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At least 1,135 records · Page 63

Projecting the Local Impacts of Climate Change on a Central American Montane Avian Community

Significant changes in the climates of Central America are expected over the next century. Lowland rainforests harbor high alpha diversity on local scales (<1 km2), yet montane landscapes often support higher beta diversity on 10-100 km2 scales. Climate change will likely disrupt the altitudinal zonation of montane communities that produces such landscape diversity. Projections of biotic response to climate change have often used broad-scale modelling of geographical ranges, but understanding likely impacts on population viability is also necessary for anticipating local and global extinctions. We model species abundances and estimate range shifts for birds in the Tilaran Mountains of Costa Rica, asking whether projected changes in temperature and rainfall could be sufficient to imperil high-elevation endemics and whether these variables will likely impact communities similarly. We find that nearly half of 77 forest bird species can be expected to decline in the next century. Almost half of species projected to decline are endemic to Central America, and seven of eight species projected to become locally extinct are endemic to the highlands of Costa Rica and Panam . Logistic-regression modelling of distributions and similarity in projections produced by temperature and rainfall models suggest that changes in both variables will be important. Although these projections are probably conservative because they do not explicitly incorporate biological or climate variable interactions, they provide a starting point for incorporating more realistic biological complexity into community-change models. Prudent conservation planning for tropical mountains should focus on regions with room for altitudinal reorganization of communities comprised of ecological specialists.

Gasner, Matthew R.↗

Building Climate Resilience at NASA Ames

NASA Ames Research Center, located at the southern end of the San Francisco Bay (SFB) estuary has identified three primary vulnerabilities to changes in climate. The Ames Climate Adaptation Science Investigator (CASI) workgroup has studied each of these challenges to operations and the potential exposure of infrastructure and employees to an increased frequency of hazards. Sea level rise inundation scenarios for the SFB Area generally refer to projected scenarios in mean sea level rather than changes in extreme tides that could occur during future storm conditions. In the Summer of 2014, high resolution 3-D mapping of the low lying portion of Ames was performed. Those data are integrated with improved sea level inundation scenarios to identify the buildings, basements and drainage systems potentially affected. We will also identify the impacts of sea level and storm surge effects on transportation to and from the Center. This information will help Center Management develop future Master Plans. Climate change will also lead to changes in temperature, storm frequency and intensity. These changes have potential impacts on localized floods and ecosystems, as well as on electricity and water availability. Over the coming decades, these changes are going to be imposed on top of ongoing land use and land cover changes, especially those deriving from continued urbanization and increase in impervious surface areas. These coupled changes have the potential to create a series of cascading impacts on ecosystems, including changes in primary productivity and disturbance of hydrological properties and increased flood risk.The majority of the electricity used at Ames is supplied by hydroelectric dams, which will be influenced by reductions in precipitation or changes in the timing or phase of precipitation which reduces snow pack. Coupled with increased demand for summertime air conditioning and other cooling needs, NASA Ames is at risk for electricity shortfalls. To assess the anticipated energy usage as climate changes, the Ames CASI team is collecting historical energy usage data from Ames facilities, historical weather data, and projected future weather parameters from the CASI Climate subgroup. This data will be incorporated into the RETScreen model to predict how energy usage at Ames will change over the coming century.

climate↗

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗

Sensitivity of Regional Climate to Deforestation in the Amazon Basin

The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem.

Eltahir, Elfatih A. B.↗

First principles calculations in support of Pu aging: calculating the effects of lattice imperfections on thermodynamics

Plutonium (Pu) has, in theory, well defined crystal structures: its atoms are arranged in regular spatial patterns. But Pu is radioactive, and as its nuclei decay those regular spatial patterns are interrupted. The interruptions are lattice imperfections, which are known to affect how materials respond to their environment. To adequately model Pu, we need to know which lattice imperfections are present, how they interact with each other, and how they affect the material’s response to its environment. The work presented here aims to use density functional theory (DFT) calculations to begin to answer the latter, in particular, how individual lattice imperfections affect measurable effects including thermal expansion (the change in volume in response to a change in temperature), heat capacity (the amount of thermal energy needed to change a material’s temperature), and elastic moduli (a material’s resistance to applied stresses). Pu poses many computational challenges. The $\textit{f}$ electrons require special attention. Of all the elements, Pu has the largest number of electrons that must be included in the calculations. Thermal effects require calculating the phonons (the lattice vibrations), which for systems containing lattice imperfections demand large, complex computational cells - but computational resources limit the size and complexity. With careful restructuring of how the calculations are performed, all these challenges have been met to enable calculations that provide insight into how lattice imperfections affect Pu’s response to its environment. Reported here are the computational challenges and the advances developed to meet them, along with the first results showing the strong effect that one prototype lattice imperfection (an interstitial Pu atom in a delta-phase Pu lattice) has on Pu’s response to its environment.

36 MATERIALS SCIENCE↗

Thermoresponsive antifouling ultrafiltration membranes from mesophase templating

Nanostructured polymers synthesized by lyotropic liquid crystal (LLC) templates with normal hexagonal (H 1 ) structure exhibit a 3D-continuous transport path, which makes them ideal for membrane separation application. Incorporating additional functionality, especially stimuli-responsiveness, in such an ordered structure provides even more application opportunities. Here, in this work, we present the first successful synthesis of H 1 -structured thermoresponsive ultrafiltration (UF) membranes via LLC templating. The membrane contains thermoresponsive Pluronic P84 diacrylate (P84DA) which not only acts as the monomer and structure-directing amphiphile, but also enables the pore size change with temperature. Experimental studies reveal that the swelling capacity of H 1 -templated polymer as well as permeability and selectivity of the obtained membrane can be altered by changing the temperature. Increasing the temperature from 25 to 45 °C increases the normalized flux from 28 to 68 L m -2 h -1 μm and molecular weight cut-off (MWCO) from 2200 to 3900 Da. Furthermore, the membrane shows an outstanding fouling resistance against different solutes.

36 MATERIALS SCIENCE↗

Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery

Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (p < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, p < 0.001, D = 0.99; KS test 2019 vs. 2021, p < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.

Barker, Matthew I. (ORCID:0000000252864930)↗

How Can Future Climate Change Affect the Corn Production System in Nebraska, USA?

The increasing temperatures and changing precipitation patterns have affected both crop yields and water requirements challenging agricultural systems in sustaining high crop yields and ensuring water and food security. In the present study, we evaluated the impact of climate change on the corn production under irrigated and rainfed cropping systems in Nebraska considering four climate zones until 2100 as a case study for the US Corn Belt. Additionally, suggests ways to reduce the impact of climate change on corn yield and water resources. Five global circulation model datasets from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) interconnected to Shared Socioeconomic Pathways (SSPs), were selected. Three future periods: near (2020–2039), mid (2040–2069), and far future (2070–2100) under SSP226, SSP370, and SSP585 scenarios were used to predict the climate changes, crop cycle length, crop yield, and crop water requirement. Additionally, we input annual CO2 concentration scenarios for each SSP scenario to model changes from 2015 to 2100 using the CERES-Maize model. Temperatures are forecasted to rise, precipitation to decline, and crop cycle length to decrease, particularly for SSP370 (up to 49% yield decrease) and SSP585 (up to 67% yield decrease) by 2070–2100. Yields are expected to decline across all scenarios and periods for irrigated and rainfed fields due to the reduction in crop cycle length. Crop water demand is projected to increase, with rainfed systems facing heightened impact due to reduced precipitation. Addressing climate change in Nebraska requires actions like developing new corn varieties to longer the crop season, transitioning to efficient irrigation systems, improving irrigation management for water and food security, and reducing the risk of conflicts over its use. These results open possibilities for discussion about the actions that can be taken to cope with climate change and guarantee water and food security in the US Corn Belt.

CMIP6↗

Radiative forcing perturbation due to observed increases in tropospheric ozone at Hohenpeissenberg

The effect on surface temperature due to changes in atmospheric O3 depends highly on the latitude where the change occurs. Previous sensitivity calculations indicate that ozone changes in the upper troposphere and lower stratosphere are more effective in causing surface temperature change (Wang et al., 1980). Long term ground-based observations show that tropospheric ozone, especially at the tropopause region, has been increasing at middle and high latitudes in the Northern Hemisphere (NATO, 1988; Quadrennial Ozone Symposium, 1992). These increases will enhance the greenhouse effect and increase the radiative forcing to the troposphere-surface system, which is opposite to the negative radiative forcing calculated from the observed stratospheric ozone depletion recently reported in WMO (1992). We used more than two thousands regularly measured ozonesondes providing reliable vertical O3 distribution at Hohenpeissenberg (47N; 11E) for the 1967-1990 to study the instantaneous solar and longwave radiative forcing the two decades 1971-1990 and compare the forcing with those caused by increasing CO2, CH4, N2O, and CFCs. Calculations are also made to compare the O3 radiative forcing between stratospheric depletion and tropospheric increase. Results indicate that the O3 changes will induce a positive radiative forcing dominated by tropospheric O3 increase and the magnitude of the forcing is comparable to that due to CO2 increases during the two decades. The significant implications of the tropospheric O3 increase to the global climate are discussed.

Wang, Wei-Chyung↗

Radial evolution of the solar wind from IMP 8 to Voyager 2

Voyager 2 and Interplanetary Monitoring Platform (IMP) 8 data from 1977 through 1994 are presented and compared. Radial velocity and temperature structures remain intact over the distance from 1 to 43 AU, but density structures do not. Temperature and velocity changes are correlated and nearly in phase at 1 AU, but in the outer heliosphere temperature changes lead velocity changes by tens of days. Solar cycle variations are detected by both spacecraft, with minima in flux density and dynamic pressure near solar maxima. Differences between Voyager 2 and IMP 8 observations near the solar minimum in 1986-1987 are attributed to latitudinal gradients in solar wind properties. Solar rotation variations are often present even at 40 AU. The Voyager 2 temperature profile is best fit with a R(exp -0.49 +/- 0.01) decrease, much less steep than an adiabatic profile.

Richardson, John D.↗

Remotely controllable actuating device

An actuating device can change a position of an active member that remains in substantially the same position in the absence of a force of a predetermined magnitude on the active member. The actuating device comprises a shape-memory alloy actuating member for exerting a force when actuated by changing the temperature thereof, which shape-memory alloy actuating member has a portion for connection to the active member for exerting thereon a force having a magnitude at least as large as the predetermined magnitude for moving the active member to a desired position. Actuation circuitry is provided for actuating the shape-memory alloy actuating member by changing the temperature thereof only for the time necessary to move the active member to the desired position. The invention is particularly useful for changing the position of a camber-adjusting tab on a helicopter rotor blade by using two shape-memory alloy members that can act against each other to adjust dynamic properties of the rotor blade as it is rotating.

McKillip, Jr., Robert M.↗

Spatial organization and time dependence of Jupiter's tropospheric temperatures, 1980-1993

The spatial organization and time dependence of Jupiter's temperature near 250-millibar pressure were measured through a jovian year by imaging thermal emission at 18 micrometers. The temperature field is influenced by seasonal radiative forcing, and its banded organization is closely correlated with the visible cloud field. Evidence was found for a quasi-periodic oscillation of temperatures in the Equatorial Zone, a correlation between tropospheric and stratospheric waves in the North Equatorial Belt, and slowly moving thermal features in the North and South Equatorial Belts. There appears to be no common relation between temporal changes of temperature and changes in the visual albedo of the various axisymmetric bands.

Orton, Glenn S.↗

In-Flight Calibration of the MMS Fluxgate Magnetometers

We present an overview of the approach to in-flight calibration, which is a coordinated effort between the University of California Los Angeles (UCLA), Space Research Institute, Graz, Austria (IWF) and the NASA Goddard Space Flight Center (GSFC). We present details of the calibration effort at GSFC. During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection↗

Seasonal Changes in Titan's Surface Temperatures

Cassini's extended mission has provided the opportunity to search for seasonal variations on Titan. In particular, surface temperatures are expected to have shifted significantly in latitude during the completed portion of the mission. Spectra recorded by the Composite Infrared Spectrometer (CIRS) during the nominal mission (2004-08) and the Equinox mission. (2008-10) have already shown changes in temperature. CIRS has detected a seasonal shift in the latitudinal distribution of surface brightness temperatures by comparing zonal averages from two time segments, one period in late northern winter centered on L(sub s) approximately 335 deg and a second period centered on the equinox (L(sub s) approximately 0 deg.). The earlier period had a meridional distribution similar to that previously reported: 93.5 K at the equator, 91.7 K at 85 S and 899 K at 85 N. The newly measured distribution near equinox shows a cooling in the south and a warming in the north, both by about 0.5 K. We estimate that. the centroid of the distribution moved from approximately 16 S to 7 S between the two periods. This gives a seasonal lag behind insolation of delta L(sub s) approximately 13 deg. The CIRS equinox results are consistent with those of Voyager IRIS, which encountered Titan in November 1980, just following the previous northern equinox (L(sub s) = 10 deg.). When compared with predictions from general circulation models, seasonal variations of surface temperature can help constrain the identification of surface materials. Our measurements most closely match the case of a porous ice regolith treated by Tokano, but with some apparent differences between the northern and southern hemispheres. CIRS will extend its study of seasonal variations in surface temperature on Titan as Cassini continues through northern spring.

Jennings, Donald E.↗

Contrasting long-term temperature trends reveal minor changes in projected potential evapotranspiration in the US Midwest

Abstract Warming generally leads to increased evaporative demand, altering the amount of water needed for growing crops. For the Midwest, some studies have suggested that reaching yield targets by 2050 will not be possible without additional precipitation or large expansion of irrigation. Here, we show that this claim is not supported by the historical summer climate trends, which indicate that the warming of daily average temperatures is largely driven by increases in minimum temperatures, while maximum temperatures have decreased. This has translated into a net decrease in vapor pressure deficit (VPD) and potential evapotranspiration (PET). With the increasing rainfall, this suggests that crop water deficits have likely become less frequent in the region despite the warming climate. By projecting these trends into 2050 and ancillary use of a crop model, we estimate minor changes in PET that would have minimal effects on corn yields (<6%) under persistence of these trends.

54 ENVIRONMENTAL SCIENCES↗

Mechanisms and Feedbacks Causing Changes in Upper Stratospheric Ozone in the 21st Century

Stratospheric ozone is expected to increase during the 21st century as the abundance of halogenated ozone-depleting substances decrease to 1960 values. However, climate change will likely alter this "recovery" of stratospheric ozone by changing stratospheric temperatures, circulation, and abundance of reactive chemical species. Here we quantity the contribution of different mechanisms to changes in upper stratospheric ozone from 1960 to 2100 in the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM), using multiple linear regression analysis applied to simulations using either Alb or A2 greenhouse gas (GHG) scenarios. In both these scenarios upper stratospheric ozone has a secular increase over the 21st century. For the simulation using the Alb GHG scenario, this increase is determined by the decrease in halogen amounts and the greenhouse gas induced cooling, with roughly equal contributions from each mechanism. There is a larger cooling in the simulation using the A2 GHG scenario, but also enhanced loss from higher NOy and HOx concentrations, which nearly offsets the increase due to cooler temperatures. The resulting ozone evolutions are similar in the A2 and Alb simulations. The response of ozone due to feedbacks from temperature and HOx changes, related to changing halogen concentrations, are also quantified using simulations with fixed halogen concentrations.

Oman, Luke↗

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗