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

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At least 631 records · Page 35
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DOE OSTI2018

A Bird’s Eye View: Development of an Operational ARM Unmanned Aerial Capability for Atmospheric Research in Arctic Alaska

Here, we present that unmanned aerial capabilities offer exciting new perspectives on the Arctic atmosphere and the US Department of Energy is working with partners to offer such perspectives to the research community. Thorough understanding of aerosols, clouds, boundary layer structure and radiation is required to improve representation of the Arctic atmosphere in weather forecasting and climate models. To develop such understanding, new perspectives are needed to provide details on the vertical structure and spatial variability of key atmospheric properties, along with information over difficult-to-reach surfaces such as newly-forming sea ice. Over the last three years, the US Department of Energy (DOE) has supported various flight campaigns using unmanned aircraft systems (UAS, also known as UAVs and drones) and tethered balloon systems (TBS) at Oliktok Point, Alaska. These activities have featured in-situ measurements of thermodynamic state, turbulence, radiation, aerosol properties, cloud microphysics and turbulent fluxes to provide a detailed characterization of the lower atmosphere. Alongside a suite of active and passive ground-based sensors and radiosondes deployed by the DOE Atmospheric Radiation Measurement (ARM) program through the third ARM Mobile Facility (AMF-3), these flight activities demonstrate the ability of such platforms to provide critically-needed information. In addition to providing new and unique datasets, lessons learned during initial campaigns have assisted toward the development of an exciting new community resource.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Observations of Clouds, Aerosols, Precipitation, and Surface Radiation over the Southern Ocean: An Overview of CAPRICORN, MARCUS, MICRE, and SOCRATES

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. Furthermore, the combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Absorption Properties of Supercooled Liquid Water between 31 and 225 GHz: Evaluation of Absorption Models Using Ground-Based Observations

Microwave radiometers (MWR) are commonly used to quantify the amount of supercooled liquid water (SLW) in clouds; however, the accuracy of the SLW retrievals is limited by the poor knowledge of the SLW dielectric properties at microwave frequencies. Six liquid water permittivity models were compared with ground-based MWR observations between 31 and 225 GHz from sites in Greenland, the German Alps, and a low-mountain site; average cloud temperatures of observed thin cloud layers range from 0° to –33°C. A recently published method to derive ratios of liquid water opacity from different frequencies was employed in this analysis. These ratios are independent of liquid water path and equal to the ratio of αL at those frequencies that can be directly compared with the permittivity model predictions. The observed opacity ratios from all sites show highly consistent results that are generally within the range of model predictions; however, none of the models are able to approximate the observations over the entire frequency and temperature range. Findings in earlier published studies were used to select one specific model as a reference model for αL at 90 GHz; together with the observed opacity ratios, the temperature dependence of αL at 31.4, 52.28, 150, and 225 GHz was derived. The results reveal that two models fit the opacity ratio data better than the other four models, with one of the two models fitting the data better for frequencies below 90 GHz and the other for higher frequencies. Furthermore, these findings are relevant for SLW retrievals and radiative transfer in the 31–225-GHz frequency region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Liquid–Ice Mass Partition in Tropical Maritime Convective Clouds

The liquid–ice mass partitioning in tropical maritime convective clouds is studied in this paper using data collected by the National Center for Atmospheric Research C-130 research aircraft during the Ice in Clouds Experiment–Tropical project. The clouds investigated by the C-130 in this study generally contained weak to moderate updrafts. The liquid water content (LWC) is calculated using a combination of hot-wire and imaging probes. The total condensed water content (CWC) is measured by a counterflow virtual impactor. The ice water content (IWC) is calculated as CWC minus LWC. Taking into account potential significant measurement uncertainties, the liquid fraction [i.e., LWC/(LWC + IWC)] between 0° and -15°C appears to decrease by a factor of about 3 in updrafts near (<500 m) cloud top and a factor of 2 in updrafts far below (>500 m) cloud top. The decrease in liquid fraction as a function of temperature is also correlated with cloud life cycle. In dissipating clouds, ice dominates in all temperature ranges. A comparison between this study and two parameterizations shows that at different geographic locations the liquid fraction in convective clouds differs. Because of the sampling bias and the limitations of instruments, more measurements, especially with more advanced instruments, are needed in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Ultraclean Layers and Optically Thin Clouds in the Stratocumulus-to-Cumulus Transition. Part I: Observations

A common feature of the stratocumulus-to-cumulus transition (SCT) is the presence of layers in which the concentration of particles larger than 0.1 μm is below 10 cm –3 . These ultraclean layers (UCLs) are explored using aircraft observations from 14 flights of the NSF–NCAR Gulfstream V (G-V) aircraft between California and Hawaii. UCLs are commonly located in the upper part of decoupled boundary layers, with coverage increasing from less than 5% within 500 km of the California coast to ~30%–60% west of 130°W. Most clouds in UCLs are thin, horizontally extensive layers containing drops with median volume radii ranging from 15 to 30 μm. Many UCL clouds are optically thin and do not fully attenuate the G-V lidar and yet are frequently detected with a 94-GHz radar with a sensitivity of around –30 dBZ. Satellite data indicate that UCL clouds have visible reflectances of ~0.1–0.2 and are often quasi laminar, giving them a veil-like appearance. These optically thin veil clouds exist for 1–3 h or more, are associated with mesoscale cumulus clusters, and likely grow by spreading under strong inversions. Active updrafts in cumulus (Cu) clouds have droplet concentrations of ~25–50 cm –3 . Collision–coalescence in the Cu and later sedimentation in the thinner UCL clouds are likely the key processes that remove droplets in UCL clouds. UCLs are relatively quiescent, and a lack of mixing with dry air above and below the cloud may help to explain their longevity. In conclusion, the very low and highly variable droplet concentrations in UCL clouds, together with their low geometrical and optical thickness, make these clouds particularly challenging to represent in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Reply to “What Is the Maximum Entropy Principle? Comments on ‘Statistical Theory on the Functional Form of Cloud Particle Size Distributions’”

We welcome the opportunity to correct the misunderstandings and misinterpretations contained in Yano’s comment that led him to incorrectly state that Wu and McFarquhar misunderstood the maximum entropy (MaxEnt) principle. As correctly stated by Yano, the principle itself does not suffer from the problem of a lack of invariance. But, as restated in this reply and in Wu and McFarquhar, the commonly used Shannon–Gibbs entropy does suffer from a lack of invariance for coordinate transform when applied in continuous cases, and this problem is resolved by the use of the relative entropy. Further, it is restated that the Wu and McFarquhar derivation of the PSD form using MaxEnt is more general than the formulation by Yano and allows more constraints with any functional relations to be applied. The derivation of Yano is nothing new but the representation of PSDs in other variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Shape and Density Evolution of Snow Aggregates

Abstract Snow aggregates evolve into a variety of observed shapes and densities. Despite this diversity, models and observational studies employ fractal or Euclidean geometric measures that are assumed universal for all aggregates. This work therefore seeks to improve understanding and representation of snow aggregate geometry and its evolution by characterizing distributions of both observed and Monte Carlo–generated aggregates. Two separate datasets of best-fit ellipsoid estimates derived from Multi-Angle Snowflake Camera (MASC) observations suggest the use of a bivariate beta distribution model for capturing aggregate shapes. Product moments of this model capture shape effects to within 4% of observations. This mathematical model is used along with Monte Carlo simulated aggregates to study how combinations of monomer properties affect aggregate shape evolution. Plate aggregates of any aspect ratio produce a consistent ellipsoid shape evolution whereas thin column aggregates evolve to become more spherical. Thin column aggregates yield fractal dimensions much less than the often-assumed value of 2.0. Ellipsoid densities and fractal analogs of density (lacunarity) are much more variable depending on combinations of monomer size and shape. Simple mathematical scaling relationships can explain the persistent triaxial ellipsoid shapes that appear in both observed and modeled aggregates. Overall, both simulations and observations prove aggregates are rarely oblate. Therefore, the use of the proposed bivariate ellipsoid distribution in models will allow for similar-sized aggregates to exhibit a realistic dispersion of masses and fall speeds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impacts of Varying Concentrations of Cloud Condensation Nuclei on Deep Convective Cloud Updrafts—A Multimodel Assessment

Abstract This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations among seven state-of-the-art cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas, are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced updraft changes. The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5%–15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~−5% to 0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dependencies of Four Mechanisms of Secondary Ice Production on Cloud-Top Temperature in a Continental Convective Storm

Various mechanisms of secondary ice production (SIP) cause multiplication of numbers of ice particle, after the onset of primary ice. A measure of SIP is the ice enhancement ratio (“IE ratio”) defined here as the ratio between number concentrations of total ice (excluding homogeneously nucleated ice) and active ice-nucleating particles (INPs). A convective line observed on 11 May 2011 over the Southern Great Plains in the Mesoscale Continental Convective Cloud Experiment (MC3E) campaign was simulated with the “Aerosol–Cloud” (AC) model. AC is validated against coincident MC3E observations by aircraft, ground-based instruments, and satellite. Four SIP mechanisms are represented in AC: the Hallett–Mossop (HM) process of rime splintering, and fragmentation during ice–ice collisions, raindrop freezing, and sublimation. The vertical profile of the IE ratio, averaged over the entire simulation, is almost uniform (10 2 to 10 3 ) because fragmentation in ice–ice collisions dominates at long time scales, driving the ice concentration toward a theoretical maximum. The IE ratio increases with both the updraft (HM process, fragmentation during raindrop freezing, and ice–ice collisions) and downdraft speed (fragmentation during ice–ice collisions and sublimation). As reported historically in aircraft sampling, IE ratios were predicted to peak near 10 3 for cloud-top temperatures close to the −12°C level, mostly due to the HM process in typically young clouds with their age less than 15 min. Here, at higher altitudes with temperatures of −20° to −30°C, the predicted IE ratios were smaller, ranging from 10 to 10 2 , and mainly resulted from fragmentation in ice–ice collisions.

Aerosols↗
DOE OSTI2023

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part II: Aerosol–Meteorology–Cloud Interaction

Aerosol effects on micro/macrophysical properties of marine stratocumulus clouds over the western North Atlantic Ocean (WNAO) are investigated using in situ measurements and large-eddy simulations (LES) for two cold-air outbreak (CAO) cases (28 February and 1 March 2020) during the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). The LES is able to reproduce the vertical profiles of liquid water content (LWC), effective radius r eff and cloud droplet number concentration N c from fast cloud droplet probe (FCDP) in situ measurements for both cases. Furthermore, we show that aerosols affect cloud properties (N c , r eff , and LWC) via the prescribed bulk hygroscopicity of aerosols ($\bar{κ}$) and aerosol size distribution characteristics. N c , r eff , and liquid water path (LWP) are positively correlated to $\bar{κ}$ and aerosol number concentration (N a ) while cloud fractional cover (CFC) is insensitive to $\bar{κ}$ and aerosol size distributions for the two cases. The realistic changes to aerosol size distribution (number concentration, width, and the geometrical diameter) with the same meteorology state allow us to investigate aerosol effects on cloud properties without meteorological feedback. We also use the LES results to evaluate cloud properties from two reanalysis products, ERA5 and MERRA-2. Compared to LES, the ERA5 is able to capture the time evolution of LWP and total cloud coverage within the study domain during both CAO cases while MERRA-2 underestimates them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Cloud Phase and Relative Humidity Distributions over the Southern Ocean in Austral Summer Based on In Situ Observations and CAM5 Simulations

Cloud phase and relative humidity (RH) distributions at -67° to 0°C over the Southern Ocean during austral summer are compared between in situ airborne observations and global climate simulations. A scale-aware comparison is conducted using horizontally averaged observations from 0.1 to 50 km. Cloud phase frequencies, RH distributions, and liquid mass fraction are found to be less affected by horizontal resolutions than liquid and ice water content (LWC and IWC, respectively), liquid and ice number concentrations (Nc liq and Nc ice , respectively), and ice supersaturation (ISS) frequency. At -10° to 0°C, observations show 27%–34% and 17%–37% of liquid and mixed phases, while simulations show 60%–70% and 3%–4%, respectively. Simulations overestimate (underestimate) LWC and Nc liq in liquid (mixed) phase, overestimate Nc ice in mixed phase, underestimate IWC in ice and mixed phases, and underestimate (overestimate) liquid mass fraction below (above) -5°C, indicating that observational constraints are needed for different cloud phases. RH frequently occurs at liquid saturation in liquid and mixed phases for all datasets, yet the observed RH in ice phase can deviate from liquid saturation by up to 20%–40% at -20° to 0°C, indicating that the model assumption of liquid saturation for coexisting ice and liquid is inaccurate for low liquid mass fractions (<0.1). Simulations lack RH variability for partial cloud fractions (0.1–0.9) and underestimate (overestimate) ISS frequency for cloud fraction <0.1 (≥0.6), implying that improving RH subgrid-scale parameterizations may be a viable path to account for small-scale processes that affect RH and cloud phase heterogeneities. Lastly, two sets of simulations (nudged and free-running) show very similar results (except for ISS frequency) regardless of sample sizes, corroborating the statistical robustness of the model–observation comparisons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Regime-Oriented Approach to Observationally Constraining Extratropical Shortwave Cloud Feedbacks

The extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m -2 per kelvin SST increase (35°–75°N) and 1.2–1.9 W m -2 per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks

58 GEOSCIENCES↗
DOE OSTI2021

The influence of fire aerosols on surface climate and gross primary production in the Energy Exascale Earth System Model (E3SM)

Fire-emitted aerosols play an important role in influencing Earth’s climate, directly by scattering and absorbing radiation and indirectly by influencing cloud microphysics. The quantification of fire-aerosol interactions, however, remains challenging and subject to uncertainties in emissions, plume parameterizations, and aerosol properties. Here we optimized fire-associated aerosol emissions in the Energy Exascale Earth System Model (E3SM) using the Global Fire Emissions Database (GFED) and AERONET aerosol optical depth (AOD) observations during 1997-2016. Furthermore, we distributed fire emissions vertically using smoke plume heights from Multi-angle Imaging SpectroRadiometer (MISR) satellite observations. From the optimization, we estimate that global fires emit 45.5 Tg y -1 of primary particulate organic matter and 3.9 Tg y -1 of black carbon. We then performed two climate simulations with and without the optimized fire emissions. We find that fire aerosols significantly increase global AOD by 14 ± 7% and contribute to a reduction in net shortwave radiation at the surface (-2.3 ± 0.5 W m -2 ). Together, fire-induced direct and indirect aerosol effects cause annual mean global land surface air temperature to decrease by 0.17 ± 0.15°C, relative humidity to increase by 0.4 ± 0.3%, and diffuse light fraction to increase by 0.5 ± 0.3%. In response, GPP declines by 2.8 Pg C y -1 , as a result of large positive drivers (decreases in temperature and increases in humidity and diffuse light) nearly cancelling out large negative drivers (decreases shortwave radiation and soil moisture). Our analysis highlights the importance of fire aerosols in modifying surface climate and photosynthesis across the tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Final Technical Report for Collaborative Research: CRI-EaSM Multiscale Modeling Aerosol Indirect Effects on Decadal Timescales

Originally, the main role of the P.I. (Sungsu Park) in this project was to improve the treatment of cloud microphysics in the CAM5 shallow and deep convection scheme. During the progress of the project, however, the main research theme was changed to develop a new unified convection scheme (so called, UNICON) with the permission of the program manager.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

BAECC Biogenic Aerosols - Effects on Clouds and Climate

“Biogenic Aerosols - Effects on Clouds and Climate (BAECC)”, featured the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program’s 2nd Mobile Facility (AMF2) in Hyytiälä, Finland. It operated for an 8-month intensive measurement campaign from February to September 2014. The main research goal was to understand the role of biogenic aerosols in cloud formation. One of the reasons to perform BAECC study in Hyytiälä was the fact that it hosts SMEAR-II (Station for Measuring Forest Ecosystem-Atmosphere Relations), which is one of the world’s most comprehensive surface in-situ observation sites in a boreal forest environment. The station has been measuring atmospheric aerosols, biogenic emissions and an extensive suite of parameters relevant to atmosphere-biosphere interactions continuously since 1996. The BAECC enables combining vertical profiles from AMF2 with surface-based in-situ SMEAR-II observations and allows the processes at the surface to be directly related to processes occurring throughout the entire tropospheric column. With the inclusion of extensive surface precipitation measurements, and intensive observation periods involving aircraft flights and novel radiosonde launches, the complementary observations of AMF2 and SMEAR-II provide a unique opportunity for investigating aerosol-cloud interactions, and cloud-to-precipitation processes. The BAECC dataset will initiate new opportunities for evaluating and improving models of aerosol sources and transport, cloud microphysical processes, and boundary-layer structures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Alpenglow Instruments All Phase Water Probe: SBIR Phase I Final Report

Current approaches for measuring water vapor, ice water content, and liquid water content in the atmosphere have a variety of limitations. This is particularly true for ice water content measurements, which are needed in a variety of contexts including understanding the impact of clouds on global climate. The Alpenglow All-Phase Water Probe, which was motivated by limitations of current approaches to measuring water vapor, liquid water, and ice water content in the atmosphere, uses Raman scattering to derive these quantities. The use of Raman scattering signals for retrieval of water vapor mixing ratio, liquid and ice water content has been used in remote sensing applications. This project explored the use of the same approach in an in situ probe to measure all three phases of water in the atmosphere. The prototype device developed in this Phase 1 DOE SBIR proposal was used to demonstrate proof of concept for using Raman scattering to detect signals from water vapor, liquid water, and ice water. The prototype instrument consisted of the transmitting laser (355 nm, 7ns pulse), collector optics and receiver body, and data system. The receiver section body split the return signal into four channels, one for nitrogen plus channels dominated by water vapor, liquid water, and ice. Tests were conducted over a range of conditions ranging from ambient conditions in the lab (low water vapor mixing ratio, no liquid or ice water content), through a cool but saturated plume produced by an off-the-shelf humidifier (moderate water vapor mixing ratio plus some liquid water content), and hot, saturated stream containing extremely high water vapor mixing ratios with liquid water. Data from these tests, which was recorded using a Licel photon-counting data system, demonstrated the sensitivity of the system to varying water vapor mixing ratios ranging from ~5 g m -3 to > 20 g m -3 . Signals in the water vapor and ice channels were observed during the humidifier and hot vapor tests, as expected given the overlap between the ice and water vapor Raman spectra, with the relative contributions to each channel varying as expected with temperature.

58 GEOSCIENCES↗
DOE OSTI2017

Evolution of Precipitation Particle Size Distributions within MC3E Systems and its Impact on Aerosol-Cloud-Precipitation Interactions: Final Report

This is a multi-institutional, collaborative project using observations and modeling to study the evolution (e.g. formation and growth) of hydrometeors in continental convective clouds. Our contribution was in data analysis for the generation of high-value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: i) the development of novel, state-of-the-art dual-wavelength radar algorithms for the retrieval of cloud microphysical properties and ii) the evaluation of large domain, high-resolution models using comprehensive multi-sensor observations. Our research group developed statistical summaries from numerous sensors and developed retrievals of vertical air motion in deep convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Learned implicit representations of aerosol chemistry and physics for enhancing the predictability of water cycle extreme events

Focal Area(s): Focal area 2: Predictive modeling through the use of AI-derived model components; and Focal area 3: physics-guided AI. Science Challenge: Comprehensive models of many geophysical processes require a large number of state variables, disqualifying them for inclusion in Earth System Models (ESMs) for the foreseeable future. This white paper proposes the paradigm shift from the use of state variables representing explicit physical quantities to the use of machine-learning to create and integrate a compact, implicit representation of a physical system with a smaller number of state variables. As an initial application, we propose to create parsimonious machine-learned surrogate models of gas- and aerosol-phase chemistry and physics with the purpose of improving the accuracy of the representation of cloud formation and cloud-aerosol interaction in the E3SM model. This type of improved representation of cloud microphysics is critical for enhancing the predictability of water cycle extremes.

54 ENVIRONMENTAL SCIENCES↗