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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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7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Investigating the Global Biogeophysical Impact of Area and Mass Based Wood Harvest in a Vegetation Demography Model

Wood harvesting alters land surface properties and energy redistribution, but there is a lack of studies estimating these changes on a global scale. We coupled a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator, with the E3SM land model to perform offline model simulation to investigate the land biogeophysical responses, including canopy coverage, leaf area index, albedo, surface roughness length, and energy fluxes, to historical wood harvest on the global scale. In this study, we found 50% less harvested carbon (C) when choosing the area-based harvest rate as driving data that has not been spatially harmonized, compared to reharmonized mass-based harvesting. By considering the uncertainty from reconstruction of historical wood harvest time series and the choice of wood harvest approach in the model, continuous wood harvest (1850–2015) results in 5%–10% of canopy coverage loss, contributing 0.5%–1% increase of albedo over disturbed land, which is much stronger than a non-demographic land surface model. Changes in energy flux from the wood harvest are negligible (<1%), but the responses of land surface properties vary (up to 30%) due to differences in model structure between the single canopy, sun-shade leaf model and vegetation demographic model.

Shu, Shijie [Lawrence Berkeley National Laboratory↗
DOE OSTI2023

Biogeophysical Effects of Land-Use and Land-Cover Change Not Detectable in Warmest Month

Land-use and land-cover changes (hereafter simply “land use”) alter climates biogeophysically by affecting surface fluxes of energy and water. Yet, near-surface temperature responses to land use across observational versus model-based studies and spatial-temporal scales can be inconsistent. Here we assess the prevalence of the historical land use signal of daily maximum temperatures averaged over the warmest month of the year (t LU ) using regularized optimal fingerprinting for detection and attribution. We use observations from the Climatic Research Unit and Berkeley Earth alongside historical simulations with and without land use from phase 6 of the Coupled Model Intercomparison Project to reconstruct an experiment representing the effects of land use on climate. To assess the signal of land use at spatially resolved continental and global scales, we aggregate all input data across reference regions and continents, respectively. At both scales, land use does not comprise a significantly detectable set of forcings for two of four Earth system models and their multimodel mean. Furthermore, using a principal component analysis, we find that t LU is mostly composed of the nonlocal effects of land use rather than its local effects. These findings show that, at scales relevant for climate attribution, uncertainties in Earth system model representations of land use are too high relative to the effects of internal variability to confidently assess land use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Estella Atekwana: Autobiographical Notes

I describe my career journey from a young girl in Cameroon, West Africa, to a trailblazing geophysicist to my current role as dean. I chronicle my time as a student, the transition to being an early career faculty, launching my research career, and ultimately finding my way to administration. Along the way I helped pioneer biogeophysics as a subdiscipline in geophysics while simultaneously maintaining an international research program in continental rift tectonics. I also describe the many intersectionalities in my life including being the first Black woman in many spaces, being a champion for student success, developing a diverse talent pipeline by enhancing diversity in the geosciences, and navigating academic job searches as part of a dual-career couple. Finally, I acknowledge all those who helped shape my career including the many students I had the opportunity to mentor. • Many underrepresented minority geoscientists lack the social capital and professional networks critical for their success. • Geoscience departments must be intentional and deliberate in promoting and ensuring more inclusive workplace environments. • Dual-career couples remain a major challenge, impacting retention and recruitment of top talent; universities should provide resources to alleviate this challenge. • Biogeophysics has untapped potential for advancing understanding of subsurface biogeochemical processes and the search for life in extreme environments. • To date, considerable speculation remains regarding the fundamental geodynamic processes that initiate and sustain the evolution of magma-deficient rifts.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Modeling perennial bioenergy crops in the E3SM land model (ELMv2)

Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few earth system models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Model (E3SM) Land Model (ELMv2) to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality , although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.

09 BIOMASS FUELS↗
DOE OSTI2024

Land Processes Can Substantially Impact the Mean Climate State

Terrestrial processes influence the atmosphere by controlling land-to-atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model version 2 under preindustrial conditions. We find that an observationally-informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (σ = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagate to the entire Earth system, and provides insights into where and how land process uncertainty influences climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A bioenergy-focused versus a reforestation-focused mitigation pathway yields disparate carbon storage and climate responses

Limiting global warming to 2 °C requires urgent action on land-based mitigation. This study evaluates the biogeochemical and biogeophysical implications of two alternative land-based mitigation scenarios that aim to achieve the same radiative forcing. One scenario is primarily driven by bioenergy expansion (SSP226Lu-BIOCROP), while the other involves re/afforestation (SSP126Lu-REFOREST). We find that overall, SSP126Lu-REFOREST is a more efficient strategy for removing CO2 from the atmosphere by 2100, resulting in a net carbon sink of 242 ~ 483 PgC with smaller uncertainties compared to SSP226Lu-BIOCROP, which exhibits a wider range of -78 ~ 621 PgC. However, SSP126Lu-REFOREST leads to a relatively warmer planetary climate than SSP226Lu-BIOCROP, and this relative warming can be intensified in certain re/afforested regions where local climates are not favorable for tree growth. Despite the cooling effect on a global scale, SSP226Lu-BIOCROP reshuffles regional warming hotspots, amplifying summer temperatures in vulnerable tropical regions such as Central Africa and Southeast Asia. Our findings highlight the need for strategic land use planning to identify suitable regions for re/afforestation and bioenergy expansion, thereby improving the likelihood of achieving the intended climate mitigation outcomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Benchmarking soil moisture and its relationship to ecohydrologic variables in Earth System Models

Soil moisture (SM) is a key regulator of ecosystem biogeophysics, influencing plant water relations and land-atmosphere energy exchanges. We evaluate the representation of SM in 16 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) using the International Land Model Benchmarking (ILAMB) framework, focusing on surface (0–5, 0–10 cm) and rootzone (0–100 cm) depths, as well as key ecohydrological variables like gross primary productivity (GPP), leaf area index (LAI), and evapotranspiration (ET), and their coupling. Models are benchmarked against multiple observational and assimilated datasets to assess both state variables and cross-variable relationships. Surface SM is generally well represented (r > 0.87), while rootzone SM variability is systematically overestimated (normalized standard deviation > 1). ET shows strong agreement with observations (r > 0.9), whereas GPP and LAI exhibit larger inter-model spread. Skill in individual variables does not guarantee realistic SM–ecohydrology coupling, which varies strongly across models and depends on the reference dataset. Köppen-based regional analyses reveal strong regime dependence, with several models performing well in Tropical and Temperate regions but degrading in Continental (high-latitude) zones. Across both global and regional benchmarks, models cluster by land surface framework, indicating that structural choices in soil hydrology and soil–plant coupling exert a first-order control on performance. These results provide process-relevant benchmarks and suggest that improving the representation of vertical soil structure, rooting depth distributions, and soil–plant hydraulic coupling will be central to advancing soil moisture realism in next-generation Earth system models.

CMIP6↗