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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Coherent optical array receiver experiment : design, implementation and BER performance of a multichannel coherent optical receiver for PPM signals under atmospheric turbulence

The performance of a coherent free-space optical communication system operating in the presence of turbulence is investigated. Maximum Likelihood Detection techniques are employed to optimally detect Pulse Position Modulated signals with a focal-plane detector array, and reconstruct the turbulence-degraded signals. The experimental demonstration of this project and results may be divided in three parts; two of which have already been explained in previous publications (1,2). This latest paper shows the final experimental results, including investigation of performance of the Coherent Optical Receiver Experiment (CORE) performed at the laboratory facilities at JPL. Bit Error Rate (BER) is presented for single and multichannel optical receivers, where quasi-shot noise limited performance is achieved, under simulated turbulence conditions using non-coherent post-detection processing techniques.

Hassibi, Babak↗
NASA NTRS2013

Spring-Summer Temperatures Since AD 1780 Reconstructed from Stable Oxygen Isotope Ratios in White Spruce Tree-Rings from the Mackenzie Delta, Northwestern Canada

High-latitude delta(exp 18)O archives deriving from meteoric water (e.g., tree-rings and ice-cores) can provide valuable information on past temperature variability, but stationarity of temperature signals in these archives depends on the stability of moisture source/trajectory and precipitation seasonality, both of which can be affected by atmospheric circulation changes. A tree-ring delta(exp 18)O record (AD 1780-2003) from the Mackenzie Delta is evaluated as a temperature proxy based on linear regression diagnostics. The primary source of moisture for this region is the North Pacific and, thus, North Pacific atmospheric circulation variability could potentially affect the tree-ring delta(exp 18)O-temperature signal. Over the instrumental period (AD 1892-2003), tree-ring delta(exp 18)O explained 29% of interannual variability in April-July minimum temperatures, and the explained variability increases substantially at lower-frequencies. A split-period calibration/verification analysis found the delta(exp 18)O-temperature relation was time-stable, which supported a temperature reconstruction back to AD 1780. The stability of the delta(exp 18)O-temperature signal indirectly implies the study region is insensitive to North Pacific circulation effects, since North Pacific circulation was not constant over the calibration period. Simulations from the NASA-GISS ModelE isotope-enabled general circulation model confirm that meteoric delta(exp 18)O and precipitation seasonality in the study region are likely insensitive to North Pacific circulation effects, highlighting the paleoclimatic value of tree-ring and possibly other delta(exp 18)O records from this region. Our delta(exp 18)O-based temperature reconstruction is the first of its kind in northwestern North America, and one of few worldwide, and provides a long-term context for evaluating recent climate warming in the Mackenzie Delta region.

Canada↗
DOE OSTI2021

Local summer insolation and greenhouse gas forcing drove warming and glacier retreat in New Zealand during the Holocene

Geological climate archives from the Holocene Epoch provide baseline information concerning natural climate variability. Temperate mountain glacier extent is sensitive to summer air temperature, thus geological records of past glacier length changes are a useful proxy for this climatic variable. Here we present a new cosmogenic 10 Be chronology of glacier length changes at Dart Glacier in the Southern Alps, New Zealand. Prominent moraines deposited 321 ± 44 yr ago (n = 11) and 7.8 ± 0.3 ka (n = 5) show glaciers during the Little Ice Age were less extensive than during the early Holocene. This pattern of net Holocene glacier retreat is consistent with emerging data from other catchments in New Zealand and across the southern mid-latitudes. Using the physical framework of a transient global climate model simulation, we suggest that cool summers in the early Holocene were promoted by the local summer insolation minimum, together with low atmospheric greenhouse gas concentrations, causing an early Holocene austral glacial maximum. An insolation-driven reduction in seasonality at southern mid-latitudes may reconcile differences between early Holocene temperature reconstructions where climate proxies have different seasonal sensitivities. Furthermore, we suggest that rising greenhouse gas concentrations after 7 ka caused regional-scale glacier retreat and appear to be the dominant driver of multi-millennial summer temperature trends in the southern mid-latitudes during the present interglacial.

58 GEOSCIENCES↗
DOE OSTI2024

Neutron-antineutron oscillation sensitivity study at DUNE

The Deep Underground Neutrino Experiment (DUNE) aims to measure neutrino oscillations as well as search for beyond the standard model physics such as baryon number violating (BNV) processes. DUNE will use a 70 kt Liquid Argon Time Projection Chamber (LArTPC) located more than 1 km underground. A promising BNV process is neutron-antineutron oscillation ($n \rightarrow \bar{n}$) which, if discovered, would offer unique insight into the baryon asymmetry of the universe. We are developing a classification algorithm that separates $n \rightarrow \bar{n}$ events from major background atmospheric neutrino interactions using DUNE far detector simulations. We will perform the classification of signals and backgrounds by analyzing key features such as the multiplicity, isotropy, and kinematics of the reconstructed events. In the future, this algorithm can be used to obtain the sensitivity of the DUNE detectors to the neutron-antineutron oscillation lifetime.

Wheeler, Justin↗
NASA NTRS1992

Crosstalk in solar polarization measurements

The instrumental crosstalk associated with the Marshall Space Flight Center Vector Magnetograph and the solar crosstalk created by the magnetic field are described and their impact on the reconstruction of the solar vector magnetic field is analyzed. It is pointed out that identifying and correcting the crosstalk is important in the development of realistic models describing the solar atmosphere. Solar crosstalk is spatially dependent on the structure of the magnetic field while instrumental crosstalk is dependent on the position of the analyzer.

West, E. A.↗
NASA NTRS2023

Sea Surface Temperature Gradients Estimation Using Top-of-Atmosphere Observations from the ESA Earth Explorer 10 Harmony Mission: Preliminary Studies

The Harmony satellite mission was recently approved as the next European Space Agency (ESA) Earth Explorer 10. The mission science objectives cover several applications related to solid earth, the cryosphere, upper-ocean dynamics and air–sea interactions. The mission consists of a constellation of two satellites, flying with the Copernicus Sentinel 1 (C or D) spacecraft, each hosting a C-band receive-only radar and a thermal infrared (TIR) payload. From an ocean dynamics/air–sea interaction perspective, the mission will provide the unique opportunity to observe simultaneously the signature of submesoscale upper-ocean processes via synthetic aperture radar and TIR imagery. The TIR imager is based on microbolometer technology and its acquisitions will rely on four channels: three narrow-band channels yielding observations at a ≃1 km spatial sampling distance (SSD) and a panchromatic (PAN, 8–12 μm) channel characterized by a ≃300 m SSD. Our study investigates the potential of Harmony in retrieving spatial features related to sea surface temperature (SST) gradients from the high-resolution PAN channel, relying on top-of-atmosphere (TOA) observations. Compared to a standard SST gradient retrieval, our approach does not require atmospheric correction, thus avoiding uncertainties due to inter-channel co-registration and radiometric consistency, with the possibility of exploiting the higher resolution of the PAN channel. The investigations were carried out simulating the future Harmony TOA radiances (TARs), as well as relying on existing state-of-the-art level 1 satellite products. Our approach enables the correct description of SST features at the sea surface avoiding the generation of spurious features due to atmospheric correction and/or instrumental issues. In addition, analyses based on existing satellite products suggest that the clear-sky TOA observations, in a typical mid-latitude scene, allow the reconstruction of up to 85% of the gradient magnitudes found at the sea-surface level. The methodology is less efficient in tropical areas, suffering from smoothing effects due to the high concentrations of water vapor.

sea surface temperature (SST)↗
DOE OSTI2024

Signal discrimination for neutron-antineutron oscillation sensitivity study at DUNE

The Deep Underground Neutrino Experiment (DUNE) aims to measure neutrino oscillations as well as search for beyond the standard model physics such as baryon number violating (BNV) processes. DUNE will use a 70 kt Liquid Argon Time Projection Chamber (LArTPC) located more than 1 km underground. A promising BNV process is neutron-antineutron oscillation $\left(n\rightarrow\bar{n}\right)$ which, if discovered, would offer unique insight into the baryon asymmetry of the universe. We are developing a classification algorithm that separates $n\rightarrow\bar{n}$ events from major background atmospheric neutrino interactions using DUNE far detector simulations. We will perform the classification of signals and backgrounds by analyzing key features such as the multiplicity, isotropy, and kinematics of the reconstructed events. In the future, this algorithm can be used to obtain the sensitivity of the DUNE detectors to the neutron-antineutron oscillation lifetime.

Wheeler, Justin↗
DOE OSTI2024

Behavior and mechanisms of Doppler wind lidar error in complex terrain: stable flow case study at Perdigão

A numerical experiment is carried out investigating the magnitude of biases in ground-based lidar measurements in complex flow conditions. Biases assessed include those arising from flow curvature and from the interaction of turbulence with the wind field reconstruction (WFR) algorithms used by a WindCube lidars and anemometers. RANS-CFD and WRF-LES simulations were performed for the Perdig˜ao Field Experiment site for a range of atmospheric conditions. Virtual anemometer and lidar data were generated for four locations: two near exposed ridge tops and two in low-speed regions in the valley. The LES data at these four locations show that the scalar inflation terms (the relation between scalar and vector averaged wind speed) for virtual lidar and virtual cups agree very well with predictions using perturbation theory. While the lidar errors vary greatly with location and height, the contribution from the flow curvature tends to be larger than the differences arising from scalar inflation. For one lidar/mast pair near the ridge top, comparisons between simulations and measurements are carried out for a resonant mountain wave event on June 14th, 2017, and for the whole duration of the Perdigão campaign for winds perpendicular to the ridges. The lidar error during the mountain wave, a period of strong stability and low inversion height, is significantly larger than the campaign average. The sensitivity of the lidar error to atmospheric stability is confirmed by the RANS simulations, which suggests strong sensitivity of flow curvature error to stability conditions and to the shape of the wind speed profile near the top of the boundary layer.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Assimilation of Reconstructed Radiances from IASI Principal Component Scores into the GEOS-ADAS

Hyperspectral Infrared sounders such as IASI, AIRS, and CrIS have long been an integral part of radiance assimilation in numerical weather prediction (NWP), providing vertical profiles of water vapor and temperature information. Principal Component Scores (PCS) are a lossy form of compression that retains most information, such as temperature and moisture, by using a large training set of atmospheric profiles. However, PCS may not well represent profiles which are rare events, such as volcanic eruptions, and drops some sources of random noise. There has been an increased interest in the use of PCS as EUMETSAT plans to distribute future geostationary sounder radiances from MTG-IRS via PCS only. NWP centers use two approaches to deal with PCS: direct assimilation of the PCS by modifying the radiative transfer model to produce PCS and the associated Jacobians, or a simpler approach of decompressing the PCS and reconstructing the radiances back into channel space to allow assimilating radiances without modifications to the data assimilation system. EUMETSAT has developed a PCS product for IASI that has been operational since 2011. We utilize this product opting for the simpler approach, decompressing IASI PCS into channel space, and assimilating those radiances using the GEOS-ADAS. We then compare this with a control using the standard IASI radiance product. Resulting differences in global forecast statistics, differences in Forecast Sensitivity to Observation Impact, along with implications for implementation and quality control are discussed.

Bryan M. Karpowicz↗
DOE OSTI2023

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

Proxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter-annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP-class GCMs. We examine in a perfect-model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1-year lead-time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM-emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗
NASA NTRS2008

On Combining Thermal-Infrared and Radio-Occultation Data of Saturn's Atmosphere

Radio-occultation and thermal-infrared measurements are complementary investigations for sounding planetary atmospheres. The vertical resolution afforded by radio occultations is typically approximately 1 km or better, whereas that from infrared sounding is often comparable to a scale height. On the other hand, an instrument like CIRS can easily generate global maps of temperature and composition, whereas occultation soundings are usually distributed more sparsely. The starting point for radio-occultation inversions is determining the residual Doppler-shifted frequency, that is the shift in frequency from what it would be in the absence of the atmosphere. Hence the positions and relative velocities of the spacecraft, target atmosphere, and DSN receiving station must be known to high accuracy. It is not surprising that the inversions can be susceptible to sources of systematic errors. Stratospheric temperature profiles on Titan retrieved from Cassini radio occultations were found to be very susceptible to errors in the reconstructed spacecraft velocities (approximately equal to 1 mm/s). Here the ability to adjust the spacecraft ephemeris so that the profiles matched those retrieved from CIRS limb sounding proved to be critical in mitigating this error. A similar procedure can be used for Saturn, although the sensitivity of its retrieved profiles to this type of error seems to be smaller. One issue that has appeared in inverting the Cassini occultations by Saturn is the uncertainty in its equatorial bulge, that is, the shape in its iso-density surfaces at low latitudes. Typically one approximates that surface as a geopotential surface by assuming a barotropic atmosphere. However, the recent controversy in the equatorial winds, i.e., whether they changed between the Voyager (1981) era and later (after 1996) epochs of Cassini and some Hubble observations, has made it difficult to know the exact shape of the surface, and it leads to uncertainties in the retrieved temperature profiles of one to a few kelvins. This propagates into errors in the retrieved helium abundance, which makes use of thermal-infrared spectra and synthetic spectra computed with retrieved radio-occultation temperature profiles. The highest abundances are retrieved with the faster Voyager-era winds, but even these abundances are somewhat smaller than those retrieved from the thermal-infrared data alone (albeit with larger formal errors). The helium abundance determination is most sensitive to temperatures in the upper troposphere. Further progress may include matching the radio-occultation profiles with those from CIRS limb sounding in the upper stratosphere.

Flasar, F. M.↗
NASA NTRS2012

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

We report a series of experiments to explore clima~ responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.

Wen, G.↗
NASA NTRS2012

The Role of Forcing and Internal Dynamics in explaining the 'Medieval Climate Anomaly'

Proxy reconstructions suggest that peak global temperature during the past warm interval known as the Medieval Climate Anomaly (MCA, roughly 950-1250 AD) has been exceeded only during the most recent decades. To better understand the origin of this warm period, we use model simulations constrained by data assimilation establishing the spatial pattern of temperature changes that is most consistent with forcing estimates, model physics and the empirical information contained in paleoclimate proxy records. These numerical experiments demonstrate that the reconstructed spatial temperature pattern of the MCA can be explained by a simple thermodynamical response of the climate system to relatively weak changes in radiative forcing combined with a modification of the atmospheric circulation, displaying some similarities with the positive phase of the so-called Arctic Oscillation, and with northward shifts in the position of the Gulf Stream and Kuroshio currents. The mechanisms underlying the MCA are thus quite different from anthropogenic mechanisms responsible for modern global warming.

Goossee, Hugues↗
NASA NTRS1996

Planetary Atmosphere Dynamics and Radiative Transfer

This research program has dealt with two projects in the field of planetary atmosphere dynamics and radiative energy transfer, one theoretical and one experimental. The first project, in radiative energy transfer, incorporated the capability to isolate and quantify the contribution of individual atmospheric components to the Venus radiative balance and thermal structure to greatly improve the current understanding of the radiative processes occurring within the Venus atmosphere. This is possible by varying the mixing ratios of each gas species, and the location, number density and aerosol size distributions of the clouds. This project was a continuation of the work initiated under a 1992 University Consortium Agreement. Under the just completed grant, work has continued on the use of a convolution-based algorithm that provided the capability to calculate the k coefficients of a gas mixture at different temperatures, pressures and spectral intervals from the separate k-distributions of the individual gas species. The second primary goal of this research dealt with the Doppler wind retrieval for the Successful Galileo Jupiter probe mission in December, 1995. In anticipation of the arrival of Galileo at Jupiter, software development continued to read the radioscience and probe/orbiter trajectory data provided by the Galileo project and required for Jupiter zonal wind measurements. Sample experiment radioscience data records and probe/orbiter trajectory data files provided by the Galileo Radioscience and Navigation teams at the Jet Propulsion Laboratory, respectively, were used for the first phase of the software development. The software to read the necessary data records was completed in 1995. The procedure by which the wind retrieval takes place begins with initial consistency checks of the raw data, preliminary data reductions, wind recoveries, iterative reconstruction of the probe descent profile, and refined wind recoveries. At each stage of the wind recovery consistency is checked and maintained between the orbiter navigational data, the radioscience data, and the probe descent profile derived by the Atmospheric Instrument Team. Preliminary results show that the zonal winds at Jupiter increase with depth to approximately 150 m/s.

Atkinson, David H.↗
NASA NTRSDate not supplied

Overview of the Dragonfly Entry Aerosciences Measurements (DrEAM) Suite

NASA Ames and Langley arepartnering with DLR to propose acomprehensive instrumentation suite known as the Dragonfly Entry Aerosciences Meas-urements (DrEAM). DrEAM being the first competed mission to fly EDL instrumentation as part of NASA’s Engineering Science Investigation (ESI).DrEAM will provide key aerothermodynamicdata and performance analysisfor Dragonfly’s forebody and backshell therma lprotection system (TPS),and also includes a DLR-provided Data Acquisition System(DAS).Titan’s atmosphere predominantly consists of nitro-gen (~98% by mole) with small amounts of methane(~2% by mole)and other trace gases. CN is a strong ra-diator and is found in nonequilibriumconcentrationsfor Titan entry. The accurate modeling of nonequilibrium CN radiation has proven to be a difficult task. Prompted by the Huygensmission, many experimental campaigns and analyses were performed to better understand the aerothermal environments experience by the probe dur-ing Titan entry[1].However, the Huygens probe carried no heatshieldinstrumentation. Therefore,the DrEAM instrumentation suite will significantly advance the state-of-the-art not only by documenting theenviron-ment and performance of Dragonfly’sentry system but also by making keymeasurements in Titan’s atmos-phere for thefirst time, thus providing new benchmark dataapplicable to entry science more generally. Current Measurement Goals: Aerothermal envi-ronments and TPS responsewill be measured using sen-sors similarto the Mars Entry, Descent, and Landing In-strumentation2 (MEDLI2) Integrated Sensor Plug(MISP) and the COMbined Aerothermaland Radiome-ter Sensor (COMARS)suite[2], with the latter supplied by DLR.For MEDLI2, MISP usedembedded thermo-couples (TCs) todirectly measure in-depth temperature of theTPS at several locations,which can also be used to infer surface environmentsvia inverse analysis. For DrEAM, the MISPstyle plugswill be known as Drag-onfly Sensors for Aero-Thermal Reconstruction (Drag-STR)plugs. On Schiaparelli, the COMARSsuite in-cludedthree total surface-mounted heatflux sensors, three pressure sensors, and one radiometer. For DrEAM, the COMARS package will be known as COmbined Sensor System for Titan Atmosphere (COSSTA). Atmospheric density measurements and capsuleaerodynamic data will be obtained throughthe onboard Inertial Measurement Unit (IMU),supple-mented by pressure transducers similar tothose used by the MEDLI Mars Entry AtmosphericData System (MEADS).The DrEAM pressure sensors will be known as Dragonfly Atmospheric Flight Transducers(DrAFT) Both DragSTR and DrAFThave flight heritagefrom MISP and MEADS on the MSLand Mars 2020mis-sions, and the COMARS suite successfullyflew on the ESA Schiaparelli EDMlander. A preliminary layout of the sensors is shown in Fig. 1. Because Dragonflyuses the same aeroshell provider (i.e., LockheedMartin) and materials for the TPS,with what are expected to be sim-ilar thicknesses as MSL and Mars 2020on both the heat shield and backshell, theDrEAMinstrumentation will look to utilize the same techniques and processes as de-veloped byMEDLI and MEDLI2for vehicle integra-tion. This commonality alsoenables DrEAMto lever-age the extensiveground test qualifications performed forMEDLI and MEDLI2 and claim substantial heritagefor this system.

A Brandis↗
NASA NTRS1974

Remote sounding of cloudy atmospheres. I - The single cloud layer

The relaxation method for the inverse solution of the radiative transfer equation is applied in a dual-frequency scheme for the determination of complete vertical temperature profiles in cloudy atmospheres from radiance observations alone, without any additional information related to the expected solutions. The dual-frequency principle employs to advantage a property in the Planck function of the dependence of intensity on frequency. This property leads to the formulation of a new convergence criterion for the selection of cloud-sounding frequencies to be used for reconstructing the clear column radiance from observations made in the presence of a broken cloud layer in all fields of view. The principle is applied to the case of observations in two adjacent or partially overlapping fields of view and to the case of observations in a single field of view. The solutions are illustrated by numerical examples in the dual-frequency ranges of the 4.3 and 15-micron CO2 bands of the terrestrial atmosphere.

Chahine, M. T.↗
DOE OSTI2022

GAL08, an Uncultivated Group of Acidobacteria, Is a Dominant Bacterial Clade in a Neutral Hot Spring

GAL08 are bacteria belonging to an uncultivated phylogenetic cluster within the phylum Acidobacteria . We detected a natural population of the GAL08 clade in sediment from a pH-neutral hot spring located in British Columbia, Canada. To shed light on the abundance and genomic potential of this clade, we collected and analyzed hot spring sediment samples over a temperature range of 24.2–79.8°C. Illumina sequencing of 16S rRNA gene amplicons and qPCR using a primer set developed specifically to detect the GAL08 16S rRNA gene revealed that absolute and relative abundances of GAL08 peaked at 65°C along three temperature gradients. Analysis of sediment collected over multiple years and locations revealed that the GAL08 group was consistently a dominant clade, comprising up to 29.2% of the microbial community based on relative read abundance and up to 4.7 × 10 5 16S rRNA gene copy numbers per gram of sediment based on qPCR. Using a medium quality threshold, 25 single amplified genomes (SAGs) representing these bacteria were generated from samples taken at 65 and 77°C, and seven metagenome-assembled genomes (MAGs) were reconstructed from samples collected at 45–77°C. Based on average nucleotide identity (ANI), these SAGs and MAGs represented three separate species, with an estimated average genome size of 3.17 Mb and GC content of 62.8%. Phylogenetic trees constructed from 16S rRNA gene sequences and a set of 56 concatenated phylogenetic marker genes both placed the three GAL08 bacteria as a distinct subgroup of the phylum Acidobacteria , representing a candidate order ( Ca. Frugalibacteriales) within the class Blastocatellia. Metabolic reconstructions from genome data predicted a heterotrophic metabolism, with potential capability for aerobic respiration, as well as incomplete denitrification and fermentation. In laboratory cultivation efforts, GAL08 counts based on qPCR declined rapidly under atmospheric levels of oxygen but increased slightly at 1% (v/v) O 2 , suggesting a microaerophilic lifestyle.

59 BASIC BIOLOGICAL SCIENCES↗