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DOE OSTI2020

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

South Atlantic Anomaly Entry and Exit as Measured by the X-Ray Timing Explorer

The Rossi X-ray Timing Explorer (RXTE) carries instruments that must switch off high voltages (HV) when passing through the South Atlantic Anomaly (SAA). The High Energy X-ray Timing Experiment (HEXTE) contains a particle monitor that detects the increased particle flux associated with the SAA and autonomously reduces its voltage. The Proportional Counter Array (PCA) relies on uplinked predictions of SAA entry/exit times based on ephemeris data provided by the Flight Dynamics Facility. A third instrument, the All-Sky Monitor (ASM) also uses a predicted SAA model to reduce voltage when passing through the SAA. Data collected from the HEXTE particle monitor, as well as other instrument readings near the times of SAA entry/exit offer the potential for refining models of the boundaries of the SAA. The SAA has an increased particle flux which causes high rates of detection in the RXTE instruments designed to observe x-rays. The high counting rates could degrade the PCA if HV is not reduced during SAA passages. On the other hand, PCA downtime can be minimized and the science return can be optimized by having the best possible model of the SAA boundary. Thus, the PCA team planned an extensive effort during in-orbit checkout to utilize both the HEXTE particle monitor data and instrument counting rates to refine the model of the SAA boundary. The times of SAA entry and exit are compared with the definitive epemeris to determine the precise location (latitude and longitude) of the SAA boundary. Over time, the SAA and its perimeter were mapped. The RXTE Science Operations Center is continuously working to feed back the results of this effort into the science scheduling process, improving the SAA model as it affects the RXTE instruments, thus obtaining more accurate estimates of the SAA entry/exit times.

Smith, Evan↗

NASA NTRS1994

Hot-Gas-Slide and Coolant-Side Heat Transfer in Liquid Rocket Engine Combustors

The objectives of this article are to develop a multidisciplinary, computational methodology to predict the hot-gas-side and coolant-side heat transfer in film cooling assisted, regeneratively cooled liquid rocket engine combustors, and to use it in parametric studies to recommend optimized design of the coolant channels for a developmental combustor. An integrated numerical model which incorporates computational fluid dynamics (CFD) for the hot-gas thermal environment, and thermal analysis for the liner and coolant channels, was developed. This integrated CFD/thermal model was validated by comparing predicted heat fluxes with those of hot-firing test and industrial design methods for a 40-k calorimeter thrust chamber and the Space Shuttle Main Engine main combustion chamber. Parametric studies were performed for the advanced main combustion chamber to find a strategy for a proposed coolant channel design.

Ten-see Wang↗

NASA NTRS1998

Burner Emissions Associated with Lobed and Non-Lobed Fuel Injectors

The present experimental study examines NO(sub x), and CO emissions associated with three alternative fuel-injector geometries. These injectors mix fuel and air and strain their interfaces to differing extents and thus create different local equivalence ratios within flow regions upstream of flame ignition and stabilization. Two of the devices studied are lobed fuel injectors, in which molecular mixing of reactants is associated with streamwise vorticity generation, while the third one is a non-lobed fuel injector. Results show that rapid mixing allowed both lobed injector geometries to produce very lean premixed flame structures, with a lower achievable turn-down or fuel/air mass flux ratio than for the analogous non-lobed injector, which largely, produced distinct diffusion flames. All three injectors exhibited some level of sooting near walls and in the far-field region, with the non-lobed injector sooting to the greatest extent. At low fuel flow rates, in which the lobed injectors created locally very lean premixed conditions, there resulted lower NO(sub x) emissions as compared with non-lobed injector emissions. Yet at higher fuel-air mass flux ratios, NO(sub x) emissions from the lobed injectors were actually higher than for the nonlobed injector, likely due to reduced sooting and hence reduced radiative heat losses associated with enhanced mixing. For both lobed injector geometries examined here, CO emissions became high for low values of the fuel/air mass flux ratio, again consistent with locally premixed combustion behavior, despite the fact that fuel was injected separately from air directly into the burner test section. The present study demonstrates that, for fuel-air mixing enhancement devices, control of the local equivalence ratio is critical in order to optimize burner emissions.

Mitchell, M. G.↗

NASA NTRS2002

Toward a Comprehensive Carbon Budget for North America: Potential Applications of Adjoint Methods with Diverse Datasets

A detailed mechanistic understanding of the sources and sinks of CO2 will be required to reliably predict future COS levels and climate. A commonly used technique for deriving information about CO2 exchange with surface reservoirs is to solve an "inverse problem," where CO2 observations are used with an atmospheric transport model to find the optimal distribution of sources and sinks. Synthesis inversion methods are powerful tools for addressing this question, but the results are disturbingly sensitive to the details of the calculation. Studies done using different atmospheric transport models and combinations of surface station data have produced substantially different distributions of surface fluxes. Adjoint methods are now being developed that will more effectively incorporate diverse datasets in estimates of surface fluxes of CO2. In an adjoint framework, it will be possible to combine CO2 concentration data from long-term surface monitoring stations with data from intensive field campaigns and with proposed future satellite observations. A major advantage of the adjoint approach is that meteorological and surface data, as well as data for other atmospheric constituents and pollutants can be efficiently included in addition to observations of CO2 mixing ratios. This presentation will provide an overview of potentially useful datasets for carbon cycle research in general with an emphasis on planning for the North American Carbon Project. Areas of overlap with ongoing and proposed work on air quality/air pollution issues will be highlighted.

Andrews, A.↗

NASA NTRS2004

Discontinuous Spectral Difference Method for Conservation Laws on Unstructured Grids

A new, high-order, conservative, and efficient discontinuous spectral finite difference (SD) method for conservation laws on unstructured grids is developed. The concept of discontinuous and high-order local representations to achieve conservation and high accuracy is utilized in a manner similar to the Discontinuous Galerkin (DG) and the Spectral Volume (SV) methods, but while these methods are based on the integrated forms of the equations, the new method is based on the differential form to attain a simpler formulation and higher efficiency. Conventional unstructured finite-difference and finite-volume methods require data reconstruction based on the least-squares formulation using neighboring point or cell data. Since each unknown employs a different stencil, one must repeat the least-squares inversion for every point or cell at each time step, or to store the inversion coefficients. In a high-order, three-dimensional computation, the former would involve impractically large CPU time, while for the latter the memory requirement becomes prohibitive. In addition, the finite-difference method does not satisfy the integral conservation in general. By contrast, the DG and SV methods employ a local, universal reconstruction of a given order of accuracy in each cell in terms of internally defined conservative unknowns. Since the solution is discontinuous across cell boundaries, a Riemann solver is necessary to evaluate boundary flux terms and maintain conservation. In the DG method, a Galerkin finite-element method is employed to update the nodal unknowns within each cell. This requires the inversion of a mass matrix, and the use of quadratures of twice the order of accuracy of the reconstruction to evaluate the surface integrals and additional volume integrals for nonlinear flux functions. In the SV method, the integral conservation law is used to update volume averages over subcells defined by a geometrically similar partition of each grid cell. As the order of accuracy increases, the partitioning for 3D requires the introduction of a large number of parameters, whose optimization to achieve convergence becomes increasingly more difficult. Also, the number of interior facets required to subdivide non-planar faces, and the additional increase in the number of quadrature points for each facet, increases the computational cost greatly.

Liu, Yen↗

NASA NTRS2004

An Adjoint-Based Analysis of the Sampling Footprints of Tall Tower, Aircraft and Potential Future Lidar Observations of CO2

A detailed mechanistic understanding of the sources and sinks of CO2 will be required to reliably predict future CO2 levels and climate. A commonly used technique for deriving information about CO2 exchange with surface reservoirs is to solve an 'inverse problem', where CO2 observations are used with an atmospheric transport model to find the optimal distribution of sources and sinks. Synthesis inversion methods are powerful tools for addressing this question, but the results are disturbingly sensitive to the details of the calculation. Studies done using different atmospheric transport models and combinations of surface station data have produced substantially different distributions of surface fluxes. Adjoint methods are now being developed that will more effectively incorporate diverse datasets in estimates of surface fluxes of CO2. In an adjoint framework, it will be possible to combine CO2 concentration data from longterm surface and aircraft monitoring stations with data from intensive field campaigns and with proposed future satellite observations. We have recently developed an adjoint for the GSFC 3-D Parameterized Chemistry and Transport Model (PCTM). Here, we will present results from a PCTM Adjoint study comparing the sampling footprints of tall tower, aircraft and potential future lidar observations of CO2. The vertical resolution and extent of the profiles and the observation frequency will be considered for several sites in North America.

Andrews, Arlyn↗

NASA NTRS2006

Computational Analysis of the Effect of Porosity on Shock Cell Strength at Cruise

A computational flow field analysis is presented of the effect of core cowl porosity on shock cell strength for a modern separate flow nozzle at cruise conditions. The goal of this study was to identify the primary physical mechanisms by which the application of porosity can reduce shock cell strength and hence the broadband shock associated noise. The flow is simulated by solving the asymptotically steady, compressible, Reynoldsaveraged Navier-Stokes equations on a structured grid using an implicit, up-wind, flux-difference splitting finite volume scheme. The standard two-equation k - epsilon turbulence model with a linear stress representation is used with the addition of a eddy viscosity dependence on total temperature gradient normalized by local turbulence length scale. Specific issues addressed in this study were the optimal area required to weaken a shock impinging on the core cowl surface and the optimal level of porosity and placement of porous areas for reduction of the overall shock cell strength downstream. Two configurations of porosity were found to reduce downstream shock strength by approximately 50%.

Massey, Steven J.↗

NASA NTRS2008

Ground-based SMART-COMMIT Measurements for Studying Aerosol and Cloud Properties

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.

Tsay, Si-Chee↗

DOE OSTI2022

An improved representation of the relationship between photosynthesis and stomatal conductance leads to more stable estimation of conductance parameters and improves the goodness-of-fit across diverse data sets

Stomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO 2 between the leaf and the atmosphere. Representation of stomatal conductance (g sw ) is therefore an essential component of models that seek to simulate water and CO 2 exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO 2 concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g sw and photosynthetic CO 2 assimilation (A). However, measurement of leaf-level g sw response curves to changes in A are rare, particularly in the tropics, resulting in only limited data to evaluate this key assumption. Here, we measured the response of g sw and A to irradiance in six tropical species at different leaf phenological stages. We showed that the relationship between g sw and A was not linear, challenging the key assumption upon which optimality theory is based-that the marginal cost of water gain is constant. Our data showed that increasing A resulted in a small increase in g sw at low irradiance, but a much larger increase at high irradiance. We reformulated the popular Unified Stomatal Optimization (USO) model to account for this phenomenon and to enable consistent estimation of the key conductance parameters g 0 and g 1 . Our modification of the USO model improved the goodness-of-fit and reduced bias, enabling robust estimation of conductance parameters at any irradiance. In addition, our modification revealed previously undetectable relationships between the stomatal slope parameter g 1 and other leaf traits. We also observed nonlinear behavior between A and g sw in independent datasets that included data collected from attached and detached leaves, and from plants grown at elevated CO 2 concentration. We propose that this empirical modification of the USO model can improve the measurement of g sw parameters and the estimation of plant and ecosystem-scale water and CO 2 fluxes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

Composite propulsion feedlines for cryogenic space vehicles, volume 1

Thin metallic liners that provide leak-free service in cryogenic propulsion systems are overwrapped with a glass-fiber composite that provides strength and protection from handling damage. The resultant tube is lightweight, strong and has a very low thermal flux. Several styles of tubing ranging from 5 to 38 cm in diameter and up to 305 cm long were fabricated and tested at operating temperatures from 294 to 21 K and operating pressures up to 259 N/sq cm. The primary objective for the smaller sizes was thermal performance optimization of the propulsion system while the primary objective of the larger sizes was weight optimization and to prove fabricability. All major program objectives were met resulting in a design concept that is adaptable to a wide range of aerospace vehicle requirements. Major items of development included: bonding large diameter aluminum end fittings to the thin Inconel liner; fabrication of a 38 cm diameter tube from 0.008 cm thick Inconel; and evaluation of tubing which provides essentially zero quality propellant in a very short period of time resulting in a lower mass of propellant expended in chilldown.

Hall, C. A.↗

NASA NTRS1979

The effect of nonuniform wind shear on the intensification and reflection of mountain waves

A study is made of the intensification and reflection of mountain waves when the shear of the basic wind profile is nonuniform. A two-layer atmospheric model is treated, and the wind profile in the troposphere is assumed to be parabolic. The Scorer parameter includes the wind profile curvature term, which may not be neglected if the Richardson number Ri is finite. When Ri is finite, the optimal phase difference across the troposphere for maximum surface velocity intensifications is found to be slightly greater than Pi. As Ri increases, the optimal phase difference decreases with Ri and approaches the limiting value Pi. This implies that waves approximately reverse phase between the surface and the tropopause for maximum wave intensifications in most physically realistic atmospheric situations. The concept of Eliassen and Palm concerning the additivity of the vertical wave energy fluxes is expanded (valid at least up to the parabolic wind profile), by which the upward and downward energy transporting modes are identified.

Hyun, J. M.↗

NASA NTRS1986

Optimization of spherical facets for parabolic solar concentrators

Solar concentrator designs which employ deployable hexagonal panels are being developed for space power systems. An offset optical configuration has been developed which offers significant system level advantages over previously proposed collector designs for space applications. Optical analyses have been performed which show offset reflector intercept factors to be only slightly lower than those for symmetric reflectors with the same slope error. Fluxes on the receiver walls are asymmetric but manageable by varying the tilt angle of the receiver. Greater producibility is achieved by subdividing the hexagonal panels into triangular mirror facets of spherical contour. Optical analysis has been performed upon these to yield near-optimum sizes and radii.

White, J. E.↗

NASA NTRS1992

Numerical analysis of the hot-gas-side and coolant-side heat transfer in liquid rocket engine combustors

The objective of this paper are to develop a multidisciplinary computational methodology to predict the hot-gas-side and coolant-side heat transfer and to use it in parametric studies to recommend optimized design of the coolant channels for a regeneratively cooled liquid rocket engine combustor. An integrated numerical model which incorporates CFD for the hot-gas thermal environment, and thermal analysis for the liner and coolant channels, was developed. This integrated CFD/thermal model was validated by comparing predicted heat fluxes with those of hot-firing test and industrial design methods for a 40 k calorimeter thrust chamber and the Space Shuttle Main Engine Main Combustion Chamber. Parametric studies were performed for the Advanced Main Combustion Chamber to find a strategy for a proposed combustion chamber coolant channel design.

Wang, Ten-See↗

NASA NTRS2007

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Case, Jonathan L.↗

DOE OSTI2024

The Impact of Radiative Transfer at Reduced Spectral Resolution in Large‐Eddy Simulations of Convective Clouds

Abstract Many radiative transfer schemes approximate the spectral integration over ∼10 5 to ∼10 6 wavelengths with correlated k ‐distributions methods that typically require only 10 1 –10 2 spectral integration points ( g ‐points). The exact number of g ‐points is then chosen as an optimal balance between computational costs and accuracy, normally assessed in terms of a number of radiative quantities. How this radiative accuracy propagates to simulation accuracy, however, is not straightforward. In this study, we therefore explore the sensitivity of cloud properties in large‐eddy simulations (LES) to the accuracy of radiative fluxes and heating rates. We first generate smaller sets of g ‐points from existing k ‐distributions by repeatedly combining adjacent g ‐points while maintaining the highest possible accuracy on a chosen set of radiative metrics. Next, we perform three sets of LES with varying cloud—radiation coupling pathways, and therefore different requirements for the accuracy of the radiative transfer computations, to investigate how these smaller and thus less accurate k ‐distributions affect simulation characteristics. The decrease in radiative accuracy with 3–4 times smaller k ‐distributions results in biases in cloud properties that are relative small compared to their temporal fluctuations. These results show potential for speeding up radiative transfer computations in cloud‐resolving models by reducing the resolved spectral detail. However, more statistically converged simulations and a wider set of case studies is required to fully assess the robustness of our results.

Meteorology & Atmospheric Sciences↗

DOE OSTI2025

Thermal acclimation of stem respiration implies a weaker carbon-climate feedback

The efflux of carbon dioxide (CO2) from woody stems, a proxy for stem respiration, is a critical carbon flux from ecosystems to the atmosphere, which increases with temperature on short timescales. However, plants acclimate their respiratory response to temperature on longer timescales, potentially weakening the carbon-climate feedback. The magnitude of this acclimation is uncertain despite its importance for predicting future climate change. We develop an optimality-based theory dynamically linking stem respiration with leaf water supply to predict its thermal acclimation. We show that the theory accurately reproduces observations of spatial and seasonal change. We estimate the global value for current annual stem CO2 efflux as 27.4 ± 5.9 PgC. By 2100, incorporating thermal acclimation reduces projected stem respiration without considering acclimation by 24 to 46%, thus reducing land ecosystem carbon emissions.

Zhang, Han↗

NASA NTRS2009

Optimization of Layer Densities for Spacecraft Multilayered Insulation Systems

Numerous tests of various multilayer insulation systems have indicated that there are optimal densities for these systems. However, the only method of calculating this optimal density was by a complex physics based algorithm developed by McIntosh. In the 1970's much data were collected on the performance of these insulation systems with many different variables analyzed. All formulas generated included number of layers and layer density as geometric variables in solving for the heat flux, none of them was in a differentiable form for a single geometric variable. It was recently discovered that by converting the equations from heat flux to thermal conductivity using Fourier's Law, the equations became functions of layer density, temperatures, and material properties only. The thickness and number of layers of the blanket were merged into a layer density. These equations were then differentiated with respect to layer density. By setting the first derivative equal to zero, and solving for the layer density, the critical layer density was determined. Taking a second derivative showed that the critical layer density is a minimum in the function and thus the optimum density for minimal heat leak, this is confirmed by plotting the original function. This method was checked and validated using test data from the Multipurpose Hydrogen Testbed which was designed using McIntosh's algorithm.

Johnson, W. L.↗