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At least 181 records · Page 10

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM(post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat- Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 gm22 lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

General circulation models

Validation of Quasi-Invariant Ice Cloud Radiative Quantities with MODIS Satellite-Based Cloud Property Retrievals

Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If t(1v) and t(1vg) are conserved where t is optical thickness, v the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1wg)factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1w)(1(exp. 1/2)wg)]12, also tend to be similar.

Radiative transfer

Investigating Aerosol and Meteorological Influences on Convective Clouds in Houston, Texas, during the TRACER/ESCAPE Field Campaigns

Aerosols serve as cloud condensation nuclei, shaping the microphysical properties of cloud droplets. Aerosol effects on convective clouds are complex and remain controversial. The debate centers around the process of aerosol-induced invigoration of deep convection, a phenomenon that could significantly affect convective cloud properties but lacks robust evidence due to methodological limitations in observational approaches and questions about the robustness of modeling studies. Resolving these discrepancies is crucial for understanding how aerosols affect the atmosphere. Here, this study examines the effects of meteorological and aerosol parameters in a weakly synoptic-driven convective environment, where the influence of aerosols may be more pronounced and observable. Daily atmospheric soundings and aerosol concentrations from several ground instruments collected during the summer of 2022 in Houston, Texas, as part of the Tracking Aerosol Convection interactions Experiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) field campaigns are analyzed. Statistical learning methods are applied to uncover the complex relationships between aerosols, meteorology, and convective cloud characteristics, such as cell area and echo-top height. The findings reveal that higher aerosol concentrations are associated with narrower convective cells, which we argue contradicts the idea of stronger convection with increased aerosol loading. However, once the data are clustered by the synoptic environment, the relationship between aerosol loading and convective cell area diminishes, indicating that the covariablity between synoptic-scale weather patterns, local thermodynamics, and aerosol loading makes it challenging to draw definitive conclusions about the specific impacts of aerosols on convective cloud properties.

54 ENVIRONMENTAL SCIENCES

Evaluation of E3SM Simulated Aerosols and Aerosol‐Cloud Interactions Across GCM and Convection‐Permitting Scales

This paper introduces an Earth system modeling testbed for predicting aerosols and aerosol‐cloud interactions (ACIs) at convection‐permitting scales. Using the Energy Exascale Earth System Model (E3SM) version 2 with a four‐mode Modal Aerosol Module, we conduct simulations at 3.25 km resolution on a regionally refined mesh (RRM) across four regions with distinct aerosol and cloud regimes. Results are compared with the standard 100 km E3SM configuration and evaluated against satellite, aircraft, and ground‐based observations. We find that increasing model resolution improves heavy precipitation simulation but amplifies positive bias in light drizzle at coarse resolution. These resolution‐induced changes affect cloud and aerosol properties to varying degrees across regions. Generally, cloud cover and liquid water path (LWP) show better agreement with satellite retrievals at 3.25 km, though surface‐based comparisons suggest otherwise. Aerosol composition remains poorly represented at both resolutions. The RRM increases Aitken mode aerosol number concentrations via enhanced new particle formation. However, accumulation mode aerosols are decreased at higher resolution as aerosol removals become more efficient. This partially contributes to fewer cloud condensation nuclei (CCN) and lower cloud droplet number concentrations (N d ), which produces larger model biases in some scenarios. These findings suggest that solely increasing horizontal resolution to kilometer scales is insufficient to broadly improve aerosol and cloud predictions without concurrent advancements in physical and chemical process representations. Nonetheless, the RRM moderately improves key ACI relationships such as CCN‐N d correlation, reflecting enhanced aerosol activation representation. The LWP‐N d relationship is also better captured by RRM, suggesting a better characterization of LWP adjustment.

Huang, Meng [Pacific Northwest National Laboratory

Towards retrieving cloud top entrainment velocities from MISR cloud motion vectors

Although important, direct retrievals of entrainment rates in cloud-topped planetary boundary layer (PBL) remain elusive. Here we present a novel technique for retrieving cloud-top entrainment velocities using only Multi-angle Imaging Spectro-Radiometer (MISR) stereoscopic retrievals of cloud-motion vectors (CMVs) and cloud-top heights (CTHs). Mesoscale vertical air velocity at CTH is diagnosed from the continuity equation and then used to derive entrainment velocities from the PBL mass-budget equation. The algorithm is demonstrated through a case of marine stratocumulus deck off the California coast, with comparisons made against data from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis (ERA5) and the data from other satellites. MISR low-cloud CTH for this case were lower than the ERA5 reported PBL depth by 189 ± 87 m. These differences in cloud top heights partly modulate the differences in the ERA5 and MISR horizontal winds, with larger differences in meridional over zonal wind components. Average difference between ERA5 and MISR derived mesoscale vertical air motion at cloud top was 0.14 ± 0.73 cm s −1 , while the same for entrainment rate was −0.09 ± 0.46 cm s −1 . The uncertainties in the utilized CTHs and CMVs are propagated to derive systematic and random retrieval uncertainties. Fractional uncertainty is lower than 25 % when the retrieved mesoscale vertical air motion is stronger than ±0.04 cm s −1 and entrainment velocities are stronger than ±0.03 cm s −1 . These results showcase the ability to derive mesoscale vertical air motion and entrainment rates from MISR observations and motivate its extension to generate a global climatology leveraging its full 23-year record (2000–2022). Nonetheless comprehensive validation of the retrievals is warranted through comparisons with estimates from an independent dataset across diverse weather conditions.

Mitra, Arka [Argonne National Laboratory (ANL), Ar

Stratocumulus cloud field reflected fluxes - The effect of cloud shape

The reflected fluxes of stratocumulus cloud fields are calculated as a function of sky cover aspect ratio and cloud shape. In order to obtain a better fit with general circulation models (GCMs), cloud liquid water volume values were kept invariant relative to cloud shape. On the basis of the required accuracy of the Earth Radiation Budget Experiment (ERBE), an order of magnitude value of 10 W per sq m was used to estimate the difference between plane-parallel and broken cloudiness reflected fluxes. An empirical relationship for effective cloud cover at a solar zenith angle of 60 deg is derived. The relationship allows for the accurate computation of broken cloud field reflected fluxes using plane-parallel calculations. It is predicted that more accurate estimates of broken cloud field radiative properties may be possible in the future.

Welch, R. M.

Cloud fraction and cloud size distributions derived using Landsat Multispectral Scanner data

Initial results are presented on the spatial structure of cumulus cloud fields derived using Landsat digital data. Techniques to determine clear, overcast, and cloud edge pixels are discussed and used to analyze four Landsat scenes. Cloud number densities, cloud cover, cloud aspect ratio, and the ratio of interior to cloud edge pixels are obtained for the four scenes and are discussed. This new application of Landsat digital data should prove useful in developing and testing models of the radiative and dynamical properties of cumulus cloud fields on GCM spatial scales.

Wielicki, B. A.

Cloud field reflectance variations traceable to finite cloud effects

Variations in cloud field reflectances resulting from the organization of clouds within a cloud field are examined using a cloud field optical simulator. The problem of changing spot size is studied as a function of view angle for a fixed field of view detector. Also, problems associated with the assumption of isotropy are discussed and the effect of cloud interactions within cloud fields is investigated. The results show that radiance variation increases when the photodiodes measure radiances from portions of cloud fields which move in and out of the fields of view as the position of the photodiode changes. In addition, the experiments reveal several factors that are important in the determination of accurate reflectances.

Alberta, Timothy L.

Clustered or regular cumulus cloud fields - The statistical character of observed and simulated cloud fields

The spatial distribution of cumulus clouds is assumed to be the result of the effects of convective activity on the thermodynamic environment. The effects can be parameterized in terms of a stabilization function representing the time rate of change of convective available potential energy. Using these results, a new inhibition hypothesis explaining the expected characteristics of the spatial distribution of cumulus clouds is postulated. This paper performs a verification of the inhibition hypothesis on real and simulated cloud fields. In order to do so, an objective measure of the spatial characteristics of cumulus clouds is introduced. Multiple cloud experiments are performed with a three-dimensional numerical cloud model. Skylab pictures of real cumuli are also used in the verification. Results of applying this measure to simulated and observed cumulus cloud fields confirm the inhibition hypothesis.

Ramirez, Jorge A.

Global, seasonal cloud variations from satellite radiance measurements. II - Cloud properties and radiative effects

Cloud and surface radiative properties and their effects on the earth and surface radiation budgets are obtained based on global daily visible and IR radiance measurements. The magnitude of cloud property variations and their effects on radiation increase strongly with decreasing space/time scales. Cloud properties are systematically different between land and ocean, with ocean having larger cloud cover with somewhat larger optical thicknesses and lower cloud top altitudes. Although cloud variations appear to be the primary cause of regional radiation budget variability at 5-30 daytime scales, the effects of their seasonal variations at larger spatial scales are less important than the changes associated with changes in solar declination and atmospheric/surface temperatures. The largest seasonal variations in radiation occur in the 30-60 deg latitude band in each hemisphere. Although clouds have a net cooling effect on the global, annual mean radiation balance at both the top of the atmosphere and the surface, their net effect on regional, seasonal balances is much more varied.

Rossow, William B.

A technique for determining cloud free vs cloud contaminated pixels in satellite imagery

Since the first earth orbiting satellite sent pictures of the earth back to them, atmospheric scientists have been focused on the possibilities of using that information as both a forecasting tool and as a meteorological research tool. With the latest generation of Geostationary Operational Environmental Satellites (GOES) now entering service, that view of the earth yields views at a frequency and resolution never before available. These satellites have imagers with a five band multi-spectral capability with high spatial resolution. In addition, the sounder has eighteen thermal infrared (IR) channels plus one low-resolution visible band. With a resolution as small as one kilometer, GOES provides scientists with a powerful eye on the atmosphere. Menzel and Purdom (1994) detail both the imager and sounder capability as well as other systems on the GOES satellites. Immediately apparent in the visible channel are the patterns of clouds swirling over both oceans and continents. These clouds range in size from huge planetary systems covering thousands of kilometers to puffy fair weather cumulus clouds on the order of half a kilometer in size. With the IR sensors temperature patterns are observed. High clouds appear very cold, while low stratus field show temperatures near that of the surface. The surface, in turn, generally appears warmer than the clouds. It would seem then a simple manner to determine cloud and surface temperature from the imagery, but such is not the case. While most of the atmospheric constituents are well mixed and homogeneous, water vapor is not. The water molecule, because of its unique structure and vibration modes, affects the transmittance of the atmosphere most notably in the infrared regions. There are regions of the IR spectrum where water vapor acts as a strong absorber, and at others it is nearly transparent. The transparent wavelengths are called windows, and one such window occurs at 11.2 microns. Adjacent to this window at 12.7 microns which is strongly absorbed by water vapor. These two wavelengths form what is known as a split window, the utility of which was used. Using the linearized form of the radiative transfer equation, they were able to use the split window to determine the amount of water vapor present in the atmosphere. Jedlovec developed the physical split-window (PSW) technique which determines the integrated water content (IWC). The PSW method using Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) found on the older versions of the GOES satellites was used. Recently, Jedlovec and colleagues have been attempting to apply the PSW method using full disk IR imagery obtained by the new generation of GOES satellites. IWC is essential for improved analysis and prediction of convective storms which have been observed to develop in regions of both strong and rapidly evolving moisture gradients. It has also been used in the prediction of clouds and precipitation.

Wohlman, Richard A.

A Quantitative Investigation of Entrainment and Detrainment in Numerically Simulated Convective Clouds: Simulations of Cumulonimbus Clouds - Pt. 2

Deep cumulonimbus clouds are simulated using a model that makes accurate diagnoses of entrainment and detrainment rates and of the properties of entrained and detrained air. Clouds generated by a variety of initial thermodynamic soundings are compared. In the simulations, updraft entrainment rates are large near and above cloud base, through the entire depth of the conditionally unstable layer. Stronger updrafts in a more unstable environment are better able to entrain relatively undisturbed environmental air, while weaker updrafts can entrain only air that has been modified by the clouds. When the maximum buoyancy is large, the updraft includes parcels with a wide range of buoyancies, while weaker clouds are more horizontally uniform. Strong downdrafts originate from levels at which updrafts detrain, and their mass flux depends on the mass flux of the updraft. The magnitude of mixing between cloud and environment, not the entrainment rate, varies inversely with the cloud radius. How much of the mixed air is entrained depends on the buoyancy.

Cohen, Charles

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Tao, Wei-Kuo

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Tao, Wei-Kuo

Microphysical Timescales in Clouds and their Application in Cloud-Resolving Modeling

Computational phenomena (i.e., spurious supersaturation and negative mixing ratio of cloud water) usually exist in cloud-resolving models when the time step for explicit integration is larger than a microphysical timescale in clouds. In this paper, the microphysical timescales in clouds are studied, showing that the timescale of water vapor condensation (or cloud water evaporation) is smaller than 10 s - the order of a typical time step for cloud-resolving models. To avoid spurious computational phenomena in cloud-resolving modeling, it is suggested that moist entropy be used as a prognostic thermodynamic variable, and temperature be diagnosed from that and other prognostic variables. A simple numerical model with moist entropy as a prognostic variable, for example, is presented to show that spurious computational phenomena are removed when moist entropy is used as a prognostic variable.

Zeng, Xi-Ping

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

Tao, Wei-Kuo

A Hierarchical Modeling Study of the Interactions Among Turbulence, Cloud Microphysics, and Radiative Transfer in the Evolution of Cirrus Clouds

This project used a hierarchy of cloud resolving models to address the following science issues of relevance to CRYSTAL-FACE: What ice crystal nucleation mechanisms are active in the different types of cirrus clouds in the Florida area and how do these different nucleation processes influence the evolution of the cloud system and the upper tropospheric humidity? How does the feedback between supersaturation and nucleation impact the evolution of the cloud? What is the relative importance of the large-scale vertical motion and the turbulent motions in the evolution of the crystal size spectra? How does the size spectra impact the life-cycle of the cloud, stratospheric dehydration, and cloud radiative forcing? What is the nature of the turbulence and waves in the upper troposphere generated by precipitating deep convective cloud systems? How do cirrus microphysical and optical properties vary with the small-scale dynamics? How do turbulence and waves in the upper troposphere influence the cross-tropopause mixing and stratospheric and upper tropospheric humidity? The models used in this study were: 2-D hydrostatic model with explicit microphysics that can account for 30 size bins for both the droplet and crystal size spectra. Notably, a new ice crystal nucleation scheme has been incorporated into the model. Parcel model with explicit microphysics, for developing and evaluating microphysical parameterizations. Single column model for testing bulk microphysics parameterizations

Curry, Judith