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

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Accounting for herbaceous communities in process‐based models will advance our understanding of “grassy” ecosystems

Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Community Dynamics Drive Calcium Carbonate Production in an Enriched Consortium of Soil Microbes

Recently, there has been a focus on using soil microbes as a means to store carbon in the soil in the form of calcium carbonate, outcomes of which include soil stabilization and biocementation. The molecular processes involved in microbially induced calcium carbonate formation are known, but there is still a significant knowledge gap regarding how community interactions, emergent processes that are distinct from the roles of individual members, may drive the formation of carbonate. To answer these questions, we describe the development and application of a consortium of soil microbes consisting of one species each of the Rhodococcus , Microbacterium , and Curtobacterium genera and two species from the Bacillus genus. We term these five species cultivated together carbon storing consortium A (CSC-A). Growth assays show that only a subset of CSC-A members produces CaCO 3 with Rhodococcus producing the most CaCO 3 but the complete CSC-A produces significantly higher amounts of CaCO 3 compared to the sum total carbonate produced by all member species. The development of CSC-A shows that CaCO 3 production may be as much a community process as it is the contribution of individual species, requiring us to move beyond single species analysis to fully understand carbonate formation by microbial communities in nature. CSC-A will allow the scientific community to ask and answer key questions about the molecular interactions surrounding inorganic carbon formation in soil, an important knowledge gap that must be filled if we wish to stabilize soils and harness microbial processes for materials production.

calcium carbonate↗
DOE OSTI2024

Quantifying the Influence of Size, Shape, and Density of Microplastics on Their Transport Modes: A Modeling Approach

Microplastics (MPs) pose significant risks to marine ecosystems and human health, necessitating accurate predictions of their distributions in aquatic environments for effective risk mitigation. However, understanding MP transport dynamics is challenging because of the inadequate representation of MP characteristics such as size, shape, and density in numerical models. Further, the accuracy of the MP vertical profiles in existing models has not been thoroughly validated. Thus, we developed an MP transport model within the Finite Volume Community Ocean Model framework (FVCOM-MP) by integrating MP characteristics. We validated FVCOM-MP against experimental and analytical data, focusing on various MP transport modes and transitions. FVCOM-MP successfully replicates MP profiles in different transport modes, including the bedload, surface-load, suspended-load, and mixed-load modes. Additionally, we introduce phase diagrams for classifying MP transport modes based on particle characteristics, enhancing our understanding of MP dynamics in aquatic systems. The transport modes for a number of real-world MP particles, including fishing line, plastic bag/bottle fragments, synthetic fibers, tire wear particles, polyvinyl chloride and expanded polystyrene pellets, were analyzed with these phase diagrams.

Microplastic transport, Settling velocity, Rising ↗
DOE OSTI2025

Synthetic communities as a model for determining interactions between a biofertilizer chassis organism and native microbial consortia

Biofertilizers are critical for sustainable agriculture because they can replace ecologically disruptive chemical fertilizers while improving the trajectory of soil and plant health. However, for improving deployment, the persistence of biofertilizers within native soil consortia must be elucidated and enhanced. In this study we characterized a high-throughput, modular, and automation-friendly in vitro approach to screen for biofertilizer persistence within soil-derived consortia after co-cultivation with stable synthetic soil microbial communities (SynComs) obtained through a top-down cultivation process. Here, we profiled ~1200 SynComs isolated from various soil sources and cultivated in divergent media types, and we detected significant phylogenetic diversity (e.g. Shannon index >4) and richness (observed richness >400) across these communities. We observed high reproducibility in SynCom community structure from common soil and media types, which provided a testbed for assessing biofertilizer persistence within representative native consortia. Furthermore, we demonstrated that the screening method described herein can be coupled with microbial engineering to efficiently identify soil-derived SynComs in which an engineered biofertilizer organism (i.e. Bacillus subtilis) persists. Accordingly, we discovered that B. subtilis persisted in ~10% of SynComs that generally followed the diversity–invasion principle. Additionally, our approach enabled analysis of the ecological impact of B. subtilis inoculation on SynCom structure and profile alterations in community diversity and richness associated with the presence of a genetically modified model bacterium. Ultimately, this work has established a modular pipeline that could be integrated into a variety of microbiology/microbiome-relevant workflows or related applications that would benefit from assessment of the persistence of a specific organism of interest and its interaction with native consortia.

biofertilizers↗
DOE OSTI2025

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

A summation and inhibition model of annoyance response to multiple community noise sources

A model of annoyance due to combined noise sources was developed. The model provides for the summation of the subjective magnitudes of annoyance due to the separate noise sources and for the inhibition of the subjective magnitudes of each source by the presence of the other noise sources. The inhibition process is assumed to mathematically obey a power-group transformation. The results of an experiment in which subjects judged the annoyance of 15 minute sessions of combined aircraft and with several other models of combined source annoyance. These comparisons indicated that the model developed herein provides better qualitative and quantitative agreement with experimental responses than the other models. The application of the model to multiple community noises is discussed.

Powell, C. A.↗
NASA NTRS1990

Simulated forecast error and climate drift resulting from the omission of the upper stratosphere in numerical models

Using an NCAR community climate model, Version I, the forecast error growth and the climate drift resulting from the omission of the upper stratosphere are investigated. In the experiment, the control simulation is a seasonal integration of a medium horizontal general circulation model with 30 levels extending from the surface to the upper mesosphere, while the main experiment uses an identical model, except that only the bottom 15 levels (below 10 mb) are retained. It is shown that both random and systematic errors develop rapidly in the lower stratosphere with some local propagation into the troposphere in the 10-30-day time range. The random growth rate in the troposphere in the case of the altered upper boundary was found to be slightly faster than that for the initial-condition uncertainty alone. However, this is not likely to make a significant impact in operational forecast models, because the initial-condition uncertainty is very large.

Boville, Byron A.↗
NASA NTRS2009

Between the Rock and a Hard Place: The CCMC as a Transit Station Between Modelers and Forecasters

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involved model evaluations, model transitions to operations, and the development of draft Space Weather forecasting tools. This presentation will focus on the latter element. Specifically, we will discuss the process of transition research models, or information generated by research models, to Space Weather Forecasting organizations. We will analyze successes as well as obstacles to further progress, and we will suggest avenues for increased transitioning success.

Hesse, Michael↗
DOE OSTI2020

An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models

Abstract The Community Earth System Model 2 (CESM2) is the latest Earth System Model developed by the National Center for Atmospheric Research in collaboration with the university community and is significantly advanced in most components compared to its predecessor (CESM1). Here, CESM2's representation of the large‐scale atmospheric circulation and its variability is assessed. Further context is providedthrough comparison to the CESM1 large ensemble and other models from the Coupled Model Intercomparison Project (CMIP5 and CMIP6). This includes an assessment of the representation of jet streams and storm tracks, stationary waves, the global divergent circulation, the annular modes, the North Atlantic Oscillation, and blocking. Compared to CESM1, CESM2 is substantially improved in the representation of the storm tracks, Northern Hemisphere (NH) stationary waves, NH winter blocking and the global divergent circulation. It ranks within the top 10% of CMIP class models in many of these features. Some features of the Southern Hemisphere (SH) circulation have degraded, such as the SH jet strength, stationary waves, and blocking, although the SH jet stream is placed at approximately the correct location. This analysis also highlights systematic deficiencies in these features across the new CMIP6 archive, such as the continued tendency for the SH jet stream to be placed too far equatorward, the North Atlantic westerlies to be too strong over Europe, the storm tracks as measured by low‐level meridional wind variance to be too weak and a lack of blocking in the North Atlantic sector.

Simpson, Isla R.↗
DOE OSTI2020

The Role of the Mean State on MJO Simulation in CESM2 Ensemble Simulation

Here we examine the role of the mean state in the propagation of the Madden-Julian oscillation (MJO) over the Maritime Continent (MC). We use an ensemble of simulations made with a single model—the Community Earth System Model version 2—to assess the effect of the mean state that is unaffected by that of model components such as parameterization schemes. Results show that the background meridional moisture gradient is much steeper over the MC region in the periods with a stronger MJO propagation. Column water vapor budget of the MJO strongly suggests that the simulated mean state affects MJO via its impacts on moisture dynamics—a greater advection of mean moisture by MJO wind in the MC region is responsible for the anomalous MJO activity.

58 GEOSCIENCES↗
DOE OSTI2021

Reservoir Computing as a Tool for Climate Predictability Studies

Reduced-order dynamical models play a central role in developing our understanding of predictability of climate irrespective of whether we are dealing with the actual climate system or surrogate climate models. In this context, the linear inverse modeling (LIM) approach, by capturing a few essential interactions between dynamical components of the full system, has proven valuable in providing insights into predictability of the full system. We demonstrate that reservoir computing (RC), a form of learning suitable for systems with chaotic dynamics, provides an alternative nonlinear approach that improves on the predictive skill of the LIM approach. We do this in the example setting of predicting sea surface temperature in the North Atlantic in the preindustrial control simulation of a popular earth system model, the Community Earth System Model so that we can compare the performance of the new RC-based approach with the traditional LIM approach both when learning data are plentiful and when such data are more limited. The improved predictive skill of the RC approach over a wide range of conditions—larger number of retained EOF coefficients, extending well into the limited data regime, etc.—suggests that this machine-learning technique may have a use in climate predictability studies. While the possibility of developing a climate emulator—the ability to continue the evolution of the system on the attractor long after failing to be able to track the reference trajectory—is demonstrated in the Lorenz-63 system, it is suggested that further development of the RC approach may permit such uses of the new approach in more realistic predictability studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Description and Evaluation of a New Deep Convective Cloud Model Considering In-cloud Inhomogeneity

Convections still need to be parameterized in general circulation models (GCMs) in the coming decades. Performances of GCMs are significantly influenced by the convection schemes used. In contrast to most conventional cloud models that ignore in-cloud inhomogeneities, a new convective cloud model explicitly considering in-cloud inhomogeneities is developed. The new model adopts a single bulk plume approach, but divides the plume into a series of interacting sub-plumes in order to mimic the transition from the plume core to its edges. We implemented the new cloud model in NCAR Community Atmosphere Model version 5.0 (CAM5) and evaluated its performance. Single-column tests show a stronger mass flux profile and low-level detrainment with the new model. In global simulations, the long-lasting wet bias in the tropical free troposphere of CAM5 is alleviated. Spatial pattern and intensity distribution of precipitation is improved, but the global hydrological cycle is slightly over-enhanced. The diurnal cycle of tropical precipitation is also better captured though the precipitation peak still occurs earlier than the observations and the amplitude of the cycle tends to weaken. MJO simulation is slightly improved with the new scheme. In addition, the new cloud model generated more tropical cyclones, in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Spatial Dipole Pattern in Asian Aerosol Changes on East Asian Summer Monsoon

Since China implemented the Air Pollution Prevention and Control Action Plan in 2013, the aerosol emissions in East Asia have been greatly reduced, while emissions in South Asia have continued to increase. This has led to a dipole pattern of aerosol emissions between South Asia and East Asia. We report the East Asian summer monsoon (EASM) responses to the dipole changes in aerosol emissions during 2013–17 are investigated using the atmosphere model of Community Earth System Model version 2 (CESM2). We show that decreases in East Asian emissions alone lead to a positive aerosol effective radiative forcing (ERF) of 1.59 (±0.97) W m -2 over central-eastern China (25°–40°N, 105°–122.5°E), along with a 0.09 (±0.07)°C warming in summer during 2013–17. The warming intensified the land–sea thermal contrast and increased the rainfall by 0.32 (±0.16) mm day -1 . When considering both the emission reductions in East Asia and increases in South Asia, the ERF is increased to 3.39 (±0.89) W m -2 , along with an enhanced warming of 0.20 (±0.08)°C over central-eastern China, while the rainfall insignificant decreased by 0.07 (±0.16) mm day -1 . It is due to the westward shift of the strengthened western Pacific subtropical high, linked to the increase in black carbon in South Asia. Based on multiple EASM indices, the reductions in aerosol emissions from East Asia alone increased the EASM strength by almost 5%. Considering the effect of the westward shift of WPSH, the dipole changes in emissions together increased the EASM by 5%–15% during 2013–17, revealing an important role of South Asian aerosols in changing the East Asian climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Spatial Dipole Pattern in Asian Aerosol Changes on East Asian Summer Monsoon

Since China implemented the Air Pollution Prevention and Control Action Plan in 2013, the aerosol emissions in East Asia have been greatly reduced, while emissions in South Asia have continued to increase. This has led to a dipole pattern of aerosol emissions between South Asia and East Asia. Here, the East Asian summer monsoon (EASM) responses to the dipole changes in aerosol emissions during 2013–17 are investigated using the atmosphere model of Community Earth System Model version 2 (CESM2). We show that decreases in East Asian emissions alone lead to a positive aerosol effective radiative forcing (ERF) of 1.59 (±0.97) W m -2 over central-eastern China (25°–40°N, 105°–122.5°E), along with a 0.09 (±0.07)°C warming in summer during 2013–17. The warming intensified the land–sea thermal contrast and increased the rainfall by 0.32 (±0.16) mm day -1 . When considering both the emission reductions in East Asia and increases in South Asia, the ERF is increased to 3.39 (±0.89) W m -2 , along with an enhanced warming of 0.20 (±0.08)°C over central-eastern China, while the rainfall insignificant decreased by 0.07 (±0.16) mm day -1 . It is due to the westward shift of the strengthened western Pacific subtropical high, linked to the increase in black carbon in South Asia. Based on multiple EASM indices, the reductions in aerosol emissions from East Asia alone increased the EASM strength by almost 5%. Finally, considering the effect of the westward shift of WPSH, the dipole changes in emissions together increased the EASM by 5%–15% during 2013–17, revealing an important role of South Asian aerosols in changing the East Asian climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spatiotemporal evolution of melt ponds on Arctic sea ice

Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition presented a valuable opportunity to investigate the seasonal evolution of melt ponds through a rich array of atmosphere-ice-ocean measurements across spatial and temporal scales. In this study, we characterize the seasonal behavior and variability in the snow, surface scattering layer, and melt ponds from spring melt to autumn freeze-up using in situ surveys and auxiliary observations. We compare the results to satellite retrievals and output from two models: the Community Earth System Model (CESM2) and the Marginal Ice Zone Modeling and Assimilation System (MIZMAS). During the melt season, the maximum pond coverage and depth were 21% and 22 ± 13 cm, respectively, with distribution and depth corresponding to surface roughness and ice thickness. Compared to observations, both models overestimate melt pond coverage in summer, with maximum values of approximately 41% (MIZMAS) and 51% (CESM2). This overestimation has important implications for accurately simulating albedo feedbacks. During the observed freeze-up, weather events, including rain on snow, caused high-frequency variability in snow depth, while pond coverage and depth remained relatively constant until continuous freezing ensued. Both models accurately simulate the abrupt cessation of melt ponds during freeze-up, but the dates of freeze-up differ. MIZMAS accurately simulates the observed date of freeze-up, while CESM2 simulates freeze-up one-to-two weeks earlier. This work demonstrates areas that warrant future observation-model synthesis for improving the representation of sea-ice processes and properties, which can aid accurate simulations of albedo feedbacks in a warming climate.

54 ENVIRONMENTAL SCIENCES↗