Combined impacts of convection and microphysics parameterizations on the simulations of precipitation and cloud properties over Asia
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Liu, Dongqing (ORCID:0000000312584499)↗
SEARCH · Engineering Papers
Results for “model parameterization”
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Intercomparison of Martian Lower Atmosphere Simulated Using Different Planetary Boundary Layer Parameterization Schemes
We use the mesoscale modeling capability of Mars Weather Research and Forecasting (MarsWRF) model to study the sensitivity of the simulated Martian lower atmosphere to differences in the parameterization of the planetary boundary layer (PBL). Characterization of the Martian atmosphere and realistic representation of processes such as mixing of tracers like dust depend on how well the model reproduces the evolution of the PBL structure. MarsWRF is based on the NCAR WRF model and it retains some of the PBL schemes available in the earth version. Published studies have examined the performance of different PBL schemes in NCAR WRF with the help of observations. Currently such assessments are not feasible for Martian atmospheric models due to lack of observations. It is of interest though to study the sensitivity of the model to PBL parameterization. Typically, for standard Martian atmospheric simulations, we have used the Medium Range Forecast (MRF) PBL scheme, which considers a correction term to the vertical gradients to incorporate nonlocal effects. For this study, we have also used two other parameterizations, a non-local closure scheme called Yonsei University (YSU) PBL scheme and a turbulent kinetic energy closure scheme called Mellor- Yamada-Janjic (MYJ) PBL scheme. We will present intercomparisons of the near surface temperature profiles, boundary layer heights, and wind obtained from the different simulations. We plan to use available temperature observations from Mini TES instrument onboard the rovers Spirit and Opportunity in evaluating the model results.
Natarajan, Murali↗
A Model of Grain Boundary Complexion Transitions and Grain Growth in Yttria-Doped Alumina
In this work, we present a physically-parameterized microstructure evolution model for the Yttria-doped alumina system. Yttria-doped alumina is a well-known ceramic system which undergoes first-order phase-like transitions at grain boundaries, which can radically alter interface properties. The change in interfacial properties in turn can radically change microstructure outcomes during processing, including the induction of abnormal grain growth modes. In this work, we develop a simulation that evolves alumina microstructure as a function of yttria concentration and temperature. In the window studied, we achieve strong agreement with reviewed experimental results in identifying the windows for large grains, small grains, abnormal grain growth, and complexion transition kinetics. We then apply the model to study and demonstrate how the possible inclusion of second-phase particles or uneven solute distribution profiles will impact microstructure evolution. It is found that particles do not significantly affect abnormal grain growth in the window studied (but do lead to reduced grain size through pinning effects). It is found that even modest amounts of solute inhomogeneity will result in substantial changes in microstructure outcomes, frequently leading to clusters of abnormal grains. This model largely corroborates the expectations and hypotheses made from recent experimental studies in oxide-doped alumina systems. Further, it is found that there exists a peak transition fraction for the system at which abnormal grain size tends to be maximized.
Grain Growth, Grain Boundary Complexion, abnormal ↗
WE-H-BRA-02: Radiobiological Modeling of Tumor Control Probability (TCP) and Radiation-Induced Pneumonitis (RP) for Lung Cancer Patients Treated with Monte Carlo-Based Lung SBRT
Purpose: To present radiobiological modeling of TCP using tumor size-adjusted BED(s-BED)and PTV(D99) to lung SBRT patients treated with X-ray Voxel Monte Carlo(XVMC) algorithm, apply parameterized Lyman-NTCP model to predict grade-2 RP and subsequently, compare with clinical outcomes/observations. Methods: Dosimetric parameters and clinical follow-up for XVMC-based lung-SBRT patients were retrospectively evaluated. Patients were treated at Novalis-TX with hybrid(2 non-coplanar partial-arcs plus 3–6 static-beams)plan using HD-MLC/6MV-SRS-beam.For TCP,s-BED modelling was utilized: TCP=EXP[sBED-TCD50]/k/(1.0+EXP[sBED-TCD50]/k), where k=31Gy corresponding to TCD50=0Gy and s-BED was defined as BED10 minus 10 times the tumor diameter(in centimeters)by Ohri et al.(IJROBP,2012). For 2-yr local-control, we used more-realistic MC-computed PTVD99 as a predictive parameter, s-BED(D99).Due to relatively shorter median follow-up interval(12-months),Kaplan-Meier curves were generated to estimate 2-yr observed local-control and compared to predicted-rate by TCP modeling. For NTCP, we employed parameterized Lyman-NTCP model utilizing normal-lung DVH and α/β=3Gy fitted to predict grade-2 RP after lung-SBRT. Results: Total 108 patients (137 tumors) treated for 35–70Gy in 3–5 fractions, either primary-lung(n=74)or metastatic-lung(n=53)tumors were included.F or the given prescription dose with MC-computed MUs, 2-yr local-control rates with s-BED(D99) was 87±8%. Kaplan-Meier generated observed local-control rate at 2-yr was 87.5%,suggesting that PTV(D99) could be a potential predictor (p-value=0.38). Observed vs predicted TCP for primary-lung tumors and metastatic tumors were 97% vs 88±7% and 94% vs 86±9%.NTCP model predicted well for symptomatic-RP with predicted vs observed (3±5% vs 2%). Radiographic and clinically significant RP was observed in 13% and 2% of patients. Higher rates of radiographic change were observed in patients who received >50Gy compared to ≤50Gy(24% vs 10%). Conclusion: Utilizing MC-computed PTVD99, our TCP results were well correlated with clinical outcome. The predicted grade-2 RP rate was comparable to clinical observations. Clinical application of these radiobiological models may potentially allow for target dose escalation and/or lung-toxicity reduction. Further validation of these radiobiological models with longer follow up interval for large cohorts of lung-SBRT patients is anticipated.
60 APPLIED LIFE SCIENCES↗
LAROMance Grade 91 Model Integration in NEML2
New reactor designs are targeting higher operating temperatures for increased thermal efficiency when compared to the current fleet of light water reactors. Designing structural components for these high temperature environments with reliable long-term operations requires material models that can accurately capture the deformation mechanisms active in these environments. The LAROMance surrogate material models are based on a database of mechanistic crystal plasticity simulations for high-temperature conditions. Inputs to the LAROMance models reflect the microstructural pedigree of the material, like dislocation densities and precipitate contents. Based on the evolution of these microstructural features, the LAROMance model provides the engineering scale constitutive model response. The LAROMance model was recently parameterized for Grade 91, a high temperature alloy. In the present work, the Grade 91 LAROMance model is implemented in the New Material Model Library, version 2 (NEML2). NEML2 provides a modular way to build material models from smaller blocks and was developed to vectorize the material update to efficiently run on modern computational architectures with graphics processing unit accelerators. NEML2 constitutive models can be used in simulations based on the multiphysics object-oriented simulation environment (MOOSE). This report provides details on the implementation of the Grade 91 LAROMance model in NEML2 and its verification of engineering scale finite element simulations in MOOSE.
42 - ENGINEERING↗
On the Fidelity of Computational Models for the Flow of Milled Loblolly Pine: A Benchmark Study on Continuum-Mechanics Models and Discrete-Particle Models
The upstream of bioenergy industry has suffered from unreliable operations of granular biomass feedstocks in handling equipment. Computational modeling, including continuum-mechanics models and discrete-particle models, offers insightful understandings and predictive capabilities on the flow of milled biomass and can assist equipment design and optimization. This paper presents a benchmark study on the fidelity of the continuum and discrete modeling approaches for predicting granular biomass flow. We first introduce the constitutive law of the continuum-mechanics model and the contact law of the coarse-grained discrete-particle model, with model parameters calibrated against laboratory characterization tests of the milled loblolly pine. Three classical granular material flow systems (i.e., a lab-scale rotating drum, a pilot-scale hopper, and a full-scale inclined plane) are then simulated using the two models with the same initial and boundary conditions as the physical experiments. The close agreement of the numerical predictions with the experimental measurements on the hopper mass flow rate, the hopper critical outlet width, the material stopping thickness on the inclined plane, and the dynamic angle of repose, clearly indicates that the two methods can capture the critical flow behavior of granular biomass. The qualitative comparison shows that the continuum-mechanics model outperforms in parameterization of materials and wall friction, and large-scale systems, while the discrete-particle model is more preferred for discontinuous flow systems at smaller scales. Industry stakeholders can use these findings as guidance for choosing appropriate numerical tools to model biomass material flow in part of the optimization of material handling equipment in biorefineries.
Jin, Wencheng↗
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.
54 ENVIRONMENTAL SCIENCES↗
Radiative Flux and Forcing Parameterization Error in Aerosol-Free Clear Skies
This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentially unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. A dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.
Climate↗
The Radiative Forcing Model Intercomparison Project (RFMIP): Experimental protocol for CMIP6
The phrasing of the first of three questions motivating CMIP6 – “How does the Earth system respond to forcing?” – suggests that forcing is always well-known, yet the radiative forcing to which this question refers has historically been uncertain in coordinated experiments even as understanding of how best to infer radiative forcing has evolved. The Radiative Forcing Model Intercomparison Project (RFMIP) endorsed by CMIP6 seeks to provide a foundation for answering the question through three related activities: (i) accurate characterization of the effective radiative forcing relative to a near-preindustrial baseline and careful diagnosis of the components of this forcing; (ii) assessment of the absolute accuracy of clear-sky radiative transfer parameterizations against reference models on the global scales relevant for climate modeling; and (iii) identification of robust model responses to tightly specified aerosol radiative forcing from 1850 to present. Complete characterization of effective radiative forcing can be accomplished with 180 years (Tier 1) of atmosphere-only simulation using a sea-surface temperature and sea ice concentration climatology derived from the host model's preindustrial control simulation. Assessment of parameterization error requires trivial amounts of computation but the development of small amounts of infrastructure: new, spectrally detailed diagnostic output requested as two snapshots at present-day and preindustrial conditions, and results from the model's radiation code applied to specified atmospheric conditions. In conclusion, the search for robust responses to aerosol changes relies on the CMIP6 specification of anthropogenic aerosol properties; models using this specification can contribute to RFMIP with no additional simulation, while those using a full aerosol model are requested to perform at least one and up to four 165-year coupled ocean–atmosphere simulations at Tier 1.
54 ENVIRONMENTAL SCIENCES↗
The diurnal cycle of clouds and precipitation at the ARM SGP site: Cloud radar observations and simulations from the multiscale modeling framework
Millimeter Wavelength Cloud Radar (MMCR) data from December 1996 to December 2010, collected at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site, are used to examine the diurnal cycle of hydrometeor occurrence. These data are categorized into clouds (-40 dBZ e ≤ reflectivity < -10 dBZ e ), drizzle and light precipitation (-10 dBZ e ≤ reflectivity < 10 dBZ e ), and heavy precipitation (reflectivity ≥ 10 dBZ e ). The same criteria are implemented for the observation-equivalent reflectivity calculated by feeding outputs from a Multiscale Modeling Framework (MMF) climate model into a radar simulator. The MMF model consists of the National Center for Atmospheric Research Community Atmosphere Model with conventional cloud parameterizations replaced by a cloud-resolving model. We find that a radar simulator combined with the simple reflectivity categories can be an effective approach for evaluating diurnal variations in model hydrometeor occurrence. It is shown that the MMF only marginally captures observed increases in the occurrence of boundary layer clouds after sunrise in spring and autumn and does not capture diurnal changes in boundary layer clouds during the summer. Above the boundary layer, the MMF captures reasonably well diurnal variations in the vertical structure of clouds and light and heavy precipitation in the summer but not in the spring.
54 ENVIRONMENTAL SCIENCES↗
Water balance model for Kings Creek
Particular attention is given to the spatial variability that affects the representation of water balance at the catchment scale in the context of macroscale water-balance modeling. Remotely sensed data are employed for parameterization, and the resulting model is developed so that subgrid spatial variability is preserved and therefore influences the grid-scale fluxes of the model. The model permits the quantitative evaluation of the surface-atmospheric interactions related to the large-scale hydrologic water balance.
Wood, Eric F.↗
Dynamic modeling of subcellular phenylpropanoid metabolism in Arabidopsis lignifying cells
Not provided.
Biotechnology & Applied Microbiology↗
Climate and hydraulic traits interact to set thresholds for liana viability
Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.
54 ENVIRONMENTAL SCIENCES↗
Data-driven recovery of hidden physics in reduced order modeling of fluid flows
In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework is based on using first principles to model the known physics in conjunction with utilizing the data-driven machine learning tools to model the remaining residual that is hidden in data. This framework employs proper orthogonal decomposition as a compression tool to construct orthonormal bases and Galerkin projection (GP) as a model to build the dynamical core of the system. Our proposed methodology hence compensates structural or epistemic uncertainties in models and utilizes the observed data snapshots to compute true modal coefficients spanned by these bases. The GP model is then corrected at every time step with a data-driven rectification using a long short-term memory (LSTM) neural network architecture to incorporate hidden physics. A Grassmannian manifold approach is also adopted for interpolating basis functions to unseen parametric conditions. The control parameter governing the system's behavior is thus implicitly considered through true modal coefficients as input features to the LSTM network. The effectiveness of the HAM approach is then discussed through illustrative examples that are generated synthetically to take hidden physics into account. Furthermore, our approach thus provides insights addressing a fundamental limitation of the physics-based models when the governing equations are incomplete to represent underlying physical processes.
42 ENGINEERING↗
An Improved Convection Parameterization with Detailed Aerosol–Cloud Microphysics for a Global Model
Abstract A new microphysical treatment that includes aerosol–cloud interactions and secondary ice production (SIP) mechanisms is implemented in the convection scheme of the Community Atmosphere Model, version 6 (CAM6). The approach is to embed a 1D Lagrangian parcel model in the bulk convective plume of the existing deep convection parameterization. Aerosol activation, growth processes including collision/coalescence, and three processes of SIP mechanisms, two of which are normally overlooked in atmospheric models, are represented in this embedded parcel model. These microphysical processes are treated with a hybrid bin/bulk scheme and a high spatial and temporal resolution for the integration of the embedded parcel in 1D, allowing vertical velocity to determine the microphysical evolution following the in-cloud motion during ascent. Simulations of an observed case (Midlatitude Continental Convective Clouds Experiment) of a mesoscale convective system in Oklahoma, United States, with a single-column model (SCAM) version of CAM, are compared with aircraft in situ and ground-based observations of microphysical properties from the convection and precipitation. Results from the validation show the new microphysical scheme has a good representation of the ice initiation in the bulk convective plume, including the known and empirically quantified pathways of primary and secondary initiation, with benefits for the accuracy of properties of its supercooled cloud liquid. The sensitivity simulations and use of tagging tracers for the validated simulation confirm that the newly included SIP mechanisms are of paramount importance for convective microphysics and can be successfully treated in the global model.
54 ENVIRONMENTAL SCIENCES↗
Comparison of INP Parameterizations for Dust Minerals in Climatological Simulations With a Global Model
The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in weather and climate prediction. We utilize an improved sectional dust module in NASA GISS Earth System ModelE2.1, which distinguishes eight different mineral species and accretions between iron oxides and the other minerals. Simulations over a period of 20 years have been carried out with this model, and the mineral fields and other model variables (temperature, relative humidity) are used to calculate the ice nucleating particle (INP) number concentration, applying time-independent and time-dependent INP parameterizations, such as active site parameterization and water activity based immersion freezing model (ABIFM). We study how the dependence of the parameterizations on different model variables affects the mean INP number concentration. The sensitivity of the INP number concentration to fundamental dust properties such as emitted mineral size distributions and mixing state between minerals is also investigated. Results show that the sensitivity of the total INP number concentration to the emitted dust size distribution is rather small, but the sensitivity over the whole size range obscures offsetting differences in the magnitude and the sign of the sensitivity between smaller and larger particles.
INP Parameterizations↗
Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models
A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.
Famiglietti, J. S.↗
Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau through Fractional Vegetation Cover Derived from a Remotely Sensed Clumping Index and Model-Simulated Leaf Area Index
Parameterizations of fractional vegetation cover (FVC) in land surface models have important effects on simulations of surface energy budget, especially in arid and semiarid regions. This study uses a FVC scheme in which FVC is derived from leaf area index and a remotely sensed clumping index. The performance of the new scheme (SMFVC) is evaluated against Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and in situ soil temperature observations, together with two other FVC schemes, a general FVC scheme (CTL) based on land cover map and a climatology-based FVC scheme (RSFVC) that uses long-term remotely sensed Normalized Difference Vegetation Index of MODIS. The three FVC schemes were implemented in the Common Land Model (CoLM) and applied in the Tibetan Plateau using the same forcing data and default parameters. Our results demonstrate that FVC schemes have significant influence on the CoLM performance: (1) the RSFVC and SMFVC schemes significantly reduce the LST biases found in CTL, particularly in grassland and during summer; (2) soil temperature evaluation by in situ observations from three networks on the Tibetan Plateau corroborates the LST results; and (3) the improvements are mainly related to representing temporal (seasonal) variability and subgrid heterogeneity of FVC, which improves surface albedo and surface energy balance. In other words, by including more vegetation characteristics, such as using a clumping index, land surface models may better simulate surface vegetation condition and further better represent the land surface energy budget over the Tibetan Plateau.
Li, Chengwei↗