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DOE OSTI2023

Empirical evidence that mean soil contaminant concentration is not a conservative indicator of external exposure to wildlife

Adequate information on external exposure is often a limiting factor in ecological risk assessments because of a lack of exposure data for free-ranging animals as they interact with a heterogeneous distribution of contaminants. Instead, most wildlife exposure data are estimated from model simulations. However, empirical exposure data are rarely available to verify model results, or to test fundamental assumptions inherent in exposure assessments. We used novel, GPS-coupled radiation dosimeters on reindeer (Rangifer tarandus) to quantify their external exposure for five months in a Chernobyl fallout affected mountainous area of Norway. The exposure data were then used to test a fundamental assumption in screening-level risk assessments: Mean soil contaminant concentrations can be used to conservatively estimate chronic external exposures to representative animals. External exposure and GPS coordinates were obtained hourly and compared to model simulations of exposure based on airborne surveys of 137 Cs soil contamination. Our objectives were to determine 1) if modelled dose estimates based on mean 137 Cs soil concentrations were conservative, and 2) if modelled dose estimates could be improved by adjusting for spatial–temporal heterogeneity of contaminants using 137 Cs concentrations within reindeers’ GPS-defined home ranges and core areas. We found that external exposure modelled from mean soil contaminant concentrations underestimated exposure by 70% compared to empirical measurements from GPS-dosimeter collars worn on individual animals. Using area-weighted mean contaminant levels within the animals’ home range improved the model estimates, but still underestimated the field dosimeter data by 53%. The best estimate of external exposure was obtained when high-use areas within their home range, along with spatial heterogeneity of the contaminant, was accounted for by using area-weighted mean soil contaminant levels within GPS-derived core areas. Accounting for temporal use of core areas within animals’ home range provided a 24% improvement. Here, a comparison of our analyses to similar work performed on Chernobyl wolves found the two studies concur that risk assessors should be cautious in relying on the paradigm of using averaged soil contaminant levels to provide conservative estimates of external exposure to representative individuals. Results of modelled external exposure based on mean soil contaminant concentrations could misguide assessors and cause inappropriate management decisions.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2024

Jacobian-scaled K-means clustering for physics-informed segmentation of reacting flows

This work introduces Jacobian-scaled K-means (JSK-means) clustering, which is a physicsinformed clustering strategy centered on the K-means framework. The method allows for the injection of underlying physical knowledge into the clustering procedure through a distance function modification: instead of leveraging conventional Euclidean distance vectors, the JSKmeans procedure operates on distance vectors scaled by matrices obtained from dynamical system Jacobians evaluated at the cluster centroids. The goal of this work is to show how the JSKmeans algorithm - without modifying the input dataset - produces clusters that capture regions of dynamical similarity, in that the clusters are redistributed towards high-sensitivity regions in phase space and are described by similarity in the source terms of samples instead of the samples themselves. The algorithm is demonstrated on a complex reacting flow simulation dataset (a channel detonation configuration), where the dynamics in the thermochemical composition space are known through the highly nonlinear and stiff Arrhenius-based chemical source terms. Interpretations of cluster partitions in both physical space and composition space reveal how JSK-means shifts clusters produced by standard K-means towards regions of high chemical sensitivity (e.g., towards regions of peak heat release rate near the detonation reaction zone). Furthermore, the findings presented here illustrate the benefits of utilizing Jacobian-scaled distances in clustering techniques, and the JSK-means method in particular displays promising potential for improving former partition-based modeling strategies in reacting flow (and other multi-physics) applications.

Clustering↗

DOE OSTI2023

Quarkyonic mean field theory

We discuss mean field theory of quarkyonic matter at zero temperature. We treat the nucleons with contact interactions in mean field approximation, discussing both vector and scalar mean field interactions. We treat the quarks without mean field vector interactions, but allow mass terms to be generated consistently from a scalar mean field consistent with the additive quark model for quark masses. Quarkyonic matter is composed of a shell of nucleons that under-occupy the total available phase space associated with the underlying quark degrees of freedom. Here, the fully occupied Fermi sphere beneath this shell of nucleons at high densities is thought of as quarks, but when this fully occupied distribution of states first appears, although the phase space is filled, the matter is at low density. For the transition between this low density and high density saturated matter, we advocate a dual description of the fully filled Fermi sea in terms of hadrons, and make a phenomenological hypothesis for the equation of state of this matter. We then proceed to an example where the mean field interactions are all vector and only associated with the nucleons, ignoring the effects of mass change associated with the scalar interactions. Except for the effects of Pauli blocking, the nucleons and quarks do not interact. To get a reasonable transition to quarkyonic matter the interaction of the quarks among themselves are assumed to be nonperturbative, and a simple phenomenological relation between quark Fermi energy and density is introduced.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

The Dependence of Mean Climate State on Shortwave Absorption by Water Vapor

Abstract State-of-the-art climate models exhibit significant spread in the climatological value of atmospheric shortwave absorption (SWA). This study investigates both the possible causes and climatic impacts of this SWA intermodel spread. The intermodel spread of global-mean SWA largely originates from the intermodel difference in water vapor shortwave absorptivity. Hence, we alter the water vapor shortwave absorptivity in the Community Earth System Model, version 1, with the Community Atmosphere Model, version 4 (CESM1-CAM4). Increasing the water vapor shortwave absorptivity leads to a reduction in global-mean precipitation and a La Niña–like cooling over the tropical Pacific. The global-mean atmospheric energy budget suggests that the precipitation is suppressed as a way to compensate for the increased SWA. The precipitation reduction is driven by the weakened surface winds, stabilized planetary boundary layer, and surface cooling. The La Niña–like cooling over the tropical Pacific is attributed to the zonal asymmetry of climatological evaporative damping efficiency and the low cloud enhancement over the eastern basin. Complementary fixed SSTs simulations suggest that the latter is more fundamental and that it primarily arises from atmospheric processes. Consistent with our experiments, the CMIP5/6 models with a higher global-mean SWA tend to produce tropical Pacific toward a more La Niña–like mean state, highlighting the possible role of water vapor shortwave absorptivity for shaping the mean-state climate patterns.

Kim, Hanjun↗

DOE OSTI2023

MJO in Different Orbital Regimes: Role of the Mean State in the MJO’s Amplitude during Boreal Winter

Abstract The Madden–Julian oscillation (MJO) exhibits pronounced seasonality, with one of the key unanswered questions being the following: what controls the maximum in MJO precipitation variance in the Southern Hemisphere during boreal winter? In this study, we examine a set of global climate model simulations in which the eccentricity and precession of Earth’s orbit are altered to change the boreal winter mean state in an attempt to reveal the processes that are responsible for the MJO’s amplitude in the boreal winter. In response to the forced insolation changes, the north–south asymmetry in sea surface temperature is amplified in boreal fall, which intensifies the Hadley circulation in boreal winter. The stronger Hadley circulation yields higher mean precipitation and stronger mean lower-tropospheric westerlies in the southern part of the Indo-Pacific warm pool. The MJO precipitation variability increases significantly where the mean precipitation and lower-tropospheric westerlies strengthen. In the column-integrated moisture budget of the simulated MJO, only surface latent heat flux feedback shows a trend that is consistent with the MJO’s amplitude, suggesting an important role for the surface latent heat flux feedback in the MJO’s amplitude during the boreal winter. An analysis of the moisture–precipitation relationship in the simulations shows that the increase in the mean precipitation lowers the convective moisture adjustment time scale, leading to the increase in precipitation variance. Our results suggest that the mean-state precipitation plays a critical role in the maintenance mechanism of the MJO.

Meteorology & Atmospheric Sciences↗

DOE OSTI2023

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Detection and attribution (D&A) of forced precipitation change are challenging due to internal variability, limited spatial, and temporal coverage of observational records and model uncertainty. These factors result in a low signal-to-noise ratio of potential regional and even global trends. Here, we use a statistical method – ridge regression – to create physically interpretable fingerprints for the detection of forced changes in mean and extreme precipitation with a high signal-to-noise ratio. The fingerprints are constructed using Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model output masked to match coverage of three gridded precipitation observational datasets – GHCNDEX, HadEX3, and GPCC – and are then applied to these observational datasets to assess the degree of forced change detectable in the real-world climate in the period 1951–2020. We show that the signature of forced change is detected in all three observational datasets for global metrics of mean and extreme precipitation. Forced changes are still detectable from changes in the spatial patterns of precipitation even if the global mean trend is removed from the data. This shows the detection of forced change in mean and extreme precipitation beyond a global mean trend is robust and increases confidence in the detection method's power as well as in climate models' ability to capture the relevant processes that contribute to large-scale patterns of change. We also find, however, that detectability depends on the observational dataset used. Not only coverage differences but also observational uncertainty contribute to dataset disagreement, exemplified by the times of emergence of forced change from internal variability ranging from 1998 to 2004 among datasets. Furthermore, different choices for the period over which the forced trend is computed result in different levels of agreement between observations and model projections. These sensitivities may explain apparent contradictions in recent studies on whether models under- or overestimate the observed forced increase in mean and extreme precipitation. Lastly, the detection fingerprints are found to rely primarily on the signal in the extratropical Northern Hemisphere, which is at least partly due to observational coverage but potentially also due to the presence of a more robust signal in the Northern Hemisphere in general.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

On the mean meridional mass motions of the stratosphere and mesosphere

Using a simplified, approximate 'Lagrangian-mean' dynamical formulation, the mean meridional mass circulation of the stratosphere and mesosphere is discussed. Under solstice conditions, it is shown that this Lagrangian-mean circulation may be inferred, as a first approximation, from the Eulerian-mean diabatic heating. Diabatic heating rates for the solstices, originally derived by Murgatroyd and Goody (1958), result in Lagrangian-mean rising motion at the tropical tropopause, subsidence across the extra-tropical tropopause, and a very strong summer-to-winter pole flow in the mesosphere. This circulation is exactly that obtained by Murgatroyd and Singleton (1961) for the solstices. Those authors, however, attempted to identify this circulation as the Eulerian-mean motion, and were later criticized for their neglect of the meridional eddy heat flux in the calculation, which proved to be extremely important in the winter hemisphere. The present study, nevertheless, indicates that Murgatroyd and Singleton's circulation may in fact be representative of actual air parcel motions in the stratosphere and mesosphere.

Dunkerton, T.↗

NASA NTRS1980

Theoretical mean colors for RR Lyrae variables

A hydrodynamically pulsating 0.6 solar mass model of a typical RR Lyrae variable was studied with a radiation transport-hydrodynamic computer program to predict theoretical T sub 3 and colors at many phases and to find the proper methods for getting mean colors and the consequent mean effective temperatures. The variable Eddington radiation approximation method was used with gray and with multifrequency absorption coefficients to represent the radiation flow in the outer optically thin layers. Comparison between observed and computed B-V colors indicate that these low Z population 2 models are reasonably accurate using King 1A composition opacities. The well known Oke, Giver, and Searle relation between B-V and T sub e reproduced. Mean colors were found by four different averaging methods. The method that gives a mean color and the mean T sub e closest to the nonpulsating model was the separate intensity means of B and V.

Davis, C. G.↗

NASA NTRS1984

The motion of the earth-moon system in modern tabular ephemerides. II - Inertial motion, mean longitude of the sun, and general precession in longitude

Properties of astronomical time scales (ET and UT) are considered, with particular emphasis on correctly determining of-date longitude as the sum of inertial mean longitude of the sun relative to the mean equinox of a fixed epoch (1950.0), and the general precession in longitude accumulated since the epoch. The inertial mean longitude and motion (relative to the mean equinox) are derived from tabular ephemerides such as the Jet Propulsion Laboratories' DE 102 and DE 96, by comparisons with subroutines based on Newcomb's perturbation theory. An unresolved inconsistency of approximately 1 second per century among the mean inertial motion of DE 102, IAU precession speed (1976), and the classical Newcomb of-date mean motion is found. Interpretation difficulties arising from the use of different systems of Ephemeris Time are also discussed.

Stumpff, P.↗

NASA NTRS1990

The development of the July 1989 1 deg x 1 deg and 30' x 30' terrestrial mean free-air anomaly data bases

In June 1986 a 1 x 1 deg/mean free-air anomaly data file containing 48955 anomalies was completed. In August 1986 a 30 x 30 min mean free-air anomaly file was defined containing 31787 values. For the past three years data has been collected to upgrade these mean anomaly files. The primary emphasis was the collection of data to be used for the estimation of 30 min means anomalies in land areas. The emphasis on land areas was due to the anticipated use of 30 min anomalies derived from satellite altimeter data in the ocean areas. There were 10 data sources in the August 1986 file. Twenty-eight sources were added based on the collection of both point and mean anomalies from a number of individuals and organizations. A preliminary 30 min file was constructed from the 38 data sources. This file was used to calculate 1 x 1 deg mean anomalies. This 1 x 1 deg file was merged with a 1 x 1 deg file which was a merger of the June 1986 file plus a 1 x 1 deg file made available by DMA Aerospace Center. Certain bad 30 min anomalies were identified and deleted from the preliminary 30 min file leading to the final 30 min file (the July 1989 30 min file) with 66990 anomalies and their accuracy. These anomalies were used to again compute 1 x 1 deg anomalies which were merged with the previous June 86 DMAAC data file. The final 1 x 1 deg mean anomaly file (the July 89 1 x 1 deg data base) contained 50793 anomalies and their accuracy. The anomaly data files were significantly improved over the prior data sets in the following geographic regions: Africa, Scandinavia, Canada, United States, Mexico, Central and South America. Substantial land areas remain where there is little or no available data.

Kim, Jeong-Hee↗

NASA NTRS1990

Mean sea surface and variability of the Gulf of Mexico using Geosat altimetry data

Geosat Exact Repeat Mission (ERM) altimetric measurements of the sea surface height in the Gulf of Mexico are used to determine the mean sea surface height with respect to the ellipsoid and mesoscale variability along Geosat ground tracks in the gulf for the time period from November 8, 1986 to November 25, 1988. A mean surface generated using the Geosat ERM along-track mean is calculated and contrasted with a previously derived mean surface determined using GEOS 3 and Seasat crossover differences. This provides a first look at the variability in the mean between the time periods of 1987-1988 and 1975-1978. In addition, the along-track mesoscale variability time series has been produced from the Geosat ERM data set by using a robust orbit-error removal algorithm to determine the variability of the sea-surface height with respect to the along-track mean. Good qualitative and quantitative agreement with previous in situ observations in the region is found. This study demonstrates the potential of satellite altimetry for oceanographic studies of the Gulf of Mexico.

Leben, Robert R.↗

NASA NTRS1991

Mean flow and variability in the Kuroshio Extension from Geosat altimetry data

The mean flow and temporal and spatial variations of the Kuroshio Extension in the region of 140-180 deg E and 30-40 deg N are investigated using altimeter data from the Geosat Exact Repeat Mission (ERM). Mean surface height profiles are estimated along individual tracks by assuming the velocity profile of the Kuroshio Extension to be Gaussian-shaped and by successively fitting this synthetic current's height profile to the residual height data. The mean profiles from ascending and descending tracks are used to derive the mean surface height by an inverse method and to obtain the absolute surface height fields for the first 2.5 yr of the Geosat ERM. Both the mean and the instantaneous height fields thus derived compare well with the available hydrographic data and the SST patterns from the NOAA satellites. Effects of deep mean flow and baroclinic shear are found to be important in explaining the observed propagation speeds.

Qiu, BO↗

NASA NTRS1995

Space and time aliasing structure is monthly mean polar-orbiting satellite data

Monthly mean wind fields from the European Remote Sensing Satellite (ERS1) scatterometer are presented. A banded structure which resembles the satellite subtrack is clearly and consistently apparent in the isotachs as well as the u and v components of the routinely produced fields. The structure also appears in the means of data from other polar-orbiting satellites and instruments. An experiment is designed to trace the cause of the banded structure. The European Centre for Medium-Range Weather Forecast (ECMWF) gridded surface wind analyses are used as a control set. These analyses are also sampled with the ERS1 temporal-spatial samplig pattern to form a simulated scatterometer wind set. Both sets are used to create monthly averages. The banded structures appear in the monthly mean simulated data but do not appear in the control set. It is concluded that the source of the banded structure lies in the spatial and temporal sampling of the polar-orbiting satellite which results in undersampling. The problem involves multiple timescales and space scales, oversampling and under-sampling in space, aliasing in the time and space domains, and preferentially sampled variability. It is shown that commonly used spatial smoothers (or filters), while producing visually pleasing results, also significantly bias the true mean. A three-dimensional spatial-temporal interpolator is designed and used to determine the mean field. It is found to produce satisfactory monthly means from both simulated and real ERS1 data. The implications to climate studies involving polar-orbiting satellite data are discussed.

Zeng, Lixin↗

NASA NTRS2017

The Relationships Between the Trends of Mean and Extreme Precipitation

This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

global warming↗

DOE OSTI2023

Symmetry-projected cluster mean-field theory applied to spin systems

We introduce S z spin-projection based on cluster mean-field theory and apply it to the ground state of strongly correlated spin systems. In cluster mean-fields, the ground state wavefunction is written as a factorized tensor product of optimized cluster states. In previous work, we have focused on unrestricted cluster mean-field, where each cluster is S z symmetry adapted. We here remove this restriction by introducing a generalized cluster mean-field (GcMF) theory, where each cluster is allowed to access all S z sectors, breaking S z symmetry. In addition, a projection scheme is used to restore global S z , which gives rise to the S z spin-projected generalized cluster mean-field (S z GcMF). Both of these extensions contribute to accounting for inter-cluster correlations. We benchmark these methods on the 1D, quasi-2D, and 2D J 1 – J 2 and XXZ Heisenberg models. Furthermore, our results indicate that the new methods (GcMF and S z GcMF) provide a qualitative and semi-quantitative description of the Heisenberg lattices in the regimes considered, suggesting them as useful references for further inter-cluster correlations, which are discussed in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Impacts of Mean State Ocean Heat Transport on Climate and Its Response to CO 2 Forcing

Simulations of the slab ocean configuration of the coupled Energy Exascale Earth System Model (E3SM) were used to isolate the role of poleward ocean heat transport (OHT) in shaping the climate and its response to CO 2 forcing. Imposed changes to mean-state OHT produce compensating changes in atmospheric heat transport (AHT) that are mediated by changes in surface evaporation. A reduction of maximum OHT by 0.56 PW (32%) reduces the global mean surface air temperature by 3.6°C. However, this cooler mean state exhibits 1.2°C more warming under CO 2 quadrupling, with the largest differences occurring at high latitudes. The amplified warming arises from stronger surface albedo and lapse rate feedbacks in polar regions and a shortwave cloud feedback in the southern midlatitudes. These results highlight the critical role of mean-state OHT in modulating mean-state climate, the partitioning between the OHT and AHT, and climate sensitivity.

Atmosphere-ocean-ice interactions↗

DOE OSTI2022

Quantum efficiency, photoemission energy spectra, and mean transverse energy of ultrananocrystalline diamond photocathode

The quantum efficiency and mean transverse energy of electrons emitted from a cathode determine the quality of beams generated from photoinjectors. The nitrogen-incorporated ultrananocrystalline diamond, (N)UNCD, is a new class of robust semiconductor photocathodes, which has been considered in photoinjectors for high peak current extraction. In this work, we measure the spectral response in quantum efficiency, photoemission energy spectra, and mean transverse energy of the (N)UNCD photocathode using a photoemission electron microscope. The observed quantum efficiency was comparable to that of copper photocathodes. Photoemission spectra showed the evidence of scattering of electrons before emission. This relaxation of electrons due to scattering is also observed in the spectral response of the mean transverse energy. The mean transverse energy is limited to ∼70 meV at the threshold. We attribute this to the physical and chemical roughness of the (N)UNCD photocathode and, hence, smoother films will be required to further reduce the mean transverse energy obtained from the (N)UNCD photocathode.

Kachwala, A. (ORCID:0000000301756478)↗

DOE OSTI2024

A Primer on Mean Opacities in the Radiative Transfer Equation

The radiative transfer equation is used in many applications, including the simulation of nuclear weapons. Opacity is a term that is often used in conjunction with the radiative transfer equation along with mean opacities. For someone new to the subject, there may be confusion over various parts of the radiative transfer equation or why opacities and mean opacities are so important to solving certain problems. This report aims to give a brief introduction to the radiative transfer equation as well as an explanation to why opacities and mean opacities are important. We also derive the Planck and Rosseland mean opacities, which are the most common mean opacities used in applications. At the end of the report are references that can be used to learn more about the subject.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗