Search NASA⌕ Search

SEARCH · Search NASA

Results for “COMMUNITY ATMOSPHERE MODEL”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The Response of the South Asian Summer Monsoon to Temporal and Spatial Variations in Absorbing Aerosol Radiative Forcing

Previous studies on the response of the South Asian summer monsoon to the direct radiative forcing caused by anthropogenic absorbing aerosols have emphasized the role of premonsoonal aerosol forcing. This study examines the roles of aerosol forcing in both pre- and postonset periods using the Community Earth System Model, version 1.0.4, with the Community Atmosphere Model, version 4. Simulations were perturbed by model-derived radiative forcing applied (i) only during the premonsoonal period (May–June), (ii) only during the monsoonal period (July–August), and (iii) throughout both periods. Soil water storage is found to retain the effects of premonsoonal forcing into succeeding months, resulting in monsoonal central India drying. Monsoonal forcing is found to dry all of India through local responses. Large-scale responses, such as the meridional rotation of monsoon jet during June and its weakening during July–August, are significant only when aerosol forcing is present throughout both premonsoonal and monsoonal periods. Monsoon responses to premonsoonal forcing by the model-derived “realistic” distribution versus a uniform wide-area distribution were compared. Both simulations exhibit central India drying in June. June precipitation over northwestern India (increase) and southwestern India (decrease) is significantly changed under realistic but not under wide-area forcing. Finally, the same aerosol forcing is found to dry or moisten the July–August period following the warm or cool phase of the simulations’ ENSO-like internal variability. The selection of years used for analysis may affect the precipitation response obtained, but the overall effect seems to be an increase in rainfall variance over northwest and southwest India.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Global Climate Impacts of Fixing the Southern Ocean Shortwave Radiation Bias in the Community Earth System Model (CESM)

Here, a large, long-standing, and pervasive climate model bias is excessive absorbed shortwave radiation (ASR) over the midlatitude oceans, especially the Southern Ocean. This study investigates both the underlying mechanisms for and climate impacts of this bias within the Community Earth System Model, version 1, with the Community Atmosphere Model, version 5 [CESM1(CAM5)]. Excessive Southern Ocean ASR in CESM1(CAM5) results in part because low-level clouds contain insufficient amounts of supercooled liquid. In a present-day atmosphere-only run, an observationally motivated modification to the shallow convection detrainment increases supercooled cloud liquid, brightens low-level clouds, and substantially reduces the Southern Ocean ASR bias. Tuning to maintain global energy balance enables reduction of a compensating tropical ASR bias. In the resulting preindustrial fully coupled run with a brighter Southern Ocean and dimmer tropics, the Southern Ocean cools and the tropics warm. As a result of the enhanced meridional temperature gradient, poleward heat transport increases in both hemispheres (especially the Southern Hemisphere), and the Southern Hemisphere atmospheric jet strengthens. Because northward cross-equatorial heat transport reductions occur primarily in the ocean (80%), not the atmosphere (20%), a proposed atmospheric teleconnection linking Southern Ocean ASR bias reduction and cooling with northward shifts in tropical precipitation has little impact. In summary, observationally motivated supercooled liquid water increases in shallow convective clouds enable large reductions in long-standing climate model shortwave radiation biases. Of relevance to both model bias reduction and climate dynamics, quantifying the influence of Southern Ocean cooling on tropical precipitation requires a model with dynamic ocean heat transport.

58 GEOSCIENCES↗
DOE OSTI2013

Sensitivity of Remote Aerosol Distributions to Representation of Cloud-Aerosol Interactions in a Global Climate Model

Many global aerosol and climate models, including the widely used Community Atmosphere Model version 5 (CAM5), have large biases in predicting aerosols in remote regions such as upper troposphere and high latitudes. In this study, we conduct CAM5 sensitivity simulations to understand the role of key processes associated with aerosol transformation and wet removal affecting the vertical and horizontal long-range transport of aerosols to the remote regions. Improvements are made to processes that are currently not well represented in CAM5, which are guided by surface and aircraft measurements together with results from a multi-scale aerosol-climate model (PNNL-MMF) that explicitly represents convection and aerosol-cloud interactions at cloud-resolving scales. We pay particular attention to black carbon (BC) due to its importance in the Earth system and the availability of measurements. We introduce into CAM5 a new unified scheme for convective transport and aerosol wet removal with explicit aerosol activation above convective cloud base. This new implementation reduces the excessive BC aloft to better simulate observed BC profiles that show decreasing mixing ratios in the mid- to upper-troposphere. After implementing this new unified convective scheme, we examine wet removal of submicron aerosols that occurs primarily through cloud processes. The wet removal depends strongly on the sub-grid scale liquid cloud fraction and the rate of conversion of liquid water to precipitation. These processes lead to very strong wet removal of BC and other aerosols over mid- to high latitudes during winter months. With our improvements, the Arctic BC burden has a10-fold (5-fold) increase in the winter (summer) months, resulting in a much better simulation of the BC seasonal cycle as well. Arctic sulphate and other aerosol species also increase but to a lesser extent. An explicit treatment of BC aging with slower aging assumptions produces an additional 30-fold (5-fold) increase in the Arctic winter (summer) BC burden. This BC aging treatment, however, has minimal effect on other under-predicted species. Interestingly, our modifications to CAM5 that aim at improving prediction of high-latitude and upper tropospheric aerosols also produce much better AOD and AAOD over various other regions globally when compared to multi-year AERONET retrievals. The improved aerosol distributions have impacts on other aspects of CAM5, improving the simulation of global mean liquid water path and cloud forcing.

aerosol↗
DOE OSTI2022

Idealized Simulations of the Tropical Climate and Variability in the Single Column Atmosphere Model (SCAM): Radiative-Convective Equilibrium

To explore the interactions among column processes in the Community Atmosphere Model (CAM), the single-column version of CAM (SCAM) is integrated for 1000 days in radiative-convective equilibrium (RCE) with tropical values of boundary conditions, spanning a parameter or configuration space of model physics versions (v5 vs. v6), vertical resolution (standard and 60 levels), sea surface temperature (SST), and some interpretation-driven experiments. The simulated time-mean climate is reasonable, near observations and RCE of a cyclic cloud-resolving model. Updraft detrainment in the deep convection scheme produces distinctive grid-scale structures in humidity and cloud, which also interact with radiative transfer processes. These grid artifacts average out in multi-column RCE results reported elsewhere, illustrating the nuts-and-bolts interpretability that SCAM adds to the hierarchy of model configurations. Multi-day oscillations of precipitation arise from descent of warm convection-capping layers starting near the tropopause, eventually reset by a burst of convective deepening. Experiments reveal how these oscillations depend critically on an internal parameter that controls the number of neutral buoyancy levels allowed for determining cloud top and computing dilute convective available potential energy in the deep convection scheme, and merely modified a little by disabling cloud-base radiation (heating of cloud base). This strong dependence of transient behavior in 1D on this parameter will be tested in the second part of this work, in which SCAM is coupled to a parameterized dynamics of two-dimensional, linearized gravity wave, and in the 3D simulations in future study.

Meteorology & Atmospheric Sciences↗
DOE OSTI2015

Final Report. Evaluating the Climate Sensitivity of Dissipative Subgrid-Scale Mixing Processes and Variable Resolution in NCAR's Community Earth System Model

The goals of this project were to (1) assess and quantify the sensitivity and scale-dependency of unresolved subgrid-scale mixing processes in NCAR’s Community Earth System Model (CESM), and (2) to improve the accuracy and skill of forthcoming CESM configurations on modern cubed-sphere and variable-resolution computational grids. The research thereby contributed to the description and quantification of uncertainties in CESM’s dynamical cores and their physics-dynamics interactions.

58 GEOSCIENCES↗
DOE OSTI2016

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the C ommunity E arth S ystem M odel

Abstract This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super‐Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual‐mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double‐ITCZ bias. However, unfolding intensity distributions reveal several improvements in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden‐Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM's low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved‐scale processes in CAM, few differences discriminate the rainfall properties of the two models. These results are discussed in light of their implication for future rainfall changes in response to climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A new and inexpensive non-bit-for-bit solution reproducibility test based on time step convergence (TSC1.0)

A test procedure is proposed for identifying numerically significant solution changes in evolution equations used in atmospheric models. The test issues a fail signal when any code modifications or computing environment changes lead to solution differences that exceed the known time step sensitivity of the reference model. Initial evidence is provided using the Community Atmosphere Model (CAM) version 5.3 that the proposed procedure can be used to distinguish rounding-level solution changes from impacts of compiler optimization or parameter perturbation, which are known to cause substantial differences in the simulated climate. The test is not exhaustive since it does not detect issues associated with diagnostic calculations that do not feedback to the model state variables. Nevertheless, it provides a practical and objective way to assess the significance of solution changes. The short simulation length implies low computational cost. The independence between ensemble members allows for parallel execution of all simulations, thus facilitating fast turnaround. The new method is simple to implement since it does not require any code modifications. We expect that the same methodology can be used for any geophysical model to which the concept of time step convergence is applicable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Impacts of cloud superparameterization on projected daily rainfall intensity climate changes in multiple versions of the Community Earth System Model

Abstract Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high‐order statistics of present‐day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter‐Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high‐order statistics are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale‐insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (∼2°) versions of CAM are not able to capture the response simulated with higher resolution (∼1°). Moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Sensitivity of Tropospheric Chemical Composition to Halogen-Radical Chemistry Using a Fully Coupled Size-Resolved Multiphase Chemistry-Global Climate System: Halogen Distributions, Aerosol Composition, and Sensitivity of Climate-Relevant Gases

Observations and model studies suggest a significant but highly non-linear role for halogens, primarily Cl and Br, in multiphase atmospheric processes relevant to tropospheric chemistry and composition, aerosol evolution, radiative transfer, weather, and climate. The sensitivity of global atmospheric chemistry to the production of marine aerosol and the associated activation and cycling of inorganic Cl and Br was tested using a size-resolved multiphase coupled chemistry/global climate model (National Center for Atmospheric Research’s Community Atmosphere Model (CAM); v3.6.33). Simulation results showed strong meridional and vertical gradients in Cl and Br species. The simulation reproduced most available observations with reasonable confidence permitting the formulation of potential mechanisms for several previously unexplained halogen phenomena including the enrichment of Br- in submicron aerosol, and the presence of a BrO maximum in the polar free troposphere. However, simulated total volatile Br mixing ratios were generally high in the troposphere. Br in the stratosphere was lower than observed due to the lack of long-lived organobromine species in the simulation. Comparing simulations using chemical mechanisms with and without reactive Cl and Br species demonstrated a significant temporal and spatial sensitivity of primary atmospheric oxidants (O3, HOx, NOx), CH4, and non-methane hydrocarbons (NMHC’s) to halogen cycling. Simulated O3 and NOx were globally lower (65% and 35%, respectively, less in the planetary boundary layer based on median values) in simulations that included halogens. Globally, little impact was seen in SO2 and non-sea-salt SO42- processing due to halogens. Significant regional differences were evident: The lifetime of nss-SO42- was extended downwind of large sources of SO2. The burden and lifetime of DMS (and its oxidation products) were lower by a factor of 5 in simulations that included halogens, versus those without, leading to a 20% reduction in nss-SO42- in the southern hemisphere planetary boundary layer based on median values.

chemical composition↗
DOE OSTI2014

Algorithmically scalable block preconditioner for fully implicit shallow-water equations in CAM-SE

Performing accurate and efficient numerical simulation of global atmospheric climate models is challenging due to the disparate length and time scales over which physical processes interact. Implicit solvers enable the physical system to be integrated with a time step commensurate with processes being studied. The dominant cost of an implicit time step is the ancillary linear system solves, so we have developed a preconditioner aimed at improving the efficiency of these linear system solves. Our preconditioner is based on an approximate block factorization of the linearized shallow-water equations and has been implemented within the spectral element dynamical core within the Community Atmospheric Model (CAM-SE). Furthermore, in this paper we discuss the development and scalability of the preconditioner for a suite of test cases with the implicit shallow-water solver within CAM-SE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The atmospheric hydrologic cycle in the ACME v0.3 model

We examine the global water cycle characteristics in the Accelerated Climate Modeling for Energy v0.3 model (a close relative to version 5.3 of the Community Atmosphere Model) in atmosphere-only simulations spanning the years 1980–2005. We evaluate the simulations using a broad range of observational and reanalysis datasets, examine how the simulations change when the horizontal resolution is increased from 1° to 0.25, and compare the simulations against models participating in the the Atmosphere Model Intercomparison Project of the 5th Coupled Model Intercomparison Project (CMIP5). Particular effort has been made to evaluate the model using the best available observational estimates and verifying model biases with additional datasets when differences are known to exist among the observations. Regardless of resolution, the model exhibits several biases: global-mean precipitation, evaporation, and precipitable water are too high, light precipitation occurs too frequently, and the atmospheric residence time of water is too short. Many of these biases are shared by the multi-model mean climate of models participating in CMIP5. The reasons behind regional biases in precipitation are discussed by examining how different fields, such as local evaporation and transport of water vapor, contribute to the bias. Although increasing the horizontal resolution does not drastically change the water cycle, it does lead to a few differences: an increase in global mean precipitation rate, an increase in the fraction of total precipitation that falls over land, more frequent heavy precipitation (>30 mm day -1 ), and a decrease in precipitable water. One of the most notable changes is the shift of precipitation produced by the convective parameterization to that produced by the large-scale microphysics parameterization. We analyze how changes in moisture and circulation with resolution contribute to this shift in the precipitation partitioning. Because changing horizontal resolution requires some re-tuning, the effect of that tuning was evaluated by performing an additional simulation at 1 but using the tunings from the 0.25 simulation. In conclusion, the evaluation shows that the more frequent heavy precipitation, the decrease in precipitable water, and the shift from convective to large-scale precipitation are predominantly due to resolution changes, while tuning changes have a major influence on the global mean precipitation and the land/ ocean partitioning of precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Influence of Atmospheric Rivers on Mountain Snowpack in the Western U.S.

In the coastal mountain regions of western North America, most extreme precipitation is associated with atmospheric rivers, narrow bands of moisture originating in the tropics. Here we quantify how the interannual variability in atmospheric rivers influences snowpack in the western United States in observations and a model. We simulate the historical climate with the Model for Prediction Across Scales with physics from the Community Atmosphere Model Version 5 (MPAS-CAM5) using prescribed sea surface temperatures. In the global variable resolution domain, regional refinement (at 30 km) is applied to our region of interest over western North America and upwind over the northeast Pacific. To better characterize internal variability, we conduct simulations with three ensemble members over 30 years of the historical period. In the Cascade Mountains, with some exceptions, winters with more atmospheric river days are associated with less snowpack. In California’s Sierra Nevada the sign is the opposite. In observations, the results are consistent in winter, but statistically significant only for California. In spring, internal variance plays an important role in determining the sign of the relationship between number of atmospheric river days and snowpack. Cumulative atmospheric river days starting in winter through spring, on the other hand, yield a spring relationship with the same sign as the winter one for a given location. Thus, the impact of atmospheric rivers on winter snowpack has a greater influence on spring snowpack than spring atmospheric rivers, in the model for both regions and in California consistently in observations.

Goldenson, Naomi L.↗
DOE OSTI2014

The Robust Dynamical Contribution to Precipitation Extremes in Idealized Warming Simulations across Model Resolutions

The impact of the circulation shift under climate warming on the distribution of precipitation extremes and the associated sensitivity to model resolution are investigated using the aquaplanet Community Atmosphere Model CAM3. The response of the probability density function of the precipitation to a uniform SST warming can be interpreted as superimposition of a dynamically induced poleward shift and a thermodynamically induced upward shift toward higher intensities, which give rise to manyfold increase in the frequency of the most extreme categories of the precipitation events at the poleward side of the midlatitude storm track. Meanwhile, the thermodynamic contribution to the intensification of the precipitation extremes is substantially less than expected from the Clausius-Clapeyron relation, implicative of significant change in the vertical structure of the precipitation processes. While coarser resolutions underestimate the dynamical contribution to the increase of precipitation extremes, a modest increase of the equator-to-pole SST warming gradient can have a significant opposite effect.

dynamical↗
DOE OSTI2015

Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison

Aerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate-air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF-CAM5) to simulate aerosol-cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near-surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO 2 , NO 2 , HCHO, and O 3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NO x at all sites and SO 2 , O 3 , PM 2.5 , and PM 10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul-Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107–113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation, shortwave cloud forcing, and precipitation. Here, the model evaluation identifies several areas of improvements including emissions and their vertical allocation as well as model formulations such as aerosol formation, cloud droplet nucleation, and ice nucleation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Analysis of secondary organic aerosol simulation bias in the Community Earth System Model (CESM2.1)

Organic aerosol (OA) has been considered as one of the most important uncertainties in climate modeling due to the complexity in presenting its chemical production and depletion mechanisms. To better understand the capability of climate models and probe into the associated uncertainties in simulating OA, we evaluate the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 (CAM6) with comprehensive tropospheric and stratospheric chemistry representation (CAM6-Chem) through a long-term simulation (1988–2019) with observations collected from multiple datasets in the United States. We find that CESM generally reproduces the interannual variation and seasonal cycle of OA mass concentration at surface layer with a correlation of 0.40 compared to ground observations and systematically overestimates (69%) in summer and underestimates (-19%) in winter. Through a series of sensitivity simulations, we reveal that modeling bias is primarily related to the dominant fraction of monoterpene-formed secondary organic aerosol (SOA), and a strong positive correlation of 0.67 is found between monoterpene emission and modeling bias in the eastern US during summer. In terms of vertical profile, the model prominently underestimates OA and monoterpene concentrations by 37%–99% and 82%–99%, respectively, in the upper air (>500 m) as validated against aircraft observations. Our study suggests that the current volatility basis set (VBS) scheme applied in CESM might be parameterized with monoterpene SOA yields that are too high, which subsequently results in strong SOA production near the emission source area. We also find that the model has difficulty in reproducing the decreasing trend of surface OA in the southeastern US probably because of employing pure gas VBS to represent isoprene SOA which is in reality mainly formed through multiphase chemistry; thus, the influence of aerosol acidity and sulfate particle change on isoprene SOA formation has not been fully considered in the model. This study reveals the urgent need to improve the SOA modeling in climate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Convective response to large-scale forcing in the tropical western Pacific simulated by spCAM5 and CanAM4.3

Changes in the large-scale environment during convective precipitation events in the tropical western Pacific simulated by version 4.3 of the Canadian Atmospheric Model (CanAM4.3) are compared against those simulated by version 5.0 of the super-parameterized Community Atmosphere Model (spCAM5). This is done by compositing sub-hourly output of convective rainfall, convective available potential energy (CAPE), CAPE generation due to large-scale forcing in the free troposphere (dCAPE LSFT ) and near-surface vertical velocity ( ω ) over the time period May–July 1997. Compared to spCAM5, CanAM4.3 tends to produce more frequent light convective precipitation ( <0.2 mm h -1 ) and underestimates the frequency of extreme convective precipitation ( >2 mm h -1 ). In spCAM5, 5 % of convective precipitation events lasted less than 1.5 h and 75 % lasted between 1.5 and 3.0 h, while in CanAM4.3 80 % of the events lasted less than 1.5 h. Convective precipitation in spCAM5 is found to be a function of dCAPE LSFT and the large-scale near-surface ω with variations in ω slightly leading variations in convective precipitation. Convective precipitation in CanAM4.3 does not have the same dependency and instead is found to be a function of CAPE.

58 GEOSCIENCES↗
DOE OSTI2026

TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high-performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. In a proof-of-concept integration with the particle-resolved model PartMC, TChem-atm reproduces the existing PartMC–CAMP implementation within solver tolerances and delivers substantial GPU speedups, especially for large particle populations. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. TChem-atm enables performance-portable execution across CPUs and GPUs, though optimal efficiency may require modest architecture-specific tuning (e.g., team and vector sizes), with up to a twofold improvement on the NVIDIA H100. It directly supports sectional and particle-resolved host models, while modal aerosol schemes require minor adaptation to provide particle-scale quantities such as representative diameters. By enabling chemically detailed, multiphase simulations with performance portability and host-model flexibility, TChem-atm facilitates the incorporation of advanced chemistry into atmospheric models.

Díaz-Ibarra, Oscar Homero [Sandia National Laborat↗
DOE OSTI2017

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↗