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At least 163 records · Page 9

Physics–Dynamics Coupling with Element-Based High-Order Galerkin Methods: Quasi-Equal-Area Physics Grid

Atmospheric modeling with element-based high-order Galerkin methods presents a unique challenge to the conventional physics–dynamics coupling paradigm, due to the highly irregular distribution of nodes within an element and the distinct numerical characteristics of the Galerkin method. The conventional coupling procedure is to evaluate the physical parameterizations ( physics) on the dynamical core grid. Evaluating the physics at the nodal points exacerbates numerical noise from the Galerkin method, enabling and amplifying local extrema at element boundaries. Grid imprinting may be substantially reduced through the introduction of an entirely separate, approximately isotropic finite-volume grid for evaluating the physics forcing. Integration of the spectral basis over the control volumes provides an area-average state to the physics, which is more representative of the state in the vicinity of the nodal points rather than the nodal point itself and is more consistent with the notion of a “large-scale state” required by conventional physics packages. This study documents the implementation of a quasi-equal-area physics grid into NCAR’s Community Atmosphere Model Spectral Element and is shown to be effective at mitigating grid imprinting in the solution. The physics grid is also appropriate for coupling to other components within the Community Earth System Model, since the coupler requires component fluxes to be defined on a finite-volume grid, and one can be certain that the fluxes on the physics grid are, indeed, volume averaged.

54 ENVIRONMENTAL SCIENCES↗

MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation Using the SWIFT Datasen

Modeling the transition from mesoscale to microscale is necessary in order to model different processes that affect a wind farm and to develop forecasting tools that operate at the farm scale. The mesoscale-to-microscale coupling (MMC) project is an A2e (Atmosphere-toelectrons) coordinated activity for developing modeling capabilities at the wind farm scale. By moving the focus of the research from a single wind turbine to the collection of turbines that comprise a wind farm, A2e extends the range of spatial and timescales that need representation in a model from tens of meters to hundreds of kilometers and timescales from a few seconds to days (Bokharaie et al. 2016). In the atmosphere, these scales are represented by mesoscale-tomicroscale models. The modeling available at these scales has differed in its representation of various physical processes. The MMC group is responsible for evaluating existing models at these scales and recommending a set of options for coupling the mesoscale and microscale with the best-performing models. The group was organized in 2015 and will explore options for coupling strategies with real-world test problems in fiscal year (FY) 2017. The model of choice for this exercise is WRF (Weather Research Forecasting) for mesoscale and WRF-LES (Large Eddy Simulation) for microscale simulations. The MPAS (Model Prediction Across Scales) variable mesh model that can be continuously refined; it has dynamic core and physics options adopted from WRF, which offer an alternative platform for modeling the mesoscale.

54 ENVIRONMENTAL SCIENCES↗

Predicting Ice Sheet and Climate Evolution on Extreme Scales (PISCEES) Final Report

Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES) PISCEES is a SciDAC Earth System Modeling project with the following goals: To develop and apply robust, accurate, and scalable dynamical cores for ice sheet modeling on structured and unstructured meshes with adaptive refinements To evaluate ice sheet models using new tools and data sets for verification and validation (V&V) and uncertainty quantification (UQ) To integrate these models and tools into DOE's Accelerated Climate Model for Energy (ACME) using improved estimates of ice sheet initial conditions, we will simulate decade-to-century-scale evolution of the Greenland and Antarctic ice sheets, running PISCEES ice sheet models both in standalone mode and coupled to ACME. We aim to provide useful, credible predictions, including uncertainty ranges, of future ice-sheet mass loss and resulting changes in climate and sea level. PISCEES is jointly funded by the Office of Biological and Environmental Research (BER) and the Office of Advanced Scientific Computing Research (ASCR) of the DOE Office of Science. Participating institutions: Los Alamos National Laboratory (LANL) Lawrence Berkeley National Laboratory (LBNL) Oak Ridge National Laboratory (ORNL) Sandia National Laboratories (SNL) Florida State University (FSU) Massachusetts Institute of Technology (MIT) University of South Carolina (USC) University of Texas at Austin (UT) National Center for Atmospheric Research (NCAR) (https://www.scidac.gov/PISCEES/).

54 ENVIRONMENTAL SCIENCES↗

A Non-hydrostatic Variable Resolution Atmospheric Model in ACME

The Accelerated Climate Modeling for Energy (ACME) Project is designed to perform coupled climate simulations at high resolution on current and next generation DOE leadership class supercomputers. Prior to this project, the ACME atmospheric model employed the primitive equations of motion, which constrained its maximum resolution and limited the physical phenomena that it could resolve. Our team removed this constraint by implementing a non-hydrostatic (NH) atmospheric model in the ACME Framework. Collaboration with SciDAC FASTMath institutes facilitated improvements to key technologies needed for the non-hydrostatic model. This model was tested in a variable resolution framework, which enables high resolution simulation regions at reasonable computational costs. The correct performance of the NH model was verified with standard dynamical-core tests, and by demonstrating that it reproduced expected climate statistics in the hydrostatic regime. The completed model was applied to evaluate the limitations of existing turbulent mountain stress and gravity wave drag parameterizations, in order to demonstrate the power of the new nonhydrostatic model to model new phenomena and enhance the quality of present day 1/4 degree simulations.

Hall, David Matthew↗

Performance Portability of the Aeras Atmosphere Model to Next Generation Architectures using Kokkos

The subject of this report is the performance portability of the Aeras global atmosphere dynamical core (implemented within the Albany multi-physics code) to new and emerging architecture machines using the Kokkos library and programming model. We describe the process of refactoring the finite element assembly process for the 3D hydrostatic model in Aeras and highlight common issues associated with development on GPU architectures. After giving detailed build and execute instructions for Aeras with MPI, OpenMP and CUDA on the Shannon cluster at Sandia National Laboratories and the Titan supercomputer at Oak Ridge National Laboratory, we evaluate the per- formance of the code on a canonical test case known as the baroclinic instability problem. We show a speedup of up to 4 times on 8 OpenMP threads, but we were unable to achieve a speedup on the GPU due to memory constraints. We conclude by providing methods for improving the performance of the code for future optimization.

97 MATHEMATICS AND COMPUTING↗

A Hybrid Climate Modeling System Using AI-assisted Process Emulators

This white paper addresses Focus Area II. We advocate developing a hybrid modeling system to improve the understanding of decadal- and longer-scale predictability of high impact water cycle components. This hybrid model combines a partial differential equation (PDE)-based dynamic core with AI/ML based emulators to represent many of the computationally expensive processes in Earth’s climate models. The hybrid modeling system has the potential to exploit emerging graphics processing unit (GPU)-accelerated architectures and allows for the generation of large ensemble (~1000’s) simulations to better characterize the model uncertainty and understand predictability.

58 GEOSCIENCES↗

The E3SM version 1 single-column model

Abstract. The single-column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM) but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to “replay” a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long-standing biases in the full GCM runs while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation.

54 ENVIRONMENTAL SCIENCES↗

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

54 ENVIRONMENTAL SCIENCES↗

Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)

Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

58 GEOSCIENCES↗

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

58 GEOSCIENCES↗

HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model

Abstract. A new set of standalone parameterizations is presented for simulating the injection, evolution, and radiative forcing by stratospheric volcanic aerosols against an idealized Held–Suarez–Williamson (HSW) atmospheric background in the Energy Exascale Earth System Model version 2 (E3SMv2). In this model configuration (HSW with enabled volcanism, HSW-V), sulfur dioxide (SO2) and ash are injected into the atmosphere with a specified profile in the vertical, and they proceed to follow a simple exponential decay. The SO2 decay is modeled as a perfect conversion to a long-living sulfate aerosol which persists in the stratosphere. All three species are implemented as tracers in the model framework and are transported by the dynamical core's advection algorithm. The aerosols contribute simultaneously to local heating of the stratosphere and cooling of the surface by a simple plane-parallel Beer–Lambert law applied on two zonally symmetric radiation broadbands in the longwave and shortwave ranges. It is shown that the implementation parameters can be tuned to produce realistic temperature anomaly signatures of large volcanic events. In particular, results are shown for an ensemble of runs that mimic the volcanic eruption of Mt. Pinatubo in 1991. The design requires no coupling to microphysical subgrid-scale parameterizations and thus approaches the computational affordability of prescribed aerosol forcing strategies. The idealized simulations contain a single isolated volcanic event against a statistically uniform climate, where no background aerosols or other sources of externally forced variability are present. HSW-V represents a simpler-to-understand tool for the development of climate source-to-impact attribution methods.

Hollowed, Joseph P. (ORCID:0000000286581672)↗

A Fortran–Python interface for integrating machine learning parameterization into earth system models

Abstract. Parameterizations in earth system models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation, and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran–Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and scikit-learn. We demonstrate the interface's modularity and reusability through two cases: an ML trigger function for convection parameterization and an ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗

A Fortran-Python Interface for Integrating Machine Learning Parameterization into Earth System Models

Parameterizations in Earth System Models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran-Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and Scikit-learn. We demonstrate the interface's modularity and reusability through two cases: a ML trigger function for convection parameterization and a ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗

Alcator C-Mod: Research in support of ITER and steps beyond

This paper presents an overview of recent highlights from research on Alcator C-Mod. Significant progress has been made across all research areas over the last two years, with particular emphasis on divertor physics and power handling, plasma-material-interaction studies, ELM-suppressed pedestal dynamics, core transport and turbulence, and RF heating and current drive utilizing Ion Cyclotron and Lower Hybrid tools. Specific results of particular relevance to ITER include: inner wall SOL transport studies that have led, together with results from other experiments, to the change of the detailed shape of the inner wall in ITER; runaway electron studies showing that the critical electric field required for runaway generation is much higher than predicted from collisional theory; core tungsten impurity transport studies reveal that tungsten accumulation is naturally avoided in typical C-Mod conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamic analysis of gas-core reactor system

A heat transfer analysis was incorporated into a previously developed model CODYN to obtain a model of open-cycle gaseous core reactor dynamics which can predict the heat flux at the cavity wall. The resulting model was used to study the sensitivity of the model to the value of the reactivity coefficients and to determine the system response for twenty specified perturbations. In addition, the model was used to study the effectiveness of several control systems in controlling the reactor. It was concluded that control drums located in the moderator region capable of inserting reactivity quickly provided the best control.

Turner, K. H., Jr.↗

Equivalent source modeling of the main field using MAGSAT data

The software was considerably enhanced to accommodate a more comprehensive examination of data available for field modeling using the equivalent sources method by (1) implementing a dynamic core allocation capability into the software system for the automatic dimensioning of the normal matrix; (2) implementing a time dependent model for the dipoles; (3) incorporating the capability to input specialized data formats in a fashion similar to models in spherical harmonics; and (4) implementing the optional ability to simultaneously estimate observatory anomaly biases where annual means data is utilized. The time dependence capability was demonstrated by estimating a component model of 21 deg resolution using the 14 day MAGSAT data set of Goddard's MGST (12/80). The equivalent source model reproduced both the constant and the secular variation found in MGST (12/80).

Source record↗

Application of the Regional Atmospheric Modeling System to the Martian Atmosphere

The core dynamics of the Regional Atmospheric Modeling System (RAMS), a widely used and powerful mesoscale Earth model, is adapted to the Martian Atmosphere and applied in the study of aeolian surface features. In particular, research efforts focused on the substitution of Martian planetary and atmospheric properties such as rotation rate, and thermodynamic constants in place of hard-wired Earth properties. Application of the model was restricted to three-dimensional flow impinging upon impact craters, and the search for plausible wind patterns that could produce the so-called light and dark streaks downwind of topographic barriers.

Rafkin, Scot C. R.↗

Simulations of Water Vapor in the Upper Troposphere and Lower Stratosphere

A detailed study of the water vapor budget in the upper troposphere and lower stratosphere of the "Finite Volume CCM3" (FVCCM3) model is presented. The model is based on a combination of a finite-volume dynamical core (developed by Lin and Rood) and the physical package from Version 3 of the Community Climate Model (CCM3, developed at NCAR). The model was used with a horizontal resolution of 2 by 2.5 degrees and 55 levels, with the upper boundary at 0.0lhPa and a vertical resolution of about 1.2km near the tropopause. Most results presented are from a 17-year simulation performed for the Atmospheric Model Intercomparison Project. It is shown that the model simulates a realistic thermal structure in the tropical tropopause region and that water vapor distributions are in qualitative accord with observations (which are uncertain). The longitudinal structure of the tropical atmosphere is slightly too asymmetric, compared to reasonable estimates of the truth. The processes leading to the horizontal and vertical transport of water vapor in the tropopause region are analyzed in detail. Special attention is given to the realism of horizontal transport events (the ability of the model to retain sharply defined features) and to the role of localized vertical motions in transporting air (and water vapor) between the troposphere and stratosphere. It is shown that the vertical transport of water vapor in the tropical lower stratosphere occurs at about the same rate as that observed, while in many other models this vertical transport is too fast.

Pawson, Steven↗