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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A Public-Private-Academic Partnership to Advance Solar Power Forecasting

Executive Summary NOAA is making major contributions to the solar forecasting project in three areas. First, it is improving its forecasts of solar irradiance, clouds, and aerosols in its numerical weather prediction models. Second, it is providing advanced satellite products for DOE's FOA awardees to use in their forecast systems. Third, it is using high-quality ground-based measurements from SURFRAD and ISIS stations to verify and validate forecast model output. This reports covers results from all three areas for the period May 1, 2014 - April 30, 2015. Modeling In its modeling effort, NOAA continues work to improve the skill of solar forecasts from the Earth System Research Lab (ESRL) research versions of the 13-km Rapid Refresh (RAP) and the 3-km High-Resolution Rapid Refresh (HRRR) models, which are in turn transitioned into operations at the National Centers for Environmental Prediction (NCEP). A major milestone was achieved in September 2014 with the initial operational implementation of the HRRR at NCEP. In the ESRL research versions of the models, testing and development, in both real-time runs and retrospective experiments, is guided by an extensive in-house verification system. Early in the SFIP project, we developed the capability to verify our model forecasts against the high-quality surface radiation measurements from the SURFRAD and ISIS networks. This highlighted some shortcomings with the RAP and HRRR forecasts of incoming shortwave radiation. Most of our effort during Phase 1 of SFIP was focused on addressing these problems with a variety of model system improvements. The RAP and HRRR models during the warm season of 2014 had a noticeable warm and dry bias in near-surface conditions over most of the central and eastern United States, and our new SURFRAD/ISIS verification revealed that there was also a large excess of incoming global horizontal irradiance in the models. We hypothesized that a lack of cloud cover (particularly low-level cloud cover) in the models was resulting in too much heating of the land surface. This, in turn, caused unrealistically strong surface heat fluxes and turbulent mixing in the planetary boundary layer (PBL), which further reduced the already deficient cloud cover. We addressed these issues with a combination of data assimilation system modifications and model physics improvements. Many of our data assimilation changes were made with a view towards improving the near-term representation of clouds and precipitation. One of these changes involved better accounting for regions of weak reflectivity in the RAP cloud / hydrometeor assimilation system, in order to improve the representation of light precipitation in the RAP initial conditions and provide more realistic initial cloud cover. Additional modifications more accurately accounted for radar beam blockage and data gaps (particularly in the western United States), which improves shorter lead times forecasts of clouds and precipitation. We have also tested the assimilation of new data sources within the RAP and the HRRR, including radar radial velocity data and surface mesonet observations. Within the HRRR, we have tested the cycling of the 3-km land surface fields to allow a higher-resolution treatment of land surface processes. In terms of model physics development for SFIP, we have implemented a shallow cumulus scheme within the RAP, and have made numerous improvements to the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme to address insufficient low-level cloud cover in the models. We have conducted tests incorporating the radiation effects of (parameterized) boundary-layer clouds within the modified MYNN PBL scheme (independent of the convective schemes). The Grell-Freitas-Olson shallow cumulus scheme has also been tested within the 3-km HRRR. Finally, we have also modified the RUC land surface model (LSM) treatment of the vegetation wilting point, reducing it to increase evapotranspiration and increase cloud cover in the boundary layer. All of these changes work in tandem to significantly improve the model forecasts of cloud cover, incoming shortwave radiation, and near-surface temperature and moisture. Satellite The role of NOAA/NESDIS in the Solar Forecasting Improvement Project is to provide Advanced Satellite Products (ASPs) for the two forecasting teams at NCAR and IBM. The ASPs are cloud, surface, and atmosphere products derived from geostationary satellite imagery at the highest possible spatial and temporal resolution - such quantities as cloud mask, cloud probability, cloud transmission, cloud top height, cloud top temperature, cloud effective particle size, etc. Ancillary data, such as elevation and numerical weather prediction fields are provided in the files at the same resolution as well. There are at this time 147 different variables in the ASP output, including quality flags and processing information. The main goals for Year 1 of the project were to implement an Advanced Satellite Products system for the use of the IBM and NCAR teams, begin validation, and make any needed changes based on feedback from the teams. ASP files are being produced every GOES Imager acquisition, which occur on a 15-30 minute schedule. Processing is done on a dedicated computer, with a turn-around time of 8-21 minutes from image acquisition to results available on ftp. Several helpful visualizations of the data are also created for users on web pages. Users have been provided with a document titled "User's Guide for 1km Cloud Products Derived from GOES Imager Data using CLAVR-x", which discusses the basics of the source imagery, the process by which it is turned into Advanced Satellite Products, and considerations users should make when using the data. Validation of selected variables from the older 4km version of the products was also included. Future work will concentrate on validation of the 1km products and improving the turn-around time, product variety, and product quality as needed. Ground Observations In the ground-based measurement effort, NOAA's main objectives are to provide high quality radiation products for validation and verification of short-term to day-ahead solar forecasts. More specifically for the three year project, our goals include (1) Maintaining and providing data from our 7 SURFRAD and 7 ISIS; (2) Update ISIS radiation measurements from 3 min to 1 min data: (3) Purchase and install new pyrheliometers for direct solar irradiance measurements at the 7 SURFRAD sites; (4) Building, testing, and deploying two mobile SURFRAD stations at two utility plants in collaboration with DOE sponsored partners, and includes ongoing maintenance and processing of the data at the mobile sites; (5) Upgrading the data acquisition and communications at 7 SURFRAD sites and 7 ISIS sites; (6) Providing radiation data at the 7 SURFRAD sites in near real-time; (7) Develop and provide aerosol optical depth and cloud images and cloud fraction at our two mobile sites; (8) Provide data recovery rates each year; (9) Provide temporally and spatially averaged radiation products for comparison to HRRR and RAP solar forecasts and advanced satellite products; (10) Provide a data-set for analysis of conversion of direct and diffuse to sloped surfaces; (11) and as time permits develop and provide spectral solar irradiance, cloud optical depth and spectral albedo from the mobile sites. Milestones this year include working with the DOE sponsored teams to find locations to deploy two mobile SURFRAD stations. One existing unit was deployed at a 30MW PV facility in the San Luis Valley in collaboration with Xcel and the NCAR team in August, 2014. The second unit was built and tested at our facilities in Boulder, CO and deployed near Green Mountain Power's Education Center in Rutland, VT in collaboration with Green Mountain Power and the IBM Team in October, 2014. Data processing was implemented and the radiation data from these two mobile sites have been made available on our ftp server in near real-time. We also are providing images and cloud fraction from the TSI cameras for these two mobile sites on our ftp site. Another milestone was upgrading our data acquisition and communication systems at 7 SURFRAD and 7 ISIS sites. We accelerated our schedule for these upgrades to provide timely radiation products. These upgrades allow more reliable and near-real time radiation data delivery to the DOE sponsored teams to meet their goals. Lastly, we changed the data rate at the ISIS sites from 3 min to 1 min.

14 SOLAR ENERGY↗
DOE OSTI2023

Rainbows and Climate Change: A tutorial on climate model diagnostics and parameterization

Earth System Models (ESMs) must represent processes below the grid scale of a model using representations (parameterizations) of physical and chemical processes. As a tutorial exercise to understand diagnostics and parameterization, this work presents a representation of rainbows for an ESM: the Community Earth System Model version 2 (CESM2). Using the 'state' of the model, basic physical laws, and some assumptions, we generate a representation of this unique optical phenomena as a diagnostic output. Rainbow occurrence and it's possible changes are related to cloud occurrence and rain formation which are critical uncertainties for climate change prediction. The work highlights issues which are typical of many diagnostics parameterizations such as assumptions, uncertain parameters and the difficulty of evaluation against uncertain observations. Results agree qualitatively with limited available global 'observations' of Rainbows. Rainbows are seen in expected locations in the sub-tropics over the ocean where broken clouds and frequent precipitation occurs. The diurnal peak is in the morning over ocean and in the evening over land. The representation of rainbows is found to be quantitatively sensitive to the assumed amount of cloudiness and the amount of stratiform rain. Rainbows are projected to have decreased, mostly in the Northern Hemisphere, due to aerosol pollution effects increasing cloud coverage since 1850. In the future, continued climate change is projected to decrease cloud cover, associated with a positive cloud feedback. As a result the rainbow diagnostic projects that rainbows will increase in the future, with the largest changes at mid-latitudes. The diagnostic may be useful for assessing cloud parameterizations, and is an exercise in how to build and test parameterizations of atmospheric phenomena.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. The chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Evaluating soil moisture feedback on convective triggering: Roles of convective and land–model parameterizations

Feedbacks between soil moisture and convective precipitation are not well represented in current Earth system models, and can affect projections of drought and heavy-precipitation extremes. To explore the atmospheric and land-surface influences on the initiation (triggering) of daytime deep convection, single-column model experiments were performed using the NCAR Community Earth System Model (CESM1.2), over the U.S. Southern Great Plains. The results indicate that the positive and negative feedback mechanisms found in earlier studies (using simplified boundary-layer models) are robust to large-scale forcing and interactions between boundary-layer turbulence, cloud dynamics, and radiation. However, systematic responses of convective triggering to soil moisture emerged only after switching from a convective available potential energy-based to a convective inhibition energy-based convective parameterization. This suggests that the choice of convective mass-flux closure largely determines the sensitivity of parameterized convective clouds to land-surface state. Errors in land-model parameterizations of evapotranspiration also affect the probability of deep convection, with vegetation (transpiration) playing an important role in linking soil moisture to surface energy partitioning and clouds. Parameterizations that permit the triggering feedback mechanism better predict the statistics of daytime shallow and deep convection, with respect to observations from the Atmospheric Radiation Measurement site in the Southern Great Plains. Here, the results illustrate how errors in the representation of evapotranspiration in land-surface models can propagate through the chain of coupled land-atmosphere processes to affect convective clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Parameterization of Turbulent Dissipation and Pressure Damping Time Scales in Stably Stratified Inversions, and its Effects on Low Clouds in Global Simulations

Abstract It is difficult for coarse‐resolution global models of the atmosphere to accurately simulate the observed distribution of low clouds. In particular, it is difficult for moist turbulence closure models to simulate sufficiently bright near‐coastal stratocumulus (Sc) without simulating overly bright marine shallow cumuli (Cu). To parameterize bright Sc, a turbulence parameterization must damp the turbulent fluxes of heat and moisture above cloud top in order to prevent excessive entrainment of dry air into cloud top. To parameterize dim shallow Cu, the subgrid variances of temperature and moisture must remain large, in order to permit partial cloudiness. However, damping the fluxes but not the variances just above cloud top is difficult if a parameterization uses a single “master” time scale to damp both. In nature, the above‐cloud fluxes are damped by pressure fluctuations, whereas scalar variances are damped by a different process, namely, turbulent dissipation. In a stably stratified inversion above cloud, pressure damping is large but turbulent dissipation is small. To avoid this problem, a multitime scale parameterization for damping has been developed. The damping parameterization has been implemented in a global model and evaluated. The parameterization is capable of dimming shallow Cu while producing adequately bright Sc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Transforming ESM Physical Parameterization Development Using Machine Learning Trained on Global Cloud-Resolving Models and Process Observations

ESMs robustly predict that 21st century greenhouse warming will slowly increase global mean precipitation, rapidly increase extreme precipitation, and increase subtropical drought. ESMs agree less about precipitation trends and extremes over particular land regions critical to human societies, e. g. in semi-arid regions such as California or the Sahel, or in wetter climates prone to monsoonal rainfall (e. g. southeast Asia) or to tropical cyclones and flooding from mesoscale convective systems (e. g. the southeastern U.S.) Deep convective parameterizations and poor representation of orography and complex vegetated land surfaces contribute to this inter-model spread; clouds, aerosols and sea-surface temperature biases are also key. Reducing regional precipitation projection uncertainty has enormous planning value for water supplies, land use, wildfire, hydropower, flood control, etc. IPCC-class ESMs are making painfully slow progress on this.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Pluminate: Quantifying aerosol injection behavior from simulation, experimentation and observations

Marine aerosol injections are a key component in further understanding of both the potentials of deliberate injection for marine cloud brightening (MCB), a potential climate intervention (CI) strategy, and key aerosol-cloud interaction behaviors that currently form the largest uncertainty in global climate model (GCM) predictions of our climate. Since the rate of spread of aerosols in a marine environment directly translates to the effectiveness and ability of aerosol injections in impacting cloud radiative forcing, it is crucial to understand the spatial and temporal extent of injected-aerosol effects following direct injection into marine environments. The ubiquity of ship-injected aerosol tracks from satellite imagery renders observational validation of new parameterizations possible in 2D, however, 3D compatible data is more scarce, and necessary for the development of subgrid scale parameterizations of aerosol-cloud interactions in GCMs. This report introduces two novel parameterizations of atmospheric aerosol injection behavior suitable for both 3D (GCM-compatible) and 2D (observation-related) modeling. Their applicability is highlighted using a wealth of different observational data: small and larger scale salt-aerosol injection experiments conducted at SNL, 3D large eddy simulations of ship-injected aerosol tracks and 2D satellite images of ship tracks. The power of experimental data in enhancing knowledge of aerosol-cloud interactions is in particular emphasized by studying key aerosol microphysical and optical properties as observed through their mixing in cloud-like environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Energy Exascale Earth System Model Version 3: 1. Overview of the Atmospheric Component

This paper describes the atmospheric component of the US Department of Energy's Energy Exascale Earth System Model (E3SM) version 3. Significant updates have been made to the atmospheric physics compared to earlier versions. Specifically, interactive gas chemistry has been implemented, along with improved representations of aerosols and dust emissions. A new stratiform cloud microphysics scheme more physically treats ice processes and aerosol‐cloud interactions. The deep convection parameterization has been largely improved with sophisticated microphysics for convective clouds, making model convection sensitive to large‐scale dynamics, and incorporating the dynamical and physical effects of organized mesoscale convection. Improvements in aerosol wet removal processes and parameter re‐tuning of key aerosol and cloud processes have improved model aerosol radiative forcing. The model's vertical resolution has increased from 72 to 80 layers with the extra eight layers added in the lower stratosphere to better simulate the Quasi‐Biennial Oscillation. These improvements have enhanced E3SM's capability to couple aerosol, chemistry, and biogeochemistry and reduced some long‐standing biases in simulating tropical variability. Compared to its predecessors, the model shows a much stronger signal for the Madden‐Julian Oscillation, Kelvin waves, mixed Rossby‐gravity waves, and eastward inertia‐gravity waves. Aerosol radiative forcing has been considerably reduced and is now better aligned with community best estimates, leading to significantly improved skill in simulating historical temperature records. Its simulated mean‐state climate is largely comparable to E3SMv2, but with some notable degradation in shortwave cloud radiative effect, precipitable water, and surface wind stress, which will be addressed in future updates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Role of the Toroidal Vortex in Cumulus Clouds' Entrainment and Mixing

Abstract Shallow convective clouds play a crucial role in Earth's energy budget, as they modulate the radiative transfer in the atmosphere and participate in the vertical transport of aerosols, energy, and humidity. The parameterizations representing these complex, vital players in weather and climate models are mostly based on a description of steady‐state plumes and are a source of major uncertainty. Recently, several studies have shown that buoyant thermals are inherent in atmospheric convection and contain a toroidal (ring) vortex. This work studies those vortices in growing shallow cumulus (Cu) clouds using high‐resolution (10 m) Large Eddy Simulations that resolve these vortices in much detail. Recent analysis of such data showed that small‐scale turbulent diffusion is unable to explain the large diluted portion of the cloud. Here we advocate for the important role of the Cu toroidal vortex (TV) in cloud dilution and present the complex dynamics and structure of a Cu TV. Nevertheless, since the vortex dominates the cloud's dilution, simplicity emerges when considering the cloud's lateral mass flux profile. The cloud mixing is quantified using direct flux calculations and Eulerian tracers. In addition, Lagrangian tracers are used to identify the origin of the entrained air and its thermodynamic properties. It shows that most of the air entrained by the vortex is not recycled by the vortex, yet is significantly more humid than the environment. We suggest that the development of new models describing thermals, together with their toroidal vortices, might improve cloud parameterizations in weather and climate models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2017

Final Technical Report for Award SC0008613

Discovering how aerosol particles, present in the atmosphere in sizes of a few nanometers to hundred micrometers, initiate ice crystal formation represents a great challenge. Atmospheric ice nucleation is important because ice crystals alter the radiative properties of clouds and thus climate, and impact precipitation and thus the hydrological cycle. The difficulty in predicting atmospheric ice formation is attributable at least in part, to the diversity of ice nucleation pathways, the physical and chemical complexity of the ice nucleating particles (INPs), and the relatively small numbers of INPs (compared with all other aerosol particles), sometimes less than one in 100000. These factors in turn makes constraining ice nucleation parameterizations for modeling applications challenging. The majority of airborne particles are known to be organic in nature or contain organic biogenic material. The presence of organic material adds to the complexity of the particles and therefore the predictability of ice nucleation events since the organic species can display different phase states, e.g. liquid or solid, in response to temperature and humidity. The award DE-SC0008613 to PI Prof. Daniel Knopf at Stony Brook University, “Relating the Chemical and Physical Properties of Aerosols to the Water Uptake and Ice Nucleation Potential of Particles Collected During the Carbonaceous Aerosols and Radiative Effects Study (CARES)”, allowed examination of laboratory generated aerosol particles and field-collected particles for their propensity to nucleate ice under typical tropospheric conditions and relate ice nucleation to the physicochemical properties of the particles including their morphology and chemical composition. This in turn allowed for development of ice nucleation parameterizations for implementation in cloud models. The award resulted in 10 peer-reviewed publications and more than 20 seminar and conference presentations. We demonstrated that the rate of immersion freezing, when a particle immersed in an aqueous droplet acts as an ice nucleus (IN), can be predicted by knowledge of the IN particle type present and the droplet’s water activity which is equal to ambient relative humidity. Our water activity based immersion freezing model is successful in predicting freezing data including INPs such as mineral dusts, marine biological material, organic species, and surfactant molecules. Its mathematical simplicity makes it an ideal candidate for implementation in cloud and climate models. Furthermore, we could show that this model can reproduce many past laboratory measurements which were generated using a variety of instruments to study immersion freezing. Lastly, we have demonstrated that this model can also be applied to field collected particles. Currently, this novel physical parameterization of immersion freezing is being implemented in a cloud model. We examined the physicochemical properties and the ice nucleation potential of particles collected during CARES applying a novel experimental method that allows identification of the individual INPs within a large population of particles sampled from an ambient environment. Taking advantage of a variety of micro-spectroscopic techniques, we characterized the composition and morphology of IN and non-IN particles present in the airborne population. We developed a new parameterization for quantifying the mixing state of the entire aerosol populations by introducing a mixing state index. We found that the identified INPs belong to the most common particle-type classes observed in the CARES field samples and as such are not special or rare particles. In other words, the INPs can be shown not to be unique in contrast to the common paradigm of being rare and exceptional. Either there are differences between particles acting as IN and particles not acting as IN which are beyond our current detection limit or nucleation occurs randomly on the surface of any one of these compositionally equivalent particles. These results suggest that total particle surface area of the different particle types present in the aerosol population is also a crucial factor when predicting ice nucleation in an air mass. We also observed that ambient organic aerosol particles can initiate ice nucleation and corroborated these findings using laboratory generated organic particles. These experiments demonstrated that information of the organic phase state is important for predicting the ice nucleation pathway and the ability of an organic particle to participate in atmospheric ice crystal formation. This award resulted in substantial new insights in the processes governing immersion freezing, the role of organic aerosol particles in ice cloud formation, and the importance of the ambient aerosol population for prediction of ice nucleation in an air parcel. These findings have significant implications for modeling and field measurement strategies of atmospheric ice nucleation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Improving Boundary-layer Turbulence and Cloud Processes in CAM with a Higher-order Turbulence Closure Scheme and ASR Measurement

In this study, a simplified intermediately prognostic higher-order turbulence closure (IPHOC) is implemented in the Community Atmosphere Model, version 5 (CAM5), to provide a consistent treatment of subgrid-scale cloud processes, except for deep convection. The planetary boundary layer (PBL) height is prognosticated to better resolve the discontinuity of temperature and moisture above the PBL top. Singlecolumn model tests show that fluxes of liquid water potential temperature and total water, cloud fraction, and liquid water content are improved with this approach. The simplified IPHOC package replaces the boundary layer dry and moist turbulence parameterizations, the shallow convection parameterization, and the liquid-phase part of the cloud macrophysics parameterization in CAM5. CAM5-IPHOC improves the simulation of the low-level clouds off the west coasts of continents and the storm track region in the Southern Hemisphere (SH). The transition from stratocumulus to cumulus clouds is more gradual. There are also improvements on the cloud radiative forcing, especially shortwave, in the subsidence regime. The improvements in the relationships among low cloud amount, surface relative humidity, lower tropospheric stability, and PBL depth are seen in some stratocumulus regions. CAM5-IPHOC, however, produces weaker precipitation at the South Pacific convergence zone than CAM5 because of less energy flux into the SH atmosphere. The more downward surface shortwave radiative cooling and the less top-of-theatmosphere longwave cloud radiative heating in the SH relative to the Northern Hemisphere explains the anomalous cooling and the lesser energy flux into the SH, which is related to the underestimate of extratropical middle/high clouds in the SH.

58 GEOSCIENCES↗
DOE OSTI2025

Quantifying the Resolution Sensitivity of the Kain–Fritsch Scheme Across the Gray Zone by Isolating Interactions: A TWP‐ICE Case Study

The resolution sensitivity of the Kain–Fritsch (KF) convection scheme and the role of interactions between the physics and dynamics within the gray zone (<10 km) were investigated using the Separate Physics and Dynamics Experiment (SPADE) framework. Two groups of experiments were conducted using the Weather Research and Forecasting (WRF) model via traditional (Tradition) runs and SPADE runs with resolutions of 1, 2, 4, and 8 km during the wet period of the Tropical Warm Pool–International Cloud Experiment (TWP‐ICE). Results show that the KF scheme simulates the weakened convective processes well as the resolution increases in both groups, and the changes in the convective variables with resolution in SPADE are smaller than in the Tradition group. This indicates the important effects of interactions between model components on convection parameterizations as the resolution changes. Additionally, the microphysics variables remain nearly unchanged with resolution in SPADE and weaken slightly in Tradition as the resolution decreases, suggesting the relatively weaker influences of model interactions for the resolved‐cloud parameterization. Therefore, the scale‐aware behavior of KF scheme is further strengthened in Tradition runs, primarily through inhibiting the strength of stratiform processes through physics–dynamics interactions and physical components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large-Eddy Simulations of Low-Level Warm Clouds

In numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate (Au), which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local Au is commonly parameterized as a function of DSD moments: cloud droplet number (n c ) and mass (q c ) concentrations. When applied in a large-scale model, the grid-mean Au must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large-eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local Au, as well as its spatial variability. The analysis of an ensemble of warm low-level cloud cases shows that the E3SMv2 formulation represents the Au reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM-tuned local Au rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of n c and its co-variability with q c in parameterizing the grid-mean Au.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Parameterizations of Entrainment-Mixing Mechanisms and their Effects on Cloud Droplet Spectral Width Based on Numerical Simulations

Entrainment-mixing mechanisms significantly affect cloud droplet number concentration, radius, and spectral shape. Quantitative examination of entrainment-mixing effects on cloud droplet spectral width is lacking. Here, we examine the effects of entrainment-mixing processes on cloud microphysics by 12,218 different setups, each simulated 10 times using the Explicit Mixing Parcel Model (EMPM) driven by the observational data from the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) campaign. Parameterizations of entrainment-mixing mechanisms are developed by relating homogeneous mixing degree to transition scale number that depends on the dissipation rate and droplet evaporation time scale. The correlation between relative dispersion of cloud droplet size distribution and homogeneous mixing degree changes from negative to positive with the decreasing homogeneous mixing degree. The different relationships are closely related to the competition between complete and partial droplet evaporation and the number concentration of small droplets, which are quantitatively described by two newly introduced dimensionless numbers. The competition is significantly affected by relative humidity and mixing fraction of entrained air as well as turbulence dissipation rate, but not much by cloud droplet number concentration. Especially, when relative humidity and dissipation rate are high, there is only a negative correlation. This study sheds new light on generalizing the homogeneous/inhomogeneous concept by considering relative dispersion, and also provides parameterizations of entrainment-mixing processes and relative dispersion for atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Drivers of the Low-Cloud Response to Poleward Jet Shifts in the North Pacific in Observations and Models

The long-standing expectation that poleward shifts of the midlatitude jet under global warming will lead to poleward shifts of clouds and a positive radiative feedback on the climate system has been shown to be misguided by several recent studies. On interannual time scales, free-tropospheric clouds are observed to shift along with the jet, but low clouds increase across a broad expanse of the North Pacific Ocean basin, resulting in negligible changes in total cloud fraction and top-of-atmosphere radiation. Here it is shown that this low-cloud response is consistent across eight independent satellite-derived cloud products. Using multiple linear regression, it is demonstrated that the spatial pattern and magnitude of the low-cloud-coverage response is primarily driven by anomalous surface temperature advection. In the eastern North Pacific, anomalous cold advection by anomalous northerly surface winds enhances sensible and latent heat fluxes from the ocean into the boundary layer, resulting in large increases in low-cloud coverage. Local increases in low-level stability make a smaller contribution to this low-cloud increase. Despite closely capturing the observed response of large-scale meteorology to jet shifts, global climate models largely fail to capture the observed response of clouds and radiation to interannual jet shifts because they systematically underestimate how sensitive low clouds are to surface temperature advection, and to a lesser extent, low-level stability. More realistic model simulations of cloud–radiation–jet interactions require that parameterizations more accurately capture the sensitivity of low clouds to surface temperature advection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Simulating Aerosol Indirect Effects with Improved Aerosol-Cloud- Precipitation Representations in a Coupled Regional Climate Model

This is a collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California at San Diego to address the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models. In this project, we propose to develop and improve parameterizations of aerosol-cloud-precipitation feedbacks in climate models and apply them to study the effect of aerosols and clouds on radiation and hydrologic cycle. Our overall objective is to develop, improve, and evaluate parameterizations to enable more accurate simulations of these feedbacks in high resolution regional and global climate models.

58 GEOSCIENCES↗
DOE OSTI2016

A reduced complexity framework to bridge the gap between AGCMs and cloud‐resolving models

Abstract The role of convective parameterizations at high horizontal resolution and their impacts on clouds, circulation, and precipitation processes represent large uncertainties in atmospheric general circulation models (AGCMs). As the statistical equilibrium in which radiative cooling is balanced by convective heating, radiative‐convective equilibrium (RCE) offers a simplified framework to investigate such uncertainties. The Community Atmosphere Model 5 is configured in a RCE setup that consists of an ocean‐covered planet with diurnally varying, spatially uniform insolation with no rotation effects. A series of simulations are performed in which the planetary radius is incrementally reduced. Because of the homogeneity of the setup, the effect is to reduce grid spacing, mimicking increased resolution without increasing the number of grid points. The results suggest that the reduced planet approach is able to reproduce the behavior of convection from full high‐resolution simulations. At grid spacing less than 20 km, convective motions are predominantly produced by resolved scales.

Reed, Kevin A.↗