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Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of historical precipitation interannual variability in CMIP6 over the United States

Interannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability of 21 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, including the 50-member fifth-generation Canadian Earth System Model single model initial-condition large ensemble (CanESM5_SMILE), to realistically simulate historical interannual precipitation variability trends within 17 regions of the contiguous United States (CONUS). We assess how accurately the CMIP6 simulations align with observational data across annual, summer, and winter periods, focusing on four key hydrometeorological metrics, including interannual precipitation variability, relative interannual precipitation variability (coefficient of variation), annual mean precipitation, and annual wet day frequency. Our findings reveal that CMIP6 ensemble members generally reproduce the spatial patterns of observed trends in annual mean precipitation. In most regions, models agree well with the signs of observed changes in annual mean precipitation, though discrepancies in trend magnitude are evident. Further, observed trends in winter mean precipitation broadly exhibit a spatial pattern similar to that of the observed annual mean. However, analysis of the CanESM5_SMILE shows that trends in precipitation variability may primarily be the result of model-simulated internal variability, suggesting caution in interpreting multi-model single-realization ensemble results. Challenges in accurately simulating interannual precipitation variability underscore the need for ongoing model refinement and validation to enhance climate projections, especially in regions vulnerable to extreme precipitation events.

54 ENVIRONMENTAL SCIENCES↗

Organochlorine pesticides and risk of papillary thyroid cancer in U.S. military personnel: a nested case-control study

Background: The effects of organochlorine pesticide (OCP) exposure on the development of human papillary thyroid cancer (PTC) are not well understood. A nested case-control study was conducted with data from the U.S. Department of Defense Serum Repository (DoDSR) cohort between 2000 and 2013 to assess associations of individual OCPs serum concentrations with PTC risk. Methods: This study included 742 histologically confirmed PTC cases (341 females, 401 males) and 742 individually-matched controls with pre-diagnostic serum samples selected from the DoDSR. Associations between categories of lipid-corrected serum concentrations of seven OCPs and PTC risk were evaluated for classical PTC and follicular PTC using conditional logistic regression, adjusted for body mass index category and military branch to compute odds ratios (OR) and 95% confidence intervals (CIs). Effect modification by sex, birth cohort, and race was examined. Results: There was no evidence of associations between most of the OCPs and PTC, overall or stratified by histological subtype. Overall, there was no evidence of an association between hexachlorobenzene (HCB) and PTC, but stratified by histological subtype HCB was associated with significantly increased risk of classical PTC (third tertile above the limit of detection (LOD) vs. <LOD, OR = 1.61, 95% CI, 1.09, 2.38; p for trend = 0.05) and significantly decreased risk of follicular variant PTC (third tertile above the limit of detection (LOD) vs. <LOD, OR = 0.38, 95% CI, 0.16, 0.91; p for trend = 0.04). Further stratified by sex, risk of classical PTC was higher for females (third tertile above LOD vs. <LOD, OR = 2.23, 95% CI: 1.23, 4.06; p-trend = 0.02) than for males (OR = 1.22, 95%CI: 0.72–2.08; p-trend = 0.56), though the test for interaction by sex was not statistically significant (p-interaction = 0.30). Similarly, β-hexachlorocyclohexane (β-HCCH) was associated with a higher risk for classical PTC for women with concentrations ≥LOD versus <LOD (OR = 1.76, 95% CI: 1.07, 2.89), while the effects were null for men. There were no consistent trends when stratified by race or birth year. Conclusions: The U.S. Environmental Protection Agency has classified HCB and other OCPs we studied here as probable human carcinogens. Our findings of increased risks for classical PTC associated with increased concentrations of HCB and β-HCCH, which were stronger among females, should be replicated in future studies of other populations.

60 APPLIED LIFE SCIENCES↗

VADER: A Tool for Criticality Safety Validation

The purpose of criticality safety is to prevent any inadvertent criticality from occurring during the handling or storage of fissile material. Calculations are frequently used to demonstrate that a sufficient subcritical margin exists. Validation is a key aspect of the evaluation process, establishing the suitability, accuracy, and associated uncertainty of the computational method and data to be used for the intended application. The validation process is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 in order to investigate the parameters at which such a critical condition is achieved. The validation parameters that are traditionally applied to safety analysis calculations are the bias and the bias uncertainty . The bias is the deviation of the average k eff of the validation suite from unity. The bias uncertainty accounts for the statistical uncertainty in the bias based on the standard deviation, sample size, and distribution of k eff values of the validation suite. The values of bias and bias uncertainty ensure that the systems predicted to be subcritical by the computational method will indeed be subcritical. The bias and bias uncertainty are often combined to determine an upper subcritical limit (USL) or computational margin that can then be applied to safety analysis calculations. Many methods have been developed by different organizations to calculate the bias and bias uncertainty for various types of criticality analyses. Each of these methods typically requires that the validity of various underpinning statistical assumptions be confirmed to demonstrate that the method is appropriate for the analysis of a given validation suite. An example of the validation decision making flow is shown in Fig.1. As shown in Fig. 1, the analyst performing the validation fits a trend line to the data and performs a test to determine if the trend was a statistically better representation of the data than if it were treated as an uncorrelated sample. If the trend line is a better representation of the data, then the analyst uses any one of a number of trending techniques to determine the bias and bias uncertainty. If a trend is not an appropriate representation of the data, then the analyst proceeds to perform a normality assessment for the data. If the normal assumption can be shown to be acceptable, then the analyst calculates the bias and bias uncertainty with the parametric technique. If the assumption of normality cannot be justified, then the nonparametric technique is used. Once the decision flow has been followed and the appropriate technique has been selected, the bias and bias uncertainty is typically combined with an administrative margin to determine a USL below which calculated values of k eff for safety analysis models can be considered subcritical. The calculations used in each decision are often performed with spreadsheets or with small programs available at various sites performing criticality analyses. Expertise in understanding and interpreting the results must be maintained to perform these calculations. This can often be an error-prone process. Oak Ridge National Laboratory (ORNL) is currently developing the Validation and Data Evaluation Resource (VADER) to simplify and automate the criticality safety validation process and to provide a software quality assurance pedigree to the calculational methods used. This paper discusses the use of the Fulcrum user interface with VADER, the anticipated initial capabilities of VADER to perform validation analyses, and the output from the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transient Pressure Interference During CO2 Injection in Saline Aquifers

Abstract CO2 injection in subsurface geological formations (e.g. deep saline aquifers) causes pressure perturbations over a large area surrounding the injection well. Observation wells are widely considered in geologic CO2 storage (GCS) projects where the pressure perturbation induced by CO2 injection is measured. In this work, we use analytical and numerical modeling tools along with field data to examine the pressure behavior in GCS projects before and after CO2 arrival at an observation well. Prior to CO2 arrival, a baseline pressure trend is established which corresponds to single-phase brine flow across the observation well (approximated by Theis solution). Therefore, analysis of early-time pressure data is straightforward, provides the single-phase flow characteristics (mobility and storativity), and helps establishing a baseline pressure change that can be extended beyond the single-phase flow period at the observation well. Upon CO2 arrival, a departure from this baseline trend is expected. For the pressure to detect the CO2 arrival at an observation well, the departure from baseline pressure behavior must be significant and well above the background noise levels. We use existing analytical models to determine the strength of the expected pressure departure signal from the baseline trend upon CO2 arrival. The strength of the expected pressure departure is found to be directly proportional to the mobility ratio. Accordingly, we establish a criterion to determine whether the pressure at an observation well can detect the CO2 arrival. We present an analysis approach through application to synthetic and field data and show the characteristic pressure behavior before and after CO2 arrival. We show that while generally the pressure can be either above or below the expected baseline pressure trend, it would be likely above the baseline upon CO2 arrival. This is because the mobility ratio becomes less than unity after CO2 arrival. We show that depending on the reservoir characteristics, changes in the pressure trend may or may not be sufficient to detect the CO2 arrival.

Engineering↗

U.S. Hydropower Market Report (January 2021 edition)

This is the third complete edition of the U.S. Hydropower Market Report (the first two were the 2014 and 2017 Hydropower Market Report published in 2015 and 2018, respectively). In intervening years between publishing the full report, updated data are also summarized and released, and can be found at the Oak Ridge National Lab (ORNL) HydroSource website. This report combines data from public and commercial sources as well as research findings from other Department of Energy (DOE) R&D projects in order to provide a comprehensive picture of developments in the U.S. hydropower and PSH fleet and industry trends. Prior to the first Market Report being published, there was a noted lack of publicly available and easily accessible information about hydropower in the United States and other important trends affecting this important sector of the energy industry. New and valuable types of information are constantly being developed in the course of DOE research activities and, in a rapidly evolving energy industry, it is important that these data be made available in a predictable and consistent manner for use by all different types of stakeholders and decision-makers.The report highlights developments in 2017–2019 (the years for which new data has become available since the publication of the 2017 Hydropower Market Report), and contextualizes this information compared to evolving high-level trends over the past 10–20 years. Apart from presenting trends over time, the report discusses differences in those trends by region, plant size, owner type, or other attributes.

13 HYDRO ENERGY↗

Unifying principles for catalytic hydrotreating processes (Final Technical Report)

This project builds on the hypothesis that the hydrotreating processes for the removal of oxygen and sulfur are fundamentally similar at the atomic-scale and existing knowledge from the treatment of petroleum derived feedstock can be leveraged for the design of novel catalysts for the upgrade of bio-oil. We tested this hypothesis by comparing computed potential energy diagrams for hydrodesulfurization (HDS) of thiophene over MoS 2 with hydrodeoxygenation (HDO) of furan over MoO 3 and concluded that certain aspects, such as catalyst promotion with transition metals, are valid strategies for both reactions. On the other hand, we also noticed significant differences in the mechanism for hydrogen (H 2 ) activation, which requires sites with metallic character. While MoS 2 is known to have metallic edge states that can catalyze H 2 dissociation, this elementary step is prohibitively slow on defect-free oxides. Only in the presence of vacancies or by creating metal/oxide interfaces can efficient H 2 activation sites during HDO be formed. The need for bifunctional catalyst when it comes to efficient and selective HDO or dehydrogenation reactions was further corroborated in joint experimental and theoretical studies of the Guerbet reaction for the coupling of biomass derived oxygenates over PdCu alloys, nitrate reduction over In-promoted Pd nanoparticles, and ethylene dehydroaromatization over Ga-exchanged ZSM-5 zeolites. All of these catalytic systems have in common that catalytic sites with distinct functional requirements are needed to create a working catalyst. Detailed computational studies were carried out for HDO of m -cresol and phenol on Ru-modified TiO 2 surfaces, which allowed us to attribute catalytic activity to the metal/oxide interface. A surprising finding was that heterolytic cleavage of the H-H bond across the Ru/TiO 2 interface was critically important, despite lower barriers for homolytic H 2 activation on Ru metal. The explanation lies in the high barriers for hydrogen spillover from Ru to TiO 2 , which becomes unnecessary in the heterolytic activation pathway. Moreover, we also reported that proton transfer steps between metal and oxide sites are mediated by weakly adsorbed surface water. During attempts to develop and validate a kinetic Monte Carlo (kMC) model for HDO reactions at the Ru/TiO 2 interface, it became clear that lateral interactions are paramount to describe realistic surface chemistry and without these interactions, the reduction and hydroxylation behavior from our simulations was inconsistent with reported experiments. To assess the importance of lateral interactions in popular computational catalyst design strategies relying on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends, we compared predicted trends with those obtained from descriptor-based kMC models. We critically evaluated the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. The mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, we concluded that the MKM approach does provide an overall better entry point for computational catalyst design. Overall, this project has led to 11 peer-reviewed publications, and their scientific is impact is well illustrated by their combined 702 citations.

08 HYDROGEN↗

Simulations of ocean deoxygenation in the historical era: insights from forced and coupled models

Ocean deoxygenation due to anthropogenic warming represents a major threat to marine ecosystems and fisheries. Challenges remain in simulating the modern observed changes in the dissolved oxygen (O 2 ). Here, we present an analysis of upper ocean (0-700m) deoxygenation in recent decades from a suite of the Coupled Model Intercomparison Project phase 6 (CMIP6) ocean biogeochemical simulations. The physics and biogeochemical simulations include both ocean-only (the Ocean Model Intercomparison Project Phase 1 and 2, OMIP1 and OMIP2) and coupled Earth system (CMIP6 Historical) configurations. We examine simulated changes in the O 2 inventory and ocean heat content (OHC) over the past 5 decades across models. The models simulate spatially divergent evolution of O 2 trends over the past 5 decades. The trend (multi-model mean and spread) for upper ocean global O 2 inventory for each of the MIP simulations over the past 5 decades is 0.03 ± 0.39×10 14 [mol/decade] for OMIP1, -0.37 ± 0.15×10 14 [mol/decade] for OMIP2, and -1.06 ± 0.68×10 14 [mol/decade] for CMIP6 Historical, respectively. The trend in the upper ocean global O2 inventory for the latest observations based on the World Ocean Database 2018 is -0.98×10 14 [mol/decade], in line with the CMIP6 Historical multi-model mean, though this recent observations-based trend estimate is weaker than previously reported trends. A comparison across ocean-only simulations from OMIP1 and OMIP2 suggests that differences in atmospheric forcing such as surface wind explain the simulated divergence across configurations in O 2 inventory changes. Additionally, a comparison of coupled model simulations from the CMIP6 Historical configuration indicates that differences in background mean states due to differences in spin-up duration and equilibrium states result in substantial differences in the climate change response of O 2 . Finally, we discuss gaps and uncertainties in both ocean biogeochemical simulations and observations and explore possible future coordinated ocean biogeochemistry simulations to fill in gaps and unravel the mechanisms controlling the O 2 changes.

54 ENVIRONMENTAL SCIENCES↗

The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment

As a genre of physics-informed machine learning, differentiable process-based hydrologic models (abbreviated as δ or delta models) with regionalized deep-network-based parameterization pipelines were recently shown to provide daily streamflow prediction performance closely approaching that of state-of-the-art long short-term memory (LSTM) deep networks. Meanwhile, δ models provide a full suite of diagnostic physical variables and guaranteed mass conservation. Here, we ran experiments to test (1) their ability to extrapolate to regions far from streamflow gauges and (2) their ability to make credible predictions of long-term (decadal-scale) change trends. We evaluated the models based on daily hydrograph metrics (Nash–Sutcliffe model efficiency coefficient, etc.) and predicted decadal streamflow trends. For prediction in ungauged basins (PUB; randomly sampled ungauged basins representing spatial interpolation), δ models either approached or surpassed the performance of LSTM in daily hydrograph metrics, depending on the meteorological forcing data used. They presented a comparable trend performance to LSTM for annual mean flow and high flow but worse trends for low flow. For prediction in ungauged regions (PUR; regional holdout test representing spatial extrapolation in a highly data-sparse scenario), δ models surpassed LSTM in daily hydrograph metrics, and their advantages in mean and high flow trends became prominent. In addition, an untrained variable, evapotranspiration, retained good seasonality even for extrapolated cases. The δ models' deep-network-based parameterization pipeline produced parameter fields that maintain remarkably stable spatial patterns even in highly data-scarce scenarios, which explains their robustness. Combined with their interpretability and ability to assimilate multi-source observations, the δ models are strong candidates for regional and global-scale hydrologic simulations and climate change impact assessment.

54 ENVIRONMENTAL SCIENCES↗

Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard

The Arctic is undergoing increased warming compared to the global mean, which has major implications for freshwater runoff into the oceans from seasonal snow and glaciers. Here, we present high-resolution (2.5 km) simulations of glacier mass balance, runoff, and snow conditions on Svalbard from 1991–2022, one of the fastest warming regions in the world. The simulations are created using the CryoGrid community model forced by Copernicus Arctic Regional ReAnalysis (CARRA) (1991–2021) and AROME-ARCTIC forecasts (2016–2022). Updates to the water percolation and runoff schemes are implemented in the CryoGrid model for the simulations. In situ observations available for Svalbard, including automatic weather station data, stake measurements, and discharge observations, are used to carefully evaluate the quality of the simulations and model forcing. We find a slightly negative climatic mass balance (CMB) over the simulation period of -0.08 mw.e.yr -1 but with no statistically significant trend. The most negative annual CMB is found for Nordenskiöldland (-0.73 mw.e.yr -1 ), with a significant negative trend of -0.27 mw.e. per decade for the region. Although there is no trend in the annual CMB, we do find a significant increasing trend in the runoff from glaciers of 0.14 mw.e. per decade. The average runoff was found to be 0.8 mw.e.yr -1 . We also find a significant negative trend in the refreezing of -0.13 mw.e. per decade. Using AROME-ARCTIC forcing, we find that 2021/22 has the most negative CMB and highest runoff over the 1991–2022 simulation period investigated in this study. We find the simulated climatic mass balance and runoff using CARRA and AROME-ARCTIC forcing are similar and differ by only 0.1 mw.e.yr -1 in climatic mass balance and by 0.2 mw.e.yr -1 in glacier runoff when averaged over all of Svalbard. There is, however, a clear difference over Nordenskiöldland, where AROME-ARCTIC simulates significantly higher mass balance and significantly lower runoff. This indicates that AROME-ARCTIC may provide similar high-quality predictions of the total mass balance of Svalbard as CARRA, but regional uncertainties should be taken into consideration. The simulations produced for this study are made publicly available at a daily and monthly resolution, and these high-resolution simulations may be re-used in a wide range of applications including studies on glacial runoff, ocean currents, and ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Identification of geostructures of continental crust particularly as they relate to mineral resource evaluation

The author has identified the following significant results. Lakes in the Arctic Coastal Plain of Alaska are dominantly elongate, with their long axes parallel and trending about N 9 W. On ERTS-1 imagery, an additional strong east-trending regional lineation, not previously recognized on aerial photographs or in field study, was noted. In addition, the alignment of many small lakes forms a large and a small ellipse superimposed on the regional lineation. Fischer and Lathram find that the trend of this lineation is parallel to the trend of deflections in contours of the magnetic and gravity fields in the area, and parallel to westerly deflections in the northwest ends of northwest-trending folds mapped to the south. These data suggest that heretofore unsuspected structures may be concealed beneath Quaternary mantling sediments in the area of the image. The strata in these folds would be younger than those tapped by the oil wells of the Umiat field to the south, and favorable sandstone facies may occur in the area. The significance of these observations to oil exploration in northern Alaska needs to be evaluated further.

Gryc, G.↗

Fault tectonics and earthquake hazards in the Peninsular Ranges, Southern California

The author has identified the following significant results. ERTS and Skylab images reveal a number of prominent lineaments in the basement terrane of the Peninsular Ranges, Southern California. The major, well-known, active, northwest trending, right-slip faults are well displayed, but northeast and west to west-northwest trending lineaments are also present. Study of large-scale airphotos followed by field investigations have shown that several of these lineaments represent previously unmapped faults. Pitches of striations on shear surfaces of the northeast and west trending faults indicate oblique-slip movement; data are insufficient to determine the net-slip. These faults are restricted to the pre-Tertiary basement terrane and are truncated by the major northwest trending faults; therefore, they may have formed in response to an earlier stress system. Future work should be directed toward determining whether the northeast and west trending faults are related to the presently active stress system or to an older inactive system, because this question relates to the earthquake risk in the vicinity of these faults.

Merifield, P. M.↗

Block V module program

An outlined overview of this module program is given. Tables are given for the following characteristics: module power trend, packing factor trend, cell and circuit characteristics, module physical characteristics, electrical performance, cell efficiency trend, module efficiency trend and module cost trend. The principal improvements are larger modules and higher performance.

Smokler, M. I.↗

Wintertime losses of ozone in high northern latitudes

Total column ozone data over the past 22 to 30 years from ground-based Dobson and filter ozonometer stations between 30 N and 80 N are analyzed for residual trends remaining after allowance for the known geophysical variations corresponding to: (1) the change of seasons; (2) the quasi-biennial oscillation; and (3) the 11-year solar sunspot cycle. Examination of the data from several ground stations between 45 and 55 N indicated a seasonal difference in the long-term ozone series, with statistically significant losses in several winter months. Accordingly, the data from individual stations were analyzed with multiple regression analysis, seeking trends on a monthly basis after allowance for the known geophysical cycles. Previous statistical analyses were conducted as tests of 1-D model calculations which do not show any differences with the seasons, and any trend toward change in ozone concentrations is expressed in a yearly trend without seasonal variation. Such a model is inappropriate for calculations with a data set which exhibits a pronounced tendency toward seasonal differences in the trends. Comparisons with model calculations then require 2-D models into which seasonal and latitudinal differences can easily be programmed.

Harris, Neil↗

Antarctic Sea ice variations and seasonal air temperature relationships

Data through 1987 are used to determine the regional and seasonal dependencies of recent trends of Antarctic temperature and sea ice. Lead-lag relationships involving regional sea ice and air temperature are systematically evaluated, with an eye toward the ice-temperature feedbacks that may influence climatic change. Over the 1958-1087 period the temperature trends are positive in all seasons. For the 15 years (l973-l987) for which ice data are available, the trends are predominantly positive only in winter and summer, and are most strongly positive over the Antarctic Peninsula. The spatially aggregated trend of temperature for this latter period is small but positive, while the corresponding trend of ice coverage is small but negative. Lag correlations between seasonal anomalies of the two variables are generally stronger with ice lagging the summer temperatures and with ice leading the winter temperatures. The implication is that summer temperatures predispose the near-surface waters to above-or below-normal ice coverage in the following fall and winter.

Weatherly, John W.↗

Solar cell angle of incidence corrections

Literature on solar array angle of incidence corrections was found to be sparse and contained no tabular data for support. This lack along with recent data on 27 GaAs/Ge 4 cm by 4 cm cells initiated the analysis presented in this paper. The literature cites seven possible contributors to angle of incidence effects: cosine, optical front surface, edge, shadowing, UV degradation, particulate soiling, and background color. Only the first three are covered in this paper due to lack of sufficient data. The cosine correction is commonly used but is not sufficient when the incident angle is large. Fresnel reflection calculations require knowledge of the index of refraction of the coverglass front surface. The absolute index of refraction for the coverglass front surface was not known nor was it measured due to lack of funds. However, a value for the index of refraction was obtained by examining how the prediction errors varied with different assumed indices and selecting the best fit to the set of measured values. Corrections using front surface Fresnel reflection along with the cosine correction give very good predictive results when compared to measured data, except there is a definite trend away from predicted values at the larger incident angles. This trend could be related to edge effects and is illustrated by a use of a box plot of the errors and by plotting the deviation of the mean against incidence angle. The trend is for larger deviations at larger incidence angles and there may be a fourth order effect involved in the trend. A chi-squared test was used to determine if the measurement errors were normally distributed. At 10 degrees the chi-squared test failed, probably due to the very small numbers involved or a bias from the measurement procedure. All other angles showed a good fit to the normal distribution with increasing goodness-of-fit as the angles increased which reinforces the very small numbers hypothesis. The contributed data only went to 65 degrees from normal which prevented any firm conclusions about extreme angle effects although a trend in the right direction was seen. Measurement errors were estimated and found to be consistent with the conclusions that were drawn. A controlled experiment using coverglasses and cells from the same lots and extending to larger incidence angles would probably lead to further insight into the subject area.

Burger, Dale R.↗

Compositional Variation in Apollo 16 Impact-Melt Breccias and Inferences for the Geology and Bombardment History of the Central Highlands of the Moon

High-precision data for the concentrations of a number of lithophile and siderophile elements were obtained on multiple subsamples from 109 impact-melt rocks and breccias (mostly crystalline) from the Apollo 16 site. Compositions of nearly all Apollo 16 melt rocks fall on one of two trends of increasing Sm concentration with increasing Sc concentration. The Eastern trend (lower Sm/Sc, Mg/Fe, and Sm/Yb ratios) consists of compositional groups 3 and 4 of previous classification schemes. These melt rocks are feldspathic, poor in incompatible and siderophile elements, and appear to have provenance in the Descartes formation to the east of the site. The Western trend (higher Sm/Sc. Mg/Fe, and Sm/ Yb ratios) consists of compositional groups 1 and 2. These relatively mafic, KREEP-bearing breccias are a major component (approx.35%) of the Cayley plains west of the site and are unusual, compared to otherwise similar melt breccias from other sites, in having high concentrations of Fe-Ni metal ( 1-2 %). The metal is the carrier of the low-Ir/Au (approx. 0.3 x chondritic) siderophile-element signature that is characteristic of the Apollo 16 site. Four compositionally distinct groups (1M, 1F, 2DB, and 2NR) of Western-trend melt breccias occur that are each represented by at least six samples. Compositional group 1 or previous classification schemes (the 'poikilitic' or 'LKFM' melt breccias) can be subdivided into two groups. Group 1M (represented by six samples, including 60315) is characterized by lower Al2O3 concentrations, higher MgO and alkali concentrations, and higher Mg/Fe and Cr/Sc ratios than group 1F (represented by fifteen samples, including 65015). Group 1M also has siderophile-element concentrations averaging about twice those of group lF and Ir/Au and Ir/Ni ratios that are even lower than those of other Western-trend melt rocks (Ir/Au = 0.24 +/- 0.03. CI-normalized). At the mafic extreme of group 2 ('VHA' melt breccias), the melt lithology occurring as clasts in feldspathic fragmental breccias from North Ray crater (group 2NR) is compositionally distinct from the melt lithology ofdimict breccias from the Cayley plains (group 2DB) in having higher concentrations of Sc, Cr, and heavy rare earth elements and lower concentrations of siderophile elements. The distinct siderophile-element signature (high absolute abundances, low Ir/Au ratio) suggest that the four groups ofmafic melt breccia are all somehow related. Ratios ofsome lithophile elements also suggest that they are more closely related to each other than then, are to melt breccias from other Apoll sites. However, none of the breccia compositions can be related to any of the others by any simple process of igneous fractionation or mixing involving common lunar materials. Thus, the origin of the four groups of mafic melt breccia is enigmatic. If they were produced in only one or two impacts, then a mechanism exists for generating regimes of impact-melt breccia in a single impact that are substantially different from each other in composition. For various reasons, including the problem of delivering large volumes of four different types of melt to the Apollo 16 site, it is unlikely that any of these breccias were produced in basin-forming impacts. If they were produced in as many as four crater-forming impacts, then the unusual siderophile-element signature is difficult to explain. Possible explanations are (1) the four groups of melt breccia all contain metal from a single, earlier impact, (2) they were each formed by related metal-rich meteoroids, or (3) some common postimpact process has resulted in metal of similar composition in each of four melt pools. Within a compositional group, most intrasample and intersample variation in lithophile element concentrations is caused by differences among samples in the proportion of a component of normative anorthosite or noritic anorthosite. In most cases, this compositional variation probably reflects variation in clast abundance. For group 2DB (and probably 2NR), differences in abundance of a component of ferroan anorthosite (estimated Al2O3 approx. 32%) accounts for the compositional variation. For groups 1M and 1F, the anorthositic component is more mafic (estimated Al203 approx. 26%). Some group-2 samples may be related by a troctolitic component of varying abundance.

Korotev, Randy L.↗

Measuring Greenland Ice Mass Variation With Gravity Recovery and the Climate Experiment Gravity and GPS

The response of the Greenland ice sheet to climate change could significantly alter sea level. The ice sheet was much thicker at the last glacial maximum. To gain insight into the global change process and the future trend, it is important to evaluate the ice mass variation as a function of time and space. The Gravity Recovery and Climate Experiment (GRACE) mission to fly in 2001 for 5 years will measure gravity changes associated with the current ice variation and the solid earth's response to past variations. Our objective is to assess the separability of different change sources, accuracy and resolution in the mass variation determination by the new gravity data and possible Global Positioning System (GPS) bedrock uplift measurements. We use a reference parameter state that follows a dynamic ice model for current mass variation and a variant of the Tushingham and Peltier ICE-3G deglaciation model for historical deglaciation. The current linear trend is also assumed to have started 5 kyr ago. The Earth model is fixed as preliminary reference Earth model (PREM) with four viscoelastic layers. A discrete Bayesian inverse algorithm is developed employing an isotropic Gaussian a priori covariance function over the ice sheet and time. We use data noise predicted by the University of Texas and JPL for major GRACE error sources. A 2 mm/yr uplift uncertainty is assumed for GPS occupation time of 5 years. We then carry out covariance analysis and inverse simulation using GRACE geoid coefficients up to degree 180 in conjunction with a number of GPS uplift rates. Present-day ice mass variation and historical deglaciation are solved simultaneously over 146 grids of roughly 110 km x 110 km and with 6 time increments of 3 kyr each, along with a common starting epoch of the current trend. For present-day ice thickness change, the covariance analysis using GRACE geoid data alone results in a root mean square (RMS) posterior root variance of 2.6 cm/yr, with fairly large a priori uncertainties in the parameters and a Gaussian correlation length of 350 km. Simulated inverse can successfully recover most features in the reference present-day change. The RMS difference between them over the grids is 2.8 cm/yr. The RMS difference becomes 1.1 cm/yr when both are averaged with a half Gaussian wavelength of 150 km. With a fixed Earth model, GRACE alone can separate the geoid signals due to past and current load fairly well. Shown are the reference geoid signatures of direct and elastic effects of the current trend, the viscoelastic effect of the same trend starting from 5 kyr ago, the Post Glacial Rebound (PGR), and the predicted GRACE geoid error. The difference between the reference and inverse modeled total viscoelastic signatures is also shown. Although past and current ice mass variations are allowed the same spatial scale, their geoid signals have different spatial patterns. GPS data can contribute to the ice mass determination as well. Additional information is contained in the original.

Wu, Xiao-Ping↗