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NASA NTRS2007

New, Improved Goddard Bulk-Microphysical Schemes for Studying Precipitation Processes in WRF

An improved bulk microphysical parameterization is implemented into the Weather Research and Forecasting ()VRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atlantic hurricane). The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with a cloud ice-snow-hail configuration agreed better with observations in terms of rainfall intensity and a narrow convective line than did simulations with a cloud ice-snow-graupel or cloud ice-snow (i.e., 2ICE) configuration. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 in For an Atlantic hurricane case, the Goddard microphysical schemes had no significant impact on the track forecast but did affect the intensity slightly. The improved Goddard schemes are also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in the southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE scheme with the hail option and the Thompson scheme agree better with observations in terms of rainfall intensity, expect that the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model simulated cloud species (i.e., snow) are quite sensitive to microphysical schemes, which is an important issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane cases. Sensitivity tests are performed for these two WRF schemes to identify that snow productions could be increased by increasing the snow intercept, turning off the auto-conversion from snow to graupel and reducing the transfer processes from cloud-sized particles to precipitation-sized ice.

Tao, Wei-Kuo↗

NASA NTRS2024

Mineral Dust Optical Properties for Remote Sensing and Global Modeling: A Review

Dust plays a key role in many Earth system processes and is ubiquitous in the Martian atmosphere. Various intensive field campaigns, laboratory analyses, space-based remote sensing missions, and global modeling efforts aim to characterize dust optical properties. This is a bountiful time for dust scientists, and yet the interpretation of retrievals and comparison to models remains complicated by various conflicting assumptions that are part of each algorithm. For example, the conversion of satellite radiance measurements into products like aerosol optical depth for model evaluation depends upon aerosol properties like particle size and shape that are often prescribed and not part of the retrieval. Conversely, the model calculation of aerosol optical depth often uses different assumptions. The goal of this review is to first document algorithmic assumptions by various satellite retrieval products and models, and identify where there is consistency and where there are differences. In general, the differences documented in this paper reflect uncertainties resulting from incomplete observational characterization of dust aerosols and limitations in our understanding. Second, we note what observations might reduce uncertainties in our knowledge and bring greater consistency to retrievals and models, allowing for a more rigorous and harmonious comparison. The lack of comprehensive and realistic shape models for dust is an outstanding issue, such that closure between forward modeling from particle refractive index, shape, and size and observed optical properties cannot be achieved. Limitations in the computational methods that must be applied to model scattering from complex shapes also makes accurate optical modeling for dust challenging. Field observations indicate the persistence of coarse and giant dust particles at higher altitudes and farther downwind from their source than previously expected. Remote sensing retrieval algorithms based on observations at visible wavelengths have limited sensitivity to these particles and generally do not consider them, although a recent product based on longwave radiances is encouraging. Current measurements of the refractive index of bulk dust and fundamental dust minerology components such as hematite vary widely, inhibiting attempts to represent the variability in dust optical properties and forcing, as expected from different major dust source regions on Earth that have varying mineralogical composition. Some remote sensing retrieval algorithms allow for limited refractive index variability in their inversion solutions through mixing with other fine mode aerosol models, or optimizing the single scattering albedo, but Earth system models surveyed for this paper assume a globally uniform, size-invariant refractive index. Although no Martian dust samples have yet been returned to Earth, remote sensing observations indicate that Martian dust is globally homogenous in composition, and a single spectral refractive index assumption has been widely adopted to represent Martian dust. The lack of comprehensive, statistically representative measurements of dust particle microphysical properties (size distribution, morphology, complex index of refraction spectra, internal structure heterogeneity), and the resulting optical properties, limits our ability to verify the fidelity of these assumptions. A chain of measurements is needed, ranging from characterizing individual dust mineralogy components (e.g., pure hematite and goethite) to in situ sampling of complex atmospheric aerosol mixtures. Such results could be applied to both remote sensing retrievals that characterize the optical properties of the total aerosol burden in the atmosphere from total radiance measurements, and to global models that represent the total aerosol burden in the atmosphere by building it up from the balance of individual aerosol sources and sinks.

Aeolian dust↗

NASA NTRS1984

An experimental investigation of the angular scattering and backscattering behaviors of the simulated clouds of the outer planets

A cryogenic, 50 liter volume Planetary Cloud Simulation Chamber has been constructed to permit the laboratory study of the cloud compositions which are likely to be found in the atmospheres of the outer planets. On the basis of available data, clouds composed of water ice, carbon dioxide, and liquid and solid ammonia and methane, both pure and in various mixtures, have been generated. Cloud microphysical observations have been permitted through the use of a cloud particle slide injector and photomicrography. Viewports in the lower chamber have enabled the collection of cloud backscattering data using 633 and 838 nm laser light, including linear depolarization ratios and complete Stokes parameterization. The considerable technological difficulties associated with the collection of angular scattering patterns within the chamber, however, could not be completely overcome.

Sassen, K.↗

NASA NTRS2012

Aerosol Direct, Indirect, Semidirect, and Surface Albedo Effects from Sector Contributions Based on the IPCC AR5 Emissions for Preindustrial and Present-day Conditions

The anthropogenic increase in aerosol concentrations since preindustrial times and its net cooling effect on the atmosphere is thought to mask some of the greenhouse gas-induced warming. Although the overall effect of aerosols on solar radiation and clouds is most certainly negative, some individual forcing agents and feedbacks have positive forcing effects. Recent studies have tried to identify some of those positive forcing agents and their individual emission sectors, with the hope that mitigation policies could be developed to target those emitters. Understanding the net effect of multisource emitting sectors and the involved cloud feedbacks is very challenging, and this paper will clarify forcing and feedback effects by separating direct, indirect, semidirect and surface albedo effects due to aerosols. To this end, we apply the Goddard Institute for Space Studies climate model including detailed aerosol microphysics to examine aerosol impacts on climate by isolating single emission sector contributions as given by the Coupled Model Intercomparison Project Phase 5 (CMIP5) emission data sets developed for Intergovernmental Panel on Climate Change (IPCC) AR5. For the modeled past 150 years, using the climate model and emissions from preindustrial times to present-day, the total global annual mean aerosol radiative forcing is -0.6 W/m(exp 2), with the largest contribution from the direct effect (-0.5 W/m(exp 2)). Aerosol-induced changes on cloud cover often depends on cloud type and geographical region. The indirect (includes only the cloud albedo effect with -0.17 W/m(exp 2)) and semidirect effects (-0.10 W/m(exp 2)) can be isolated on a regional scale, and they often have opposing forcing effects, leading to overall small forcing effects on a global scale. Although the surface albedo effects from aerosols are small (0.016 W/m(exp 2)), triggered feedbacks on top of the atmosphere (TOA) radiative forcing can be 10 times larger. Our results point out that each emission sector has varying impacts by geographical region. For example, the single sector most responsible for a net positive radiative forcing is the transportation sector in the United States, agricultural burning and transportation in Europe, and the domestic emission sector in Asia. These sectors are attractive mitigation targets.

Bauer, Susanne E.↗

NASA NTRS1994

Application of airborne field mill data for use in launch support

An airborne field mill (ABFM) system was implemented on a Learjet 36A and was used to collect electric-field and microphysical data for summertime convective clouds near Cape Canaveral and the Kennedy Space Center. This system is described and the method used for calibrating it is outlined. Data from this ABFM system were used to investigate the relationship between the strengths of electric fields at the boundaries of summer maritime convective clouds and the distances from these cloud where the fields could first be detected by this system. The relationship between the electric-field strengths at the boundaries of convective clouds and selected radar-measurable parameters of these clouds were also investigated. This study shows promise that the radar volume of these clouds can be used to estimate the order of magnitude electric-field intensity. It is possible that selected remote radar measurements could be incorporated into the launch commit criteria as a means of providing greater confidence and flexibility for determining safe stand-off distances for launch vehicles from convective clouds.

Harris-Hobbs, Ray↗

NASA NTRS1989

The role of cloud microphysical processes in climate - An assessment from a one-dimensional perspective

A one-dimensional climate model with an interactive cloud formation and precipitation program is used to study the relationship between cloud microphysical processes and climate. It is shown that the rate of precipitation is directly proportional to the fourth power of the mean cloud particle radius. The effects of CO2 doubling on the climate are examined. It is suggested that smaller cloud droplets may be produced by condensation nuclei over the oceans, as a result of greenhouse warming and pollution over land. Larger cloud droplets could be caused by the removal of cloud-forming nuclei, resulting from enhance precipitation due to greenhouse perturbations.

Liou, Kuo-Nan↗

NASA NTRS1994

Case study of a low-reflectivity pulsating microburst: Numerical simulation of the Denver, 8 July 1989, storm

On 8 July 1989, a very strong microburst was detected by the Low-Level Windshear Alert system (LLWAS), within the approach corridor just north of Denver Stapleton Airport. The microburst was encountered by a Boeing 737-200 in a 'go-around' configuration which was reported to have lost considerable air speed and altitude during penetration. Data from LLWAS revealed a pulsating microburst with an estimated peak velocity change of 48 m/s. Wilson et al. reported that the microburst was accompanied by no apparent visible clues such as rain or virga, although blowing dust was present. Weather service hourly reports indicated virga in all quadrants near the time of the event. A National Center for Atmospheric Research (NCAR) research Doppler radar was operating; but according to Wilson et al., meaningful velocity could not be measured within the microburst due to low radar-reflectivity factor and poor siting for windshear detection at Stapleton. This paper presents results from the three-dimensional numerical simulation of this event, using the Terminal Area Simulation System (TASS) model. The TASS model is a three-dimensional nonhydrostatic cloud model that includes parameterizations for both liquid and ice phase microphysics, and has been used in investigations of both wet and dry microburst case studies. The focus of this paper is the pulsating characteristic and the very-low radar reflectivity of this event. Most of the surface outflow contained no precipitation. Such an event may be difficult to detect by radar.

Proctor, Fred H.↗

DOE OSTI2024

The use of idealised experiments in testing a new convective parametrization: Performance of CoMorph-A

CoMorph is a new mass-flux convection parametrization under development at the Met Office designed for use within the Unified Model and its successor model, LFRic. Use of a three-dimensional idealised model enables controlled tests of the performance of the scheme across different regimes. This includes the interaction between the physical parametrizations and the resolved dynamics, allowing study of the emergent organisation of convection on the resolved scale. A selection of well-known cases is revisited here, with the purpose of documenting the extent to which CoMorph captures a range of important, but challenging, behaviour such as the diurnal cycle and sensitivity to tropospheric moisture. Simulations using CoMorph-A, a new physics package, that has been demonstrated to perform well at numerical weather prediction (NWP) and climate scales, are compared against the current global atmosphere configuration and high-resolution results. In addition to an entirely new convection scheme, the package of changes includes significant changes to the cloud, microphysics, and boundary-layer parametrizations. Recognising that CoMorph-A is the first version of a scheme that will continue to be substantially developed and to obtain good performance, compromises in tuning have had to be made. These idealised tests therefore show what works well in this configuration, and what areas will require further work. As such, it is quite a demanding testbed and could be viewed as some of the equipment required for a “convective playground”.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Do Arctic mixed-phase clouds sometimes dissipate due to insufficient aerosol? Evidence from comparisons between observations and idealized simulations

Abstract. Mixed-phase clouds are ubiquitous in the Arctic. These clouds can persist for days and dissipate in a matter of hours. It is sometimes unknown what causes this sudden dissipation, but aerosol–cloud interactions may be involved. Arctic aerosol concentrations can be low enough to affect cloud formation and structure, and it has been hypothesized that, in some instances, concentrations can drop below some critical value needed to maintain a cloud. We use observations from a Department of Energy ARM site on the northern slope of Alaska at Oliktok Point (OLI), the Arctic Summer Cloud Ocean Study (ASCOS) field campaign in the high Arctic Ocean, and the Integrated Characterisation of Energy, Clouds, Atmospheric state, and Precipitation at Summit – Aerosol Cloud Experiment (ICECAPS-ACE) project at the NSF (National Science Foundation) Summit Station in Greenland (SMT) to identify one case per site where Arctic boundary layer clouds dissipated coincidentally with a decrease in surface aerosol concentrations. These cases are used to initialize idealized large eddy simulations (LESs) in which aerosol concentrations are held constant until, at a specified time, all aerosols are removed instantaneously – effectively creating an extreme case of aerosol-limited dissipation which represents the fastest a cloud could possibly dissipate via this process. These LESs are compared against the observed data to determine whether cases could, potentially, be dissipating due to insufficient aerosol. The OLI case's observed liquid water path (LWP) dissipated faster than its simulation, indicating that other processes are likely the primary drivers of the dissipation. The ASCOS and SMT observed LWP dissipated at similar rates to their respective simulations, suggesting that aerosol-limited dissipation may be occurring in these instances. We also find that the microphysical response to this extreme aerosol forcing depends greatly on the specific case being simulated. Cases with drizzling liquid layers are simulated to dissipate by accelerating precipitation when aerosol is removed while the case with a non-drizzling liquid layer dissipates quickly, possibly glaciating via the Wegener–Bergeron–Findeisen (WBF) process. The non-drizzling case is also more sensitive to ice-nucleating particle (INP) concentrations than the drizzling cases. Overall, the simulations suggest that aerosol-limited cloud dissipation in the Arctic is plausible and that there are at least two microphysical pathways by which aerosol-limited dissipation can occur.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2024

General Circulation Models Simulate Negative Liquid Water Path–Droplet Number Correlations, but Anthropogenic Aerosols Still Increase Simulated Liquid Water Path

General circulation models' (GCMs) estimates of the liquid water path adjustment to anthropogenic aerosol emissions differ in sign from other lines of evidence. This reduces confidence in estimates of the effective radiative forcing of the climate by aerosol–cloud interactions (ERFaci). The discrepancy is thought to stem in part from GCMs' inability to represent the turbulence–microphysics interactions in cloud-top entrainment, a mechanism that leads to a reduction in liquid water in response to an anthropogenic increase in aerosols. In the real atmosphere, enhanced cloud-top entrainment is thought to be the dominant adjustment mechanism for liquid water path, weakening the overall ERFaci. We show that the latest generation of GCMs includes models that produce a negative correlation between the present-day cloud droplet number and liquid water path, a key piece of observational evidence supporting liquid water path reduction by anthropogenic aerosols and one that earlier-generation GCMs could not reproduce. However, even in GCMs with this negative correlation, the increase in anthropogenic aerosols from preindustrial to present-day values still leads to an increase in the simulated liquid water path due to the parameterized precipitation suppression mechanism. This adds to the evidence that correlations in the present-day climate are not necessarily causal. We investigate sources of confounding to explain the noncausal correlation between liquid water path and droplet number. These results are a reminder that assessments of climate parameters based on multiple lines of evidence must carefully consider the complementary strengths of different lines when the lines disagree.

General circulation models↗

DOE OSTI2026

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2013

Integration of the Total Lightning Jump Algorithm into Current Operational Warning Environment Conceptual Models

The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. In order to become a viable option for operational forecasters to incorporate into their severe storm monitoring process, the total lightning jump must be placed into the framework of several severe storm conceptual models (e.g., radar evolution, storm morphology) which forecasters have built through training and experience. Thus, one of the goals of this study is to examine and relate the lightning jump concept to often used radar parameters (e.g., dBZ vertical structure, VIL, MESH, MESO/shear) in the warning environment. Tying lightning trends and lightning jump occurrences to these radar based parameters will provide forecasters with an additional tool that they can use to build an accurate realtime depiction as to what is going on in a given environment. Furthermore, relating the lightning jump concept to these parameters could also increase confidence in a warning decision they have already made, help tip the scales on whether or not to warn on a given storm, or to draw the forecaster s attention to a particular storm that is rapidly developing. Furthermore the lightning information will add vital storm scale information in regions that are not well covered by radar, or when radar failures occur. The physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relation to updraft strength, updraft volume, precipitation -sized ice mass, etc.; however, very few have related the concept of the lightning jump and manifestation of severe weather to storm dynamics and microphysics using multi -Doppler and polarimetric radar techniques. Therefore, the second half of this study will combine the lightning jump algorithm and these radar techniques in order to place the lightning jump concept into a physical and dynamical framework. This analysis includes examining such parameters as mixed phase precipitation volume, charging zone, updraft strength and updraft volume. Such a study should provide increased understanding of and confidence in the strengths and limitations of the lightning jump algorithm in the storm warning process.

Schultz, Christopher J.↗

DOE OSTI2022

Spectral analysis of ultra-cool white dwarfs polluted by planetary debris

ABSTRACT We identify two ultra-cool (${T_\mathrm{eff}}\lt 4000$ K) metal-polluted (DZ) white dwarfs WD J2147−4035 and WD J1922+0233 as the coolest and second coolest DZ stars known to date with ${T_\mathrm{eff}}\approx 3050$ K and ${T_\mathrm{eff}}\approx 3340$ K, respectively. Strong atmospheric collision-induced absorption (CIA) causes the suppression of red optical and infrared flux in WD J1922+0233, resulting in an unusually blue colour given its low temperature. WD J2147−4035 has moderate infrared CIA yet has the reddest optical colours known for a DZ white dwarf. Microphysics improvements to the non-ideal effects and CIA opacities in our model atmosphere code yields reasonable solutions to observations of these ultra-cool stars. WD J2147−4035 has a cooling age of over 10 Gyr which is the largest known for a DZ white dwarf, whereas WD J1922+0233 is slightly younger with a cooling age of 9 Gyr. Galactic kinematics calculations from precise Gaia EDR3 astrometry reveal these ultra-cool DZ stars as likely members of the Galactic disc thus they could be pivotal objects in future studies constraining an upper age limit for the disc of the Milky Way. We present intermediate-resolution spectroscopy for both objects, which provides the first spectroscopic observations of WD J2147−4035. Detections of sodium and potassium are made in both white dwarfs, in addition to calcium in WD J1922+0233 and lithium in WD J2147−4035. We identify the magnetic nature of WD J2147−4035 from Zeeman splitting in the lithium line and also make a tentative detection of carbon, so we classify this star as DZQH. WD J1922+0233 likely accreted planetary crust debris, while the debris composition that polluted WD J2147−4035 remains unconstrained.

Elms, Abbigail K. (ORCID:0000000176667416)↗

NASA NTRS2011

Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

Levy, Robert C.↗

NASA NTRS1999

Large Eddy Simulation of Cirrus Clouds

The Regional Atmospheric Modeling System (RAMS) with mesoscale interactive nested-grids and a Large-Eddy Simulation (LES) version of RAMS, coupled to two-moment microphysics and a new two-stream radiative code were used to investigate the dynamic, microphysical, and radiative aspects of the November 26, 1991 cirrus event. Wu (1998) describes the results of that research in full detail and is enclosed as Appendix 1. The mesoscale nested grid simulation successfully reproduced the large scale circulation as compared to the Mesoscale Analysis and Prediction System's (MAPS) analyses and other observations. Three cloud bands which match nicely to the three cloud lines identified in an observational study (Mace et al., 1995) are predicted on Grid #2 of the nested grids, even though the mesoscale simulation predicts a larger west-east cloud width than what was observed. Large-eddy simulations (LES) were performed to study the dynamical, microphysical, and radiative processes in the 26 November 1991 FIRE 11 cirrus event. The LES model is based on the RAMS version 3b developed at Colorado State University. It includes a new radiation scheme developed by Harrington (1997) and a new subgrid scale model developed by Kosovic (1996). The LES model simulated a single cloud layer for Case 1 and a two-layer cloud structure for Case 2. The simulations demonstrated that latent heat release can play a significant role in the formation and development of cirrus clouds. For the thin cirrus in Case 1, the latent heat release was insufficient for the cirrus clouds to become positively buoyant. However, in some special cases such as Case 2, positively buoyant cells can be embedded within the cirrus layers. These cells were so active that the rising updraft induced its own pressure perturbations that affected the cloud evolution. Vertical profiles of the total radiative and latent heating rates indicated that for well developed, deep, and active cirrus clouds, radiative cooling and latent heating could be comparable in magnitude in the cloudy layer. This implies that latent heating cannot be neglected in the construction of a cirrus cloud model. The probability density function (PDF) of w was analyzed to assist in the parameterization of cloud-scale velocities in large-scale models. For the more radiatively-driven, thin cirrus case, the PDFs are approximately Gaussian. However, in the interior of the deep, convectively unstable case, the PDFs of w are multi-modal and very broad, indicating that parameterizing cloud-scale motions for such clouds can be very challenging. The results of this research are described in detail in a paper submitted to the Journal of Atmospheric Science (Wu and Cotton, 1999), which is enclosed as Appendix 2. Using soundings extracted from a mesoscale simulation of the November 26, 1991 cirrus event, the radiative effects on vapor deposition/sublimation of ice crystals was studied using a two-dimensional cloud-resolving model (CRM) version of RAMS, coupled to an explicit bin-resolving microphysics. The CRM simulations of the November 26, 1991 cirrus event demonstrate that the radiative impact on the diffusional growth (or sublimation) of ice crystals is significant. In this case, the ice particles experienced radiative warming. Model results show that radiative feedbacks in the diffusional growth of ice particles can be very complex. Radiative warming of an ice particle will restrict the particle's diffusional growth. In the case of radiative warming, ice particles larger than a certain size will experience so much radiative warming that surface ice saturation vapor pressures become large enough to cause sublimation of the larger crystals, while smaller crystals are growing by vapor deposition. However, ice mass production can be enhanced in the case of radiative cooling of an ice particle. For the November 26, 1991 cirrus event, radiative feedback results in significant reduction in the total ice mass, especially in the production of large ice crystals, and consequently, both radiative and dynamic properties of the cirrus cloud are significantly affected. A complete description of this research has been submitted as a paper to the Journal of Atmospheric Science (Wu et al., 1999), and included as Appendix 3.

Wu, Ting↗

DOE OSTI2024

The Thunderstorms With the Greatest Lightning Densities on Earth

The most intense thunderstorms on Earth were surveyed using the comprehensive meteorological instrumentation on the Tropical Rainfall Measuring Mission (TRMM) satellite. Expansive land-based Mesoscale Convective Systems (MCSs) were consistently identified among the Earth's most intense thunderstorms, with their organization into many convective cells spanning a large areal extent permitting exceptional overall flash rates for these storms. In this study, we identify a new class of extreme thunderstorm. Lightning-dense thunderstorms are relatively compact convective storms whose concentrated lightning activity hinders our ability to accurately measure their flash rates. The top storms have a flash rate of one flash spanning many seconds, as there is insufficient separation to distinguish one flash from another. While any particularly active convective cell could be capable of producing high lightning densities, we find that thunderstorms with the greatest lightning densities on Earth are found in maritime thunderstorms that have not been appreciated in prior work due to the inaccurate flash rate measurements. These storms that are mostly found throughout the Gulf of Mexico and east of South Africa (among other coastal and oceanic regions) have measured TRMM proxies for convective intensity that rival the top MCS thunderstorms, but their horizontal and vertical dimensions are small by comparison. Thus, the necessary microphysical elements for electrification processes are more highly concentrated, enabling the observed extreme lightning densities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Reducing Southern Ocean Shortwave Radiation Errors in the ERA5 Reanalysis with Machine Learning and 25 Years of Surface Observations

Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SW down exhibited large errors (mean bias = 54 W m -2 , mean absolute error = 82 W m -2 , root-mean-square error = 132 W m -2 , and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SW down with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SW down using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Thunderstorms With the Greatest Lightning Densities on Earth

54 ENVIRONMENTAL SCIENCES↗