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Results for “sensitivity analyses”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗
DOE OSTI2023

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗
NASA NTRS2012

Performance of McRAS-AC in the GEOS-5 AGCM: Part 1, Aerosol-Activated Cloud Microphysics, Precipitation, Radiative Effects, and Circulation

A revised version of the Microphysics of clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction (McRAS-AC), including, among others, the Barahona and Nenes ice nucleation parameterization, is implemented in the GEOS-5 AGCM. Various fields from a 10-year long integration of the AGCM with McRAS-AC were compared with their counterparts from an integration of the baseline GEOS-5 AGCM, and with satellite data as observations. Generally using McRAS-AC reduced biases in cloud fields and cloud radiative effects are much better over most of the regions of the Earth. Two weaknesses are identified in the McRAS-AC runs, namely, too few cloud particles around 40S-60S, and too high cloud water path during northern hemisphere summer over the Gulf Stream and North Pacific. Sensitivity analyses showed that these biases potentially originated from biases in the aerosol input. The first bias is largely eliminated in a sensitivity test using 50% smaller aerosol particles, while the second bias is much reduced when interactive aerosol chemistry was turned on. The main drawback of McRAS-AC is dearth of low-level marine stratus clouds, probably due to lack of dry-convection, not yet implemented into the cloud scheme. Despite these biases, McRAS-AC does simulate realistic clouds and their optical properties that can improve with better aerosol-input and thereby has the potential to be a valuable tool for climate modeling research because of its aerosol indirect effect simulation capabilities involving prediction of cloud particle number concentration and effective particle size for both convective and stratiform clouds is quite realistic.

Sud, Y. C.↗
DOE OSTI2026

Improved measurements of the TeV-PeV extragalactic neutrino spectrum from joint analyses of IceCube tracks and cascades

The IceCube South Pole Neutrino Observatory has discovered the presence of a diffuse astrophysical neutrino flux at energies of TeV and beyond using neutrino induced muon tracks and cascade events from neutrino interactions. Here, we present two analyses sensitive to neutrino events in the energy range 1 TeV to 10 PeV, using more than 10 years of IceCube data. Both analyses consistently reject a neutrino spectrum following a single power-law with a significance of > 4⁢𝜎 in favor of a broken power law. We describe the methods implemented in the two analyses, the spectral constraints obtained, and the validation of the robustness of the results. Additionally, we report the detection of a muon neutrino in the medium energy starting events sample, or MESE, with an energy of 11.4$^{+2.46}_{−2.53}$ PeV, the highest energy neutrino observed by IceCube to date. The results presented here show insights into the spectral shape of astrophysical neutrinos, which has important implications for inferring their production processes in a multimessenger picture.

astroparticles↗
NASA NTRS1982

Sensitivity analysis as an aid in modelling and control of (poorly-defined) ecological systems

A literature review of the use of sensitivity analyses in modelling nonlinear, ill-defined systems, such as ecological interactions is presented. Discussions of previous work, and a proposed scheme for generalized sensitivity analysis applicable to ill-defined systems are included. This scheme considers classes of mathematical models, problem-defining behavior, analysis procedures (especially the use of Monte-Carlo methods), sensitivity ranking of parameters, and extension to control system design.

Hornberger, G. M.↗
NASA NTRS2006

Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design

The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.

Kuguoglu, Latife↗
NASA NTRS1998

Thermal Characterization of a Direct Gain Solar Thermal Engine

A thermal/fluids analysis of a direct gain solar thermal upper stage engine is presented and the results are discussed. The engine has been designed and constructed at the NASA Marshall Space Flight Center for ground testing in a facility that can provide about 10 kilowatts of concentrated solar energy to the engine. The engine transfers that energy to a coolant (hydrogen) that is heated and accelerated through a nozzle to produce thrust. For the nominal design values and a hydrogen flowrate of 2 lb/hr., the results of the analysis show that the hydrogen temperature in the chamber (nozzle entrance) reaches about 3800 F after 30 minutes of heating and about 3850 F at steady-state (slightly below the desired design temperature of about 4100 F). Sensitivity analyses showed these results to be relatively insensitive to the values used for the absorber surface infrared emissivity and the convection coefficient within the cooling ducts but very sensitive to the hydrogen flowrate. Decreasing the hydrogen flowrate to 1 lb/hr. increases the hydrogen steady-state chamber temperature to about 4700 F, but also causes an undesirable decrease in thrust.

Alexander, Reginald A.↗
NASA NTRS1999

Thermal Characterization of a Direct Gain Solar Thermal Engine

A thermal/fluids analysis of a direct gain solar thermal upper stage engine is presented and the results are discussed. The engine was designed and constructed at the NASA Marshall Space Flight Center for ground testing in a facility that can provide about 10 kilowatts of concentrated solar energy to the engine. The engine transfers energy to a coolant (hydrogen) that is heated and accelerated through a nozzle to produce thrust. For the nominal design values and a hydrogen flowrate of 2 lb./hr., the results of the analysis show that the hydrogen temperature in the chamber (nozzle entrance) reaches about 3800 F after 30 minutes of heating and about 3850 F at steady-state (slightly below the desired design temperature of about 4100 F. Sensitivity analyses showed these results to be relatively insensitive to the values used for the absorber surface infrared emissivity and the convection coefficient within the cooling ducts but very sensitive to the hydrogen flowrate. Decreasing the hydrogen flowrate to 1 lb./hr. increases the hydrogen steady-state chamber temperature to about 4700 F, but also of course causes a decrease in thrust.

Alexander, Reginald A.↗
DOE OSTI2020

BASS: An R Package for Fitting and Performing Sensitivity Analysis of Bayesian Adaptive Spline Surfaces

In this work, we present the R package BASS as a tool for nonparametric regression. The primary focus of the package is fitting fully Bayesian adaptive spline surface (BASS) models and performing global sensitivity analyses of these models. The BASS framework is similar to that of Bayesian multivariate adaptive regression splines (BMARS) from Denison, Mallick, and Smith (1998), but with many added features. The software is built to efficiently handle significant amounts of data with many continuous or categorical predictors and with functional response. Under our Bayesian framework, most priors are automatic but these can be modified by the user to focus on parsimony and the avoidance of overfitting. If directed to do so, the software uses parallel tempering to improve the reversible jump Markov chain Monte Carlo (RJMCMC) methods used to perform inference. We discuss the implementation of these features and present the performance of BASS in a number of analyses of simulated and real data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

The importance of properties in modeling

Casting and welding of superalloys, stainless steel and titanium alloys are processes which can be improved through modeling of heat flow, fluid flow, residual stress development, and microstructural evolution. These simulations require inputs of thermophysical data, some of which involves the partially or totally liquid state. In particular, these processes involve melting, flow in the liquid, and solidification. Modeling of such processes can lead to an improved understanding of defects such as shrinkage, inclusions, cracks, incomplete filling (or penetration), macrosegregation, improper grain structure, and deviations from dimensional specifications. Effective modeling can shorten process development time and improve quality. An approach to these problems is to develop efficient models; validate through correlations with thermal, distortion, and microstructural data; run parametric studies; extract knowledge based rules; and apply to adaptive closed loop control systems. With the appropriate pre- and post-processing, such analyses can be made 'user friendly'. This would include graphical user interfaces as well as realistic images and color maps. In such form, these models can be used for sensitivity analyses, which are useful in defining appropriate sensors and in the development of control strategies. Such modeling can be done at several levels, e.g., the MARO level, modeling large scale phenomena such as heat and fluid flow or material deformation; the MICRO level, modeling the development of dendrites, grains or precipitates; or at the NANO level, modeling point defects, dislocations, stacking faults, etc. There are many computational issues associated with these simulations, e.g. computational efficiency and accuracy. In addition, there are many materials issues, not the least of which is the availability of accurate high temperature thermophysical data for complex alloys. This would include latent heat of fusion, temperature dependent heat capacity and thermal conductivity (for liquid and solid), viscosity, surface tension, thermal expansion, mechanical properties, etc. Preliminary data is frequently gathered from the literature; however, this is often not available for modern alloys. If additional data are required, measurements can be used; however, these are costly, time consuming and can be erroneous due to a lack of testing standards or impure materials. Microstructural predictors can be extracted from thermal information, e.g. cooling rate and thermal gradient; the prediction of microstructure is dependent on solidus and liquidus temperature, mushy zone permeability, the solidification curve, volume changes, phase transformations, alloying effects (such as surface tension or viscosity), mold/metal reactions, metal/environment reactions, etc. Defect maps may be needed to predict the onset of shrinkage, hot cracking or 'freckling'. Constants may be needed for stress relaxation, dendrite coarsening, vaporization, etc. Visualization was used as a tool to better comprehend complex data sets associated with the analysis of directional solidification (including crystal growth) and welding. Examples include not only isotherms, but also cooling rate, growth rate and thermal gradient. The latter two are not single valued scalars, but rather time and space dependent vector fields. Efficient models were developed for both casting and welding to predict heat flow and the relationship to dendrite and grain growth. These codes include many of the non-linear effects, e.g. radiation, which dominate these processes. The home-built FDM code(s) were designed to be useful not only to the scientist, but also to the process engineer. Special output can be requested to compare directly to experimental data. Visualization procedures were developed to visualize critical results, e.g. fusion zone width at the surface opposite that where the arc is applied ('penetration'). Both elaborate and simplified distortion analyses were carried out. It is clear that extensive mechanical property data are critical in order to accurately predict residual stress patterns. A scheme is currently being developed to integrate these modeling tools into a set of control algorithms; however, the success of this approach is critically dependent on the availability of accurate high temperature thermophysical data.

Giamei, A. F.↗
DOE OSTI2025

Investigation of Main Bearing Fatigue Estimate Sensitivity to Synthetic Turbulence Models Using a Novel Drivetrain Model Implemented in OpenFAST

ABSTRACT A coupled medium‐fidelity drivetrain model is developed and implemented in OpenFAST for a 10‐MW land‐based reference turbine. The implementation is verified against a fully coupled multibody wind turbine model, including a detailed drivetrain. The new model can simultaneously and accurately estimate main bearing loads and represent elastic bending of the drivetrain. It has low computational cost and is useful for early design phases, sensitivity analyses and complex systems like wind farms (where computational expense must be expended elsewhere). Here, the model is implemented for a monopile offshore wind turbine and used to investigate the sensitivity of main bearing basic rating life to different synthetic turbulence models. Large‐eddy simulations (LES) targeting stable, neutral, and unstable atmospheric conditions at below‐, near‐ and above‐rated wind speeds are used as a reference. The turbulence models recommended by the International Electrotechnical Commission, the Mann spectral tensor model, and the Kaimal spectral model with exponential coherence are fitted to the LES data. Additionally, a constrained turbulence generator, PyConTurb (short for Python Constrained Turbulence ), based on LES data, is applied in the aero‐hydro‐servo‐elastic simulations. Taking PyConTurb as the baseline, the Kaimal model significantly underestimates fatigue of the downwind main bearing, with between 10% and 40% less damage. The Mann model also underestimates the downwind main bearing fatigue by up to 30%. The upwind main bearing damage is driven by mean loads, and differences between models are less significant, although the trends are similar. Reasons for these discrepancies are investigated and attributed to differences in spatial and temporal variations among the turbulence models.

17 WIND ENERGY↗
NASA NTRS2017

Ablation and Heating During Atmospheric Entry and Its Effect on Airburst Risk

Large meteoroids and asteroids entering the atmosphere endure tremendous heating from the shock heated air, and thereby lose a significant fraction of their mass during atmospheric entry a process known as ablation. The predicted evolution of the asteroids mass as it passes through the atmosphere can affect both the predicted energy deposition profile relevant to an airburst event, or the residual mass that strikes the ground in the case of an impact event. This presentation is divided roughly into two parts. In the first part, an overview of traditional models for heat transfer and ablation that are historically used in the meteor physics community is presented, and the validity in the asteroid entry regime discussed. Sensitivity analyses performed using the recently developed Fragment-Cloud Model (FCM) will be presented which show illustrate the range of sizes and entry parameters for which the predicted asteroid threat is most sensitive to the models for ablation and heat transfer. The second part of the presentation shall focus on recent work done under NASAs Asteroid Threat Assessment Project (ATAP) to develop new models for heat transfer and ablation using high-fidelity numerical simulation in concert with state-of-the-art experiments. Coupled computational fluid dynamics (CFD)radiation transport simulations preformed using the state-of-the-art entry modeling tools at NASA show that, for large meteoroids and asteroids, there can significant attenuation of the heat transfer to the surface (95 in some cases) by the products of ablation. In addition to the heat transfer, new models for the material response and ablation of asteroidal material have been developed [cite]. In the current work, we present finding from recent novel experiments performed in the arc jet facility at NASA Ames, which allows us to, in part, simulate the extreme environment experienced by the asteroid during entry. Briefly, the experimental set-up was comprised of a 1.5 conical article of machined H5 chondrite, which was exposed to a high-enthalpy flow resulting in approximately 4 kWcm2 of heating to the surface. A still frame capture from high-speed video taken during this experiment can be seen in Figure 1. In this figure, we can observe some of the major mechanisms for meteoroid ablation, such as melt flow, spallation (mechanical removal of material), and vaporization. Major findings from this, and other experiments will be discussed, as well progress on utilizing the data from the experiments to inform and develop improved models for ablation.

Asteroids↗
NASA NTRS1992

Deep-space navigation with differenced data types. Part 3: An expanded information content and sensitivity analysis

An approximate six-parameter analytic model for Earth-based differential range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, Deep Space Network station oscillator (clock/frequency) offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Quantitative results indicate that a few differenced Doppler plus ranging passes yield angular position estimates with a precision on the order of 0.1 to 0.4 micro-rad, and angular rate precision on the order of 10 to 25 x 10(exp -12) rad/sec, assuming no a priori information on the coordinate parameters. Sensitivity analyses suggest that troposphere zenith delay calibration error is the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to troposphere calibration errors than differenced range. By comparison, results computed using wideband and narrowband (delta) VLBI under similar circumstances yielded angular precisions of 0.07 to 0.4 micro-rad, and angular rate precisions of 0.5 to 1.0 x 10(exp -12) rad/sec.

Estefan, J. A.↗
NASA NTRS1999

Solar Stirling for Deep Space Applications

A study was performed to quantify the performance of solar thermal power systems for deep space planetary missions. The study incorporated projected advances in solar concentrator and energy conversion technologies. These technologies included inflatable structures, lightweight primary concentrators, high efficiency secondary concentrators, and high efficiency Stirling convertors. Analyses were performed to determine the mass and deployed area of multi-hundred watt solar thermal power systems for missions out to 40 astronomical units. Emphasis was given to system optimization, parametric sensitivity analyses, and concentrator configuration comparisons. The results indicated that solar thermal power systems are a competitive alternative to radioisotope systems out to 10 astronomical units without the cost or safety implications associated with nuclear sources.

Mason, Lee S.↗
NASA NTRS2009

Instrumentation and Performance Analysis Plans for the HIFiRE Flight 2 Experiment

Supersonic combustion performance of a bi-component gaseous hydrocarbon fuel mixture is one of the primary aspects under investigation in the HIFiRE Flight 2 experiment. In-flight instrumentation and post-test analyses will be two key elements used to determine the combustion performance. Pre-flight computational fluid dynamics (CFD) analyses provide valuable information that can be used to optimize the placement of a constrained set of wall pressure instrumentation in the experiment. The simulations also allow pre-flight assessments of performance sensitivities leading to estimates of overall uncertainty in the determination of combustion efficiency. Based on the pre-flight CFD results, 128 wall pressure sensors have been located throughout the isolator/combustor flowpath to minimize the error in determining the wall pressure force at Mach 8 flight conditions. Also, sensitivity analyses show that mass capture and combustor exit stream thrust are the two primary contributors to uncertainty in combustion efficiency.

Gruber, Mark↗
DOE OSTI2024

Km‐Scale Simulations of Mesoscale Convective Systems Over South America—A Feature Tracker Intercomparison

Mesoscale convective systems (MCSs) are clusters of thunderstorms that are important in Earth's water and energy cycle. Additionally, they are responsible for extreme events such as large hail, strong winds, and extreme precipitation. Automated object-based analyses that track MCSs have become popular since they allow us to identify and follow MCSs over their entire life cycle in a Lagrangian framework. This rise in popularity was accompanied by an increasing number of MCS tracking algorithms, however, little is known about how sensitive analyses are concerning the MCS tracker formulation. Here, we assess differences between six MCS tracking algorithms on South American MCS characteristics and evaluate MCSs in kilometer-scale simulations with observational-based MCSs over 3 years. All trackers are run with a common set of MCS classification criteria to isolate tracker formulation differences. The tracker formulation substantially impacts MCS characteristics such as frequency, size, duration, and contribution to total precipitation. The evaluation of simulated MCS characteristics is less sensitive to the tracker formulation and all trackers agree that the model can capture MCS characteristics well across different South American climate zones. Dominant sources of uncertainty are the segmentation of cloud systems in space and time and the treatment of how MCSs are linked in time. Our results highlight that comparing MCS analyses that use different tracking algorithms is challenging. We provide general guidelines on how MCS characteristics compare between trackers to facilitate a more robust assessment of MCS statistics in future studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Peatland hydrology across scale: a probabilistic framework for confronting variability, heterogeneity, and uncertainty (Final Report)

Our project aimed to guide the representations of peatland hydrology and water-carbon feedbacks within Earth System Models, by improving process understanding and developing parsimonious models that elucidate the effects of hydroclimatic variability and spatial heterogeneity. Our research questions centered on the three key drivers of peatland hydrology: (1) seasonal and interannual hydroclimatic fluctuations, (2) spatial heterogeneity of peatland microtopography, and (3) hydrological connectivity across landscape units within a peatland watershed. Our analyses and model testing used existing long-term datasets within the Marcell Experimental Forest (MEF), with new data collected whenever necessary. To date, we have demonstrated the strong influence of water table elevations on the temperature sensitivity of CH 4 emissions, using a newly developed eddy covariance dataset spanning eleven years at MEF. Specifically, higher water tables dampen the increase in CH 4 emissions in the spring as well as their decrease in the fall, resulting in hysteresis. These results imply that any hydroclimatological changes in peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if soil temperature remains unchanged. To further investigate water table elevation change within the peatland microtopography, we installed automated water table gauges across four bog-forest transects (the “lagg”) in two peatland watersheds at MEF, which are hotspots of intense biogeochemical activity. These measurements will give us new information about the extent of lagg expansion and contraction during snowmelt and high intensity rainfall events, as well as the directionality of water and nutrient flow into the bog from the surrounding forests. Finally, we investigated the hydrological connectivity across the peatland watershed complex during early spring – a critical period where water table is elevated from snowmelt – using extended hydrological records from MEF (e.g., snow and frost depths, water table elevations, streamflow). The importance of thermal and wintertime processes within the Energy Exascale Earth System Model (E3SM) was determined through sensitivity analyses. Results from data analyses show that (i) streamflow has decreased over decades likely due to increased evapotranspiration rates (despite no detectable trends in precipitation), (ii) spring streamflow generation is controlled by a sequence of fill-and-spill pathways from the snowpack to the stream through peatland water stores, and (iii) frost depth is a key explanatory variable for the timing and magnitude of streamflow. These results suggest that frost plays an important role in connecting surface water storage in peatlands to stream outlets, and that the hydrological connectivity across the peatland watershed complex can mediate the sensitivity of hydrological responses to climate variations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Preindustrial to Present-Day Changes in Tropospheric Hydroxyl Radical and Methane Lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

We have analysed time-slice simulations from 17 global models, participating in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), to explore changes in present-day (2000) hydroxyl radical (OH) concentration and methane (CH4) lifetime relative to preindustrial times (1850) and to 1980. A comparison of modeled and observation-derived methane and methyl chloroform lifetimes suggests that the present-day global multi-model mean OH concentration is overestimated by 5 to 10% but is within the range of uncertainties. The models consistently simulate higher OH concentrations in the Northern Hemisphere (NH) compared with the Southern Hemisphere (SH) for the present-day (2000; inter-hemispheric ratios of 1.13 to 1.42), in contrast to observation-based approaches which generally indicate higher OH in the SH although uncertainties are large. Evaluation of simulated carbon monoxide (CO) concentrations, the primary sink for OH, against ground-based and satellite observations suggests low biases in the NH that may contribute to the high north–south OH asymmetry in the models. The models vary widely in their regional distribution of present-day OH concentrations (up to 34%). Despite large regional changes, the multi-model global mean (mass-weighted) OH concentration changes little over the past 150 yr, due to concurrent increases in factors that enhance OH (humidity, tropospheric ozone, nitrogen oxide (NOx) emissions, and UV radiation due to decreases in stratospheric ozone), compensated by increases in OH sinks (methane abundance, carbon monoxide and non-methane volatile organic carbon (NMVOC) emissions). The large inter-model diversity in the sign and magnitude of preindustrial to present-day OH changes (ranging from a decrease of 12.7% to an increase of 14.6%) indicate that uncertainty remains in our understanding of the long-term trends in OH and methane lifetime. We show that this diversity is largely explained by the different ratio of the change in global mean tropospheric CO and NOx burdens (Delta CO/Delta NOx, approximately represents changes in OH sinks versus changes in OH sources) in the models, pointing to a need for better constraints on natural precursor emissions and on the chemical mechanisms in the current generation of chemistry-climate models. For the 1980 to 2000 period, we find that climate warming and a slight increase in mean OH (3.5 +/- 2.2%) leads to a 4.3 +/- 1.9% decrease in the methane lifetime. Analysing sensitivity simulations performed by 10 models, we find that preindustrial to present-day climate change decreased the methane lifetime by about four months, representing a negative feedback on the climate system. Further, we analysed attribution experiments performed by a subset of models relative to 2000 conditions with only one precursor at a time set to 1860 levels. We find that global mean OH increased by 46.4 +/- 12.2% in response to preindustrial to present-day anthropogenic NOx emission increases, and decreased by 17.3 +/-2.3%, 7.6 +/- 1.5%, and 3.1 +/- 3.0% due to methane burden, and anthropogenic CO, and NMVOC emissions increases, respectively.

nitrogen oxides↗