SEARCH · Search NASA

Results for “Climate gradient”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Potential Vorticity Dynamics Explain How Extratropical Oceans and the Arctic Modulate Wintertime Land–Temperature Variations

Temperature variations across the continental northern hemisphere at the interdecadal scale are thought to be remotely modulated by oceanic internal climate variability and the Arctic. Nevertheless, further elucidating the dynamics is essential for clarifying ongoing debates. We show that potential vorticity (PV) dynamics provide a concise explanation for these teleconnections. Our findings demonstrate that extratropical oceans and the Arctic can remotely modulate the wintertime continental temperature variations by stimulating PV anomalies, which are constrained by climatological PV gradients and jet streams. A causal explanation includes anomalous temperature and precipitation over oceans and the Arctic inducing local PV anomalies via diabatic heating. Subsequently, meridional and downstream advection distributes the anomalous PV to remote land regions where the climatological PV gradients are strong, that is, involving PV fronts, as well as jet streams; therefore, PV fronts and jet streams jointly indicate land regions that are largely and frequently impacted. However, land can also modulate other regions through the same mechanism when variations over land occur in advance. Clear causality depends on which factor is independent, while interactions among those regions may convolute the causality, thereby causing further debates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Rethinking materials simulations: Blending direct numerical simulations with neural operators

Abstract Materials simulations based on direct numerical solvers are accurate but computationally expensive for predicting materials evolution across length- and time-scales, due to the complexity of the underlying evolution equations, the nature of multiscale spatiotemporal interactions, and the need to reach long-time integration. We develop a method that blends direct numerical solvers with neural operators to accelerate such simulations. This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism to enable accurate extrapolation and efficient time-to-solution predictions of the dynamics. We demonstrate the effectiveness of this hybrid framework on simulations of microstructure evolution via the phase-field method. Such simulations exhibit high spatial gradients and the co-evolution of different material phases with simultaneous slow and fast materials dynamics. We establish accurate extrapolation of the coupled solver with large speed-up compared to DNS depending on the hybrid strategy utilized. This methodology is generalizable to a broad range of materials simulations, from solid mechanics to fluid dynamics, geophysics, climate, and more.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Sulfur gas exchange in Sphagnum-dominated wetlands

Sulfur gases are important components of the global cycle of S. They contribute to the acidity of precipitation and they influence global radiation balance and climate. The role of terrestrial sources of biogenic S and their effect on atmospheric chemistry remain as major unanswered questions in our understanding of the natural S cycle. The role of northern wetlands as sources and sinks of gaseous S was investigated by measuring rates of S gas exchange as a function of season, hydrologic conditions, and gradients in trophic status. The effects of inorganic S input on the production and emission of gaseous S were also investigated. Experiments were conducted in wetlands in New Hampshire, particularly a poor fen, fens within the Experimental Lakes Area (ELA) in Ontario, Canada and in freshwater and marine tundra. Emissions were determined using Teflon enclosures, gas cryotrapping methods, and gas chromatography (GC) with flame photometric detection. Dynamic (sweep flow) and static enclosures were employed. Dissolved gases were determined by gas stripping followed by GC.

Hines, Mark E.↗

DOE OSTI2018

Large Blooms of Bacillales ( Firmicutes ) Underlie the Response to Wetting of Cyanobacterial Biocrusts at Various Stages of Maturity

Biological soil crusts (biocrusts) account for a substantial portion of primary production in dryland ecosystems. They successionally mature to deliver a suite of ecosystem services, such as carbon sequestration, water retention and nutrient cycling, and climate regulation. Biocrust assemblages are extremely well adapted to survive desiccation and to rapidly take advantage of the periodic precipitation events typical of arid ecosystems. Here we focus on the wetting response of incipient cyanobacterial crusts as they mature from “light” to “dark.” We sampled a cyanobacterial biocrust chronosequence before (dry) and temporally following a controlled wetting event and used high-throughput 16S rRNA and rRNA gene sequencing to monitor the dynamics of microbial response. Overall, shorter-term changes in phylogenetic beta diversity attributable to periodic wetting were as large as those attributable to biocrust successional stage. Notably, more mature crusts showed significantly higher resistance to precipitation disturbance. A large bloom of a few taxa within the Firmicutes , primarily in the order Bacillales , emerged 18 h after wetting, while filamentous crust-forming cyanobacteria showed variable responses to wet-up across the successional gradient, with populations collapsing in less-developed light crusts but increasing in later-successional-stage dark crusts. Overall, the consistent Bacillales bloom accompanied by the variable collapse of pioneer cyanobacteria of the Oscillatoriales order across the successional gradient suggests that the strong response of few organisms to a hydration pulse with the mortality of the autotroph might have important implications for carbon (C) balance in semiarid ecosystems. IMPORTANCE Desert biological soil crusts are terrestrial topsoil microbial communities common to arid regions that comprise 40% of Earth’s terrestrial surface. They successionally develop over years to decades to deliver a suite of ecosystem services of local and global significance. Ecosystem succession toward maturity has been associated with both resistance and resilience to disturbance. Recent work has shown that the impacts of both climate change and physical disturbance on biocrusts increase the potential for successional resetting. A larger proportion of biocrusts are expected to be at an early developmental stage, hence increasing susceptibility to changes in precipitation frequencies. Therefore, it is essential to characterize how biocrusts respond to wetting across early developmental stages. In this study, we document the wetting response of microbial communities from a biocrust chronosequence. Overall, our results suggest that the cumulative effects of altered precipitation frequencies on the stability of biocrusts will depend on biocrust maturity.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2001

Responses of Precipitation and Hydrologic Processes to Tropical SST

The goal of the research is to identify the mechanisms in the response of tropical precipitation and atmospheric hydrologic cycle to sea surface temperature (SST) variability at seasonal-to-interannual time scales, and to utilize the knowledge for better understanding of climate feedback processes relevant to global change. As a first step to achieve the goal, we characterize the inter-relationship among convective/stratiform rain, ice/water clouds water vapor, and SST using TRMM satellite data and a cloud-resolving model. We examined the daily hydrologic variables [column water vapor (PW), cloud liquid water (CW), rainfall rates (RR)] as a function of SST using high-resolution data (0.25 x 0.25, daily) derived from TRMM satellite measurements. Comparing the winter of 97/98 (El Nino condition) against the winter of 99/00 (La Nina condition), area-mean values of all four hydrologic variables in cloudy areas within the tropical Pacific are higher in the El Nino winter than in the La Nina winter. This is consistent with previous observational analyses and SST warming experiments (idealized or ENSO-like) that showed the interaction between hydrologic cyclic and radiation at the seasonal to interannual time scales leads to intensified tropical circulation and hydrologic cycle. However, there is evidence that the enhanced hydrologic cycle over the warm pool is accompanied by an expansion of radiatively -driven subsidence in response to a stronger SST gradient between warm pool and surrounding cold pool. The expanding subsidence effectively reduces cloud amounts over the warm pool. Our analysis of daily variability further indicates a more vigorous water cycle characterized by higher PW, CW, and RR in response to overall warming. This is expected from the Clausius Clapeyron relation as a thermodynamic response to warming. However cloudy areas decrease in response to overall warming. This may be due to factors that are fundamentally different. One possibility is that in a warmer climate, there may be alteration in the microphysical processes in clouds, e.g., increased coalescence of cloud size droplets and increased entrainment of dry air from above due to the invigorated convective motions in response to overall warming. As a result, cloud amounts are less. Another interpretation is that, in colder air masses, more ice particles will be produced and, because of their lower densities, are less likely to precipitate, hence the higher cloud amount. This suggests that, when averaged over a sufficiently large area covering both the rising and sinking branches of the tropical circulation, there maybe an increase in the precipitation efficiency in stratiform clouds, in conjunction with increased subsidence in an enhanced water cycle. This is supported by the residence time at different rainrates.

Sui, C.-H.↗

DOE OSTI2025

Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation

The Strong Constraint 4D Variational (SC-4DVAR) data assimilation method is widely used in climate and weather applications. SC-4DVAR involves solving a minimization problem to compute the maximum a posteriori estimate, which we tackle using the Gauss-Newton method. The computation of the descent direction is expensive since it involves the solution of a large-scale and potentially ill-conditioned linear system, solved using the preconditioned conjugate gradient (PCG) method. Here, to address this cost, we efficiently construct scalable preconditioners using three different randomization techniques, which all rely on a certain low-rank structure involving the Gauss-Newton Hessian. The proposed techniques come with theoretical guarantees on the condition number, and at the same time, are amenable to parallelization. We also develop an adaptive approach to estimate the sketch size and choose between the reuse or recomputation of the preconditioner. We demonstrate the performance and effectiveness of our methodology on two representative model problems—the Burgers and barotropic vorticity equation—showing a drastic reduction in both the number of PCG iterations and the number of Gauss-Newton Hessian products after including the preconditioner construction cost.

Gauss-Newton↗

DOE OSTI2016

Few multi-year precipitation-reduction experiments find a shift in the productivity-precipitation relationship

Well-defined productivity–precipitation relationships of ecosystems are needed as benchmarks for the validation of land models used for future projections. The productivity–precipitation relationship may be studied in two ways: the spatial approach relates differences in productivity to those in precipitation among sites along a precipitation gradient (the spatial fit, with a steeper slope); the temporal approach relates interannual productivity changes to variation in precipitation within sites (the temporal fits, with flatter slopes). Precipitation–reduction experiments in natural ecosystems represent a complement to the fits, because they can reduce precipitation below the natural range and are thus well suited to study potential effects of climate drying. Here, we analyse the effects of dry treatments in eleven multiyear precipitation–manipulation experiments, focusing on changes in the temporal fit. We expected that structural changes in the dry treatments would occur in some experiments, thereby reducing the intercept of the temporal fit and displacing the productivity–precipitation relationship downward the spatial fit. Seventy two percent of expiriments showed that dry treatments did not alter the temporal fit. This implies that current temporal fits are to be preferred over the spatial fit to benchmark land-model projections of productivity under future climate within the precipitation ranges covered by the experiments. Moreover, in two experiments, the intercept of the temporal fit unexpectedly increased due to mechanisms that reduced either water loss or nutrient loss. The expected decrease of the intercept was observed in only one experiment, and only when distinguishing between the late and the early phases of the experiment. This implies that we currently do not know at which precipitation–reduction level or at which experimental duration structural changes will start to alter ecosystem productivity. Our study highlights the need for experiments with multiple, including more extreme, dry treatments, to identify the precipitation boundaries within which the current temporal fits remain valid.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity

Abstract Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO 2 fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO 2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.

Trugman, Anna T.↗

DOE OSTI2023

Climate drivers alter nitrogen availability in surface peat and decouple N 2 fixation from CH 4 oxidation in the Sphagnum moss microbiome

Peat mosses (Sphagnum spp.) are keystone species in boreal peatlands, where they dominate net primary productivity and facilitate the accumulation of carbon in thick peat deposits. Sphagnum mosses harbor a diverse assemblage of microbial partners, including N 2 -fixing (diazotrophic) and CH 4 -oxidizing (methanotrophic) taxa that support ecosystem function by regulating transformations of carbon and nitrogen. In this work, we investigate the response of the Sphagnum phytobiome (plant + constituent microbiome + environment) to a gradient of experimental warming (+0°C to +9°C) and elevated CO 2 (+500 ppm) in an ombrotrophic peatland in northern Minnesota (USA). By tracking changes in carbon (CH 4 , CO 2 ) and nitrogen (NH 4 -N) cycling from the belowground environment up to Sphagnum and its associated microbiome, we identified a series of cascading impacts to the Sphagnum phytobiome triggered by warming and elevated CO 2 . Under ambient CO 2 , warming increased plant-available NH 4 -N in surface peat, excess N accumulated in Sphagnum tissue, and N 2 fixation activity decreased. Elevated CO 2 offset the effects of warming, disrupting the accumulation of N in peat and Sphagnum tissue. Methane concentrations in porewater increased with warming irrespective of CO 2 treatment, resulting in a ~10× rise in methanotrophic activity within Sphagnum from the +9°C enclosures. Warming's divergent impacts on diazotrophy and methanotrophy caused these processes to become decoupled at warmer temperatures, as evidenced by declining rates of methane-induced N 2 fixation and significant losses of keystone microbial taxa. In addition to changes in the Sphagnum microbiome, we observed ~94% mortality of Sphagnum between the +0°C and +9°C treatments, possibly due to the interactive effects of warming on N-availability and competition from vascular plant species. Collectively, these results highlight the vulnerability of the Sphagnum phytobiome to rising temperatures and atmospheric CO 2 concentrations, with significant implications for carbon and nitrogen cycling in boreal peatlands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Subpolar North Atlantic Mean State Affects the Response of the Atlantic Meridional Overturning Circulation to the North Atlantic Oscillation in CMIP6 Models

Abstract The Atlantic meridional overturning circulation (AMOC) plays an important role in climate, transporting heat and salt to the subpolar North Atlantic. The AMOC’s variability is sensitive to atmospheric forcing, especially the North Atlantic Oscillation (NAO). Because AMOC observations are short, climate models are a valuable tool to study the AMOC’s variability. Yet, there are known issues with climate models, like uncertainties and systematic biases. To investigate this, preindustrial control experiments from models participating in the phase 6 of Coupled Model Intercomparison Project (CMIP6) are evaluated. There is a large, but correlated, spread in the models’ subpolar gyre mean surface temperature and salinity. By splitting models into groups of either a warm–salty or cold–fresh subpolar gyre, it is shown that warm–salty models have a lower sea ice cover in the Labrador Sea and, hence, enable a larger heat loss during a positive NAO. Stratification in the Labrador Sea is also weaker in warm–salty models, such that the larger NAO-related heat loss can also affect greater depths. As a result, subsurface density anomalies are much stronger in the warm–salty models than in those that tend to be cold and fresh. As these anomalies propagate southward along the western boundary, they establish a zonal density gradient anomaly that promotes a stronger delayed AMOC response to the NAO in the warm–salty models. These findings demonstrate how model mean state errors are linked across variables and affect variability, emphasizing the need for improvement of the subpolar North Atlantic mean states in models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗

DOE OSTI2025

Myco-CORPSE simulations assessing mycorrhizal carbon allocation across U.S. forests and global change scenarios

Plants allocate a substantial portion of their fixed carbon belowground to mycorrhizal fungi in exchange for nutrients and other benefits. However, most current ecosystem models omit mycorrhizal processes, limiting our ability to predict plant–soil carbon dynamics under environmental change. To address this gap, we used a mycorrhiza-explicit soil biogeochemical model, Myco-CORPSE (Mycorrhizal Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment), to simulate tree carbon allocation to arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi in temperate forests.The dataset includes outputs from two sets of model simulations:1. Perturbation experiments: Simulations across gradients of ECM dominance (0–100%), nitrogen deposition, soil temperature, and net primary productivity (NPP) to test how these factors affect mycorrhizal C allocation and nutrient cycling.2. FIA-based simulations: Model applications to over 1,800 U.S. forest sites using site-specific data from the U.S. Forest Inventory and Analysis (FIA) program, including vegetation composition, mycorrhizal type, climate, litter traits, soil properties, and N deposition.Model outputs include simulated mycorrhizal carbon allocation and related biogeochemical variables, such as soil and microbial carbon and nitrogen stocks. Data are provided in CSV format and organized by experiment type (in separate ZIP files). Python scripts for running simulations, plotting, and spatial mapping are also included and organized similarly. No proprietary software is required. These outputs support a peer-reviewed study and were used to generate figures and tables in the associated publication.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Dynamics of canopy stomatal conductance, transpiration, and evaporation in a temperate deciduous forest, validated by carbonyl sulfide uptake

Abstract. Stomatal conductance influences both photosynthesis and transpiration, thereby coupling the carbon and water cycles and affecting surface–atmosphere energy exchange. The environmental response of stomatal conductance has been measured mainly on the leaf scale, and theoretical canopy models are relied on to upscale stomatal conductance for application in terrestrial ecosystem models and climate prediction. Here we estimate stomatal conductance and associated transpiration in a temperate deciduous forest directly on the canopy scale via two independent approaches: (i) from heat and water vapor exchange and (ii) from carbonyl sulfide (OCS) uptake. We use the eddy covariance method to measure the net ecosystem–atmosphere exchange of OCS, and we use a flux-gradient approach to separate canopy OCS uptake from soil OCS uptake. We find that the seasonal and diurnal patterns of canopy stomatal conductance obtained by the two approaches agree (to within ±6 % diurnally), validating both methods. Canopy stomatal conductance increases linearly with above-canopy light intensity (in contrast to the leaf scale, where stomatal conductance shows declining marginal increases) and otherwise depends only on the diffuse light fraction, the canopy-average leaf-to-air water vapor gradient, and the total leaf area. Based on stomatal conductance, we partition evapotranspiration (ET) and find that evaporation increases from 0 to 40 % of ET as the growing season progresses, driven primarily by rising soil temperature and secondarily by rainfall. Counterintuitively, evaporation peaks at the time of year when the soil is dry and the air is moist. Our method of ET partitioning avoids concerns about mismatched scales or measurement types because both ET and transpiration are derived from eddy covariance data. Neither of the two ecosystem models tested predicts the observed dynamics of evaporation or transpiration, indicating that ET partitioning such as that provided here is needed to further model development and improve our understanding of carbon and water cycling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Unifying soil organic matter formation and persistence frameworks: the MEMS model

Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical models have traditionally been simulated as immeasurable fluxes between conceptually defined pools. This greatly limits how empirical data can be used to improve model performance and reduce the uncertainty associated with their predictions of carbon (C) cycling. Recent advances in our understanding of the biogeochemical processes that govern SOM formation and persistence demand a new mathematical model with a structure built around key mechanisms and biogeochemically relevant pools. Here, we present one approach that aims to address this need. Our new model (MEMS v1.0) is developed from the Microbial Efficiency-Matrix Stabilization framework, which emphasizes the importance of linking the chemistry of organic matter inputs with efficiency of microbial processing and ultimately with the soil mineral matrix, when studying SOM formation and stabilization. Building on this framework, MEMS v1.0 is also capable of simulating the concept of C saturation and represents decomposition processes and mechanisms of physico-chemical stabilization to define SOM formation into four primary fractions. After describing the model in detail, we optimize four key parameters identified through a variance-based sensitivity analysis. Optimization employed soil fractionation data from 154 sites with diverse environmental conditions, directly equating mineral-associated organic matter and particulate organic matter fractions with corresponding model pools. Finally, model performance was evaluated using total topsoil (0–20 cm) C data from 8192 forest and grassland sites across Europe. Despite the relative simplicity of the model, it was able to accurately capture general trends in soil C stocks across extensive gradients of temperature, precipitation, annual C inputs and soil texture. The novel approach that MEMS v1.0 takes to simulate SOM dynamics has the potential to improve our forecasts of how soils respond to management and environmental perturbation. Ensuring these forecasts are accurate is key to effectively informing policy that can address the sustainability of ecosystem services and help mitigate climate change.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

Is There Really an Intermittent Biennial Oscillation in the Great Plains Low-Level Jet Over Texas?

In the 15-year GEOS-1 reanalysis data set, a maximum of interannual variance of low- level meridional flow for the warm season (May through August) occurs over southeast Texas. This variance maximum seems to be dominated by a marked biennial oscillation that occurs only during the first 6 (or possibly 8) years of the reanalysis period (1980-85 or possibly 1980-1987) and then completely disappears by the 9th year. This biennial oscillation seems to be associated with interannual fluctuations in ground wetness, surface temperature and surface pressure gradients over Texas. The periods of drier soil lead to warmer surface temperatures, lower surface pressures, stronger pressure gradients between Texas and the Gulf of Mexico and stronger southerly winds. This intermittent biennial oscillation is also evident in corresponding fields for the the NCEP/NCAR reanalysis data set for the years 1978-1985 (and possibly from 1978- 1987) and 1995-2000, but not during other periods. There are also obvious biennial oscillations evident during these periods in U.S. Climate Division records for the Palmer Drought Severity Index (PDSI) for Texas. Month-by-month correlations of this index with certain el Nino related indices are as high as .45 for the first period and as high as .55 or .6 for the second period for some regions in Texas. The seasonal cycle of the biennial signal in the PDSI and precipitation for the first period suggest that the drought in Texas and Mexico is ended (caused) by a reversal in the sign of anomalies in precipitation rate for the fall/winter season. Analysis of tropical Pacific SST patterns shows a .5 to .75 K biennial oscillation of SSTs along the precipitation-free track to the southwest of the Mexican coast during the fall and winter months of the 1978 to 1985 period that might explain the reversal in precipitation anomalies and hence the entire intermittent biennial oscillation in ground hydrology and low-level flow.

Helfand, H. Mark↗

NASA NTRS1997

Energy, volatile production, and climatic effects of the Chicxulub Cretaceous/Tertiary impact

A comprehensive analysis of volatiles in the Chicxulub impact strongly supports the hypothesis that impact-generated sulfate aerosols caused over a decade of global cooling, acid rain, and disruption of ocean circulation, which contributed to the mass extinction at the Cretaceous/Tertiary (K/T) boundary. The crater size, meteoritic content of the K/T boundary clay, and impact models indicate that the Chicxulub crater was formed by a short period comet or an asteroid impact that released 0.7-3.4 x 10(31) ergs of energy. Impact models and experiments combined with estimates of volatiles in the projectile and target rocks predict that over 200 gigatons (Gt) each of SO2 and water vapor, and over 500 Gt of CO2, were globally distributed in the stratosphere by the impact. Additional volatiles may have been produced on a global or regional scale that formed sulfate aerosols rapidly in cooler parts of the vapor plume, causing an early, intense pulse of sulfuric acid rain. Estimates of the conversion rate of stratospheric SO2 and water vapor to sulfate aerosol, based on volcanic production of sulfate aerosols, coupled with calculations of diffusion, coagulation, and sedimentation, demonstrate that the 200 Gt stratospheric SO2 and water vapor reservoir would produce sulfate aerosols for 12 years. These sulfate aerosols caused a second pulse of acid rain that was global. Radiative transfer modeling of the aerosol clouds demonstrates (1) that if the initial rapid pulse of sulfate aerosols was global, photosynthesis may have been shut down for 6 months and (2) that for the second prolonged aerosol cloud, solar transmission dropped 80% by the end of first year and remained 50% below normal for 9 years. As a result, global average surface temperatures probably dropped between 5 degrees and 31 degrees K, suggesting that global near-freezing conditions may have been reached. Impact-generated CO2 caused less than 1 degree K greenhouse warming and therefore was insignificant compare to the sulfate cooling. The magnitude of sulfate cooling depends largely upon the rate of ocean mixing as surface waters cool, sink, and are replaced by upwelling of deep ocean water. This upwelling apparently drastically altered ocean stratification and circulation, which may explain the global collapse of the delta 13C gradient between surface and deep ocean waters at the K/T boundary.

NASA Center JPL↗

DOE OSTI2022

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Above and belowground connections and species interactions: Controls over ecosystem fluxes

The ultimate goal of this work was to quantify soil and volatile organic compound fluxes as a function of tree species and associated mycorrhizal associations in an intact forest, but also to describe the physical and biological factors that control these emissions. The results of this research lay the foundation toward an improved mechanistic understanding of carbon pathways, fluxes, and ecosystem function, ultimately improving the representation of forest ecosystems in Earth System models. To this end, a multidisciplinary approach was necessary to fill a critical gap in our understanding of how soil and root processes may influence whole-ecosystem carbon-based volatile fluxes in the face of a rapidly changing climate. We developed a series of novel sampling protocols and coupled a variety of advanced analytical techniques, resulting in findings relevant across disciplines. Furthermore, we leveraged existing infrastructure, research sites, and datasets to design a low-cost exploratory project that links belowground processes, soil volatile emissions, and total ecosystem carbon budgets. Measurements from soil collars installed across a species/mycorrhizal gradient at the DOE-supported Moran Monroe State Forest Ameriflux tower site suggest that leaf litter is the primary source of belowground and forest floor volatile emissions, but the strength of this source is significantly affected not only by leaf litter type, but the strength of the soil as a sink. Results suggest that the strength of the sink is influenced by tree species-specific associated microbial communities that change throughout the season as a function of temperature, soil moisture, leaf litter inputs, and phenology. The magnitude of the observed volatile fluxes from the forest floor is small relative to total aboveground ecosystem flux, but the contribution of these emissions to volatile-mediated ecological interactions and soil processes (e.g. nitrification) varies substantially across the growing season. This research lays the foundation to answer important questions regarding the impacts of seasonality and forest composition on belowground volatile source-sink dynamics in mediating nutrient cycling and biogeochemistry dynamics—critical components of overall ecosystem functioning. In collaboration with the Environmental Simulations Unit (EUS) at the Helmholtz Zentrum in Munich, Germany (headed by Prof. Dr. Joerg-Peter Schinitzler), we investigated carbon investment in above and belowground plant volatile compounds in response to environmental conditions and mycorrhizal associations. Using the sophisticated phytotron facility and on-line trace gas instruments, we conducted controlled laboratory experiments that showed that biotic stresses, such as herbivore feeding, can alter the magnitude of belowground volatile emissions as well as carbon allocation towards these volatiles. We saw no effect of mycorrhizae on any induced response, suggesting that microbial effects were unrelated to source-sink dynamics driving terpene emissions. Furthermore, the results suggest that even though enzyme activity responsible for root volatile synthesis is up-regulated following herbivory, the sink strength of the soil can significantly impact what is measured at the soil/atmosphere interface and thereby what enters the atmosphere. This is important as scientists may be underestimating the magnitude of belowground volatile emissions and their influence on belowground interactions due to limitations associated with current sampling techniques. These key findings are being integrated with results from a hydroxyl radical reactivity-VOC campaign and a late season litter removal experiment to offer a comprehensive mechanistic understanding of the sources and controls over soil volatile emissions, particularly during times of the year when vegetative aboveground emissions are low (leaf senescence). Ultimately, these coupled field and laboratory experiments offer insights into seasonal dynamics of volatile emissions and the mechanisms that control carbon allocation to these compounds with an eye towards improving carbon budgets, nutrient cycling, and terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗