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NASA NTRS2022

Spatial Downscaling of GOES-R Land Surface Temperature over Urban Regions: A Case Study for New York City

The surface urban heat island (SUHI) effect is among the major environmental issues encountered in urban regions. To better predict the dynamics of the SUHI and its impacts on extreme heat events, an accurate characterization of the surface energy balance in urban regions is needed. However, the ability to improve understanding of the surface energy balance is limited by the heterogeneity of surfaces in urban areas. This study aims to enhance the understanding of the urban surface energy budget through an innovation in the use of land surface temperature (LST) observations from remote sensing satellites. A LST database with 5–min temporal and 30–m spatial resolution is developed by spatial downscaling of the Geostationary Operational Environmental Satellites—R (GOES–R) series LST product over New York City (NYC). The new downscaling method, known as the Spatial Downscaling Method (SDM), benefits from the fine spatial resolution of Landsat–8 and high temporal resolution of GOES–R, and considers the temporal variation in LST for each land cover type separately. Preliminary results show that the SDM can reproduce the temporal and spatial variability of LST over NYC reasonably well and the downscaled LST has a spatial root mean square error (RMSE) of the order of 2 K as compared to the independent Landsat–8 observations. The SDM shows smaller RMSE of 1.93 K over the tree canopy land cover, whereas RMSE is 2.19 K for built–up areas. The overall results indicate that the SDM has potential to estimate LST at finer spatial and temporal scales over urban regions.

land surface temperature↗

DOE OSTI2024

Biogeochemistry simulations for the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX)

Coastal ecosystems have been largely ignored in Earth system models but are important zones for carbon and nutrient processing. Interactions between water, microbes, soil, sediments, and vegetation are important for mechanistic representation of coastal processes and ecosystem function. To investigate the role of these feedbacks, we used a reactive transport model (PFLOTRAN) that has the capability to be connected to the Energy Exascale Earth System Model (E3SM). PFLOTRAN was used to incorporate redox reactions and track chemical species important for coastal ecosystems as well as define simple representations of vegetation dynamics. Our goal was to incorporate oxygen flux, salinity, pH, sulfur cycling, and methane production along with plant-mediated transport of gases and tidal flux. Using porewater profile and incubation data for model calibration and evaluation, we were able to create depth-resolved biogeochemical soil profiles for saltmarsh habitat and use this updated representation to simulate direct and indirect effects of elevated CO2 and temperature on subsurface biogeochemical cycling. We found that simply changing the partial pressure of CO2 or increasing temperature in the model did not fully reproduce observed changes in the porewater profile, but the inclusion of plant or microbial responses to CO2 and temperature manipulations was more accurate in representing porewater concentrations. This indicates the importance of characterizing tightly coupled vegetation-subsurface processes for developing predictive understanding and the need for measurement of plant-soil interactions on the same time scale to understand how hotspots or moments are generated.Included in this data package are PFLOTRAN input (PFLOTRAN input files and chemical database) files for simulating single column biogeochemistry, root, and tide interactions at the Global Change Research Wetland (Kirkpatrick Marsh; Edgewater, MD). The biogeochemical network includes soil organic matter decomposition, nitrogen, iron, and sulfur cycling, and methanogenesis. Reduced species can be oxidized and plant processes include oxygen and nutrient priming, methane release, and nutrient uptake.Inputs:TAI_database.dat - geochemical database for reactions, more information on database structure and variables can be found here https://www.pflotran.org/documentation/user_guide/cards/pages/geochemical_database.htmlswamp.in - input file for biogeochemical network in PFLOTRANswamp_eCO2.in - input file for biogeochemical network in PFLOTRAN with input gas partial pressures/concentrations adjusted for elevated CO2 treatmentsOutputs:swamp_obs_0.tec - hourly porewater concentrations from from multiple depths in the soil columnswamp_eCO2_obs_0.tec - hourly porewater concentrations from multiple depths in the soil column for elevated CO2 treatmentsPFLOTRAN code access: https://github.com/fmyuan/pflotran-elm-interface.git

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗

NASA NTRS1991

SEPAC data analysis in support of the environmental interaction program

Data analyses of the Space Experiments with Particle Accelerators (SEPAC) data and computer modeling were conducted to investigate spacecraft environmental effects associated with injection of electron beams, plasma clouds, and neutral gas clouds from the Shuttle orbiter. The data analysis indicates that Extremely Low Frequency oscillations from 150 to 200 Hz were seen in the Langmuir probe current when the beam was fired in a continuous mode. The strongest oscillations occurred when the ambient pressure was augmented by neutral gas releases from the SEPAC plasma accelerator magnetoplasma-dynamic (MPD) arcjet. To understand the dependence of spacecraft charging potential on beam density and other plasma parameters, a two-dimensional electrostatic particle code was used to simulate the injection of electron beams from an infinite conductor into a plasma. The simulations show that the conductor charging potential depends critically on the reflection coefficient of the conductor surface, which is defined as the percentage of incident particles reflected by the conductor. The ionization effects on spacecraft charging were examined by including interactions of electrons with neutral gas. The simulations show that the conductor charging potential decreases with increasing neutral background density due to the production of secondary electrons near the conductor surface. The simulations also indicate that the beam radius is generally proportional to the beam electron gyroradius when the conductor is charged to a large potential. It appears that the charge buildup at the beam stagnation point causes the beam radial expansion. A survey of the simulation results suggests that the ratio of the beam radius to the beam electron gyroradius increases with the square root of beam density and decreases inversely with beam injection velocity. These results are useful for explaining the spacecraft charging phenomena observed during SEPAC experiments from Spacelab 1.

Lin, Chin S.↗

NASA NTRS1990

Integrated controls-structures design methodology development for a class of flexible spacecraft

Future utilization of space will require large space structures in low-Earth and geostationary orbits. Example missions include: Earth observation systems, personal communication systems, space science missions, space processing facilities, etc., requiring large antennas, platforms, and solar arrays. The dimensions of such structures will range from a few meters to possibly hundreds of meters. For reducing the cost of construction, launching, and operating (e.g., energy required for reboosting and control), it will be necessary to make the structure as light as possible. However, reducing structural mass tends to increase the flexibility which would make it more difficult to control with the specified precision in attitude and shape. Therefore, there is a need to develop a methodology for designing space structures which are optimal with respect to both structural design and control design. In the current spacecraft design practice, it is customary to first perform the structural design and then the controller design. However, the structural design and the control design problems are substantially coupled and must be considered concurrently in order to obtain a truly optimal spacecraft design. For example, let C denote the set of the 'control' design variables (e.g., controller gains), and L the set of the 'structural' design variables (e.g., member sizes). If a structural member thickness is changed, the dynamics would change which would then change the control law and the actuator mass. That would, in turn, change the structural model. Thus, the sets C and L depend on each other. Future space structures can be roughly divided into four mission classes. Class 1 missions include flexible spacecraft with no articulated appendages which require fine attitude pointing and vibration suppression (e.g., large space antennas). Class 2 missions consist of flexible spacecraft with articulated multiple payloads, where the requirement is to fine-point the spacecraft and each individual payload while suppressing the elastic motion. Class 3 missions include rapid slewing of spacecraft without appendages, while Class 4 missions include general nonlinear motion of a flexible spacecraft with articulated appendages and robot arms. Class 1 and 2 missions represent linear mathematical modeling and control system design problems (except for actuator and sensor nonlinearities), while Class 3 and 4 missions represent nonlinear problems. The development of an integrated controls/structures design approach for Class 1 missions is addressed. The performance for these missions is usually specified in terms of (1) root mean square (RMS) pointing errors at different locations on the structure, and (2) the rate of decay of the transient response. Both of these performance measures include the contributions of rigid as well as elastic motion.

Maghami, P. G.↗

NASA NTRS2003

Computational Aeroelasticity: Success, Progress, Challenge

The formal term Computational Aeroelasticity (CAE) has only been recently adopted to describe aeroelastic analysis methods coupling high-level computational fluid dynamics codes with structural dynamics techniques. However, the general field of aeroelastic computations has enjoyed a rich history of development and application since the first hand-calculations performed in the mid 1930 s. This paper portrays a much broader definition of Computational Aeroelasticity; one that encompasses all levels of aeroelastic computation from the simplest linear aerodynamic modeling to the highest levels of viscous unsteady aerodynamics, from the most basic linear beam structural models to state-of-the-art Finite Element Model (FEM) structural analysis. This paper is not written as a comprehensive history of CAE, but rather serves to review the development and application of aeroelastic analysis methods. It describes techniques and example applications that are viewed as relatively mature and accepted, the "successes" of CAE. Cases where CAE has been successfully applied to unique or emerging problems, but the resulting techniques have proven to be one-of-a-kind analyses or areas where the techniques have yet to evolve into a routinely applied methodology are covered as "progress" in CAE. Finally the true value of this paper is rooted in the description of problems where CAE falls short in its ability to provide relevant tools for industry, the so-called "challenges" to CAE.

Schuster, David M.↗

DOE OSTI2025

The influence of wind veer and drivetrain flexibility on fatigue loading for large floating wind turbines

To reduce costs, offshore wind turbines are expected to be designed with significantly increased rotor diameters. Larger turbines become more flexible and span a larger portion of the atmospheric boundary layer. With these changes, the validity of traditional modeling assumptions should be investigated. This work challenges two common assumptions: (1) that the drivetrain can be considered rigid (except in torsion) and does not couple with the rotor and tower and 2) that wind directional change with height (veer) does not greatly influence the fatigue damage in the tower, blades and drivetrain. Two large semi-submersible floating wind turbines are considered: a 15 and a 22 MW reference turbine. Both use direct-drive generators. Aero-hydro-servo-elastic simulations are performed using OpenFAST, with drivetrain bending flexibility and main bearing response implemented in the coupled analysis. The turbines are subjected to a set of load cases at below-, near- and above-rated mean wind speeds, assembled based on the 3 km Norwegian reanalysis (NORA3) hourly wind and wave hindcast data for Utsira Nord, off the coast of Norway. In each load case, conditions with and without veer are simulated to evaluate the influence of veer on damage equivalent loads (DELs) of the turbine tower, blades and main bearings. Further, these load cases are applied to evaluate the influence of drivetrain flexibility on aero-elastic turbine response. The results indicate that, depending on the veer gradient, mean wind speed, operating regime and turbine size, veer can be very important for tower-top DELs and the fluctuations of main bearing radial loads, while main bearing and blade-root flapwise DELs are less affected. Considering these specific load cases and turbine models, drivetrain flexibility is found to significantly influence tower-top DELs of the largest turbine: the tower-top fore-aft and torsional damage equivalent moments of the 22 MW turbine are reduced by more than 20 % at near-rated wind speeds when the drivetrain is modeled as flexible.

17 WIND ENERGY↗

DOE OSTI2018

Shock compression of strongly correlated oxides: A liquid-regime equation of state for cerium(IV) oxide

Here, the shock Hugoniot for full-density and porous CeO 2 was investigated in the liquid regime using ab initio molecular dynamics (AIMD) simulations with Erpenbeck's approach based on the Rankine-Hugoniot jump conditions. The phase space was sampled by carrying out NVT simulations for isotherms between 6000 and 100 000 K and densities ranging from ρ = 2.5 to 20 g/cm 3 . The impact of on-site Coulomb interaction corrections +U on the equation of state (EOS) obtained from AIMD simulations was assessed by direct comparison with results from standard density functional theory simulations. Classical molecular dynamics (CMD) simulations were also performed to model atomic-scale shock compression of larger porous CeO 2 models. Results from AIMD and CMD compression simulations compare favorably with Z-machine shock data to 525 GPa and gas-gun data to 109 GPa for porous CeO 2 samples. Using results from AIMD simulations, an accurate liquid-regime Mie-Grüneisen EOS was built for CeO 2 . In addition, a revised multiphase SESAME-type EOS was constrained using AIMD results and experimental data generated in this work. This study demonstrates the necessity of acquiring data in the porous regime to increase the reliability of existing analytical EOS models.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRSDate not supplied

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle was simulated using the Overflow Computational Fluid Dynamics (CFD) solver. Two nozzle configurations were tested (1E and 1F) as a subset of the seven total configurations in the Descent System Study (DSS) testing campaign. A generalized, Adaptive Mesh Refinement (AMR) shock capturing and plume refinement technique was developed and calibrated for producing automatic and unique grid systems optimized for any given testing condition. Solution independence from grid resolution was determined by successively increasing grid refinement until asymptotic convergence of the mean aerodynamic loads was observed. Overflow Reynolds-averaged Navier-Stokes (RANS) solutions produced realistic SRP flow phenomena, including Mach disk normal shocks contained in high-thrust plumes and bow shock triple-points. Solutions for the 1E nozzle configuration were steady. Conversely, a subset of the 1F test conditions were unsteady and exhibited periodic, non-sinusoidal expansions and contractions of the streamwise-oriented plume, resulting in unsteady aerodynamic loads on the vehicle. Initial investigations into the effect of turbulence modeling fidelity demonstrated significant differences between the aerodynamic loads simulated with RANS and Detached Eddy Simulation (DES). Multiple flow mechanisms were identified as root causes of these differences, including bow shock shape augmentation and reduced entrainment due to reduced turbulence in the DES simulations. Initial comparisons of pitching moment control authority and aerodynamic drag performance between the tested nozzle configurations demonstrated that the 1E configuration may be more advantageous for the Mars Entry, Descent, and Landing (EDL) task.

Supersonic Retropropulsion↗

NASA NTRSDate not supplied

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic Retropropulsion↗

DOE OSTI2014

Intronic and plasmid-derived regions contribute to the large mitochondrial genome sizes of Agaricomycetes

Sizes of mitochondrial genomes vary extensively between fungal species although they typically contain a conserved set of core genes. We have characterised the mitochondrial genome of the conifer root rot pathogen Heterobasidion irregulare and compared the size, gene content and structure of 20 Basidiomycete mitochondrial genomes. The mitochondrial genome of H. irregulare was 114, 193 bp and contained a core set of 15 protein coding genes, two rRNA genes and 26 tRNA genes. In addition, we found six non-conserved open reading frames (ORFs) and four putative plasmid genes clustered in three separate regions together with 24 introns and 14 intronic homing endonuclease genes, unequally spread across seven of the core genes. The size differences among the 20 Basidiomycetes can largely be explained by length variation of intergenic regions and introns. The Agaricomycetes contained the nine largest mitochondrial genomes in the Basidiomycete group and Agaricomycete genomes are significantly (p < 0.001) larger than the other Basidiomycetes. A feature of the Agaricomycete mitochondrial genomes in this study was the simultaneous occurrence of putative plasmid genes and non-conserved ORFs, with Cantharellus cibarius as only exception, where no non-conserved ORF was identified. This indicates a mitochondrial plasmid origin of the non-conserved ORFs or increased mitochondrial genome dynamics of species harbouring mitochondrial plasmids. We hypothesise that two independent factors are the driving forces for large mitochondrial genomes: the homing endonuclease genes in introns and integration of plasmid DNA.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Incorporating the Effect of Large‐Scale Vertical Motion on Convection Through Convective Mass Flux Adjustment in E3SMv2

Abstract Recent observational studies suggest that the large‐scale dynamical forcing (vertical motion) plays important roles in deep convection development. In this study we propose a convective mass flux adjustment (MAdj) approach to represent the dynamical effects of large‐scale vertical motion on convection in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). With MAdj, convection is enhanced (suppressed) when there is large‐scale ascending (descending) motion at the planetary boundary layer top. The coupling of convection with large‐scale circulation significantly improves the simulation of climate variability in E3SMv2 across multiple scales from the diurnal cycle, convectively coupled equatorial waves, to the Madden‐Julian Oscillation (MJO). The standard E3SMv2 tends to simulate overly weak diurnal amplitude of precipitation and overly weak variance of convectively coupled equatorial Kelvin and westward inertio‐gravity (WIG) waves. It also fails to simulate the essential characteristics of the MJO: continuous eastward propagation. With MAdj, the amplitude of diurnal cycle of precipitation is systematically increased and its probability density distribution is much closer to observations. The MAdj can also simulate more realistic eastward propagation of the MJO and much stronger convectively coupled Kelvin and WIG waves. Moreover, the MAdj approach slightly improves the climatology simulations in precipitation, cloud, radiation, circulation, temperature, and moisture fields, with overall root‐mean‐square error (RMSE) of major climatological fields reduced by about 2%. The MAdj approach suppresses excessive grid‐scale precipitation, reducing precipitation wet biases over South China Sea, Philippine Sea, Himalayas, and South Pacific Convergence Zone in western Pacific in summer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability

Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit R 2 > 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation ( R 2 = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed ( R 2 = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands?

Ground solar-induced chlorophyll fluorescence (SIF) is important for the mechanistic understanding of the dynamics of vegetation gross primary production (GPP) at fine spatiotemporal scales. However, eddy covariance (EC) observations generally cover larger footprint areas than ground SIF observations (a bare fiber with nadir), and this footprint mismatch between nadir SIF and GPP could complicate the canopy SIF-GPP relationships. Here, we upscaled nadir SIF observations to EC footprint and investigated the change in SIF-GPP relationships after the upscaling in cropland. We included 13 site-years data in our study, with seven site-years corn, four site-years soybeans, and two site-years miscanthus, all located in the US Corn Belt. All sites’ crop nadir SIF observations collected from the automated FluoSpec2 system (a hemispheric-nadir system) were upscaled to the GPP footprint-based SIF using vegetation indices (VIs) calculated from high spatiotemporal satellite reflectance data. We found that SIF-GPP relationships were not substantially changed after upscaling nadir SIF to GPP footprint at our crop sites planted with corn, soybean, and miscanthus, with R 2 change after the upscaling ranging from -0.007 to 0.051 and root mean square error (RMSE) difference from -0.658 to 0.095 umol m –2 s –1 relative to original nadir SIF-GPP relationships across all the site-years. The variation of the SIF-GPP relationship within each species across different site-years was similar between the original nadir SIF and upscaled SIF. Different VIs, EC footprint models, and satellite data led to marginal differences in the SIF-GPP relationships when upscaling nadir SIF to EC footprint. Furthermore, our study provided a methodological framework to correct this spatial mismatch between ground nadir SIF and GPP observations for croplands and potentially for other ecosystems. Our results also demonstrated that the spatial mismatch between ground nadir SIF and GPP might not significantly affect the SIF-GPP relationship in cropland that are largely homogeneous.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

Pendulum Motion in Main Parachute Clusters

The coupled dynamics of a cluster of parachutes to a payload are notoriously difficult to predict. Often the payload is designed to be insensitive to the range of attitude and rates that might occur, but spacecraft generally do not have the mass and volume budgeted for this robust of a design. The National Aeronautics and Space Administration (NASA) Orion Capsule Parachute Assembly System (CPAS) implements a cluster of three mains for landing. During testing of the Engineering Development Unit (EDU) design, it was discovered that with a cluster of two mains (a fault tolerance required for human rating) the capsule coupled to the parachute cluster could get into a limit cycle pendulum motion which would exceed the spacecraft landing capability. This pendulum phenomenon could not be predicted with the existing models and simulations. A three phased effort has been undertaken to understand the consequence of the pendulum motion observed, and explore potential design changes that would mitigate this phenomenon. This paper will review the early analysis that was performed of the pendulum motion observed during EDU testing, summarize the analysis ongoing to understand the root cause of the pendulum phenomenon, and discuss the modeling and testing that is being pursued to identify design changes that would mitigate the risk.

Ray, Eric S.↗

DOE OSTI2016

SUNSPOT ROTATION AS A DRIVER OF MAJOR SOLAR ERUPTIONS IN THE NOAA ACTIVE REGION 12158

We studied the development conditions of sigmoid structure under the influence of the magnetic non-potential characteristics of a rotating sunspot in the active region (AR) 12158. Vector magnetic field measurements from the Helioseismic Magnetic Imager and coronal EUV observations from the Atmospheric Imaging Assembly reveal that the erupting inverse-S sigmoid had roots at the location of the rotating sunspot. The sunspot rotates at a rate of 0°–5° h{sup −1} with increasing trend in the first half followed by a decrease. The time evolution of many non-potential parameters had a good correspondence with the sunspot rotation. The evolution of the AR magnetic structure is approximated by a time series of force-free equilibria. The non-linear force-free field magnetic structure around the sunspot manifests the observed sigmoid structure. Field lines from the sunspot periphery constitute the body of the sigmoid and those from the interior overlie the sigmoid, similar to a flux rope structure. While the sunspot was rotating, two major coronal mass ejection eruptions occurred in the AR. During the first (second) event, the coronal current concentrations were enhanced (degraded), consistent with the photospheric net vertical current; however, magnetic energy was released during both cases. The analysis results suggest that the magnetic connections of the sigmoid are driven by the slow motion of sunspot rotation, which transforms to a highly twisted flux rope structure in a dynamical scenario. Exceeding the critical twist in the flux rope probably leads to the loss of equilibrium, thus triggering the onset of the two eruptions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Validation and Sensitivity Analysis of a 1-D Lake Model Across Global Lakes

Lakes have important influence on weather and climate from local to global scales. However, their prediction using numerical models is notoriously difficult because lakes are highly heterogeneous across the globe, but observations are sparse. In this study, we assessed the performance of a 1-D lake model in simulating the thermal structures of 58 lakes with diverse morphometric and geographic characteristics by following the phase 2a local lake protocol of the Inter-sectoral Impact Model Intercomparison Project (ISIMIP2a). After calibration, the root-mean-square errors (RMSE) were below 2 °C for 70% and 75% of the lakes for epilimnion and full-profile temperature simulations, with an average of 1.71 °C and 1.43 °C, respectively. The model performance mainly depended on lake shape rather than location, supporting the possibility of grouping model parameters by lake shape for global applications. Furthermore, through machine-learning based parameter sensitivity tests, we identified turbulent heat fluxes, wind-driven mixing and water transparency as the major processes controlling lake thermal and mixing regimes. Snow density was also important for modeling the ice phenology of high-latitude lakes. The relative influence of the key processes and the corresponding parameters mainly depended on lake latitude and depth. Turbulent heat fluxes showed a decreasing importance in affecting epilimnion temperature with increasing latitude. Wind-driven mixing was less influential to lake stratification for deeper lakes while the impact of light extinction, on the contrary, showed a positive correlation with depth. Our findings may guide improvements in 1-D lake model parameterizations to achieve higher fidelity in simulating global lake thermal dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Nutrient and moisture limitations reveal keystone metabolites linking rhizosphere metabolomes and microbiomes

Plants release a wealth of metabolites into the rhizosphere that can shape the composition and activity of microbial communities in response to environmental stress. The connection between rhizodeposition and rhizosphere microbiome succession has been suggested, particularly under environmental stress conditions, yet definitive evidence is scarce. In this study, we investigated the relationship between rhizosphere chemistry, microbiome dynamics, and abiotic stress in the bioenergy crop switchgrass grown in a marginal soil under nutrient-limited, moisture-limited, and nitrogen (N)-replete, phosphorus (P)-replete, and NP-replete conditions. We combined 16S rRNA amplicon sequencing and LC-MS/MS-based metabolomics to link rhizosphere microbial communities and metabolites. We identified significant changes in rhizosphere metabolite profiles in response to abiotic stress and linked them to changes in microbial communities using network analysis. N-limitation amplified the abundance of aromatic acids, pentoses, and their derivatives in the rhizosphere, and their enhanced availability was linked to the abundance of bacterial lineages from Acidobacteria, Verrucomicrobia, Planctomycetes, and Alphaproteobacteria. Conversely, N-amended conditions increased the availability of N-rich rhizosphere compounds, which coincided with proliferation of Actinobacteria. Treatments with contrasting N availability differed greatly in the abundance of potential keystone metabolites; serotonin and ectoine were particularly abundant in N-replete soils, while chlorogenic, cinnamic, and glucuronic acids were enriched in N-limited soils. Serotonin, the keystone metabolite we identified with the largest number of links to microbial taxa, significantly affected root architecture and growth of rhizosphere microorganisms, highlighting its potential to shape microbial community and mediate rhizosphere plant–microbe interactions.

59 BASIC BIOLOGICAL SCIENCES↗