An estimate of the present-day deep-mantle degassing rate from data on the atmosphere of Venus
Venus deep mantle water degassing rate from atmospheric hydrogen escape data
Hunten, D. M.↗
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Enhancement of digital images through band ratio techniques for geological applications
The fundamentals in the use of band ratio techniques to enhance spectral signatures of geologic interest are discussed. The path radiance, additive term of the measured radiance at any given wavelength, is almost completely eliminated from LANDSAT images by subtracting the smallest value of the radiance measured in each channel, at shadows caused by topographic relief and clouds, and deep clear water bodies. By ratioing successive spectral channels the effect of solar angle of elevation is minimized and the product expresses, to a first approximation, a relationship between reflectances, which are intrinsic characteristics of the targets. Ratios between noncorrelated channels, such as R 7/4, R 7/5, and R 6/4 are useful to show variations in the vegetation cover, probably related to geobotanical associations.
Filho, R. A.↗
U, Th, and Pb isotopes in hot springs on the Juan de Fuca Ridge
Concentrations and isotopic compositions of U, Th, and Pb in three hydrothermal fluids from the Juan de Fuca Ridge were determined from samples obtained by the Alvin submersible. The samples were enriched in Pb and Th relative to deep-sea water, and were deficient in U. No clear relationship with Mg was found, suggesting nonideal mixing between the hot hydrothermal fluids and the cold ambient seawater. Values for U-234/U-238 have a seawater signature, and show a U-234 enrichment relative to the equilibrium value. The Pb isotopic composition has a uniform midocean ridge basalt signature, and it is suggested that Pb in these fluids may represent the best average value of the local oceanic crust.
Chen, J. H.↗
High Accuracy In-Flight Wavelength Calibration of Imaging Spectrometry Data
Accurate wavelength calibration of imaging spectrometer data is essential if proper atmospheric transmission corrections are to be made to obtain apparent surface reflectance. Accuracies of 0.1 nm are necessary for a 10 nm-sampling instrument in order to match the slopes of the deep atmospheric water vapor features that dominate the 0.7-2.3 micrometer regions. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is calibrated in the laboratory to determine the wavelength position and full-width-half-maximum (FWHM) response for each of the 224 channels. The accuracies are limited by the quality of the monochromator used as a source. The accuracies vary from plus or minus to plus or minus 1.5 nm depending on the wavelength region, in general decreasing with increasing wavelength. Green et al. make corrections to the wavelength calibrations by using the known positions of 14 atmospheric absorption features throughout the 0.4-2.5 micrometer wavelength region. These features, having varying width and intensity, were matched to the MODTRAN model with a non-linear least squares fitting algorithm. A complete calibration was developed for all 224 channels by interpolation. Instrument calibration cannot be assumed to be stable to 0.1 nm over a flight season given the rigors of thermal cycling and launch and landing loads. The upcoming sensor HYDICE will require a means for in-flight spectral calibration of each scene because the calibration is both temperature and pressure sensitive. In addition, any sensor using a two-dimensional array has the potential for systematic wavelength shifts as a function of cross-track position, commonly called 'smile'. Therefore, a rapid means for calibrating complete images will be required. The following describes a method for determining instrument wavelength calibration using atmospheric absorption features that is efficient enough to be used for entire images on workstations. This study shows the effect of the surface reflectance on the calibration accuracy and the calibration history for the AVIRIS B spectrometer over the 1992 flight season.
Goetz, Alexander F. H.↗
A Laboratory Study of the Effect of Frost Flowers on C Band Radar Backscatter from Sea Ice
C band images of Arctic sea ice taken by the ERS 1 synthetic aperture radar show transitory regions of enhanced radar backscatter from young sea ice. Published field observations associate this increase with frost flower growth and the capture of blowing snow by the flowers. To investigate the first part of this phenomenon, we carried out a laboratory experiment on the response of C band radar backscatter to frost flowers growing on the surface of newly formed saline ice. The experiment took place in a 5 m by 7 m by 1.2 m deep saline water pool located in a two-story indoor refrigerated facility at the Cold Regions Research and Engineering Laboratory. Sodium chloride ice was grown in this pool at an air temperature of -28 C. The frost flowers first appeared on the ice surface as dendrites and then changed to needles as the ice sheet grew thicker and the surface temperatures became colder. The frost flowers reached to a height of 10-15 mm, and beneath each cluster of frost flowers a slush layer formed to a thickness of approximately 4 mm. Far-field radar measurements of the backscatter from the ice were made at incident angles from 20 to 40 deg and at approximately 6-hour intervals throughout the 3-day period of the experiment. A backscatter minimum occurred early in the flower growth at the time coincident with an abrupt doubling in the ice surface salinity. Once the full flower coverage was achieved, we removed first the crystal flowers and then the slush layer from the ice surface. The results for these cases show that the crystals have little impact on the backscatter, while the underlying slush patches yield a backscatter increase of 3-5 dB over that of bare ice. The laboratory results suggest that this relative backscatter increase of approximately 5 dB can be used as an index to mark the full area coverage of frost flowers.
Nghiem, S. V.↗
A Laboratory Study of the Effect of Frost Flowers on C Band Radar Backscatter from Sea Ice
C band images of Arctic sea ice taken by the ERS 1 synthetic aperture radar show transitory regions of enhanced radar backscatter from young sea ice. Published field observations associate this increase with frost flower growth and the capture of blowing snow by the flowers. To investigate the first part of this phenomenon, we carried out a laboratory experiment on the response of C band radar backscatter to frost flowers growing on the surface of newly formed saline ice. The experiment took place in a 5 m by 7 m by 1.2 m deep saline water pool located in a two-story indoor refrigerated facility at the Cold Regions Research and Engineering Laboratory. Sodium chloride ice was grown in this pool at an air temperature of -28 C. The frost flowers first appeared on the ice surface as dendrites and then changed to needles as the ice sheet grew thicker and the surface temperatures became colder. The frost flowers reached to a height of 10-15 mm, and beneath each cluster of frost flowers a slush layer formed to a thickness of approximately 4 mm. Far-field radar measurements of the backscatter from the ice were made at incident angles from 20 C to 40 C and at approximately 6-hour intervals throughout the 3-day period of the experiment. A backscatter minimum occurred early in the flower growth at the time coincident with an abrupt doubling in the ice surface salinity. Once the full flower coverage was achieved, we removed first the crystal flowers and then the slush layer from the ice surface. The results for these cases show that the crystals have little impact on the backscatter, while the underlying slush patches yield a backscatter increase of 3-5 dB over that o f bare ice. The laboratory results suggest that this relative backscatter increase of approximately 5 dB can be used as an index to mark the full areal coverage of frost flowers.
Nghiem, S. V.↗
Validation of Ocean Color Satellite Data Products in Under Sampled Marine Areas
The planktonic marine cyanobacterium, Trichodesmium sp., is broadly distributed throughout the oligotrophic marine tropical and sub-tropical oceans. Trichodesmium, which typically occurs in macroscopic bundles or colonies, is noteworthy for its ability to form large surface aggregations and to fix dinitrogen gas. The latter is important because primary production supported by N2 fixation can result in a net export of carbon from the surface waters to deep ocean and may therefore play a significant role in the global carbon cycle. However, information on the distribution and density of Trichodesmium from shipboard measurements through the oligotrophic oceans is very sparse. Such estimates are required to quantitatively estimate total global rates of N2 fixation. As a result current global rate estimates are highly uncertain. Thus in order to understand the broader biogeochemical importance of Trichodesmium and N2 fixation in the oceans, we need better methods to estimate the global temporal and spatial variability of this organism. One approach that holds great promise is satellite remote sensing. Satellite ocean color sensors are ideal instruments for estimating global phytoplankton biomass, especially that due to episodic blooms, because they provide relatively high frequency synoptic information over large areas. Trichodesmium has a combination of specific ultrastructural and biochemical features that lend themselves to identification of this organism by remote sensing. Specifically, these features are high backscatter due to the presence of gas vesicles, and absorption and fluorescence of phycoerythrin. The resulting optical signature is relatively unique and should be detectable with satellite ocean color sensors such as the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS).
Subramaniam, Ajit↗
Life in Ice: Implications to Astrobiology
During the 2008 Tawani International Expedition Schirmacher Oasis/Lake Untersee Antarctica Expedition, living and instantly motile bacteria were found in freshly thawed meltwater from ice of the Schirmacher Oasis Lakes, the Anuchin Glacier ice and samples of the that perennial ice sheet above Lake Untersee. This phenomenon of living bacteria encased in ice had previously been observed in the 32,000 year old ice of the Fox Tunnel. The bacteria found in this ice included the strain FTR1T which was isolated and published as valid new species (Carnobacterium pleistocenium) the first validly published living Pleistocene organism still alive today. Living bacteria were also extracted from ancient ice cores from Vostok, Antarctica. The discovery that many strains of bacteria are able to survive and remain alive while frozen in ice sheets for long periods of time may have direct relevance to Astrobiology. The abundance of viable bacteria in the ice sheets of Antarctica suggests that the presence of live bacteria in ice is common, rather than an isolated phenomenon. This paper will discuss the results of recent studies at NSSTC of bacteria cryopreserved in ice. This paper advances the hypothesis that cryopreserved cells, and perhaps even viable bacterial cells, may exist today--frozen in the water-ice of lunar craters, the Polar Caps or craters of Mars; or in the permafrost of Mars; ice and rocks of comets or water bearing asteroids; or in the frozen crusts of the icy moons of Jupiter and Saturn. The existence of bacterial life in ice suggests that it may not be necessary to drill through a thick ice crust to reach liquid water seas deep beneath the icy crusts of Europa, Ganymede and Enceladus. The presence of viable bacteria in the ice of the Earth s Polar Caps suggests that the possibility that cryo-panspermia (i.e., the trans-planetary transfer of microbial life by impact ejection/spallation of bacteria-rich polar ice masses) deserves serious consideration and study as a possible natural phenomenon of the solar system that may have played a profoundly important role in the Origin of Life on Earth and the Distribution of Life in the Cosmos. The paper concludes with a consideration of the protective properties of ice by absorption of UV-B, UV-C, h-rays, gamma-rays and the high energy proton environment of the Jupiter Radiation Belt. A proposed instrument that may provide additional data on the potential survivability of microbial extremophiles encased in ice and subjected to the simulated space environment will be briefly described.
Hoover, Richard B.↗
Thunderstorm and Fair-weather Quasi-Static Electric Fields Over Land and Ocean
Natural lightning and the associated clouds are known to behave differently over land and ocean, but many questions remain. We expand the related observational datasets by obtaining simultaneous quasi-static electric field observations over coastal land, near-shore water, and deep ocean regions during both fair-weather and thunderstorm periods. Oceanic observations were obtained using two 3-m NOAA buoys that were instrumented with Campbell Scientific electric field mills to measure the quasi-static electric fields. These data were compared to selected electric field records from the existing on-shore electric field mill suite of 31 sensors at Kennedy Space Center (KSC). Lightning occurrence times, locations and peak current estimates for both onshore and ocean were provided by the U.S. National Lightning Detection Network. The buoy instruments were first evaluated on-shore at the Florida coast, and the first system was calibrated for field enhancements and to confirm proper behavior of the system in elevated-field environments. The buoys were then moored 20 mi and 120 mi off the coast of KSC in February (20 mi) and August (120 mi) 2014. Diurnal fair-weather fields at both ocean sites matched will with each other and with those found during the Carnegie cruise, but mean values were 33% smaller, due at least in-part to constraints on the calibration procedure. Diurnal fair-weather fields variations at coastal and inland sites were a poorer match than offshore, likely because the offshore environment is “cleaner” with limited variations in local space charge, lower surface aerosol densities, little surface heating to disturb the surface charge layer during fair weather, and fewer local radioactive sources to modulate the near-surface electrical conductivity. Storm-related static fields were 4-5× larger at both oceanic sites than over land, likely due to decreased screening by near-surface space charge produced by corona current. The time-evolution of the electric field and field changes during storm approach are sufficiently different over land and ocean to warrant further study. This work shows the quality, accuracy, and reliability of these data, and has demonstrated the practicality of off-shore electric field measurements for safety- and launch-related decision making at KSC.
Lightning↗
Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals
The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.
Smith, William L., Jr.↗
Variability of bottom carbonate chemistry over the deep coral reefs in the Florida Straits and the impacts of mesoscale processes
Not provided.
Meteorology & Atmospheric Sciences↗
Deep-focus earthquakes and recycling of water into the earth's mantle
For more than 50 years, observations of earthquakes to depths of 100 to 650 kilometers inside earth have been enigmatic: at these depths, rocks are expected to deform by ductile flow rather than brittle fracturing or frictional sliding on fault surfaces. Laboratory experiments and detailed calculations of the pressures and temperatures in seismically active subduction zones indicate that this deep-focus seismicity could originate from dehydration and high-pressure structural instabilities occurring in the hydrated part of the lithosphere that sinks into the upper mantle. Thus, seismologists may be mapping the recirculation of water from the oceans back into the deep interior of the planet.
Meade, Charles↗
Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains
Abstract In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high‐resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. All DL models produce higher median Nash‐Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.
54 ENVIRONMENTAL SCIENCES↗
A Deep Potential model for liquid–vapor equilibrium and cavitation rates of water
Computational studies of liquid water and its phase transition into vapor have traditionally been performed using classical water models. Here, we utilize the Deep Potential methodology—a machine learning approach—to study this ubiquitous phase transition, starting from the phase diagram in the liquid–vapor coexistence regime. The machine learning model is trained on ab initio energies and forces based on the SCAN density functional, which has been previously shown to reproduce solid phases and other properties of water. Here, we compute the surface tension, saturation pressure, and enthalpy of vaporization for a range of temperatures spanning from 300 to 600 K and evaluate the Deep Potential model performance against experimental results and the semiempirical TIP4P/2005 classical model. Moreover, by employing the seeding technique, we evaluate the free energy barrier and nucleation rate at negative pressures for the isotherm of 296.4 K. Further, we find that the nucleation rates obtained from the Deep Potential model deviate from those computed for the TIP4P/2005 water model due to an underestimation in the surface tension from the Deep Potential model. From analysis of the seeding simulations, we also evaluate the Tolman length for the Deep Potential water model, which is (0.091 ± 0.008) nm at 296.4 K. Finally, we identify that water molecules display a preferential orientation in the liquid–vapor interface, in which H atoms tend to point toward the vapor phase to maximize the enthalpic gain of interfacial molecules. We find that this behavior is more pronounced for planar interfaces than for the curved interfaces in bubbles. This work represents the first application of Deep Potential models to the study of liquid–vapor coexistence and water cavitation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Depth of nutrient uptake by deep-rooted plants is regulated by water availability
The capacity of some plants to access water and nutrients at depths greater than one meter is a critical functional trait that confers resistance to drought and impacts both belowground and shallow soil processes. Here, we report water and strontium isotopic data from an alpine meadow transect showing the correlation between water and nutrient acquisition depths. The isotopic compositions of Sr ( 87 Sr/ 86 Sr ratio) and water in rock and soil, and in plant leaf tissues, reveal that deeper-rooted plants acquire a higher proportion of water, Sr, and cation nutrients that are derived from the saprolite, a zone of silicate weathering, than shallow-rooted grass. A three-decade dendrochemical record reveals that reductions of wet precipitation drive deep-rooted plants to acquire cation nutrients from deeper saprolite or bedrock regions. Thus, the depth of cation nutrient acquisition by deep-rooted plant species at this site is tightly coupled with, and likely determined by, water availability in soil, saprolite, and bedrock. The enhanced uptake of cations as well as water from deeper saprolite zones could impact the rate of bedrock weathering and watershed chemistry during drought.
biogeochemistry↗
Role of Deep Convection in Establishing the Isotopic Composition of Water Vapor in the Tropical Transition Layer
The transport of H2O and HDO within deep convection is investigated with 3-D large eddy simulations (LES) using bin microphysics. The lofting and sublimation of HDO-rich ice invalidate the Rayleigh fractionation model of isotopologue distribution within deep convection. Bootstrapping the correlation of the ratio of HDO to H2O (deltaD) to water vapor mixing ratio (q(sub v)) through a sequence of convective events produced non-Rayleigh correlations resembling observations. These results support two mechanisms for stratospheric entry. Deep convection can inject air with water vapor of stratospheric character directly into the tropical transition layer (TTL). Alternatively, moister air detraining from convection may be dehydrated via cirrus formation n the TTL to produce stratospheric water vapor. Significant production of subsaturated air in the TTL via convective dehydration is not observed in these simulations, nor is it necessary to resolve the stratospheric isotope paradox.
Smith, Jamison A.↗
Water dissociation at the water–rutile TiO 2 (110) interface from ab initio-based deep neural network simulations
The interaction of water with TiO 2 surfaces is of crucial importance in various scientific fields and applications, from photocatalysis for hydrogen production and the photooxidation of organic pollutants to self-cleaning surfaces and bio-medical devices. In particular, the equilibrium fraction of water dissociation at the TiO 2 –water interface has a critical role in the surface chemistry of TiO 2 , but is difficult to determine both experimentally and computationally. Among TiO 2 surfaces, rutile TiO 2 (110) is of special interest as the most abundant surface of TiO 2 ’s stable rutile phase. While surface-science studies have provided detailed information on the interaction of rutile TiO 2 (110) with gas-phase water, much less is known about the TiO 2 (110)–water interface, which is more relevant to many applications. In this work, we characterize the structure of the aqueous TiO 2 (110) interface using nanosecond timescale molecular dynamics simulations with ab initio-based deep neural network potentials that accurately describe water/TiO 2 (110) interactions over a wide range of water coverages. Simulations on TiO 2 (110) slab models of increasing thickness provide insight into the dynamic equilibrium between molecular and dissociated adsorbed water at the interface and allow us to obtain a reliable estimate of the equilibrium fraction of water dissociation. We find a dissociation fraction of 22 ± 6% with an associated average hydroxyl lifetime of 7.6 ± 1.8 ns. These quantities are both much larger than corresponding estimates for the aqueous anatase TiO 2 (101) interface, consistent with the higher water photooxidation activity that is observed for rutile relative to anatase.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Viscosity in water from first-principles and deep-neural-network simulations
Abstract We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗