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An Overview of NASA’s Newest Engineering Model, ORDEM 4.0

Since the mid-1990s, one of the most important products produced by the NASA Orbital Debris Program Office (ODPO) has been the Orbital Debris Engineering Model (ORDEM). This series of models distills down our knowledge of the orbital debris environment to compute debris fluxes on satellites in a given orbit. This information can be used by spacecraft and upper stage designers and operators to design missions for better protection against the debris environment. The current version of the model is ORDEM 3.2, but the ODPO is working on the next generation of ORDEM, to be designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. ORDEM 4.0 will update debris populations using the most recent measurements, including radar observations by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, data from the new Space Surveillance Network Space Fence, and observations of Geosynchronous Earth Orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). The latest in situ impact data from returned hardware surfaces will be used. In addition, ORDEM 4.0 will introduce a parameterized debris shape model based on laboratory hypervelocity impact tests, such as DebriSat. This will allow analysts to implement shape characteristics in their damage equations and more accurately predict impact damage risk by debris of different shapes and orientations. This paper provides an overview of some of the new features forthcoming in ORDEM 4.0 and a status report on its development.

Mark Matney↗
DOE OSTI2021

Electromagnetic Signatures from the Tidal Tail of a Black Hole—Neutron Star Merger

Black hole - neutron star (BH-NS) mergers are a major target for ground-based gravitational wave observatories. A merger can also produce an electromagnetic counterpart (a kilonova) if it ejects neutron-rich matter that assembles into heavy elements through r-process nucleosynthesis. We study the kilonova signatures of the unbound dynamical ejecta of a BH-NS merger. We take as our initial state the results from a numerical relativity simulation and then use a general relativistic hydrodynamics code to study the evolution of the ejecta with parameterized r-process heating models. The unbound dynamical ejecta is initially a flattened, directed tidal tail largely confined to a plane. Heating from the r-process inflates the ejecta into a more spherical shape and smooths its small-scale structure, though the ejecta retains its bulk directed motion. We calculate the electromagnetic signatures using a 3D radiative transfer code and a parameterized opacity model for lanthanide-rich matter. The light curve varies with viewing angle because of two effects: asphericity results in brighter emission for orientations with larger projected areas, while Doppler boosting results in brighter emission for viewing angles more aligned with the direction of bulk motion. For typical r-process heating rates, the peak bolometric luminosity varies by a factor of ~3 with orientation while the peak in the optical bands varies by ~3 magnitudes. The spectrum is blueshifted at viewing angles along the bulk motion, which increases the V-band peak magnitude to ~-14 despite the lanthanide-rich composition.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

CORSICA modelling of ITER hybrid operation scenarios

The hybrid operating mode observed in several tokamaks is characterized by further enhancement over the high plasma confinement (H-mode) associated with reduced magneto-hydro-dynamic (MHD) instabilities linked to a stationary flat safety factor ($q$ ) profile in the core region. The proposed ITER hybrid operation is currently aiming at operating for a long burn duration (>1000 s) with a moderate fusion power multiplication factor, $Q$ , of at least 5. This paper presents here candidate ITER hybrid operation scenarios developed using a free-boundary transport modelling code, CORSICA, taking all relevant physics and engineering constraints into account. The ITER hybrid operation scenarios have been developed by tailoring the 15 MA baseline ITER inductive H-mode scenario. Accessible operation conditions for ITER hybrid operation and achievable range of plasma parameters have been investigated considering uncertainties on the plasma confinement and transport. ITER operation capability for avoiding the poloidal field coil current, field and force limits has been examined by applying different current ramp rates, flat-top plasma currents and densities, and pre-magnetization of the poloidal field coils. Various combinations of heating and current drive (H&CD) schemes have been applied to study several physics issues, such as the plasma current density profile tailoring, enhancement of the plasma energy confinement and fusion power generation. A parameterized edge pedestal model based on EPED1 added to the CORSICA code has been applied to hybrid operation scenarios. Finally, fully self-consistent free-boundary transport simulations have been performed to provide information on the poloidal field coil voltage demands and to study the controllability with the ITER controllers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Validation of Fault Displacements from Dynamic Rupture Simulations against the Observations from the 1992 Landers Earthquake

ABSTRACT Coseismic fault displacements in large earthquakes have caused significant damage to structures and lifelines on and near fault lines. Coseismic displacements represent a real threat, especially to distributed infrastructure systems. For infrastructure systems that can not avoid active faults, engineering displacement demands are defined using probabilistic fault-displacement hazard analyses (PFDHA). However, PFDHA models are sparse and poorly constrained partly due to the scarcity of detailed fault-displacement observations. Advancements in dynamic rupture simulation methods make them an attractive approach to address this important issue. Because fault displacements can be simulated for various geologic conditions as constrained by current knowledge about earthquake processes, they can be used to supplement the observation datasets. In addition to providing on-fault displacements, when used with appropriate constitutive models for the bulk medium, they can capture off-fault distributed inelastic deformations as well. For viable extrapolation, simulations must first be validated against data. In this article, we summarize the calibration and validation of the dynamic rupture model against the observations of the well-documented 1992 Landers earthquake. We defined a preferred model that reproduces several first-order fault-displacement metrics such as the on-fault partition of the total displacement, the mean fault-zone width, and the location of the peak displacement. Simulated ground motions consistent with the observations ensure that all physics important to modeling have been properly parameterized. For the extrapolation, we generated a suite of dynamic rupture models to quantify expected fault-displacement metrics, their intercorrelations, and magnitude dependencies, which are in part supported by the Landers and other recent earthquakes. Our validation and extrapolation exercise paves the way for using dynamic rupture modeling to quantitatively address fault-displacement hazard on a broader scale. The results are promising and are expected to be useful to inform PFDHA model development.

Geochemistry & Geophysics↗
DOE OSTI2018

Simulations of Two Heavily Confined PBX 9502 Cook-off Experiments.

Finite element models of two cook-off experiments were constructed using the Aria code.These experiments provided thermocouple measurements that were used as boundary conditions to carry out finite element (FE) simulations and comparisons of the FE thermal response with internal temperature measurements in the PBX 9502. These FE models contain a pressure dependent PBX 9502 thermal decomposition model developed by Hobbs’ et al.. Comparisons of the FE results and the experiments are presented. These comparisons assess the predictive capabilities of Hobbs’ model under the experimental conditions. Limiting cases of the PBX 9502 decomposition model are considered. Two parameterizations associated with the pressure dependency of the PBX 9502 decomposition model were carried out to fit the experiments using internal temperature measurements. Two inverse heat conduction problems were implemented to estimate temperatures as functions of time at locations on the outer surface of the PBX 9502. Thermocouple conduction error studies were carried out to assess the comparisons of the FE model thermal response with the experiments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

High-frequency and Vertical Variations of Soil Moisture and their Impact on Ecosystem Dynamics

The vertical distribution of subsurface moisture is a major control on ecosystem dynamics and climate. The Mediterranean climate of California, with wet winters and dry summers, provides a testbed for understanding how transpiration is sustained through extended dry periods. The project developed and tested a new subsurface hydrology model that includes a parameterization of stochastic hydraulic conductivity to capture fracture flow, a diagnostic model of rooting profile that depends on the subsurface hydrology, and a representation of hydraulic redistribution by plant roots. A sensitivity study shows that it is plants with rooting depths >8 m that could access the subsurface moisture. The insight is applied to understand differential tree mortality during the 2012-2016 drought in California. The analysis shows that greater mortality trees on plutonic rocks than on sedimentary rocks. The study demonstrates, for the first time, the importance of lithology for the distribution and health of ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Impact of a Cold Pool Parameterization on the Diurnal Cycle and Intraseasonal Variability in the GEOS AGCM

A gradual transition from shallow to deep convection may be important both to the continental diurnal cycle of precipitation and to the tropical Madden-Julian Oscillation. However, many existing convection parameterizations transition too readily, with corresponding diurnal and intraseasonal biases. High entrainment rates can be used to delay deep convection, but typically produce mean state biases; this is the "entrainment dilemma." Cold pools and sub-grid organization offer a potential solution to this dilemma, and recent work shows parameterized cold pools can effectively modulate deep convection, with improvements to the diurnal cycle and intraseasonal variability. Here we investigate the effects of a simple prognostic cold pool scheme coupled to the Grell-Freitas convection parameterization, in a set of global simulations with the NASA GEOS model. Air detrained from parameterized downdrafts is maintained in vertically resolved cold pools, which evolve with simplified dynamics. We test several options for cold pool feedbacks on convection, including modifications to deep convective entrainment rates, convective source air properties, and thermodynamic profiles, based on the level of cold pool activity. Cold pool impacts on the diurnal cycle are evaluated against TRMM, and moisture and moist static energy budgets are used to understand changes in tropical intraseasonal variability. Preliminary results show delays in the diurnal cycle of precipitation.

Arnold, Nathan↗
DOE OSTI2017

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts: CRM Intercomparison of a Squall Line

A constrained model intercomparison study of a mid-latitude mesoscale squall line is performed using the Weather Research & Forecasting (WRF) model at 1-km horizontal grid spacing with eight cloud microphysics schemes, to understand specific processes that lead to the large spread of simulated cloud and precipitation at cloud-resolving scales, with a focus of this paper on convective cores. Various observational data are employed to evaluate the baseline simulations. All simulations tend to produce a wider convective area than observed, but a much narrower stratiform area, with most bulk schemes overpredicting radar reflectivity. The magnitudes of the virtual potential temperature drop, pressure rise, and the peak wind speed associated with the passage of the gust front are significantly smaller compared with the observations, suggesting simulated cool pools are weaker. Simulations also overestimate the vertical velocity and Ze in convective cores as compared with observational retrievals. The modeled updraft velocity and precipitation have a significant spread across the eight schemes even in this strongly dynamically-driven system. The spread of updraft velocity is attributed to the combined effects of the low-level perturbation pressure gradient determined by cold pool intensity and buoyancy that is not necessarily well correlated to differences in latent heating among the simulations. Variability of updraft velocity between schemes is also related to differences in ice-related parameterizations, whereas precipitation variability increases in no-ice simulations because of scheme differences in collision-coalescence parameterizations.

Fan, Jiwen↗
NASA NTRS1990

A scheme for parameterizing ice-cloud water content in general circulation models

The optical properties of ice clouds are a primary issue for climate and climate change. Evaluating these optical properties in three-dimensional models for studying climate will require a method to calculate the ice water content of such clouds. A procedure is developed to parameterize ice water content as a function of large-scale meteorological characteristics for use in circulation models in which the ice water content is not calculated by means of a three-dimensional prognostic equation for condensed water. The technique identifies large-scale flows in which ice clouds exist and calculates their ice water content by reconstructing the trajectory associated with cloud formation. As the cloud forms, its ice content changes both by deposition of ice from water vapor and by ice removal by sedimentation. The sedimentation process is found to modify significantly the ice water content expected from deposition alone. Ice water contents predicted by the parameterization are compared with aircraft observations collected in the middle latitudes and the tropics, and show reasonable agreement over four orders-of-magnitude of ice water content. A parameterization for the sublimation of ice crystals settling into ice-subsaturated environments is also presented.

Heymsfield, Andrew J.↗
DOE OSTI2018

100 Years of Research on Mesoscale Convective Systems

Abstract When cumulonimbus clouds aggregate, developing into a single entity with precipitation covering a horizontal scale of hundreds of kilometers, they are called mesoscale convective systems (MCSs). They account for much of Earth’s precipitation, generate severe weather events and flooding, produce prodigious cirriform anvil clouds, and affect the evolution of the larger-scale circulation. Understanding the inner workings of MCSs has resulted from developments in observational technology and modeling. Time–space conversion of ordinary surface and upper-air observations provided early insight into MCSs, but deeper understanding has followed field campaigns using increasingly sophisticated radars, better aircraft instrumentation, and an ever-widening range of satellite instruments, especially satellite-borne radars. High-resolution modeling and theoretical insights have shown that aggregated cumulonimbus clouds induce a mesoscale circulation consisting of air overturning on a scale larger than the scale of individual convective up- and downdrafts. These layers can be kilometers deep and decoupled from the boundary layer in elevated MCSs. Cooling in the lower troposphere and heating aloft characterize the stratiform regions of MCSs. As a result, long-lived MCSs with large stratiform regions have a top-heavy heating profile that generates potential vorticity in midlevels, thus influencing the larger-scale circulation within which the MCSs occur. Global satellite data show MCSs varying in structure, depending on the prevailing large-scale circulation and topography. These patterns are likely to change with global warming. In addition, environmental pollution affects MCS structure and dynamics subtly. Feedbacks of MCSs therefore need to be included or parameterized in climate models.

Houze, Jr., Robert A.↗
DOE OSTI2022

Predicting and Controlling Corrosion (Abbreviated Final Report)

Corrosion accumulates significant replacement costs in the transportation, utility, manufacturing, and infrastructure sectors. It also underpins several of LLNL’s core missions in stockpile stewardship, defense, and energy security. Whereas most corrosion and aging models are empirically parameterized to describe well-defined conditions late in the reaction, the factors that determine the early stages of corrosion—during which mitigation could be most impactful— are poorly understood. This project addressed the critical need for new approaches to predict the kinetics of corrosion initiation based on firm physical and chemical understanding. The activities encompassed degradation of relevant metals in both hydrogen-rich and environmental corrosion scenarios. The team integrated state-of-the-art multiscale simulation, in situ characterization, and data science within three technical thrusts: hydriding of Ti alloys; aqueous corrosion of Al and Ni-Cr alloys; and degradation of additively manufactured 316L stainless steel. In each case, novel capabilities were developed to identify and track the impacts of key atomistic, compositional, and microstructural features on the metal systems. For hydriding, protocols were developed to tightly integrate multiscale models, advanced multimodal characterization, and machine learning to determine how hydrogen interacts with native passivating surface oxides and nucleates new undesired phases, shedding new light on the critical role of grain boundaries, interfaces, and atomically disordered regions. For aqueous corrosion, the project demonstrated methods to predict dissolution rates of metal surfaces in corrosive solutions, to measure and understand microstructural and grain orientation effects on corrosion susceptibility, and to investigate competing growth and dissolution kinetics of surface oxides. For additively manufactured metals, analysis using state-of-the-art microscopy techniques revealed the role of specific heterogeneities invoked during laser processing, including cellular structure, dislocations, and precipitates, on corrosion susceptibility. In addition to new capabilities and understanding, the project provided an avenue for workforce development, as well as key partnerships with stakeholders in corrosion science.

08 HYDROGEN↗
NASA NTRS1999

Analysis of Cirrus Cloud Microphysical Data

The First International Satellite Cloud Climatology Regional Experiment (FIRE) program has the goal of improving our capabilities to understand, model and detect the properties of climatically-important clouds. This is being undertaken through a three-pronged effort of modeling, long-term observations and short-term intensive field studies. Through examination of satellite and other data it is apparent that stratus and cirrus cloud types have the greatest impact on climate due to their radiative effects and ubiquitous nature. As a result, the FIRE program has developed two paths of investigation, each having its own subset of research objectives and measurement programs. The work conducted under this grant was directed toward furthering our understanding of cirrus cloud systems. While it is known that cirrus are climatically important, the magnitude and even sign of the impact is unclear. Cirrus clouds affect the transfer of radiation according to their physical depth and location in the atmosphere and their microphysical composition. However, significant uncertainties still exist in how cirrus clouds form and how they are maintained, what their physical properties are and how they can be parameterized in numerical models. Better remote sensing techniques for monitoring cirrus cloud systems and improved modeling of radiative transfer through ice particles are also needed. A critical element in resolving these issues is a better understanding of cirrus cloud microphysical properties and how they vary. The focus of the research to be conducted under this grant was th data collected in situ by the University of North Dakota Citation aircraft. The goals of this research were to add to the body of knowledge of cirrus cloud microphysics, particularly at the small end of the size spectrum; and analyze the spatial variation of cirrus clouds.

Poellot, Michael R.↗
NASA NTRS1994

'Downward control' of the mean meridional circulation and temperature distribution of the polar winter stratosphere

According to the 'downward control' principle, the extratropical mean vertical velocity on a given pressure level is approximately proportional to the meridional gradient of the vertically integrated zonal force per unit mass exerted by waves above that level. In this paper, a simple numerical model that includes parameterizations of both planetary and gravity wave breaking is used to explore the influence of gravity wave breaking in the mesosphere on the mean meridional circulation and temperature distribution at lower levels in the polar winter stratosphere. The results of these calculations suggest that gravity wave drag in the mesosphere can affect the state of the polar winter stratosphere down to altitudes below 30 km. The effect is most important when planetary wave driving is relatively weak: that is, during southern winter and in early northern winter. In southern winter, downwelling weakens by a factor of 2 near the stratospause and by 20% at 30 km when gravity wave drag is not included in the calculations. As a consequence, temperatures decrease considerably throughout the polar winter stratosphere (over 20 K above 40 km and as much as 8 K at 30 km, where the effect is enhanced by the long radiative relaxation timescale). The polar winter states obtained when gravity wave drag is omitted in this simple model resemble the results of simulations with some general circulation models and suggest that some of the shortcomings of the latter may be due to a deficit in mesospheric momentum deposition by small-scale gravity waves.

Garcia, Rolando R.↗
NASA NTRS2019

The Interaction Between Boundary Layer and Convection Schemes in a WRF Simulation of Post‐Cold‐Frontal Clouds over the ARM East North Atlantic Site

The correct representation of lowlevel midlatitude clouds found in the wake of cold fronts strongly relies on the representation of planetary boundary layer (PBL) and convection processes, which are typically parameterized separately in numerical models. Using the Weather Research and Forecasting Model (WRF), this study investigates how distinct pairs of PBL and convection parameterization schemes represent cloud fraction in the postcoldfrontal region. The simulations focus on the region of the DOEARM Eastern North Atlantic observation site in the Azores Islands in the wake of a cold front that passed on December 25, 2015. Different PBL and convection schemes are combined to create 12 distinct configurations. The main differences between the selected physical parameterizations are the strength of vertical mixing and the entrainment. The simulations produce a wide range of cloud fractions, where some configurations significantly underestimate while others clearly overestimate satellite and surfacebased estimates of cloud fraction. A skill score is used to quantitatively assess the performance of each configuration with respect to groundbased radar data. The key processes that are found to significantly impact the cloud fraction distribution are the strength of the PBL decoupling, the vertical wind shear, entrainment and detrainment rates in shallow convection and the occurrence of drizzle. This indicates that to successfully simulate postcoldfrontal clouds, modeled physics must balance strong internal vertical mixing and weak exchange with the free troposphere. For this case study, cloud fraction was more sensitive to the choice of convection scheme than PBL scheme.

moist convection interaction between parameterizat↗
NASA NTRS1999

Impact of Assimilating GOES-Derived Land Surface Variables into the PSU/NCAR MM5

Land surface processes are known to have a profound impact on the overlying atmosphere over a wide range of spatial and temporal scales. Many atmospheric numerical models include special parameterizations to improve the specification and partitioning of surface fluxes which are critical to the accurate prediction of warm season boundary layer behavior, organized mesoscale circulations, and convective precipitation. However, the added degrees of freedom resulting from the inclusion of vegetation and soil schemes require the specification of additional surface parameters such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, and the vertical distribution of soil moisture. As satellite data have become more readily available in recent years, many investigations have attempted to use these new measurements to infer missing components of the surface energy budget. Sensitivity studies have shown land-skin temperature (LST) tendencies during the mid-morning hours are strongly sensitive to the surface moisture availability (a function of soil wetness and vegetation) and less sensitive to other parameters such as surface roughness. Based upon results from these and other studies, developed a simple technique that dynamically assimilates Geostationary Operational Environmental Satellite (GOES) derived land-surface products into the surface energy budget of a mesoscale model. The purpose of this paper is to demonstrate that assimilating the GOES satellite data has the potential to improve the representation of land surface characteristics within the model without prior knowledge of the land surface characteristics. The assimilation technique is presented in Section 2 and the numerical experiments are detailed in Section 3. Preliminary results and conclusions are presented in Sections 4 and 5, respectively.

Lapenta, William M.↗
DOE OSTI2022

Connecting the Radiative Influences of Aerosol upon the Mass Flux Profiles of Shallow Cumuli across the Southeast Atlantic Ocean Basin and its Boundaries (Final Report)

The Atlantic Ocean covers approximately 25% of Earth’s surface and the atmosphere above it is home to a complex array of clouds and aerosols that have important influences on regional and global weather and climate. These influences must be accurately depicted in short range, medium range, seasonal, and climate forecast models. Conditions over the tropical Atlantic are particularly complex due to continental scale plumes of dust from the Sahara Desert and smoke from agricultural burning in Africa that drift across the Atlantic Ocean basin toward the Americas. These plumes are often found meandering in the lower atmosphere above shallow tropical clouds that form above the ocean surface, presumably mingling with these clouds on occasion due to convective mixing processes. Elevated dust and smoke particles absorb incoming sunlight and substantially warm the marine atmosphere in the layer in which they are present. This warming may alter the thermal stability of the marine atmosphere and may throttle or enhance the development of clouds, change their internal structure and the rate at which they precipitate. Alternatively, it may isolate the lower atmosphere from drier layers above enabling water vapor to accumulate near the ocean surface potentially leading to the development of deeper convection. Our study was organized around the principal concept of determining the impact of African smoke and dust plumes upon cloud development at ASI and understanding how a popular shallow convection parameterization used in models responds to the presence of this aerosol. We analyzed observations collected during the US Department of Energy (DOE) Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign using the Atmospheric Radiation Measurement Program’s Mobile Facility #1 (AMF-1), which was deployed to Ascension Island (ASI) in Southeastern Atlantic for a one-year period. Ascension Island is immediately downwind from an African source of these plumes, but far enough removed to enable the lower atmosphere to have reacted to their presence. A main goal of our study was to compute radiative heating rate profiles over Ascension Island and along the trajectory from the biomass burning regions along coastal Africa to Ascension Island. To compute the radiative heating rate due to aerosols and clouds, we employed observed profiles of temperature, humidity, and clouds from LASIC alongside aerosol optical properties from the Modern-era Retrospective analysis for Research and Applications Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM). Radiative heating was also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We were successful in this effort and the resulting publication is already being cited despite its relatively short lifetime in the literature. The second part of our study involved the process-level representation of the clouds observed over the Southeastern Atlantic in models. Our initial task, upon which the balance of this portion of the study depended, was to evaluate the representativeness of the clouds observed by AMF-1. What orographic influence did Ascension Island have on the measured cloud structure? We set out to answer this question by trying to separate observations that were clearly indicative of orographic forcing from those that were representative of open ocean. The siting of AMF-1, which was 340-m above sea-level on the slope of a steep escarpment, proved demonstrably problematic for cloud process measurements. Despite considerable effort using multiple approaches including artificial intelligence (AI), we were unable to successfully compensate for the orographic forcing present at the AMF-1 site on ASI and, hence, produce process-level summaries of the convective mass flux representative of open ocean over the Southeastern Atlantic. Even though the project has officially ended, we are making a final attempt using two new types of clustering algorithm (i.e., AI) on the recommendation of a former student, who is an expert in this area. Since we have only recently begun to test these new AI schemes, the recommendations from the second part of our project outlined below are based on our experience at the time of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Interaction Between Boundary Layer and Convection Schemes in a WRF Simulation of Post Cold Frontal Clouds Over the ARM East North Atlantic Site

Abstract The correct representation of low‐level midlatitude clouds found in the wake of cold fronts strongly relies on the representation of planetary boundary layer (PBL) and convection processes, which are typically parameterized separately in numerical models. Using the Weather Research and Forecasting Model (WRF), this study investigates how distinct pairs of PBL and convection parameterization schemes represent cloud fraction in the post cold frontal region. The simulations focus on the region of the Department of Energy Atmospheric Radiation Measurement (ARM) Eastern North Atlantic observation site in the Azores Islands in the wake of a cold front that passed on 25 December 2015. Different PBL and convection schemes are combined to create 12 distinct configurations. The main differences between the selected physical parameterizations are the strength of vertical mixing and the entrainment. The simulations produce a wide range of cloud fractions, where some configurations significantly underestimate while others clearly overestimate satellite and surface‐based estimates of cloud fraction. A skill score is used to quantitatively assess the performance of each configuration with respect to ground‐based radar data. The key processes that are found to significantly impact the cloud fraction distribution are the strength of the PBL decoupling, the vertical wind shear, entrainment and detrainment rates in shallow convection, and the occurrence of drizzle. This indicates that to successfully simulate post cold frontal clouds, modeled physics must balance strong internal vertical mixing and weak exchange with the free troposphere. For this case study, cloud fraction was more sensitive to the choice of convection scheme than PBL scheme.

54 ENVIRONMENTAL SCIENCES↗