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At least 181 records · Page 10

An Alternate Method for Estimating Dynamic Height from XBT Profiles Using Empirical Vertical Modes

A technique is presented that applies modal decomposition to estimate dynamic height (0-450 db) from Expendable BathyThermograph (XBT) temperature profiles. Salinity-Temperature-Depth (STD) data are used to establish empirical relationships between vertically integrated temperature profiles and empirical dynamic height modes. These are then applied to XBT data to estimate dynamic height. A standard error of 0.028 dynamic meters is obtained for the waters of the Gulf of Alaska- an ocean region subject to substantial freshwater buoyancy forcing and with a T-S relationship that has considerable scatter. The residual error is a substantial improvement relative to the conventional T-S correlation technique when applied to this region. Systematic errors between estimated and true dynamic height were evaluated. The 20-year-long time series at Ocean Station P (50 deg N, 145 deg W) indicated weak variations in the error interannually, but not seasonally. There were no evident systematic alongshore variations in the error in the ocean boundary current regime near the perimeter of the Alaska gyre. The results prove satisfactory for the purpose of this work, which is to generate dynamic height from XBT data for coanalysis with satellite altimeter data, given that the altimeter height precision is likewise on the order of 2-3 cm. While the technique has not been applied to other ocean regions where the T-S relation has less scatter, it is suggested that it could provide some improvement over previously applied methods, as well.

Lagerloef, Gary S. E.↗

Fiber Optic Thermal Health Monitoring of Aerospace Structures and Materials

A new technique is presented for thermographic detection of flaws in materials and structures by performing temperature measurements with fiber Bragg gratings. Individual optical fibers with multiple Bragg gratings employed as surface temperature sensors were bonded to the surfaces of structures with subsurface defects or thickness variations. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. The data obtained from grating sensors were further analyzed with thermal modeling to reveal particular characteristics of the interested areas. These results were found to be consistent with those from conventional thermography techniques. Limitations of the technique were investigated using both experimental and numerical simulation techniques. Methods for performing in-situ structural health monitoring are discussed.

Wu, Meng-Chou↗

Arcjet Testing of Advanced Conformal Ablative TPS

A conformable TPS over a rigid aeroshell has the potential to solve a number of challenges faced by traditional rigid TPS materials (such as tiled Phenolic Impregnated Carbon Ablator (PICA) system on MSL. The compliant (high strain to failure) nature of the conformable ablative materials will allow integration of the TPS with the underlying aeroshell structure much easier and enable monolithic-like configuration and larger segments (or parts) to be used. In May of 2013 the CA250 project executed an arcjet test series in the Ames IHF facility to evaluate a phenolic-based conformal system (named Conformal-PICA) over a range of test conditions from 40-400Wcm2. The test series consisted of four runs in the 13-inch diameter nozzle. Test models were based on SPRITE configuration (a 55-deg sphere cone), as it was able to provide a combination of required heat flux, pressure and shear within a single entry. The preliminary in-depth TC data acquired during that test series allowed a mid-fidelity thermal response model for conformal-PICA to be created while testing of seam models began to address TPS attachment and joining of multiple segments for future fabrication of large-scale aeroshells. Discussed in this paper are the results.

Arcjet Testing↗

An Example of Aerosol Pattern Variability Over Bright Surface Using High Resolution MODIS MAIAC: The Eastern and Western Areas of the Dead Sea and Environs

The extreme rate of evaporation of the Dead Sea (DS) has serious implications for the surrounding area, including atmospheric conditions. This study analyzes the aerosol properties over the western and eastern parts of the DS during the year 2013, using MAIAC (Multi-Angle Implementation of Atmospheric Correction) for MODIS, which retrieves aerosol optical depth (AOD) data at a resolution of 1km. The main goal of the study is to evaluate MAIAC over the study area and determine, for the first time, theprevailing aerosol spatial patterns. First, the MAIAC-derived AOD data was compared with data from three nearby AERONET sites (Nes Ziona - an urban site, and Sede Boker and Masada - two arid sites), and with the conventional Dark Target (DT) and Deep Blue (DB) retrievals for the same days and locations, on a monthly basis throughout 2013. For the urban site, the correlation coefficient (r) for DTDB products showed better performance than MAIAC (r = 0.80, 0.75, and 0.64 respectively) year-round. However, in the arid zones, MAIAC showed better correspondence to AERONET sites than the conventional retrievals (r = 0.58 - 0.60 and 0.48 - 0.50 respectively). We investigated the difference in AOD levels, and its variability, between the Dead Sea coasts on a seasonal basis and calculated monthlyseasonal AOD averages for presenting AOD patterns over arid zones. Thus, we demonstrated that aerosol concentrations show a strong preference for the western coast, particularly during the summer season. This preference, is most likely a result of local anthropogenic emissions combined with the typical seasonal synoptic conditions, the Mediterranean Sea breeze, and the region complex topography. Our results also indicate that a large industrial zone showed higher AOD levels compared to an adjacent reference-site, i.e., 13 percent during the winter season.

AOD↗

Understanding and Improving Model Representation of Aerosol Optical Properties for a Chinese Haze Event Measured During KORUS-AQ

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM2.5, often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m2 g−1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm−3 in the model vs. observed average of 1.5 g cm−3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

Pablo E. Saide↗

Oceanic upper mixed layer depth determination by the use of satellite data

A method has been developed to determine the oceanic daily mean mixed layer depth from satellite observations and a mixed layer thermal inertia (MLTI) model. The algorithms were developed to use remotely-sensed values of sea surface temperature, albedo, and surface wind speeds to calculate the thermal inertia and to predict changes in subsurface diurnal mixed layer depth. The MLTI model, based on a mixed layer model of the upper ocean, has been used to simulate the diurnal mixing process and thermal inertia distribution in the Sargasso Sea around 34 deg N, 70 deg W. Sea surface temperature and albedo have been obtained from the NOAA7-AVHRR images. Surface wind speeds have been derived from the Scanning Multichannel Microwave Radiometer (SMMR) aboard Nimbus 7. Image processing was performed for images gathered between June and July 1982. The daily mean mixed layer depths predicted by the MLTI model agree well with data gathered at the LOTUS mooring located in the Sargasso Sea. This suggests that vertical mixing is the dominant physical process that controls the thermal inertia distribution in the midocean, far from major current systems, and that remote sensing is a promising tool to study such upper ocean processes.

Yan, Xiao-Hai↗

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open-forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap-filled. These data are available to download from Bonner, Smyth, et al. at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process-based snow model. We demonstrate the utility of these data with a modeling experiment that explores open-forest differences and identifies opportunities for improvements in model representation.

54 ENVIRONMENTAL SCIENCES↗

Cosmic ray intensity variations observed at Matsushiro (220 M.W.E. in depth)

Cosmic ray data from Matsushiro underground station were analyzed for four years (1981 to 84). It is found that a marked semi-annual intensity variation has been observed in this period. Solar diurnal and semi-diurnal variations have also been observed. After correcting for the spurious sidereal diurnal variation arising from the anisotropy responsible for the solar semi-diurnal variation (Nagashima et al., 1983), it is found that the corrected sidereal diurnal variation is consistent with those so far reported.

Yasue, S.↗

Characterization of Cirrus Clouds From Multi-pass AVIRIS Data

The optical depth and reflectance from thin cirrus clouds are calculated from two passes of AVIRIS over a scene in Florida. One of the passes contained partial cirrus cover, the other did not. Optical depths of 0.2 were calculated and the reflectance of the cloud at 1.381 micrometers was 0.026 The detection limit for cirrus is approximately an order of magnitude less in reflectance.

Goetz, Alexander F. H.↗

Machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado and New Mexico

Temporally continuous snow depth estimates are vital for understanding changing snow patterns in the Arctic and impacts on permafrost. We trained random forest machine learning models to predict snow depth from temperature data recorded at or just below the ground surface. Training data was collected at the Teller 27 Watershed and Kougarok 64 Hillslope during the 2021 - 2022 water year on the Seward Peninsula, Alaska using distributed temperature profiling (DTP) systems. We then applied this model to other sites where ground surface or shallow soil temperature data was available for at least one water year (see Related Datasets). Many of these temperature measurements were collocated with snow depth observations. Ground surface temperature (i.e. snow-ground interface temperature) is easy to measure using small, cheap and easy-to-deploy temperature sensors such as iButtons and TinyTags, and such measurements have previously been used to calculate a variety of snow metrics (e.g. snow onset date). However, this is the first study to estimate snow depth directly from ground surface temperature data. The present dataset contains one *.csv file which includes machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado, and New Mexico and one *.kml file including the locations of sites with snow depth predictions. No training data predictions are included in the *.csv file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Effect of Wind Speed on Aerosol Optical Depth over Remote Oceans, Based on Data from the Maritime Aerosol Network

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (approx. 0.004 - 0.005), even for strong winds over 10m/s. The relationships show significant scatter (correlation coefficients typically in the range 0.3 - 0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used

Smirnov, A.↗

Winter Arctic Sea Ice Thickness from ICESat-2 Freeboards

NASA’s ICESat-2 mission was launched in September 2018 with the primary goal of monitoring our rapidly changing polar regions. The sole instrument onboard, the Advanced Topographic Laser Altimeter System (ATLAS), is now providing routine, very high-resolution, surface elevation data across the globe, including the Arctic and Southern Oceans. In this study we demonstrate our new processing chain for converting the along-track ICESat-2 sea ice freeboard product (ATL10) into sea ice thickness, focusing our initial efforts on the Arctic Ocean. For this conversion we primarily make use of snow depth and density data from the NASA Eulerian Snow on Sea Ice Model (NESOSIM). The coarse resolution (~100 km) snow data are redistributed onto the high resolution (~30 - 100 m) ATL10 freeboards using relationships obtained from snow depth and freeboard data collected by NASA’s Operation IceBridge mission. We present regional sea ice thickness distributions and highlight their seasonal evolution through our first winter-season of data collection. We include ice thickness uncertainty estimates, while also acknowledging the limitations of these estimates. We generate a gridded monthly thickness product and compare this with various monthly sea ice thickness estimates obtained from ESA’s CryoSat-2 satellite mission, with ICE 33 Sat-2 showing consistently lower thicknesses. Finally, we compare our February/March 2019 thickness estimates to ICESat February/March (19th February – 21st March) 2008 ice thickness estimates using the same input assumptions, which show a ~0.40 m or ~21% thinning across an inner Arctic Ocean domain in this 11-year time period.

Alek A Petty↗

Real-Time Measurements of Aft Dome Insulation Erosion on Space Shuttle Reusable Solid Rocket Motor

Real-time erosion of aft dome internal insulation was measured with internal instrumentation on a static test of a lengthened version of the Space Shuffle Reusable Solid Rocket Motor (RSRM). This effort marks the first time that real-time aft dome insulation erosion (Le., erosion due to the combined effects of thermochemical ablation and mechanical abrasion) was measured in this kind of large motor static test [designated as Engineering Test Motor number 3 (ETM3)I. This paper presents data plots of the erosion depth versus time. The data indicates general erosion versus time behavior that is in contrast to what would be expected from earlier analyses. Engineers have long known that the thermal environment in the aft dome is severe and that the resulting aft dome insulation erosion is significant. Models of aft dome erosion involve a two-step process of computational fluid dynamics (CFD) modeling and material ablation modeling. This modeling effort is complex. The time- dependent effects are difficult to verify with only prefire and postfire insulation measurements. Nozzle vectoring, slag accumulation, and changing boundary conditions will affect the time dependence of aft dome erosion. Further study of this data and continued measurements on future motors will increase our understanding of the aft dome flow and erosion environment.

McWhorter, Bruce↗

Method and apparatus for dual amplitude dual time-of-flight ultrasonic imaging

A method and apparatus for ultrasonic imaging which includes scanning a test specimen located in a test fixture in a predetermined scan pattern. Propagating and receiving reflected pulses of ultrasonic energy from an ultrasonic transducer directed to a surface of the test specimen. Detecting and generating data of both the amplitude and the depth of a defect in the test specimen from the pulses received from the test specimen. Merging the data of the amplitude and the data of the depth of the defect into composite data and then displaying the composite data in a three dimensional image whereby a mesh of both amplitude and depth data of the defect is displayed in a single image of the defect.

Chern, Engmin James↗