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At least 19 records

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

snow↗

A method for transporting cloud-resolving model variance in a multiscale modeling framework

Abstract. An unphysical checkerboard pattern has recently been identified in the multiscale modeling framework configuration of the Energy Exascale Earth System Model (E3SM-MMF) that is hypothesized to be associated with the inability of large-scale dynamics to transport fluctuations within the embedded cloud-resolving model (CRM) on the global grid. To address this issue, a method is presented to facilitate the large-scale transport of CRM variance in E3SM-MMF. Simulation results show that the method is effective at reducing the occurrence of unphysical checkerboard patterns on a range of timescales from days to years. This result is confirmed both subjectively through visual inspection and quantitatively with a previously developed pattern categorization technique. The CRM variance transport does not significantly alter the model climate, although it does tend to reduce temporal variance on fields associated with convection on the global grid.

54 ENVIRONMENTAL SCIENCES↗

Multiscale Modeling Framework Using Element‐Based Galerkin Methods for Moist Atmospheric Limited‐Area Simulations

This paper presents a multiscale modeling framework (MMF) to model moist atmospheric limited-area weather. The MMF resolves large-scale convection using a coarse grid while simultaneously resolving local features through numerous fine local grids and coupling them seamlessly. Both large- and small-scale processes are modeled using the compressible Navier-Stokes equations within the Nonhydrostatic Unified Model of the Atmosphere (NUMA), and are discretized using a continuous element-based Galerkin method (spectral elements) with high-order basis functions. Consequently, the large-scale and small-scale models share the same dynamical core but have the flexibility to be adjusted individually. The proposed MMF method is tested in 2D and 3D idealized limited-area weather problems involving storm clouds produced by squall line and supercell simulations. Numerical results from the MMF showed enhanced representation of cloud processes compared to the coarse model.

Kang, Soonpil [Naval Postgraduate School, Monterey↗

Dissecting the Roles of Stability and Dynamic Regimes in Tropical Cloud Feedbacks Simulated from an Upgraded Multiscale Modeling Framework (MMF)

In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature perturbation experiment performed with a multiscale modeling framework (MMF). We sort the monthly-mean cloud and radiative properties according to circulation and stability regimes. It is found that the dynamic component of cloud feedback for a given dynamic regime dominates the thermodynamic component in terms of the absolute magnitude.

Kuan-Man Xu↗

Toward Realistic Simulation of low-Level Clouds Using a Multiscale Modeling Framework With a Third-Order Turbulence Closure in its Cloud-Resolving Model Component

This study presents preliminary results from a multiscale modeling framework (MMF) with an advanced third-order turbulence closure in its cloud-resolving model (CRM) component. In the original MMF, the Community Atmosphere Model (CAM3.5) is used as the host general circulation model (GCM), and the System for Atmospheric Modeling with a first-order turbulence closure is used as the CRM for representing cloud processes in each grid box of the GCM. The results of annual and seasonal means and diurnal variability are compared between the modified and original MMFs and the CAM3.5. The global distributions of low-level cloud amounts and precipitation and the amounts of low-level clouds in the subtropics and middle-level clouds in mid-latitude storm track regions in the modified MMF show substantial improvement relative to the original MMF when both are compared to observations. Some improvements can also be seen in the diurnal variability of precipitation.

Xu, Kuan-Man↗

Investigating Mechanisms Driving Differences in the Characteristics of Precipitation in the E3SM Multiscale Modeling Framework With 2D Versus 3D Cloud Resolving Model Configurations

Abstract In this study, we compare the Energy Exascale Earth Systems Model (E3SM) multiscale modeling framework (MMF) with the cloud resolving model (CRM) configured in two (2dMMF) and three (3dMMF) dimensions. We explore how CRM dimensionality impacts the representation of mean and extreme precipitation characteristics. Our results show that tropical mean precipitation patterns are better represented in 3dMMF compared to observations (Integrated Multi‐satellitE Retrivals for GPM and Global Precipitation Climatology Project One Degree Daily products), while 2dMMF better captures extreme precipitation intensity, with systematic land‐ocean differences in precipitation and cloud‐associated variables. These differences are attributed to the co‐occurrence of CRM throttling (i.e., suppressed convection in due to smaller numbers of CRM columns and domain size) and dilution (i.e., 3‐D cloud circulations with increased entrainment and lower precipitation efficiency) effects. Overall, throttling results in more low‐level humidity in 2dMMF and dilution contributes to more high clouds with less precipitation efficiency in 3dMMF. Since throttling occurs more strongly over the ocean than land, the 3dMMF tends to have less cloud liquid and precipitation over the ocean and more cloud ice and precipitation over land. These results may serve as a guide for choosing the CRM structure to reduce precipitation and cloud‐related biases.

54 ENVIRONMENTAL SCIENCES↗

Changes in Tropical Clouds and Atmospheric Circulation Associated with Rapid Adjustment Induced by Increased Atmospheric CO2 – A Multiscale Modeling Framework Study

The radiative heating increase due to increased CO2 concentration is the primary source for the rapid adjustment of atmospheric circulation and clouds. In this study, we investigate the rapid adjustment resulting from doubling of CO2 and its physical mechanism using a multiscale modeling framework (MMF). The MMF includes an advanced higher-order turbulence closure in its cloud-resolving model component and simulates realistic shallow and deep cloud climatology and boundary layer turbulence. The rapid adjustment over the tropics is characterized by 1) reduced ascent and descent strengths over the ocean, 2) increased lower tropospheric stability (LTS) over the subsidence region, 3) shoaling of planetary boundary layers over the ocean, 4) increased deep convection over lands and shift of cloud coverage from the ocean to lands, and 5) reduced sensible (SH) and latent heat (LH) fluxes over the oceanic deep convective regions. Unlike conventional general circulation models and another MMF, a reduction in the global-mean shortwave cloud radiative cooling is not simulated, due to the increase in low clouds at lower altitudes over the ocean, resulting from reduced cloud-top entrainment due to strengthened inversion. Changes in regional circulation play a key role in cloud changes and shift of cloud coverage to lands. Weaker energy transport resulting from water vapor and cloud CO2 masking effects reduces the upward motion and convective clouds in the oceanic regions. The ocean-land transports are linked to the partitioning of surface SH and LH fluxes that increases humidity over lands and enhances deep convection over the tropical lands.

Xu, Kuan-Man↗

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

Shen, Bo-Wen↗

Multiscale Modeling Framework for Lithium Nucleation in 3D Porous Carbon Anodes

Porous carbon scaffolds offer a promising route for mitigating non-uniform lithium (Li) plating to enhance the safety and longevity of Li metal batteries. However, the influence of microstructural morphology on Li nucleation is not well understood. Here, we present a multiscale modeling framework to investigate how the porous microstructure of carbon materials affects Li nucleation behavior. Ab initio molecular dynamics simulations quantify the nucleation energy barriers of Li on graphene as a function of Li content, surface curvature, and applied potential, providing key parameters for a classical nucleation theory (CNT) model. From macroscale half-cell simulations, we obtained Li concentration and electrical potential profiles to define boundary conditions for mesoscopic simulations. At the mesoscale, three distinct synthetic 3D microstructures with different porosities and characteristic feature sizes are generated to resolve local distributions of Li flux, current density, and mechanical stress. These outputs are integrated into the CNT model to map spatial variation in nucleation rates. Our findings reveal trade-offs between suppressing nucleation rates and achieving spatial uniformity, offering design guidelines for optimizing porous carbon anodes to balance nucleation control and mechanical integrity.

Materials science↗

Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

tropical cyclone interannual variability↗

Evaluating Mesoscale Convective Systems Over the US in Conventional and Multiscale Modeling Framework Configurations of E3SMv1

Organized mesoscale convective systems (MCSs) contribute a significant amount of precipitation in the Central and Eastern US during spring and summer, which impacts the availability of freshwater and flooding events. However, current global Earth system models cannot capture MCSs well and misrepresent the statistics of precipitation in the region. In this study, we investigate the representation of MCSs in three configurations of the Energy Exascale Earth System Model (E3SMv1) by tracking individual storms based on outgoing longwave radiation using a new application of TempestExtremes. Our results indicate that conventional parameterizations of convection, implemented in both low (LR; ~150 km) and high (HR; ~25 km) resolution configurations, fail to capture almost all MCS-like events, in-part because they underestimate high-level cloud ice associated with deep convection. On the other hand, the multiscale modeling framework (MMF; cloud-resolving models embedded in each grid-column of ~150 km resolution E3SMv1) configuration represents MCSs and their annual cycle better. Nevertheless, relative to observations, the E3SMv1-MMF spatial distribution of MCSs and associated precipitation is shifted eastward, and the diurnal timing is lagged. A comparison between the large-scale environment in E3SMv1-MMF and ERA5 reanalysis suggests that the biases during the summer in E3SMv1-MMF are associated with biases in low-level humidity and meridional moisture transport within the low-level jet. The fact that conventional parameterizations of convection, even with high-resolution, cannot capture MCSs over the US suggests that methods with explicit representation of kilometer-scale convective organization, such as the MMF, may be necessary for improving the simulation of these convective systems.

54 ENVIRONMENTAL SCIENCES↗

Implementation of a Quasi-3D Multiscale Modeling Framework to ACME

Representation of unresolved cloud processes has been one of the most challenging problems in numerical modeling of the atmosphere. During the last decades, considerable efforts have been spent to better represent the collective effects of those processes in terms of resolved scales (see Arakawa 2004 for a review). Still, the progress on this problem has been unacceptably slow as pointed out by Randall et al. (2003). The large part of the difficulty is inherent in the artificial separation of atmospheric processes into the explicitly simulated resolved scales and the highly parameterized subgrid scales. Arakawa (2004) and Arakawa et al. (2011) suggested two plausible approaches to eliminate the problem of artificial separation ofatmospheric processes: “parameterize everything” and “resolve everything”.

58 GEOSCIENCES↗

Develop a new integrated macro→micro←nano (MMN) multiscale modeling framework to optimize high strength aluminum alloys and processes for vehicle light-weighting​

Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further understanding of the relationship between microstructure and fracture properties of high-strength 6000-series alloys. This work started with microstructural characterization in both mesoscale and nanoscale and bending performance characterization of AA6111 HS2-T6 alloy at Ford, the MMN framework was applied to this alloy to simulate 3-point VDA bending. From the results of the macro-modeling of 3-point VDA bending, the critical region of fracture was identified, and the region geometry was used to construct the micro-model. The fracture criterion of micron-scale precipitates and aluminum matrix which contains submicron and nano particles (AL-SMP-NP) in the micro-model was calibrated and validated by comparing simulated and measured bending results. With the AL-SMP-NP fracture strain obtained, the fracture strain of Al-matrix containing nano particles (ALNP) will similarly be determined by a submicron scale-model using an edge-constrained FE modeling approach developed by Hu et al. With the ALNP fracture strain obtained, the fracture strain of Al-matrix containing no particles will similarly be determined by a nano scale-model using an edge-constrained FE modeling approach. After the MMN framework is built and fracture criterion calibrated, nano-model FE simulations with virtual microstructures was performed to obtain a reduced order model (ROM) of the fracture criterion of the ALNP as a function of volume fraction, size, and distribution of the nanoparticle. This nano→submicron→micro modeling part allows exploration of the influence of different material nanostructures from different process conditions on the bending properties within the multiscale bending simulation framework and the ROM of material bendability as a function of nanoparticle size and shape was established. This obtained reduced order model (ROM) could help guide the design and selection of materials to improve existing SPR process models that could replace trial-and-error rivet/die selection and help to design new rivet/die combinations capable of robustly joining new higher strength 6000 5 series alloys in automotive body structures. This would enable lightweighting of Ford vehicles leading to greater fuel efficiency and reduce manufacturing time and energy.

36 MATERIALS SCIENCE↗

Develop a new integrated macro→micro←nano (MMN) multiscale modeling framework to optimize high strength aluminum alloys and processes for vehicle light-weighting​

Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further the understanding of microstructural relationship to fracture properties of high strength 6000 series alloys.

36 MATERIALS SCIENCE↗

An Integrated Multiscale Modeling Framework for Unconventional Stimulation and Production (Final Report)

The production of oil and gas from unconventional reservoirs largely depends upon two main features operating at different scales: (1) the establishment of a reservoir scale stimulated fracture network that effectively communicates with the rock volume, enhancing permeability and transport to the wellbore and (2) the coupled multi-phase flow, chemical and mechanical processes affecting the migration of hydrocarbons from the low permeability country rock adjacent to the stimulated fracture network. To date, there has been no simulation framework that allows seamless and integrated prediction of these features across spatial scales extending from the pore structure of the reservoir rock to the volume of the reservoir. In addition, there has been a lack of suitable field measurements to test such models, as stimulation and production data are often proprietary and not freely available to national laboratories and academic institutions. New multi-scale simulation capabilities are needed that are validated against suitable field-based research experiments on hydraulic fracturing and shale production.

02 PETROLEUM↗

Modeling Progressive Damage Using Local Displacement Discontinuities Within the FEAMAC Multiscale Modeling Framework

A method for performing progressive damage modeling in composite materials and structures based on continuum level interfacial displacement discontinuities is presented. The proposed method enables the exponential evolution of the interfacial compliance, resulting in unloading of the tractions at the interface after delamination or failure occurs. In this paper, the proposed continuum displacement discontinuity model has been used to simulate failure within both isotropic and orthotropic materials efficiently and to explore the possibility of predicting the crack path, therein. Simulation results obtained from Mode-I and Mode-II fracture compare the proposed approach with the cohesive element approach and Virtual Crack Closure Techniques (VCCT) available within the ABAQUS (ABAQUS, Inc.) finite element software. Furthermore, an eccentrically loaded 3-point bend test has been simulated with the displacement discontinuity model, and the resulting crack path prediction has been compared with a prediction based on the extended finite element model (XFEM) approach.

Ranatunga, Vipul↗