Erich↗
DOE OSTI2021

Laser-induced electron diffraction of the ultrafast umbrella motion in ammonia

Visualizing molecular transformations in real-time requires a structural retrieval method with Ångström spatial and femtosecond temporal atomic resolution. Imaging of hydrogen-containing molecules additionally requires an imaging method sensitive to the atomic positions of hydrogen nuclei, with most methods possessing relatively low sensitivity to hydrogen scattering. Laser-induced electron diffraction (LIED) is a table-top technique that can image ultrafast structural changes of gas-phase polyatomic molecules with sub-Ångström and femtosecond spatiotemporal resolution together with relatively high sensitivity to hydrogen scattering. Here, we image the umbrella motion of an isolated ammonia molecule (NH3) following its strong-field ionization. Upon ionization of a neutral ammonia molecule, the ammonia cation (NH3+) undergoes an ultrafast geometrical transformation from a pyramidal (ΦHNH=107°) to planar (ΦHNH=120°) structure in approximately 8 femtoseconds. Using LIED, we retrieve a near-planar (ΦHNH=117 ± 5°) field-dressed NH3+ molecular structure 7.8−9.8 femtoseconds after ionization. Our measured field-dressed NH3+ structure is in excellent agreement with our calculated equilibrium field-dressed structure using quantum chemical ab initio calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2014

Assessment of the Accuracy of the Conventional Ray-Tracing Technique: Implications in Remote Sensing and Radiative Transfer Involving Ice Clouds.

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþIGOM are considered as a benchmark because the IITM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþIGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 micrometers) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 micrometers biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10Wm(exp 2).

remote sensing↗
NASA NTRS2016

Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

Spectrally-based depth-retrieval models↗
NASA NTRSDate not supplied

Creating Near Real-time Hourly VIIRS Radiance Mosaic over Polar Regions from SatCORPS Global Cloud Composite (GCC)

While polar orbiting satellites are essential in providing the needed observations over polar regions for data assimilation, weather diagnoses/forecasting, and flight guidance and situation awareness in airborne field campaigns, there is limited temporal coverage. Often, polar mosaics are created by overlaying multiple satellite imagers on top of each other which can lead to transition lines and discontinuities in the data products. To help ease some of these shortcomings, we utilize the NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) Mosaic algorithm for optimally fusing and merging selected imager radiances from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the Suomi National polar-orbiting Partnership (SNPP), Joint Polar Satellite System (JPSS-1), and JPSS-2 satellites, and the MODerate resolution Imaging Spectroradiometer (MODIS) instruments onboard AQUA and TERRA satellites. Since multiple satellites overpasses and instruments are used in creating hourly 3-km composites over the polar regions, selection of the best satellite data for each 3-km composite pixel is based on aggregated ranking of satellite resolution, time, viewing zenith angle, and distance from terminator. This ranking system provides a smoother transition and improves data discontinuity in the merged output resulting in a more seamless polar region dataset. We will discuss the use of this near real-time dataset to support polar airborne field campaigns and SatCORPS satellite-derived Global Cloud Composite (GCC) generation.

Satellite composites↗
NASA NTRS2002

Airborne Sunphotometer Measurements of Aerosol Optical Depth and Columnar Water Vapor During the Puerto Rico Dust Experiment, and Comparison with Land, Aircraft, and Satellite Measurements

Analyses of aerosol optical depth (AOD) and columnar water vapor (CWV) measurements obtained with the six-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) mounted on a twin-engine aircraft during the summer 2000 Puerto Rico Dust Experiment are presented. In general, aerosol extinction values calculated from AATS-6 AOD measurements acquired during aircraft profiles up to 5 km ASL reproduce the vertical structure measured by coincident aircraft in-situ measurements of total aerosol number and surface area concentration. Calculations show that the spectral dependence of AOD was small (mean Angstrom wavelength exponents of approximately 0.20) within three atmospheric layers defined as the total column beneath the top of each aircraft profile, the region beneath the trade wind inversion, and the region within the Saharan Air Layer (SAL) above the trade inversion. This spectral behavior is consistent with attenuation of incoming solar radiation by large dust particles or by dust plus sea salt. Values of CWV calculated from profile measurements by AATS-6 at 941.9 nm and from aircraft in-situ measurements by a chilled mirror dewpoint hygrometer agree to within approximately 4% (0.13 g/sq cm). AATS-6 AOD values measured on the ground at Roosevelt Roads Naval Air Station and during low altitude aircraft runs over the adjacent Cabras Island aerosol/radiation ground site agree to within 0.004 to 0.030 with coincident data obtained with an AERONET Sun/sky Cimel radiometer located at Cabras Island. For the same observation times, AERONET retrievals of CWV exceed AATS-6 values by a mean of 0.74 g/sq cm (approximately 21 %) for the 2.9-3.9 g/sq cm measured by AATS-6. Comparison of AATS-6 aerosol extinction values obtained during four aircraft ascents over Cabras Island with corresponding values calculated from coincident aerosol backscatter measurements by a ground-based micro-pulse lidar (MPL-Net) located at Cabras yields a similar vertical structure above the trade inversion. Finally, AATS-6 AOD values measured during low altitude aircraft traverses over the ocean are compared with corresponding AOD values retrieved over water from upwelling radiance measurements by the MODIS, TOMS, and GOES-8 Imager satellite sensors, with mixed results. These exercises highlight the need for continued satellite sensor comparison/validation studies to improve satellite AOD retrieval algorithms, and the usefulness of airborne sunphotometer measurements in the validation process.

Livingston, John M.↗
NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral instruments produce high-resolution and information-dense radiance spectra, thus offering the opportunity to reduce uncertainties in retrieval products. An optimal estimation-based cirrus cloud optical and microphysical product retrieval is under development for the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Earth Surface Mineral Dust Source Investigation (EMIT) instruments, and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder). The spectral coverage of all three instruments includes the ultraviolet, visible, and near-infrared. In this study a very fast radiative transfer model, the Principal Component-based Radiative Transfer Model in the solar spectral region (PCRTM-Solar), is used for forward modeling computations. This will reduce the computational burden in the forward radiance and Jacobian calculations as the cost function is minimized, enabling the entire AVIRIS, EMIT, and CLARREO-Pathfinder spectral range to be used in the optimal estimation framework. Using the entire spectrum will maximize the information content, resulting in a more robust and more accurate retrieval. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water. Preliminary results will be shown.

Jeffrey Mast↗
NASA NTRS2000

BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

Hall, Forrest G.↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES- Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2010

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within +/-0.016/km +/- 20% for at least two-thirds of land points and within +/-0.028/km +/- 20% for at least two-thirds of ocean points.

Burton, S. P.↗
NASA NTRS2019

Local Time Variation of Water Ice Clouds on Mars as Observed by THEMIS

The move of the Odyssey spacecraft during Mars Years 31 and 32 to an orbit with local time near 7:00 AM and PM has enabled the systematic retrieval of water icecloud optical depth using THEMIS thermal infrared images at a time of day not accessible from Mars Global Surveyor, Mars Reconnaissance Orbiter, or previousOdyssey observations. Because water ice clouds form by condensation, relatively small changes in atmospheric temperature can cause clouds to form or sublimatequickly, and there can be large changes in water ice cloud optical depth over the course of a day. Retrievals of water ice cloud optical depth using THEMISobservations show significant differences in cloud locations and optical depth as a function of local time and season. Cloud optical depth generally increases from theearliest (14:30) to latest (19:30) observations. During the aphelion season the increase from afternoon to evening is primarily associated with the thickening ofexisting clouds, while during the equinoctial and perihelion seasons there is a proportionally greater increase associated with the formation of clouds in the eveningat locations where clouds were not present during the afternoon.

Michael D Smith↗
NASA NTRS2018

Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing

Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) datahas shown that major aerosol pollution events with very highfine mode AOD (>1.0 in midvisible) in theChina/Korea/Japan region are often observed to be associated with significant cloud cover. This makesremote sensing of these events difficult even for high temporal resolution Sun photometer measurements.Possible physical mechanisms for these events that have high AOD include a combination of aerosolhumidification, cloud processing, and meteorological covariation with atmospheric stability andconvergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloudscreening algorithms now allow for unprecedented ability to monitor these extremefine mode pollutionevents. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening)provides an even more comprehensive assessment offine mode AOD than L2 in current and previous dataversions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA dailyaveragefine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remotesensing of AOD often did not retrieve and/or identify some of the highestfine mode AOD events in thisregion. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDAfinemode AOD was significantly higher in magnitude, particularly for the highest AOD events that were oftenassociated with significant cloudiness.

Eck, T. F.↗
NASA NTRS2012

MISR 17.6 KM Gridded Cloud Motion Vectors: Overview and Assessment

The MISR (Multi-angle Imaging SpectroRadiometer) instrument on the Terra satellite has been retrieving cloud motion vectors (CMVs) globally and almost continuously since early in 2000. In February 2012 the new MISR Level 2 Cloud product was publicly released, providing cloud motion vectors at 17.6 km resolution with improved accuracy and roughly threefold increased coverage relative to the 70.4 km resolution vectors of the current MISR Level 2 Stereo product (which remains available). MISR retrieves both horizontal cloud motion and height from the apparent displacement due to parallax and movement of cloud features across three visible channel (670nm) camera views over a span of 200 seconds. The retrieval has comparable accuracy to operational atmospheric motion vectors from other current sensors, but holds the additional advantage of global coverage and finer precision height retrieval that is insensitive to radiometric calibration. The MISR mission is expected to continue operation for many more years, possibly until 2019, and Level 2 Cloud has the possibility of being produced with a sensing-to-availability lag of 5 hours. This report compares MISR CMV with collocated motion vectors from arctic rawinsonde sites, and from the GOES and MODISTerra instruments. CMV at heights below 3 km exhibit the smallest differences, as small as 3.3 m/s for MISR and GOES. Clouds above 3 km exhibit larger differences, as large as 8.9 m/s for MISR and MODIS. Typical differences are on the order of 6 m/s.

MISR (Multi-angle Imaging SpectroRadiometer)↗
NASA NTRS2007

Cloud Motion Vectors from MISR using Sub-pixel Enhancements

The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging SpectroRadiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to co-registration and disparity assessment, and by imposing stronger quality control based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicates that CMVs pass the basic operational quality control 67% of the time, with rms differences - in speed of 2.4 m/s, in direction of 17 deg, and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 m/s, 17 deg and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminates a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 m/s for low clouds to 10 m/s for high clouds.

Davies, Roger↗
NASA NTRS1985

Flow velocity measurements by image processing of optically activated tracers

A computerized flow visualization technique capable of quantifying the flow field automatically has been developed. This technique uses afterglowing effect of optically activated phosphorescent particles to retrieve vectorial information on each trace. By using this information, in conjunction with computer image processing, the flow field of a free surface transient vortex was investigated.

Gharib, M.↗
DOE OSTI2022

Modeling and experimental validation of dynamical effects in Bragg coherent x-ray diffractive imaging of finite crystals

Bragg coherent diffractive imaging (BCDI) is a noninvasive microscopy technique that can visualize the shape and internal lattice deviations of crystals with nanoscale spatial resolution and picometer deformation sensitivity. Its strain imaging capability relies on Fourier transform–based iterative phase retrieval algorithms, which are mostly developed under the kinematical approximation. Such approximation prohibits the application of BCDI on larger crystals, which are commonly seen in most emerging functional materials. Understanding the dynamical effect in BCDI, as well as developing a validated method for modeling BCDI at the dynamical diffraction limit, is crucial for applying BCDI to hierarchical systems that contain micron-sized crystals and grains. Thus we report a comparative study on the impact of dynamical diffraction effects by comparing the reconstruction results from two measurements of the same crystal. Forward simulation is implemented to show subtle changes of interference fringes in the diffraction pattern due to the dynamical diffraction, and is compared directly with the experimental data.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Space-Based Near-Infrared CO2 Measurements: Testing the Orbiting Carbon Observatory Retrieval Algorithm and Validation Concept Using SCIAMACHY Observations over Park Falls, Wisconsin

Space-based measurements of reflected sunlight in the near-infrared (NIR) region promise to yield accurate and precise observations of the global distribution of atmospheric CO2. The Orbiting Carbon Observatory (OCO) is a future NASA mission, which will use this technique to measure the column-averaged dry air mole fraction of CO2 (XCO2) with the precision and accuracy needed to quantify CO2 sources and sinks on regional scales (approx.1000 x 1000 sq km and to characterize their variability on seasonal timescales. Here, we have used the OCO retrieval algorithm to retrieve XCO2 and surface pressure from space-based Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) measurements and from coincident ground-based Fourier transform spectrometer (FTS) measurements of the O2 A band at 0.76 mm and the 1.58 mm CO2 band for Park Falls,Wisconsin. Even after accounting for a systematic error in our representation of the O2 absorption cross sections, we still obtained a positive bias between SCIAMACHY and FTS XCO2 retrievals of approx.3.5%. Additionally, the retrieved surface pressures from SCIAMACHY systematically underestimate measurements of a calibrated pressure sensor at the FTS site. These findings lead us to speculate about inadequacies in the forward model of our retrieval algorithm. By assuming a 1% intensity offset in the O2 A band region for the SCIAMACHY XCO2 retrieval, we significantly improved the spectral fit and achieved better consistency between SCIAMACHY and FTS XCO2 retrievals. We compared the seasonal cycle of XCO2 at Park Falls from SCIAMACHY and FTS retrievals with calculations of the Model of Atmospheric Transport and Chemistry/Carnegie-Ames-Stanford Approach (MATCH/CASA) and found a good qualitative agreement but with MATCH/CASA underestimating the measured seasonal amplitude. Furthermore, since SCIAMACHY observations are similar in viewing geometry and spectral range to those of OCO, this study represents an important test of the OCO retrieval algorithm and validation concept using NIR spectra measured from space. Finally, we argue that significant improvements in precision and accuracy could be obtained from a dedicated CO2 instrument such as OCO, which has much higher spectral and spatial resolutions than SCIAMACHY. These measurements would then provide critical data for improving our understanding of the carbon cycle and carbon sources and sinks.

carbon dioxide↗