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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling

Convergence testing is a common practice in the development of dynamical cores of atmospheric models but is not as often exercised for the parameterization of sub-grid physics. An earlier study revealed that the stratiform cloud parameterizations in several predecessors of the Energy Exascale Earth System Model (E3SM) showed strong time-step sensitivity and slower-than-expected convergence when the model's time step was systematically refined. In this work, a simplified atmosphere model is configured that consists of the spectral-element dynamical core of the E3SM atmosphere model coupled with a large-scale condensation parameterization based on commonly used assumptions. This simplified model also resembles E3SM and its predecessors in the numerical implementation of process coupling and shows poor time-step convergence in short ensemble tests. We present a formal error analysis to reveal the expected time-step convergence rate and the conditions for obtaining such convergence. Numerical experiments are conducted to investigate the root causes of convergence problems. We show that revisions in the process coupling and closure assumption help to improve convergence in short simulations using the simplified model; the same revisions applied to a full atmosphere model lead to significant changes in the simulated long-term climate. This work demonstrates that causes of convergence issues in atmospheric simulations can be understood by combining analyses from physical and mathematical perspectives. Addressing convergence issues can help to obtain a discrete model that is more consistent with the intended representation of the physical phenomena.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Assessing Adaptive Mesh Refinement (AMR) in a Forced Shallow-Water Model with Moisture

Two forced shallow-water flow scenarios are explored in a 2D fourth-order finite-volume dynamical core with adaptive mesh refinement (AMR) to investigate AMR’s ability to track and resolve complex evolving features. Traditional shallow-water test cases are mainly characterized by large-scale smooth flows that do not effectively test the multiscale abilities of variable-resolution and AMR models to resolve sharp gradients and small-scale flow filaments. Therefore, adding forcing mechanisms to the shallow-water system to model key atmospheric processes adds complexity and creates small-scale phenomena. These can serve as foci for dynamic grid refinement while remaining simple enough to study the numerical design of a model’s dynamical core. The first shallow-water flow scenario represents a strengthening, tropical cyclone–like, vortex that is driven by a Betts–Miller-like convection scheme. The second shallow-water test is built upon a barotropically unstable jet with an added Kessler-like warm rain scheme that leads to precipitating frontal zones. The key feature of both tests is that there is significant sensitivity to the model grid while converging (structurally) at high resolution. Both test cases are investigated for a series of uniform resolutions and a variety of AMR tagging criteria. The AMR simulations demonstrate that grid refinement can resolve local features without requiring global high-resolution meshes. However, the results are sensitive to the refinement criteria. Criteria that trigger refinement early in a simulation reproduce the uniform-resolution reference solutions most reliably. Finally, in contrast, AMR criteria that delay refinement for several days require careful tuning of the AMR thresholds to improve results compared with uniform-resolution simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensitivity of the latitude of the westerly jet stream to climate forcing

The latitude of the westerly jet stream is influenced by a variety of climate forcings. Their effects often manifest as a tug-of-war between tropical forcing, characterized by tropical upper-tropospheric warming, and polar forcing, with a signature of Antarctic stratospheric cooling or Arctic amplification. Here we present a unified forcing-feedback frame work relating different climate forcings to their forced jet changes, in which the interactions between the westerly jet and synoptic storms are synthesized by a zonal advection feedback, analogous to the feedback framework for assessing climate sensitivity. This framework is supported by a prototype feedback analysis in the atmospheric dynamical core of a climate model with diverse thermal and mechanical forcings. Our analysis indicates that the latitude of a westerly jet is most sensitive to the thermally-induced jet speed changes near the tropopause. The jet shift also displays a larger sensitivity than linearity for the equatorward shift.

atmospheric dynamics, atmospheric variability, cli↗
DOE OSTI2023

The Flux-Differencing Discontinuous Galerkin Method Applied to an Idealized Fully Compressible Nonhydrostatic Dry Atmosphere

Dynamical cores used to study the circulation of the atmosphere employ various numerical methods ranging from finite-volume, spectral element, global spectral, and hybrid methods. In this work, we explore the use of Flux-Differencing Discontinuous Galerkin (FDDG) methods to simulate a fully compressible dry atmosphere at various resolutions. We show that the method offers a judicious compromise between high-order accuracy and stability for large-eddy simulations and simulations of the atmospheric general circulation. In particular, filters, divergence damping, diffusion, hyperdiffusion, or sponge-layers are not required to ensure stability; only the numerical dissipation naturally afforded by FDDG is necessary. We apply the method to the simulation of dry convection in an atmospheric boundary layer and in a global atmospheric dynamical core in the standard benchmark of Held and Suarez

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗
DOE OSTI2019

Interaction of the Westerlies with the Tibetan Plateau in Determining the Mei-Yu Termination

This article explores how the termination of the mei-yu is dynamically linked to the westerlies impinging on the Tibetan Plateau. It is found that the mei-yu stage terminates when the maximum upper-tropospheric westerlies shift beyond the northern edge of the plateau, around 40°N. This termination is accompanied by the disappearance of tropospheric northerlies over northeastern China. The link between the transit of the jet axis across the northern edge of the plateau, the disappearance of northerlies, and termination of the mei-yu holds on a range of time scales from interannual through seasonal and pentad. Diagnostic analysis indicates that the weakening of the meridional moisture contrast and meridional wind convergence, mainly resulting from the disappearance of northerlies, causes the demise of the mei-yu front. The authors propose that the westerlies migrating north of the plateau and consequent weakening of the extratropical northerlies triggers the mei-yu termination. Model simulations are employed to test the causality between the jet and the orographic downstream northerlies by repositioning the northern edge of the plateau. As the plateau edge extends northward, orographic forcing on the westerlies strengthens, leading to persistent strong downstream northerlies and a prolonged mei-yu. Idealized simulations with a dry dynamical core further demonstrate the dynamical link between the weakening of orographically forced downstream northerlies with the positioning of the jet from south to north of the plateau. Changes in the magnitude of orographically forced stationary waves are proposed to explain why the downstream northerlies disappear when the jet axis migrates beyond the northern edge of the plateau.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

High resolution measurements of core density collapse dynamics in LHD

The core density collapse (CDC) is an abrupt instability that degrades the performance of super dense core stellarator plasmas on the Large Helical Device (LHD). In LHD, CDCs have proved to be an operational limit in so-called outward-shifted configurations. New measurements with high time resolution Thomson scattering characterize dynamics of the instability in the core. The density profile is observed to collapse inwards, narrowing the density peak till the core itself collapses. A hot, radially localized feature is also observed in the electron temperature profile during the collapse and disappears within a few hundred microseconds of CDC onset.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Reconciling and Improving Formulations for Thermodynamics and Conservation Principles in Earth System Models (ESMs)

Abstract This paper provides a comprehensive derivation of the total energy equations for the atmospheric components of Earth System Models (ESMs). The assumptions and approximations made in this derivation are motivated and discussed. In particular, it is emphasized that closing the energy budget is conceptually challenging and hard to achieve in practice without resorting to ad hoc fixers. As a concrete example, the energy budget terms are diagnosed in a realistic climate simulation using a global atmosphere model. The largest total energy errors in this example are spurious dynamical core energy dissipation, thermodynamic inconsistencies (e.g., coupling parameterizations with the host model) and missing processes/terms associated with falling precipitation and evaporation (e.g., enthalpy flux between components). The latter two errors are not, in general, reduced by increasing horizontal resolution. They are due to incomplete thermodynamic and dynamic formulations. Future research directions are proposed to reconcile and improve thermodynamics formulations and conservation principles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Process-oriented evaluation of quasi-stationary Rossby waves and their impact on surface air temperature extremes in dynamical downscaling over North America

Quasi-stationary Rossby waves are a crucial component of the general circulation and play a significant role in regional water and energy cycles, as well as in extreme events. However, process-oriented evaluation for Rossby waves is rarely performed for dynamical downscaling simulations. To close this gap, we evaluate three classes of dynamical downscaling approaches, with a focus on quasi-stationary Rossby waves and their impact on surface air temperature over North America during Northern Hemisphere summer. The three classes of models differ in the way large-scale forcing is provided: a limited-area model (LAM) constrained only by lateral boundary conditions, represented by RegCM4 from the North American branch of the Coordinated Regional Downscaling Experiment (NA-CORDEX), a LAM with spectral nudging to maintain consistency in large-scale dynamics with the forcing data, represented by the Weather Research and Forecasting (WRF) model simulation in NA-CORDEX, and a global variable-resolution model with smoothly varying grid spacings, represented by the Community Atmosphere Model version 5.4, with the Model for Prediction Across Scales (MPAS) as its dynamical core (CAM-MPAS). With no constraints on the atmospheric dynamics, CAM-MPAS exhibits several mean biases in the upper-level circulations over the Pacific Coast region: a weaker subtropical jet, a northward-shifted mid-latitude jet, and an overestimated southerly flow. With the lateral boundary constraint alone, RegCM4 also exhibits weaker jets and overestimated southerly winds off the West Coast. Rossby ray theory reveals that those wind biases direct incoming Rossby waves northward. The erroneously routed Rossby waves distort the relationship between the accumulation of wave activity over the US West Coast and surface temperature anomalies over the Southern Great Plains, which emerges approximately 4 d after the convergence of wave-activity flux in the ERA-Interim reanalysis. Furthermore, the response of heatwaves to the extreme wave activity flux is not reproduced by the two models, a serious drawback as a dynamical downscaling framework is expected to connect large-scale forcing to local-scale phenomena. The WRF model employing spectral nudging is largely free from the aforementioned problems. A pair of sensitivity simulations suggests that spectral nudging is the key to improving the dynamics of quasi-stationary Rossby waves and their impact on surface air temperature. Our results also demonstrate the effectiveness of Rossby wave diagnostics that allow for realistic background flows for assessing the credibility of dynamical downscaling over North America, where incoming Rossby waves propagate through complex circulation patterns before traveling across the continent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Capturing Sub‐Kilometer Flood Inundation Dynamics During the California Rain‐on‐Snow Events of 2017

The severe impacts of rain‐on‐snow (ROS) extreme events have been widely recognized and studied. However, unlike hydrological processes, flood inundation dynamics and the relative contribution of rainfall and snowmelt during ROS events remain under‐investigated. We diagnosed and documented sub‐kilometer spatio‐temporal dynamics of flood inundation during the 2017 California ROS events, simulated by a 2‐dimensional hydrodynamic model, River Dynamical Core (RDycore). RDycore shows good performance in capturing fine‐scale flood inundation dynamics against gauge measurements (with a median correlation coefficient of 0.81) and satellite observations. On top of rainfall, snowmelt not only increases the mean maximum inundation depth (12.0%–25.1%), but also expands the total flooded area (19.9%–31.9%) and prolongs the mean flood duration (3.4%–7.1%) across the events. Our findings offer an explicit and accurate picture of when and where ROS flooding could occur and how snowmelt increases flood hazard, valuable for risk assessment and infrastructure planning.

Flood inundation↗
DOE OSTI2024

Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models

Abstract. Motivated by reducing errors in the energy budget related to enthalpy fluxes within the Energy Exascale Earth System Model (E3SM), we study several physics–dynamics coupling approaches. Using idealized physics, a moist rising bubble test case, and the E3SM's nonhydrostatic dynamical core, we consider unapproximated and approximated thermodynamics applied at constant pressure or constant volume. With the standard dynamics and physics time-split implementation, we describe how the constant-pressure and constant-volume approaches use different mechanisms to transform physics tendencies into dynamical motion and show that only the constant-volume approach is consistent with the underlying equations. Using time step convergence studies, we show that the two approaches both converge but to slightly different solutions. We reproduce the large inconsistencies between the energy flux internal to the model and the energy flux of precipitation when using approximate thermodynamics, which can only be removed by considering variable latent heats, both when computing the latent heating from phase change and when applying this heating to update the temperature. Finally, we show that in the nonhydrostatic case, for physics applied at constant pressure, the general relation that enthalpy is locally conserved no longer holds. In this case, the conserved quantity is enthalpy plus an additional term proportional to the difference between hydrostatic pressure and full pressure.

58 GEOSCIENCES↗
DOE OSTI2021

Energy Exascale Earth System Model v2.0

First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.

E3SM Project, DOE↗
DOE OSTI2024

Final Report on Predictive Analyses of PRD as Function of Anomalies

This report summarizes the work completed in FY-2024 to analyze the power reactivity decrement (PRD) concepts of the ARC-100 core. The PRD has been traditionally defined by the reactivity change from a hot zero power (HZP) to a particular power. Consequently, the PRD accounts for the core reactivity changes due to increase coolant temperature gradient axially and radially across the core, and increased fuel temperature. The coolant temperature gradient leads to sodium and structure density changes, to radial core expansion from assembly flowering and bowing (due to axial and radial temperature gradients within the assemblies), and to control rod driveline thermal expansion. The fuel temperature increase associated with coolant temperature and power increases leads to Doppler effect and axial thermal expansion. In this work, the normal operating Hot Full Power (HFP) state is the only power level of interest, so analyses focus on the PRD calculated from HZP to HFP. The PRD has been used to assess the reactor safety features asymptotically in unprotected accident scenarios, including the loss of heat sink (LOHS), loss of flow (LOF), and transient overpower (TOP) without scram. The PRD concept relies on the “global” reactivity coefficients A, B, and C that are estimated based on “individual” reactivity effects (Doppler, sodium density, etc.). The objectives of this work are: 1) to improve and verify the methodology used to calculate the ABC coefficients used in the PRD, 2) to assess if the PRD can be used to reliably identify abnormal events. This report fulfills the FY-2024 scope of WBS#1.15.8.3 activity, “ANL0120 – Predictive Analyses of PRD as function of deformation”. The PRD concept is described in Sections 2. Additional effort in refining the methodology for core bowing modeling is performed in Sections 3. Then, two verification exercises are proposed in Section 4 to benchmark these coefficients based on direct neutronic-only calculations and on dynamic core transient simulations. Finally, the PRD approach is assessed for the detection of several unexpected events, such as primary flow perturbation or improper fuel loading, in Section 5.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗
DOE OSTI2021

Embedding condition describing shearing, dissipative collapse

Highlights: • Perturbative approach to the time-dependent Karmarkar condition in shearing collapse. • Analysis of the (in)stability of the collapsing fluid using the TOV equation. • Study of the temperature profiles using a causal heat transport equation. In this work we employ the time-dependent Karmarkar condition to model dissipative gravitational collapse in the presence of shear which leads to a final static configuration. We believe that this is a first attempt at using the time-dependent Karmarkar condition describing a radiating star with shear in which the collapsing core dissipates energy in the form of a radial heat flux. The final static configuration which is described by an embedding class I spacetime was obtained by Hansraj and Moodly who showed that this solution satisfies all the physical requirements for a static compact object. As the collapse proceeds and the heat flux tends to zero the dynamical core evolves into a static compact core with the exterior spacetime being described by the vacuum Schwarzschild solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Effect of Mechanical Deformation on the Dielectric Electric Field in Dynamic Umbilical Cables

Wave energy converter (WEC) systems have unique umbilical cable design requirements compared to conventional marine designs. Due to their dynamic nature, WEC umbilical cables are required to handle increased loads and larger motions over longer deployment scenarios. However, the life expectancy of dynamic umbilical cables is predominantly analyzed for mechanical fatigue, with little consideration given to the effect of mechanical stress on the response of the dielectric as it has been previously assumed that the non-polymeric components will fail prior to the polymeric components. In this work, we explore the effects of mechanical bending on the concentration of the electric field in the insulation of a conceptual three-core dynamic umbilical cable to determine the limiting requirements for life expectancy. A conceptual industrial schematic of a medium voltage dynamic umbilical cable was used as the basis for the WEC system under study. Simulations on the dynamic umbilical cable were performed using COMSOL Multiphysics®. Mechanical loads up to the calculated limit (2.64 m minimum bend radius or 388 kN transverse load) were applied to the dynamic umbilical in a step-wise fashion with one end of the umbilical cable fixed. One-way coupling in three-dimensions was conducted by first determining the engineering strains, then using the engineering strains as the initial condition for determination of the Green-Lagrange strains, and lastly calculating the electric field in the deformed dielectric. Based upon the input load, deformation of the dielectric at the minimum bend radius produced an increase in the electric field of more than 12% when compared to the undeformed umbilical cable, which may lead to dielectric breakdown of the insulation prior to mechanical failure of the umbilical cable.

Spencer, Mychal P.↗
DOE OSTI2019

Collaborative Project: An Integrated Parameterization of Boundary Layer and Convective Mixing: The Eddy-Diffusivity/Mass-Flux (EDMF) Approach

The key goal of this project was to reduce cloud modeling deficiencies and biases by developing and implementing a new unified boundary layer and convection parameterization based on the multi-plume Eddy-Diffusivity/Mass-Flux (EDMF) approach. This is a turbulence and convection parameterization that can be considered fully unified, in the sense that it is able to represent convective processes from boundary layer convection to deep moist convection with one single parameterization. This project will ultimately lead to more accurate climate predictions, which have a significant societal impact. In general, turbulence and convection in the atmosphere are at the core of key climate prediction problems. For example: i) to reduce uncertainties in climate projections, it is essential to improve predictions of cloud feedbacks (how clouds respond to, and influence, climate change), which are controlled by the interactions between a turbulent flow with water phase transitions and radiation; (ii) to improve extreme weather prediction under climate change, it is essential to improve our understanding of how moist convection responds to a warmer world. A fully unified boundary layer and convection parameterization, such as EDMF, will help better represent and predict boundary layer, cloud and convection processes in the atmosphere during present and future climate. The following are the specific tasks that were completed and addressed the project’s objectives: i) Implementation and evaluation of the multi-plume EDMF parameterization into the Single Column Model (SCM) version of CESM; ii) Development of a fully unified multi-plume (shallow to deep convection) EDMF parameterization – that is also scale-aware; iii) Implementation and evaluation of the moist multi-plume EDMF scheme in the global version of WRF; iv) Extension and evaluation of the LES model to deep moist convection regimes; v) Implementation of EDMF in the SCM version of the LBL dynamical core.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multiscale Simulation of Precipitation Over East Asia by Variable Resolution CAM-MPAS

This study evaluates the precipitation over East Asia simulated by the variable resolution CAM-MPAS featuring the Model for Prediction Across Scales (MPAS) atmospheric dynamical core coupled with the physics parameterizations of the Community Atmosphere Model (CAM) version 5.4. Two CAM-MPAS experiments, one with a global quasi-uniform resolution mesh of 120 km (MPAS-UR) and the other with a variable resolution mesh of 30 to 120 km refined over East Asia (MPAS-VR), are conducted from 1989 to 2005 following the Atmospheric Model Intercomparison Project protocol. Two regional climate model simulations at ~25 km resolution from the Coordinated Regional Downscaling Experiment East Asia second plan are also analyzed for comparison. Results show that CAM-MPAS performs better than the selected regional models in simulating the precipitation climatology over East Asia. Compared with MPAS-UR, MPAS-VR with refinement over East Asia better simulates the precipitation over and around the Tibetan Plateau (TP), the frequency distribution of light, moderate, and heavy precipitation in various regions of China, and the interannual precipitation pattern associated with the East Asian summer monsoon. The improvements in MPAS-VR relative to MPAS-UR largely come from the decreased grid spacing rather than the use of finer-scale terrain information. Particularly, decreased grid spacing is more essential for simulating the precipitation magnitude over TP and the location of peak precipitation south of TP, likely due to the better resolved physical and dynamical processes associated with orographic precipitation. The 30-120 km CAM-MPAS model is shown to be a promising tool for precipitation simulation over East Asia.

54 ENVIRONMENTAL SCIENCES↗