An improved neural operator framework for large-scale CO2 storage operations
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58 GEOSCIENCES↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The Transport of Asian Dust and Combustion Aerosols and Associated Ozone to North America as Observed From a Mountaintop Monitoring Site in the California Coast Range
Aerosol and tropospheric ozone transport to North America has important implications for regional air quality and climate. We present data from Chews Ridge, a remote mountaintop site in California, in February–September 2012, which identifies separate Asian dust and Asian combustion aerosol signals and quantifies exogenous ozone. We use positive matrix factorization of size-fractionated aerosol X-ray fluorescence data and 206 Pb/ 207 Pb and 208 Pb/ 207 Pb isotope measurements to isolate aerosol signals of Asian origins and find good agreement between both types source attribution techniques. Power spectra of Asian dust and Asian combustion signals reveal two distinct peaks, one seasonal (~90 days) and one monthly (~25–30 days). Overall, 89% of the Asian dust signal occurs in March–May, compared with June–September, whereas only 51% of the Asian combustion signal occurs in March–May. Nearly half the Pb observed at Chews Ridge was derived from Asia (46%; 8.3% from Asian dust, 23% from Asian combustion, and 15% of the Asian Pb signal was not explained by the positive matrix factorization). A positive correlation between deseasonalized ozone concentrations and the Asian factors suggests that ozone is elevated by 6.3 ± 0.8 ppb due to transpacific transport. Scanning mobility particle size spectra were also measured from May to September and indicate that new particles are often produced and grow throughout the afternoon during onshore flow. We hypothesize that particle nucleation on the windward edge of the continent is an important source of new particles.
54 ENVIRONMENTAL SCIENCES↗
Estimation of Evapotranspiration of Amazon Rainforest Using the Maximum Entropy Production Method
Energy budget of Amazonian forests has a large influence on regional and global climate, but relevant data are scarce. A novel energy partition method based on the maximum entropy production (MEP) theory is applied to simulate evapotranspiration in Amazonia. Using site-level eddy flux data, the MEP method shows high skill at the hourly, daily, and monthly scales. Consistent performance under different levels of land surface dryness is revealed, hinting that drought signal is appropriately resolved. The site-level MEP-based estimates outperform the estimates of the Moderate Resolution Imaging Spectroradiometer evapotranspiration product, which is commonly used for large-scale assessments. At the Amazon basin scale, the two series yield similar averages but exhibit spatial differences. The parameter parsimony and demonstrated skill of the MEP method make it an attractive approach for environments with diverse strategies of water flux control.
54 ENVIRONMENTAL SCIENCES↗
A Deep Learning Parameterization for Ozone Dry Deposition Velocities
Abstract The loss of ozone to terrestrial and aquatic systems, known as dry deposition, is a highly uncertain process governed by turbulent transport, interfacial chemistry, and plant physiology. We demonstrate the value of using Deep Neural Networks (DNN) in predicting ozone dry deposition velocities. We find that a feedforward DNN trained on observations from a coniferous forest site (Hyytiälä, Finland) can predict hourly ozone dry deposition velocities at a mixed forest site (Harvard Forest, Massachusetts) more accurately than modern theoretical models, with a reduction in the normalized mean bias (0.05 versus ~0.1). The same DNN model, when driven by assimilated meteorology at 2° × 2.5° spatial resolution, outperforms the Wesely scheme as implemented in the GEOS‐Chem model. With more available training data from other climate and ecological zones, this methodology could yield a generalizable DNN suitable for global models.
Silva, S. J.↗
Middle to Late Holocene Sea Surface Temperature and Productivity Changes in the Northeast Pacific
Variations of the sea surface temperature (SST) and primary productivity in the northeast Pacific have far‐reaching implications. In addition to influencing the regional and global temperature and hydroclimate, these conditions also control marine ecosystems and their services, which subsequently impact regional economies. Yet, our understanding of the variability and controls of northeast Pacific SST and productivity on timescales exceeding observational records remains limited. Here, we use marine sediment records from seven locations, spanning 25.2°N–59.6°N, in the northeast Pacific to characterize the millennial‐scale variability of SST and productivity from 9,000 to 1,000 years BP. We explore the dynamics of their spatiotemporal evolution and compare these data with transient climate model outputs to identify potential drivers. Through a heat budget analysis and optimal fingerprinting analysis, we characterize the spatial pattern of forcings. We find that SST varied spatially in the northeast Pacific, with higher latitudes exhibiting greater magnitude changes than lower latitudes, which differs from previous work suggesting regional synchronicity and coherence during the Holocene. Our analysis did not find evidence for coherent variability of primary producer community nor carbon export, highlighting the difficulty of identifying the complex interactions between environmental conditions, producers, and carbon export. Model‐proxy disagreement demonstrates the need for higher resolution model frameworks, but shows nonetheless that observed variability in the proxy records can be explained by a combination of greenhouse gas and orbital forcing. Here we suggest that the complex SST variations and marine ecosystem responses to forced changes are important factors that can drive disagreements in model projections.
54 ENVIRONMENTAL SCIENCES↗
Using Ecosystem Experiments to Improve Vegetation Models
Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. We explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.
54 ENVIRONMENTAL SCIENCES↗
Modeling exports of dissolved organic carbon from landscapes: a review of challenges and opportunities
Inland waters receive large quantities of dissolved organic carbon (DOC) from soils and act as conduits for the lateral transport of this terrestrially derived carbon, ultimately storing, mineralizing, or delivering it to oceans. The lateral DOC flux plays a crucial role in the global carbon cycle, and numerous models have been developed to estimate the DOC export from different landscapes. We reviewed 34 published models and compared their characteristics to identify challenges in model applications and opportunities for future model development. We classified these models into three types: indicator-driven, hydrology-forced, and process-based DOC export simulation models. They differ mainly in their environmental inputs, simulation approaches for soil DOC production, leaching from soils to inland waters, and transit through inland waters. It is essential to consider landscape characteristics, climate conditions, available data, and research questions when selecting the most appropriate model. Given the substantial assumptions associated with these models, sufficient measurements are required to benchmark estimates. Accurate accounting of terrestrially derived DOC export to oceans requires incorporating the DOC produced in aquatic ecosystems and deposited with rainwater; otherwise, global export estimates may be overestimated by 40.7%. Additionally, improving the representation of mineralization and burial processes in inland waters allows for more accurate accounting of carbon sequestration through land ecosystems. When all the inland water processes are ignored or assuming DOC leaching is equivalent to DOC export, the loss of soil carbon through this lateral flux could be underestimated by 43.9%.
54 ENVIRONMENTAL SCIENCES↗
Legacy Effects of Cropping System and Precipitation Influence the Core Camelina sativa Microbiome
Camelina ( Camelina sativa L.) is a potential biofuel crop and beneficial rotation crop in dryland cropping systems. Little is known about camelina microbiota or the legacy effect of soil origin/cropping system zones on camelina-associated microbiome assembly. To explore camelina-microbe associations, we grew camelina in the greenhouse using soil transplanted from 33 locations in the dryland wheat production area of eastern Washington. Bacterial, archaeal, and fungal communities from bulk soil, rhizosphere, and endosphere were characterized with 16S rRNA and internal transcribed spacer amplicon sequencing and were analyzed alongside site-specific climatic and edaphic data. We found that soil from the highest precipitation zone had higher alpha diversity than soil from the driest zone, but this effect was not seen in the greenhouse rhizosphere or endosphere. Plant compartment, cropping system zone, and soil origin all significantly influenced microbial composition, with soil pH and organic matter, as well as precipitation at origin, as major predictors. Analysis of abundance–occupancy distributions showed that the Actinobacteriota Aeromicrobium and Marmoricola and the fungus Pseudogymnoascus in the rhizosphere were plant-selected, while the endosphere was characterized by a number of Actinobacteriota, Rhizobium, and Clostridium. Sphingomonas amplicon sequence variants were also consistently enriched in the rhizosphere, suggesting that they are present in soils collected throughout eastern Washington and may represent good candidate biostimulants. Several lignin decomposing fungi had site-specific rhizospheric distributions, suggesting that they may be dispersal-limited or result from the legacy effect of long-term wheat cropping. Overall, this study contributes to our understanding of microbiome assembly in and on camelina roots while also highlighting the potential impact of cropping history on soil- and plant-associated microbiomes. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2025.
Barnes, Elle M↗
Radiometric Standards and Best Practices: Recent Progress
International standards and best practices for solar resource assessments provide assurance for traceable measurements associated with a low uncertainty. This benefits the solar energy industry by reducing the investment risks through heightened confidence in the solar resource information. NREL, in collaboration with international organizations, such as subcommittees G03 of ASTM (Radiometry) and TC180/SC1 of ISO (Climate measurement and data), recently revised some standards that are widely used by the solar industry. These include radiometric standards that assist in (i) maintaining calibration traceability; (ii) uncertainty analysis; (iii) measurement quality assurance, and (iv) establishing reference spectral irradiance distributions. The latter are widely used by the solar community to evaluate the actual absorptance, reflectance, and transmittance of solar energy materials, or the performance of solar energy devices and systems, relative to standard conditions. This paper provides a summary of the recent changes brought to these standards as a way to better support the solar energy industry.
industries↗
Tracking Pulses of the Madden-Julian Oscillation
An international field campaign aiming at atmospheric and oceanic processes associated with the Madden-Julian Oscillation (MJO) was conducted in and around the tropical Indian Ocean (IO) during October 2011 - March 2012. The objective of the field campaign was to collect observations urgently needed to expedite the progress of understanding the key processes of the MJO, focusing on its initiation but also including propagation and maturation, and ultimately to improve skills of numerical simulation and prediction of the MJO. Primary targets of the field campaign include interaction of atmospheric deep convection with its environmental moisture, evolution of cloud populations, and air-sea interaction. Several MJO events were captured by ground-based, airborne, and oceanic instruments with advanced observing technology. Numerical simulations and real-time forecasts were integrated components of the field campaign in its design and operation. Observations collected during the campaign provide unprecedented opportunities to reveal detailed processes of the MJO and to assist evaluation, improvement and development of weather and climate models. The data policy of the campaign encourages the broad research community to use the field observations to advance the MJO study.
madden-julian↗
A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation
Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.
54 ENVIRONMENTAL SCIENCES↗
BSDF Data generation for daylight applications: A call for international standardization
Standardized methods for generating angle-dependent, bidirectional, solar-optical properties for complex fenestration systems do not exist, which means that energy and daylight evaluations in building performance simulations often suffer from major inaccuracies. This position paper provides an overview of state-of-the-art data-driven methods for characterizing light scattering properties of fenestration materials and blind systems (e.g. fabrics, metal slats, patterned glazing), validation via laboratory, simulation and field tests, and salient issues in support of standardization of such methods via the International Standardization Organization (ISO). The ISO standard is intended to provide the fundamental underpinnings for recently mandated daylight standards that rely on bidirectional scattering distribution function data for climate-based daylight modelling and building performance simulations.
Geisler-Moroder, D.↗
Analysis of Joist Masonry Moisture Content Monitoring
There are many existing buildings with load-bearing mass masonry walls, whose energy performance could be improved with the retrofit of insulation. However, adding insulation to the interior side of walls of such masonry buildings in cold (and wet) climates may cause performance and durability problems. Some concerns, such as condensation and freeze-thaw have known solutions. But wood members embedded in the masonry structure will be colder (and potentially wetter) after an interior insulation retrofit. Moisture content & relative humidity were monitored at joist ends in historic mass brick masonry walls retrofitted with interior insulation in a cold climate (Zone 5A); data were collected from 2012-2015. Eleven joist ends were monitored in all four orientations. One limitation of these results is that the renovation is still ongoing, with limited wintertime construction heating and no permanent occupancy to date. Measurements show that many joists ends remain at high moisture contents, especially at north- and east-facing orientations, with constant 100% RH conditions at the worst cases. These high moisture levels are not conducive for wood durability, but no evidence for actual structural damage has been observed. Insulated vs. non-insulated joist pockets do not show large differences. South facing joists have safe (10-15%) moisture contents. Given the uncertainty pointed out by research, definitive guidance on the vulnerability of embedded wood members is difficult to formulate. In high-risk situations, or when a very conservative approach is warranted, the embedded wood member condition can be eliminated entirely, supporting the joist ends outside of the masonry pocket.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Biases of the MET Temperature and Relative Humidity Sensor (HMP45) Report
The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Data Quality (DQ) Office was alerted to a potential bias in the surface meteorological instrumentation (MET) temperature when compared with a nearby Mesonet station. This led to an investigation into this problem that was expanded to include many of the other extended facilities (EF) and both the temperature and relative humidity (RH) variables. For this study, the Mesonet was used as the standard reference due to results that showed an increased accuracy in high-humidity environments along with the fact that the Mesonet had previous documented a problem with the HMP45C sensors. Some differences between the sites were taken into account during the analysis: 1. ARM MET sensors were upgraded from an HMP35 to an HMP45 throughout 2007 2. Mesonet switched to aspirated shields in 2009 – To mitigate the differences between aspirated and non-aspirated measurements, data were only analyzed when the wind speed was higher than 3 m/s. This reduced the uncertainty for the non-aspirated measurements from 1.51 ºC to 0.4 ºC. 3. ARM MET is mounted 0.5m higher than the Mesonet station (2.0m versus 1.5m) – This is assumed to have a negligible effect on the differences. 4. Sites were not co-located – For some locations, the distances between sites were as much as 45 km. As part of the investigation into the differences, the Mesonet had reported that the HMP45 sensors had a low-temperature bias in high-humidity environments. This was verified at two different sites where the ARM measurements were compared with the Mesonet measurements. The Mesonet provided redundant temperature measurements from two different sensors at each site. These measurements compared fairly well, while the ARM sensor showed a bias overnight when the humidities were higher. After reviewing the yearly average differences in the data and analyzing the RH data during fog events when we assume it should be 100%, we determined that a majority of the sites have a bias in the RH compared to the Mesonet sites, but that only a few sites show a bias in the temperature measurements that are outside the range of instrument uncertainties. We note that there can be a lot of variability across some of the distances between the MET and Mesonet sites and these biases reported herein should not be used as offsets.
47 OTHER INSTRUMENTATION↗
Institutional Transformation (IX) 2.5 Building Module Help Manual
The Institutional Transformation (IX) building module is a software tool developed at Sandia National Laboratories to evaluate energy conservation measures (ECMs) on hundreds of DOE-2 building energy models simultaneously. In IX, ECMs can be designed through parameterizing DOE-2 building models and doing further processing via visual basic for applications subroutines. IX provides the functionality to handle multiple building models for different years, which enables incrementally changing a site of hundreds of buildings over time. It also enables evaluation of the effects of changing climate, comparisons between data and modeling results, and energy use of centralized utility buildings (CUBs). IX consists of a Microsoft Excel® user interface, Microsoft Access® database, and Microsoft Excel® CUB build utility whose functionalities are described in detail in this report. In addition to descriptions of the user interfaces, descriptions of every ECM already designed in IX is included.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
2024 IUFRO Tree Biotechnology Conference (Aug 4-8, 2024)
The 2024 IUFRO Tree Biotechnology Conference is the biennial meeting on genomics, molecular biology, and biotechnology of forest trees, associated with the IUFRO Working Party 2.04.06. This year's meeting was held in Annapolis, MD, USA from August 4th to 8th and was hosted by Yiping Qi (University of Maryland), Edward Eisenstein (University of Maryland), Gary Coleman (University of Maryland), and Heather Coleman (Syracuse University). The conference covered seven topics over the course of five days: 1) Biological and ecological insights from OMICS, 2) Advancing technologies for targeted trait manipulation and acceptability to diverse tree species, 3) Genes, development, and physiology, 4) Translating genomics and biotechnology to practice, 5) Trees in a changing world, 6) Genetic and phenotypic diversity for breeding and genomic selection, and 7) Biotechnology for biomaterials and bioeconomy. In addition to the sessions, there were two plenary sessions, provided by John Ralph (University of Wisconsin) and Tanja Pyrhäjärvi (University of Helsinki). The meeting celebrated the second awardees of the newly created IUFRO WG 2.04.06 Award: Excellence in Forest Molecular Biology and Genomics, which was presented to Chung-Jui (C.J.) Tsai (University of Georgia). Greg Goralogia (Oregon State University) was the recipient of the associated Early Career Award. The scientific presentations at the conference highlighted cutting-edge advancements in many facets of forest biotechnology research, including applications of genomic selection in forest genetics and breeding, the use of genetic editing, tree physiology, stress response, molecular breeding, wood development, "omics" technologies, and the social and economic impacts of genetically modified (GM) trees. Scientific take homes from the meeting include the power of NMR to dissect the composition of lignin, the genomic diversity of forest trees that has enormous potential for tree improvement and the integration of systems biology with climate and geographical data. The conference attracted a mix of students (25), postdoctoral fellows (32), and scientists from academia (66) and industry (18). In all, the conference was attended by 141 registered participants, representing 20 countries that participated in 23 invited lectures (including 6 'early-career' keynotes), 27 voluntary talks and 61 poster presentations. Support for the conference was drawn from a wide variety of Academia, Industry, and Government sources, and included financial support from several tree improvement companies. Overall, the conference was a great success, providing an exceptional mix of science and social activities in a relaxed and collegial atmosphere. More information about the meeting can be found at treebiotech.org. The next meeting will be held in Stellenbosch, South Africa, in 2026, hosted jointly by Zander Myburg, Dave Drew (University of Stellenbosch,) and Sanushka Naidoo (University of Pretoria, FABI).
59 BASIC BIOLOGICAL SCIENCES↗
PNNL-ANL Hydrometeorological Super Ensemble
The current dataset contains data upload links to the following **hydrologic (water balance), river routing (water management), and hydropower simulation** data over CONUS: * Climate Forcing: **Livneh** (https://www.nature.com/articles/sdata201542) * Simulation Scenario: **Historical** * Simulation Period: **1971-2013 (1972-2013 for Hydropower)** * Simulation Models: **VIC (Variable Infiltration Capacity)**, **mosartwmpy (Model for Scale Adaptive River Transport-Water Management in Python)**, and **PNNL B1Hydro** * Output Format: **NetCDF** and **CSV**
Tidwell, Vincent C [Pacific Northwest National Lab↗
PNNL-ANL Hydrometeorological Super Ensemble
The current dataset contains data upload links to the following hydrologic (water balance), river routing (water management), and hydropower simulation data over CONUS: Climate Forcing: ClimRR (https://climrr.anl.gov/climrrdata) Simulation Scenario: Historical, Mid-Century, End-Century Simulation Period: 1995-2004, 2045-2054, 2085-2094 Simulation Models: VIC (Variable Infiltration Capacity), mosartwmpy (Model for Scale Adaptive River Transport-Water Management in Python), and PNNL B1Hydro Output Format: NetCDF and CSV
Tidwell, Vincent C [Pacific Northwest National Lab↗