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DOE OSTI2020

Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States

Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.

Cheng, Yanyan↗

NASA NTRS1994

An evaluation with the Fourier Amplitude Sensitivity Test (FAST) of which land-surface parameters are of greatest importance in atmospheric modeling

Land-surface parameterizations based on a statistical-dynamical have been suggested recently to improve the representation of the surface forcing from heterogeneous land in atmospheric models. With this approach, land-surface characteristics are prescribed by probability density functions (PDFs) rather than single 'representative' values as in 'big-leaf' parameterizations. Yet the use of many PDFs results in an increased computational burden and requires the complex problem of representing covariances between PDFs to be addressed. In this study, a sensitivity analysis of a land-surface parameterization for atmospheric modeling was performed to evaluate the surface parameters most important to the variability of surface heat fluxes. The Fourier amplitude sensitivity test (FAST) used for this analysis determines the relative contribution of individual input parameters to the variance of energy fluxes resulting from a heterogeneous surface. By simultaneously varying all parameters according to their individual probability density functions, the number of computations needed is very much reduced by this technique. This analysis demonstrates that most of the variability of surface heat fluxes may be described by the distributions of relative stomatal conductance and surface roughness. Thus, the statistical-dynamical approach may be simplified by the use of only these two probability density functions.

Collins, Dan C.↗

DOE OSTI2023

Quantifying model prediction sensitivity to model-form uncertainty

Computational and mathematical models are essential to understanding complex systems and phenomena. However, when developing such models, limited knowledge and/or resources necessitates the use of simplifying assumptions. It is therefore crucial to quantify the impact of such simplifying assumptions on the reliability and accuracy of resulting model predictions. This work develops a first-of-its-kind approach to quantify the impact of physics modeling assumptions on predictions. Here, we leverage the emerging field of model-form uncertainty (MFU) representations, which are parameterized modifications to modeling assumptions, in combination with grouped Sobol’ indices to quantitatively measure an assumption’s importance. Specifically, we compute the grouped Sobol’ index for the MFU representation’s parameters as a single importance measure of the assumption for which the MFU representation characterizes uncertainty. To ensure this approach is robust to the subjective choice of how to parameterize a MFU representation, we establish bounds for the difference between sensitivity results for two different MFU representations based on differences in model prediction statistics. The capabilities associated with this approach are demonstrated on three exemplar problems: an upscaled subsurface contaminant transport problem, ablation modeling for hypersonic flight, and nuclear waste repository modeling. We found that our grouped approach is able to assess the impact of modeling assumptions on predictions and offers computational advantages over classical Sobol’ index computation while providing more interpretable results.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Overview of the HI-SCALE Field Campaign: A New Perspective on Shallow Convective Clouds

Shallow convective clouds are common, occurring over many areas of the world, and are an important component in the atmospheric radiation budget. In addition to synoptic and mesoscale meteorological conditions, land-atmosphere interactions and aerosol-radiation-cloud interactions can influence the formation of shallow clouds and their properties. However, these processes exhibit large spatial and temporal variability and occur at the sub-grid scale for all climate and operational forecast models and must be represented by parameterizations. Uncertainties in shallow cloud parameterization predictions arise from many sources, including insufficient coincident data needed to adequately represent the coupling of cloud macrophysical and microphysical properties with inhomogeneity in the surface layer, boundary layer, and aerosol properties. Predictions in the transition of shallow to deep convection and the onset of precipitation are also affected by errors in simulated shallow clouds. Coincident data is a key factor needed to achieve a more complete understanding of the lifecycle of shallow convective clouds and to develop improved model parameterizations. To address these issues, the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the Atmospheric Radiation and Measurement (ARM) Southern Great Plains site in north-central Oklahoma during 2016. We describe the scientific objectives of HI-SCALE as well as the experimental approach, the overall weather conditions during the campaign, and preliminary findings from the measurements. Finally, we discuss the remaining scientific gaps in our understanding of shallow clouds that can be addressed by analysis and modeling studies that use HI-SCALE data including: the effects of heterogeneous land-use, vegetation, and soil moisture conditions on boundary layer mixing and consequently cloud formation; factors that contribute to the transition of shallow to deep convection; the role of cloud population on

Fast, Jerome D.↗

NASA NTRS1992

Relaxed Arakawa-Schubert - A parameterization of moist convection for general circulation models

A simple implementation of the Arakawa and Schubert (1974) cumulus parameterization is presented. The major simplification made is to 'relax' the state toward equilibrium each time the parameterization is invoked, rather than requiring that the final state be balanced, as in the original Arakawa-Schubert implementation. This relaxed Arakawa-Schubert (RAS) scheme is evaluated in off-line tests using the Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) Phase III data. The results show that RAS is equivalent to the standard implementation of Arakawa-Schubert but is more economical and simpler to code. RAS also avoids the ill-posed problem that occurs in Arakawa-Schubert as a result of having to solve for a balanced state.

Moorthi, Shrinivas↗

NASA NTRS2015

Organic Aerosol Volatility Parameterizations and Their Impact on Atmospheric Composition and Climate

Despite their importance and ubiquity in the atmosphere, organic aerosols are still very poorly parameterized in global models. This can be explained by two reasons: first, a very large number of unconstrained parameters are involved in accurate parameterizations, and second, a detailed description of semi-volatile organics is computationally very expensive. Even organic aerosol properties that are known to play a major role in the atmosphere, namely volatility and aging, are poorly resolved in global models, if at all. Studies with different models and different parameterizations have not been conclusive on whether the additional complexity improves model simulations, but the added diversity of the different host models used adds an unnecessary degree of variability in the evaluation of results that obscures solid conclusions. Aerosol microphysics do not significantly alter the mean OA vertical profile or comparison with surface measurements. This might not be the case for semi-volatile OA with microphysics.

Aerosols↗

NASA NTRS2019

Extratropical Cyclone Clouds in the GFDL Climate Model: Diagnosing Biases and the Associated Causes

The clouds in southern hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of AM4, a model GFDL will utilize for CMIP6, the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low-levels (again by differing amounts), especially in the post-cold frontal (PCF) region, when compared to observations. Focusing on only the models, their differences in high and mid-level clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

Catherine M Naud↗

NASA NTRS2015

Organic Aerosol Volatility Parameterizations and Their Impact on Atmospheric Composition and Climate

Volatility↗

NASA NTRS2004

An Empirical Cumulus Parameterization Scheme for a Global Spectral Model

Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This also suggests that in the absence of explicit models for convection, the proposed statistical scheme improves the modeling of the vertical distribution of heating and moistening in areas of deep convection.

Rajendran, K.↗

DOE OSTI2014

Integrating Cloud Processes in the Community Atmosphere Model, Version 5.

This paper provides a description on the parameterizations of global cloud system in CAM5. Compared to the previous versions, CAM5 cloud parameterization has the following unique characteristics: (1) a transparent cloud macrophysical structure that has horizontally non-overlapped deep cumulus, shallow cumulus and stratus in each grid layer, each of which has own cloud fraction, mass and number concentrations of cloud liquid droplets and ice crystals, (2) stratus-radiation-turbulence interaction that allows CAM5 to simulate marine stratocumulus solely from grid-mean RH without relying on the stability-based empirical empty stratus, (3) prognostic treatment of the number concentrations of stratus liquid droplets and ice crystals with activated aerosols and detrained in-cumulus condensates as the main sources and evaporation-sedimentation-precipitation of stratus condensate as the main sinks, and (4) radiatively active cumulus. By imposing consistency between diagnosed stratus fraction and prognosed stratus condensate, CAM5 is free from empty or highly-dense stratus at the end of stratus macrophysics. CAM5 also prognoses mass and number concentrations of various aerosol species. Thanks to the aerosol activation and the parameterizations of the radiation and stratiform precipitation production as a function of the droplet size, CAM5 simulates various aerosol indirect effects associated with stratus as well as direct effects, i.e., aerosol controls both the radiative and hydrological budgets. Detailed analysis of various simulations revealed that CAM5 is much better than CAM3/4 in the global performance as well as the physical formulation. However, several problems were also identifed, which can be attributed to inappropriate regional tuning, inconsistency between various physics parameterizations, and incomplete model physics. Continuous efforts are going on to further improve CAM5.

CAM5↗

DOE OSTI2018

Advanced Tool for Computer Aided Battery Engineering (SNL)

This project aims to provide experimental support, including support for validation and parameterization, for mechanical failure modeling work as part of DOE's Computer Aided Engineering for Electric-Drive Vehicle Batteries (CAEBAT) program. This work involves mechanical deformation testing on both charged and discharged cells, including abusive mechanical testing leading to battery failure. The mechanical data generated is provided to the modeling teams to provide empirical parameterization as well as validation for newly developed models. Testing fully charged cells and packs (abusive battery testing) also allows for a better understanding of what conditions are most likely to lead to a potentially hazardous thermal runaway event.

25 ENERGY STORAGE↗

DOE OSTI2020

Characterization of Spall in Hard Rock from Observations and Simulations of the Source Physics Experiment Phase I

In this work, spall signals from the Source Physics Experiments are presented, analyzed, and modeled for insight to the explosion source. The observed signal is similar in nature to nearby historical nuclear explosions, and the surface force-time history or velocity can be interpreted with the same model. We use the models for peak spall velocity, spalled mass, and spall depth and radius derived from historical nuclear explosions to parameterize the physical force-time history model from Stump (1985) and show that this parameterized model can be used for spall prediction. The spall signal is also investigated with a numerical continuum model that incorporates gravity. Peak velocity and dwell time are well predicted, and the multiple slap-down phases are captured if one includes a weak near-surface layer similar to the geologic observation.

58 GEOSCIENCES↗

DOE OSTI2014

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Toward a Unified Parameterization of the Boundary Layer and Moist Convection: A New Type of Mass-Flux Model - Part 1

Higher-order closure (HOC) models have been proposed for parameterization of the turbulent planetary boundary layer (PBL). HOC models must include closures for higher-order moments (e.g., fourth moments in third-order closure models), for pressure terms, and for dissipation terms. Mass-flux closure (MFC) models have been proposed for parameterization of cumulus convection and, more recently, the convective PBL. MFC models include closures for lateral mass exchanges and for pressure terms (which are usually ignored). The authors developed a new kind of model that combines HOC and MFC, which they hope will be useful for the parameterization of both the PBL and cumulus convection, in a unified framework. Such a model is particularly well suited to regimes in which the PBL turbulence and the cumulus convection are not well separated, for example, the broken stratocumulus and shallow cumulus regimes. The model makes use of an assumed joint probability distribution for the variables of interest, and the equations typically used in HOC models can be derived by integrating over the distribution. Accordingly, the model is called Assumed-Distribution Higher-Order Closure (ADHOC). The prognostic variables of ADHOC are the mean state, the second and third moments of the vertical velocity, and the vertical fluxes of other quantities of interest. All of the parameters of the distribution can be determined from the predicted moments, thereafter the joint distribution is effectively known, and so any and all moments can be constructed as needed. In this way, the usual closure problem of "higher moments" is avoided. The pressure-term parameterizations previously developed for HOC models are used to predict the convective fluxes and the moments of the vertical velocity. In companion papers, parameterizations of lateral mass exchanges and subplume-scale fluxes are presented, and then ADHOC is applied to several observationally based tropical, subtropical, and dry convective boundary layers.

Lappen, Cara-Lyn↗

NASA NTRS2001

The Continuing Evolution of Land Surface Parameterizations

Land surface models (LSMs) play a critical role in the simulation of climate, for they determine the character of a large fraction of the atmosphere's lower boundary. The LSM partitions the net radiative energy at the land surface into sensible heat, latent heat, and energy storage, and it partitions incident precipitation water into evaporation, runoff, and water storage. Numerous modeling experiments and the existing (though very scant) observational evidence suggest that variations in these partitionings can feed back on the atmospheric processes that induce them. This land-atmosphere feedback can in turn have a significant impact on the generation of continental precipitation. For this and other reasons (including the role of the land surface in converting various atmospheric quantities, such as precipitation, into quantities of perhaps higher societal relevance, such as runoff), many modeling groups are placing a high emphasis on improving the treatment of land surface processes in their models. LSMs have evolved substantially from the original bucket model of Manabe et al. This evolution, which is still ongoing, has been documented considerably. The present paper also takes a look at the evolution of LSMs. The perspective here, though, is different - the evolution is considered strictly in terms of the 'balance' between the formulations of evaporation and runoff processes. The paper will argue that a proper balance is currently missing, largely due to difficulties in treating subgrid variability in soil moisture and its impact on the generation of runoff.

Koster, Randal↗

NASA NTRSDate not supplied

CERES Fast Longwave And SHortwave Radiative Flux (FLASHFlux): Research to Operation

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed as to provide key radiative flux data products within a week of observations for scientific, applied science research and educational usage. FLASHFlux achieves this by using simplified calibration process and optimized CERES data fusion production system, an operation meteorology product from Global Modeling and Assimilation Office(GMAO), and surface parameterized radiative flux models. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1ox1o gridded data that combines Aqua and Terra observations.The current operational Version 3C is being transitioned to Version4A. We compare the FLASHFlux Version4A fluxes using the specialized calibration to Version3C and to the climate quality CERES Edition4A TOA and surface fluxes over time for Terra and Aqua to determine the uncertainties of the calibration process. In addition, we also compare the impact of the fluxes by using the near real-time GMAO GEOS FP-IT instead of GMAO G5-CERES meteorology data.We also compare both SSF overpass products (for Terra and Aqua) and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement.Lastly, we introduce the first CERES FF SSF data products from the CERES instrument on board NOAA-20.

P Sawaengphokhai↗

DOE OSTI2022

Persistent, extensive channelized drainage modeled beneath Thwaites Glacier, West Antarctica

Abstract. Subglacial hydrology is a leading control on basal friction and the dynamics of glaciers and ice sheets. At low discharge, subglacial water flows through high-pressure, sheet-like systems that lead to low effective pressures. However, at high discharge, subglacial water melts the overlying ice into localized channels that efficiently remove water from the bed, thereby increasing effective pressure and basal friction. Recent observations suggest channelized subglacial flow exists beneath Thwaites Glacier, yet it remains unclear if stable channelization is feasible in West Antarctica, where surface melting is nonexistent and water at the bed is limited. Here, we use the MPAS-Albany Land Ice model to run a suite of over 130 subglacial hydrology simulations of Thwaites Glacier across a wide range of physical parameter choices to assess the likelihood of channelization. We then narrow our range of viable simulations by comparing modeled water thicknesses to previously observed radar specularity content, which indicates flat, spatially extensive water bodies at the bed. In all of our data-compatible simulations, stable channels reliably form within 100–200 km of the grounding line and reach individual discharge rates of 35–110 m3 s−1 at the ice–ocean boundary. While only one to two channels typically form across the 200 km width of the glacier in our simulations, their high efficiency drains water across the entire lateral extent of the glacier. We posit the large catchment size of Thwaites Glacier, its funnel-like geometry, and high basal melt rates together accumulate enough water to form stable channels. No simulations resembled observed specularity content when channelization was disabled. Our results suggest channelized subglacial hydrology has two consequences for Thwaites Glacier dynamics: (i) amplifying submarine melting of the terminus and ice shelf while (ii) simultaneously raising effective pressure within 100 km of the grounding line and increasing basal friction. The distribution of effective pressure implied from our modeling differs from parameterizations typically used in large-scale ice sheet models, suggesting the development of more process-based parameterizations may be necessary.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Functional-type modeling approach and data-driven parameterization of methane emissions in wetlands (Final Technical Science Report)

Our goals are to improve understanding and quantitative representation of the multiple processes that affect methane emissions at a high (patch level, vertically detailed) spatial resolution, and translate this understanding to improved modeling capability of coastal wetland fluxes using the E3SM Land Model (ELM v1) wetland CH4 biogeochemistry module. We propose an experimental approach to identify and parameterize uncertainties in ELM. Understanding of methane emissions can be improved along three conceptual axes: (i) horizontal (ecohydrological patch resolution), (ii) vertical (through the depth of the soil column), and (iii) process level (e.g., resolving microbial pathways, vegetation specific transport pathways). Along each of the three axes, we will characterize, quantify, and model, the key ecological, hydrological, and meteorological controls of methane (CH4) flux heterogeneity in four model coastal wetlands.

54 ENVIRONMENTAL SCIENCES↗