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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term experiments

Climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (<10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle

Shortwave (SW) cloud feedback ($SW_{FB}$) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report ‘likely’ maximum (4.5K) due to extratropical $SW_{FB}$’s that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean $SW_{FB}$ can be predicted from the sensitivity of column-integrated liquid water mass (LWP) to moisture convergence and to surface temperature. In this work, the response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean $SW_{FB}$— inconsistent with extreme ECS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Anisotropic Melt Inclusions as a Confounding Signal for Ice‐Penetrating Radar Observations

Ice-penetrating radar is a powerful geophysical tool for understanding the subsurfaces of Earth, Mars, and icy moons. Radar reflectivity, attenuation, and birefringence are used to infer subsurface hydrology, englacial temperature, water content, and crystal orientation fabric. However, conventional radar sounding analyses either ignore melt or use classical mixing models which assume spherical melt inclusions, obscuring anisotropic contributions of melt. Here, we use geometric mixing models to calculate the reflectivity, attenuation, and birefringence of temperate ice containing anisotropic melt. We find that anisotropic melt can introduce significant deviations in radar measurements. For instance, melt anisotropy may impact reflectivity-based estimates of water content by up to 30% volume fraction, while attenuation-based estimates may vary by up to 43%. Critically, a melt volume fraction of just $f$ ~ 10 -5 can reproduce birefringence signals previously attributed to ice fabric. We conclude that melt anisotropy may significantly impact analyses of englacial hydrology, subglacial hydrology, and ice fabric.

58 GEOSCIENCES↗
DOE OSTI2026

Development, Monitoring, and Control of Fracture Thermal Energy Storage (FTES) in Crystalline Rock Formations (DEMO-FTES) (CRADA Final Report)

The DEMO-FTES project sought to demonstrate the thermal efficiency of fracture thermal energy storage (FTES) through numerical simulations, laboratory and meso-scale field tests. A detailed dimensional and scaling analysis was performed to identify key parameters and how they can be most effectively scaled to the laboratory and decameter scale. Numerical models were developed and used for three purposes: 1. Before field experiments, numerical modelling can be used to estimate fracture properties based on previous data from the EGS Collab experiment and then predict thermal hydrological behaviors of the fracture system with hot water injection/withdrawal, therefore, help to design the experiments (e.g., to decide the duration of the cycles based on the flow rate the pump can provide, and the estimated fracture properties); 2. After the field experiment, to estimate the system properties during the experiment (as the size and shape of a fracture could change over time), and understand why system performance is different than what has been predicted, i.e., to help understand the meso-scale test; and, 3. To model the lab experiments and estimate fracture properties and storage efficiency. Ultimately, the experiment and numerical models could shed light on the processes and uncertainty happening during fracture activation and help understand the scaling between lab and field test, and finally, the design and optimization of potential fracture thermal energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Modeling Terrestrial Dissolved Organic Carbon Loading to Western Arctic Rivers

The mobilization and land-to-ocean transfer of dissolved organic carbon (DOC) in Arctic watersheds is intricately linked with the region's climate and water cycle, and furthermore at risk of changes from climate warming and associated impacts. This study quantifies model-simulated estimates of runoff, surface and active layer leachate DOC concentrations and loadings to western Arctic rivers, specifically for basins that drain into coastal waters between and including the Yukon and Mackenzie Rivers. Model validation leverages data from other field measurements, synthesis studies, and modeling efforts. The simulations effectively quantify DOC leaching in surface and subsurface runoff and broadly capture the seasonal cycle in DOC concentration and mass loadings reported from other studies that use river-based measurements. A marked east-west gradient in simulated spring and summer DOC concentrations of 24 drainage basins on the North Slope of Alaska is captured by the modeling, consistent with independent data derived from river sampling. Simulated loadings for the Mackenzie and Yukon show reasonable agreement with estimates of DOC export for annual totals and four of the six seasonal comparisons. Nearly equivalent loading occurs to rivers which drain north to the Beaufort Sea and west to the Bering and Chukchi Seas. The modeling framework provides a basis for understanding carbon export to coastal waters and for assessing impacts of hydrological cycle intensification and permafrost thaw with ongoing warming in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Deep Learning Advances Arctic River Water Temperature Predictions

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0°C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation—factors associated with energy balance—were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Financial Analysis of the Smallmouth Bass Flows implemented at the Glen Canyon Dam during Water Year 2024

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specifies criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report presents a financial analysis of the Smallmouth bass (Micropterus dolomieu) (SMB) flows implemented at GCD during Water Year (WY) 2024. These bypass flows were introduced by the U.S. Bureau of Reclamation (USBR) as an emergency response to the growing threat posed by invasive SMB in the Colorado River ecosystem downstream of the dam. SMB are a non-native predatory species that pose a significant threat to native fish populations, including the endangered humpback chub (Gila cypha). The thermal regime below GCD, typically cold due to hypolimnetic releases from Lake Powell, has historically served as a thermal barrier limiting SMB establishment. However, persistently low reservoir levels in recent years have reduced stratification in Lake Powell, allowing warmer water to be released downstream. This has enabled SMB to spawn successfully below the dam, prompting urgent ecological concerns. To mitigate the risk of SMB proliferation, the USBR implemented a series of bypass flows in WY 2024. Drawn from a lower elevation than the penstocks, the bypass structures released cooler water downstream. These short-duration bypass flows aimed to keep temperatures cool enough to prevent SMB from spawning, thereby reducing the ecological threat posed by this invasive species. Although motivated by ecological objectives, these bypass flows came with financial tradeoffs. Releasing water through the bypass structures instead of the turbines at GCD reduced hydropower generation, resulting in a significantly lower financial position for Western Area Power Administration (WAPA), which is responsible for marketing the electricity produced by the GCD Powerplant. This report analyzes the financial impact of the SMB flows implemented from July to November 2024. These experimental releases led to an estimated financial cost of approximately $18.9 million, primarily driven by the substantial volume of water diverted through the bypass structures. This study applies an integrated set of tools to estimate WAPA financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the water operations that actually occurred, including the SMB bypass flows, and (2) a “Without Experiment” case that simulates operations under the assumption that the SMB flows did not occur. Both cases comply with LTEMP hourly and daily operating criteria, and the monthly water release volumes are assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices.

13 HYDRO ENERGY↗
DOE OSTI2020

2D Dam-Break Analysis of L Lake and PAR Pond Dams Using HEC-RAS

In 1991 a dam-break study was conducted for the high hazard dams located at L Lake and PAR Pond on the Savannah River Site. Two scenarios were considered, over topping from a Probable Maximum Flood (PMF), and a fair weather dam-break for either or both dams. Unfortunately, no inundation map was developed from the study. The purpose of this project was to redo the original dam-break study with improved data and methodology to generate Inundation maps to assist with emergency response and evacuation plans. The Hydrologic Engineering Center's River Analysis System (HEC-RAS) is a free to download river analysis modeling program developed by the US Army Corps of Engineers capable of 1D and 2D hydraulic calculations. Version 5.0.7 (released March 2019) was used for this project. Digital elevation models for the area were retrieved from the US Geological Survey database and converted to a .hdf file within the program. Then the 2D flood area was identified from the contours. Both L Lake and PAR Pond were inputted as 1D storage areas because DEM data does not contain elevation values under water bodies. An elevation vs volume curve was available for both storage areas. Initial elevations were set for both scenarios. Both dams are earthen dams. The Steel Creek dam at L Lake has 6 ft diameter conduit with an upper and lower sluice gate. PAR pond dam consist of a weir and sluice gate connected to an 8 x 8 ft channel. Both outlets were modeled with a pool elevation vs discharge curve. The steel creek dam sluice gates were assumed to be fully open in all cases. As in the previous study, the dams were set to breach when they were overtopped by 1.5 ft during PMF conditions (Figure 1). A fair weather breach was set to be due to a piping failure (Figure 1). In the dual dam break during fair weather conditions the PAR pond dam fails 3 hours after Steel Creek to achieve maximum flooding in the down stream reaches. Simulation was run 3 days for each case and with a 1 minute computational interval. Maximum flooding occurs under PMF conditions with the failure of both dams. PAR pond dam fails first 16 hours and 32 minutes after the start of the simulation with the Steel creek dam failing 6 minutes later. In all cases, the bridges and roads spanning Steel Creek and Lower Three Runs will be inundated and potentially washed away. The Burtons Ferry Highway south of the storage areas will be partially flooded during PMF failure, dual fair weather failure, and PAR pond failure under fair weather conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Joint Inversion of Surface Electrical Resistivity Tomography and Seismic Refraction Data between the 200 Areas

Geologic stratigraphy on the Hanford Site influences groundwater and contaminant migration through the aquifer system and the vadose zone. The current geologic framework model (GFM) relies heavily on a sparse distribution of borehole data in some locations to map geologic contacts and hydrologic properties in the subsurface. Non-invasive geophysical methods such as electrical resistivity tomography (ERT), transient electromagnetic surveying, and seismic imaging are being used at Hanford to map subsurface structure in areas with limited well observations. This is to develop and mature the capability of geophysical methods to aid in GFM refinement, to identify regions of subsurface complexity, and for optimal well siting. A joint inversion of co-located seismic refraction and ERT data was carried out for data collected on a ~2.3-km profile between the 200 Areas on the Hanford Site. While ERT and seismic refraction images have sensitivity to overlapping physical properties (porosity, moisture content, lithology), the resolution and physics used to acquire each of these datasets are different and therefore information can be different or mutually complementary. Performing a joint inversion provides a reasonable option for a coherent, coupled interpretation for mutually complementary datasets. Between the 200 Areas, there are few boreholes to interpret the geologic framework model, and these data sets were obtained to provide a first line of evidence toward identifying stratigraphic structure. The seismic refraction and ERT data were independently inverted during fiscal year 2022 and broadly showed a two-layer structure with a trough-like feature that is ~1 km wide and upwards of 150 m deep. The depth of the trough feature was greater in the ERT image compared to the seismic image, which indicated a maximum depth of approximately 110 m. The objective of the joint inversion described in this report was to invert the seismic refraction and ERT data together while constraining the ERT image to be structurally similar to the seismic refraction image. The approach was applied using the geophysical inverse modeling program E4D, which has the capability to invert first-arrival times from seismic refraction data and ERT resistances using a “cross-gradient” constraint. The application of cross-gradient constraints with different weights produces ERT models that show a high degree of similarity within the upper 100 m (above ~120 m elevation). None of the ERT models show an improved structural similarity to the seismic result; therefore, it is recommended that further attempts to jointly interpret these models focus on petrophysics and image resolution. Petrophysical measurements of core samples would improve knowledge of what drives the ERT response in this region and, along with downhole geophysical measurements, could be used to “ground truth” the surface-based geophysical results. Image resolution studies would provide insight into which regions of the inverted images are reliable and which regions are poorly constrained.

58 GEOSCIENCES↗
DOE OSTI2024

DECOVALEX-2023: Task E Final Report

This is the Task E final report for DECOVALEX-2023. Task E is focused on understanding thermal, two-phase hydrological, and mechanical (TH2M) processes, especially related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and essentially non-porous in the far field (away from excavations). Investigation of the short-term (days to years) near-field (centimeters to tens of meters) behavior of salt is important for radioactive waste disposal because this early period strongly controls the amount of brine in a salt repository. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment. The main test case used in Task E is the ongoing Brine Availability Test in Salt (BATS) heater test located underground at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, New Mexico, USA. The Task was divided into a series of Steps. Step 0 was an introduction to processes in salt, that included matching historical unheated brine inflow data from boreholes at WIPP and matching temperature observations during BATS heater test 1a. Step 1 included validation of models against a thermo-poroelastic analytical solution relevant to heated boreholes in salt, and two-phase flow around an excavation in salt. Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the BATS 1a heater test. There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. The key learning points from Task E have been: • Heat conduction through salt typically requires non-linear thermal conductivity (as a function of temperature), but most models do a good job matching observations, given appropriate adjustments to the applied power and some thermocouple locations. • Thermal pressurization requires coupled thermal-hydrological-mechanical (THM) responses that consider the thermal expansion of the fluid and solid phases. • Initialization of two-phase flow models around a borehole or excavation in salt are more realistically represented as “wetting up”, rather than “drying down” (i.e., the initial state after excavation is mostly dry, rather than mostly wet). • The BATS 1a heater test includes a significant release of brine after the end of heating, which requires a large increase in permeability to recreate. Task E has been a great learning experience for all the teams involved, and feedback from the modeling teams has led to changes in the design of follow-on BATS experiments, which are now ongoing underground at WIPP. There was a balance throughout the task between freedom to model phenomena how each team saw fit, and prescriptiveness in problem design to bring the modeling teams closer together to allow attribution of smaller differences between models to different modeling choices. The modeling approaches seem to go through two phases: an early phase of discovery or testing, and a later phase of refinement and improvement. In future modeling efforts, different field data could be used (e.g., BATS 2) and more time should be included in the processes for teams to make multiple model refinement or even significant changes to their conceptual model or setup, based on lessons learned from the modeling exercise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Hy-DAT: A Tool to Address Hydropower Modeling Gaps Using Interdependency, Efficiency Curves, and Unit Dispatch Models

As the power system continues to be flooded with intermittent resources, it becomes more important to accurately assess the role of hydro and its impact on the power grid. While hydropower generation has been studied for decades, dependency of power generation on water availability and constraints in hydro operation are not well represented in power system models used in the planning and operation of large-scale interconnection studies. There are still multiple modeling gaps that need to be addressed; if not, they can lead to inaccurate operation and planning reliability studies, and consequently to unintentional load shedding or even blackouts. As a result, it is very important thathydropower is represented correctly in both steady-state and dynamic power system studies. In this paper, we discuss the development and use of the Hydrological Dispatch and Analysis Tool (Hy-DAT) as an interactive graphical user interface (GUI), that uses a novel methodology to address the hydropower modeling gaps like water availability and inter-dependency using a database, and algorithms, to generate accurate representative models for power system simulation.

Wang, Dewei↗
DOE OSTI2021

Exploring Sources of Surface Bias in HRRR Using New York State Mesonet

In recent years, there has been increasing demand for applications of short-term forecasting of renewable energy potential and assessments of the likelihood of extreme weather events using the High-Resolution Rapid Refresh (HRRR) model. Examining the biases in the newest version of HRRR is necessary to promote further model development. Using data from one of the most comprehensive and dense monitoring networks, New York State Mesonet (NYSM), we evaluate the HRRR version 3 meteorological fields for an entire year. In this work, the land-atmosphere-cloud coupling system is evaluated as an integrated whole. We investigate the physical processes influencing the soil hydrological balance and the thermodynamic interactions, from surface fluxes up to the level of boundary layer convection from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2 m temperature and humidity biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme nocturnal cold bias in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inaccurate representation of energy partition and soil hydrological process across different land use types as well as a hydrological bias in describing spring snowmelt are identified as the main source of the land-surface-induced bias. A feedback loop linking cloud presence, flux changes, and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Scale-dependent spatial variabilities of hydrological exchange flows and transit time in a large regulated river

Hydrological exchange flows (HEF) across the river-aquifer interface and the associated residence time of river water in the aquifer have important implications for contaminant plume migration and biogeochemical processes in the river corridor. HEFs and residence time are influenced by both subsurface physical features and hydrologic forcing related to the transport process, which can exhibit complex spatial and temporal variations. In this study, we used a massively parallel subsurface flow model and a particle-tracking model to study the influences of different control factors on spatial variability of HEFs and residence time distributions (RTD) in the Hanford Reach of the Columbia River in Washington State. A total number of 100M particles were randomly injected in time and space and then tracked in a model domain that covers a 51-km 2 area (15.1M model cells). We used hourly river stages and groundwater levels to drive the model to provide dynamic velocity fields for the particle tracking in the simulation period that was longer than 2 years. The groundwater flow simulation and particle-tracking results provide the first comprehensive assessment of the spatial distribution of HEFs and residence time in large complex river corridors. Overall, our results show that the aquifer hydrogeological structure has the strongest correlation with the extent and magnitude of exchange flux. The residence time exhibits complex patterns that are impacted by all the river geomorphologic, hydrodynamic, and hydrogeologic factors and are strongly correlated with the downwelling ratio of exchange flux. The new insights gained through this study can be used to support the development of reduced-order models of HEFs and RTDs for large complex river systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CLM5 CAMELS Basins Ensemble

Land surface models such as Community Land Model Version 5 (CLM5) are essential tools for simulating the behaviors of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrologic parameters and the implications that these uncertainties have on water resources applications. To address this long-standing issue, we conduct a comprehensive hydrologic parameter uncertainty characterization (UC) of CLM5 over the hydroclimatic gradients of the Conterminous United States using five meteorological datasets. Key datasets produced from the UC experiment include a benchmark dataset of CLM5 default hydrological performance, parameter sensitivity identified for 28 hydrological metrics, and large ensemble outputs for hydrological predictions. The presented datasets can assist CLM5 calibration and to support broad applications such as evaluating vulnerabilities to droughts and floods. The dataset can be used to identify under what hydroclimate conditions parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how land runoff uncertainties interact with other Earth system processes. Please refer to the README.pdf for a description of the included files. Note that raw CLM5 model outputs for each forcing dataset are hosted on a Globus endpoint: https://app.globus.org/file-manager?destination_id=d22ef858-27b0-11ed-a910-fd3165076336.

Yan, Hongxiang↗
DOE OSTI2021

Warm-season net CO 2 uptake outweighs cold-season emissions over Alaskan North Slope tundra under current and RCP8.5 climate

Abstract Arctic warming has increased vegetation growth and soil respiration during recent decades. The rate of Arctic warming will likely amplify over the 21st century. Previous studies have revealed that the most severe Arctic warming occurred during the cold season (September to May). The cold-season warming has posited significant CO 2 emissions to the atmosphere via respiration, possibly offsetting warm-season (June to August) net CO 2 uptake. However, prevailing Earth system land models poorly represent cold-season CO 2 emissions, making estimates of Arctic tundra annual CO 2 budgets highly uncertain. Here, we demonstrate that an improved version of the energy exascale Earth system model (E3SM) land model (ELMv1-ECA) captures the large amount of cold-season CO 2 emissions over Alaskan Arctic tundra as reported by two independent, observationally-constrained datasets. We found that the recent seven-decades warming trend of cold-season soil temperature is three times that of the warm-season. The climate sensitivity of warm-season net CO 2 uptake, however, is threefold higher than for the cold-season net CO 2 loss, mainly due to stronger plant resilience than microbial resilience to hydroclimatic extremes. Consequently, the modeled warm-season net CO 2 uptake has a larger positive trend (0.74 ± 0.14 gC m −2 yr −1 ) than that of cold-season CO 2 emissions (0.64 ± 0.11 gC m −2 yr −1 ) from 1950 to 2017, supported by enhanced plant nutrient uptake and increased light- and water-use efficiency. With continued warming and elevated CO 2 concentrations under the representative concentration pathway (RCP) 8.5 scenario, the increasing rate of warm-season net CO 2 uptake is more than twice the rate of cold-season emissions (1.33 ± 0.32 gC m −2 yr −1 vs 0.50 ± 0.12 gC m −2 yr −1 ), making the modeled Alaskan Arctic tundra ecosystem a net CO 2 sink by 2100. However, other geomorphological and ecological disturbances (e.g. abrupt permafrost thaw, thermokarst development, landscape-scale hydrological changes, wildfire, and insects) that are not considered here might alter our conclusion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CLM5 CAMELS Basins Ensemble

Land surface models such as Community Land Model Version 5 (CLM5) are essential tools for simulating the behaviors of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrologic parameters and the implications that these uncertainties have on water resources applications. To address this long-standing issue, we conduct a comprehensive hydrologic parameter uncertainty characterization (UC) of CLM5 over the hydroclimatic gradients of the Conterminous United States using five meteorological datasets. Key datasets produced from the UC experiment include a benchmark dataset of CLM5 default hydrological performance, parameter sensitivity identified for 28 hydrological metrics, and large ensemble outputs for hydrological predictions. The presented datasets can assist CLM5 calibration and to support broad applications such as evaluating vulnerabilities to droughts and floods. The dataset can be used to identify under what hydroclimate conditions parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how land runoff uncertainties interact with other Earth system processes. Please refer to the included README.pdf for a description of the included files. Note that raw CLM5 model outputs for each forcing dataset are hosted on a Globus endpoint: https://app.globus.org/file-manager?destination_id=d22ef858-27b0-11ed-a910-fd3165076336.

Yan, Hongxiang↗
DOE OSTI2021

Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan

Mountains are the natural water towers of the world, effectively turning water vapor into readily available fresh water through precipitation, snowpack, and runoff. Unfortunately, Earth system models (ESMs) have persistently been unable to predict the timing and availability of water resources from mountains because the source(s) of model error are difficult to isolate in complex terrain with limited atmospheric or land-surface observations. Further complications arise from the gross scale mismatch between ESM grid box sizes and the relevant scales of mountainous hydrological processes. The mountain hydrometeorology community has repeatedly called for integrated atmospheric and land observations of water and energy budgets in complex terrain that span these scales to establish benchmarks against which scale-dependent models can be further developed.

54 ENVIRONMENTAL SCIENCES↗