Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cloud parameterizations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Response of Tropical Terrestrial Gross Primary Production to the Super El Niño Event in 2015

The gross primary production (GPP) in tropical terrestrial ecosystems plays a critical role in the global carbon cycle and climate change. The strong 2015–2016 El Niño event offers a unique opportunity to investigate how GPP in the tropical terrestrial ecosystems responds to climatic forcing. This study uses two GPP products and concurrent climate data to investigate the GPP anomalies and their underlying causes. We find that both GPP products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the multiyear mean of 2001–2015, and this enhancement is the net result of GPP increase in tropical forests and decrease in nonforests. We show that the increased GPP in tropical forests during the El Nino event is consistent with increased photosynthesis active radiation as a result of a reduction in clouds, while the decreased GPP in nonforests is consistent with increased water stress as a result of a reduction of precipitation and an increase of temperature. These results reveal the strong coupling of ecosystem and climate that is different in forest and nonforest ecosystems and provide a test case for carbon cycle parameterization and carbon-climate feedback simulation in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Planck intermediate results: XXIX. All-sky dust modelling with Planck , IRAS, and WISE observations

In this paper, we present all-sky modelling of the high resolution Planck, IRAS, and WISE infrared (IR) observations using the physical dust model presented by Draine & Li in 2007 (DL, ApJ, 657, 810). We study the performance and results of this model, and discuss implications for future dust modelling. The present work extends the DL dust modelling carried out on nearby galaxies using Herschel and Spitzer data to Galactic dust emission. We employ the DL dust model to generate maps of the dust mass surface density Σ Md , the dust optical extinction A V , and the starlight intensity heating the bulk of the dust, parametrized by U min . The DL model reproduces the observed spectral energy distribution (SED) satisfactorily over most of the sky, with small deviations in the inner Galactic disk and in low ecliptic latitude areas, presumably due to zodiacal light contamination. In the Andromeda galaxy (M31), the present dust mass estimates agree remarkably well (within 10%) with DL estimates based on independent Spitzer and Herschel data. We compare the DL optical extinction A V for the diffuse interstellar medium (ISM) with optical estimates for approximately 2 × 10 5 quasi-stellar objects (QSOs) observed inthe Sloan Digital Sky Survey (SDSS). The DL A V estimates are larger than those determined towards QSOs by a factor of about 2, which depends on U min . The DL fitting parameter U min , effectively determined by the wavelength where the SED peaks, appears to trace variations in the far-IR opacity of the dust grains per unit A V , and not only in the starlight intensity. These results show that some of the physical assumptions of the DL model will need to be revised. To circumvent the model deficiency, we propose an empirical renormalization of the DL A V estimate, dependent of U min , which compensates for the systematic differences found with QSO observations. This renormalization, made to match the A V estimates towards QSOs, also brings into agreement the DL A V estimates with those derived for molecular clouds from the near-IR colours of stars in the 2 micron all sky survey (2MASS). The DL model and the QSOs data are also used to compress the spectral information in the Planck and IRAS observations for the diffuse ISM to a family of 20 SEDs normalized per A V , parameterized by U min , which may be used to test and empirically calibrate dust models. Finally, the family of SEDs and the maps generated with the DL model are made public in the Planck Legacy Archive.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Aerosol-Cloud-Meteorology Interaction Airborne Field Investigations: Using Lessons Learned from the US West Coast in the Design of ACTIVATE off the US East Coast

We report on a multi-year set of airborne field campaigns (2005 – 2016) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) (2019–2023). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (> 500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here (i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and (ii) quantification of model-relevant metrics associated with aerosol-cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing Impacts of Waves on Hub-Height Winds off the U.S. West Coast Using Lidar Buoys and Coupled Modeling Approaches

Given the importance of offshore wind energy development to the U.S. clean energy targets, it is vital to be able to characterize the wind resource in that environment accurately. Toward that end, two Bureau of Ocean Energy Management buoys equipped with Doppler lidar are being maintained by Pacific Northwest National Laboratory on behalf of the Department of Energy and deployed to regions of potential offshore wind development. In addition to standard meteorological and oceanographic measurements, the buoys document the wind profile between about 40 m and 250 m above the sea surface through Doppler lidar retrievals. After a multiyear deployment of two buoys along the U.S. East Coast, the buoys were redeployed to the U.S. West coast from 2020 – 2022 to locations near the Humboldt and Morro Bay lease areas. The buoys provide nearly continuous, multiyear datasets that can be used to evaluate predictions of hub-height (~100 m) wind speed for standard atmospheric models in the region. In the absence of measurements at the study site, offshore wind developers rely on model-based data to assess site conditions. Potential sources of model error in this environment include under-resolution or misrepresentation of coastal topographically forced flows, marine boundary layer dynamics and the evolution of their associated cloud and turbulence fields, the role of upwelling and other currents on surface heat fluxes into the boundary layer, and the impact of wave fields on surface momentum fluxes and thus the wind speed profile. In particular, most predictive models of wind speed do not predict wave fields at all, relying on parameterizations to represent their effects. In thus study, we focus on evaluating the role of wind / wave interactions on modeled hub-height wind speed and error by using the Coupled Ocean–Atmosphere–Wave–Sediment–Transport Modeling System to capture two-way interactions between an atmospheric model (Weather Research and Forecasting (WRF)) and a wave model (WAVEWATCHIII (WW3)) and compare to both stand-alone WRF and one-way coupled WRF / WW3 configurations. Our approach is similar to that used in Gaudet et al. (2022) to evaluate wind / wave coupling over the U.S. East Coast, but applied to the very different environment of the U.S. West Coast. We show examples for two cases, a cold-season frontal case and a warm-season low-level jet case. We find that wind / wave coupling makes little impact on model error for these cases at the location of the lidar buoys, for which other misrepresentations of model physics seems to be responsible for model-observation discrepancies. However, domain-wide evaluations, which also make use of the National Buoy Data Center network, show that a two-way coupling approach is less prone to systematic errors in the hub-height wind field than the one-way coupled approach. WRF resolution of kilometer-scale or less is needed to properly capture the sharp wind speed gradients that can be found along the coastline, and WW3 simulations driven by the downscaled WRF produce better bulk and spectral wave fields when compared to observations. Implications of the results for wind resource characterization are then discussed.

17 WIND ENERGY↗
DOE OSTI2014

Simulation of the Summer Monsoon Rainfall over East Asia using the NCEP GFS Cumulus Parameterization at Different Horizontal Resolutions

The most recent version of Simplified Arakawa-Schubert (SAS) cumulus scheme in National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) (GFS SAS) has been implemented into the Weather and Research Forecasting (WRF) model with a modification of triggering condition and convective mass flux to become depending on model’s horizontal grid spacing. East Asian Summer Monsoon of 2006 from June to August is selected to evaluate the performance of the modified GFS SAS scheme. Simulated monsoon rainfall with the modified GFS SAS scheme shows better agreement with observation compared to the original GFS SAS scheme. The original GFS SAS scheme simulates the similar ratio of subgrid-scale precipitation, which is calculated from a cumulus scheme, against total precipitation regardless of model’s horizontal grid spacing. This is counter-intuitive because the portion of resolved clouds in a grid box should be increased as the model grid spacing decreases. This counter-intuitive behavior of the original GFS SAS scheme is alleviated by the modified GFS SAS scheme. Further, three different cumulus schemes (Grell and Freitas, Kain and Fritsch, and Betts-Miller-Janjic) are chosen to investigate the role of a horizontal resolution on simulated monsoon rainfall. The performance of high-resolution modeling is not always enhanced as the spatial resolution becomes higher. Even though improvement of probability density function of rain rate and long wave fluxes by the higher-resolution simulation is robust regardless of a choice of cumulus parameterization scheme, the overall skill score of surface rainfall is not monotonically increasing with spatial resolution.

CPS↗
DOE OSTI2019

Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Field Campaign Report

General circulation models and downscaled regional models exhibit persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation fraction, and anvil coverage (e.g., Del Genio 2012, Del Genio et al. 2012, Hohenegger and Stevens 2013, Song et al. 2013). Despite important impacts on the distribution of atmospheric heating, moistening, momentum, and precipitation (e.g., Hartmann et al. 1984, Fritsch et al. 1986, Houze 1989, 2004, Donner et al. 2001, Del Genio and Kovari 2002, Schumacher et al. 2004, Nesbitt et al. 2006, Storelvmo 2012), nearly all climate models fail to represent mesoscale convective organization (Del Genio 2012), while system evolution is not represented at all (Ovchinnikov et al. 2006). Recent advances in cumulus parameterization coupled with increasing model resolution have improved predictions, but even relatively higher-resolution models without parameterized deep convection have some persistent kinematic and microphysical biases (e.g., Blossey et al. 2007, Matsui et al. 2009, Luo et al. 2010, Lang et al. 2011, Varble et al. 2011, Fridlind et al. 2012, Hagos et al. 2014, Varble et al. 2014a-b, Fan et al. 2017, Stanford et al. 2017, Han et al. 2019). To improve representation of convective systems in models requires adequate characterization of their predictability as a function of environmental conditions. Because of the significant sensitivities of deep convective initiation, intensity, lifetime, propagation, and mesoscale convective organization to many factors including multi-scale atmospheric circulations, ambient environmental stability, humidity, wind distributions, and cloud microphysical processes, this characterization relies on comprehensively observing many cases of convective initiation, non-initiation, organization, and non-organization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models

Abstract While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement In successive generations of computer models that simulate Earth’s atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth’s surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model’s vertical grid spacing.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Advancing Organized Convection Representation in the Unified Model: Implementing and Enhancing Multiscale Coherent Structure Parameterization

To address the effect of stratiform latent heating on meso- to large-scale circulations, an enhanced implementation of the Multiscale Coherent Structure Parameterization (MCSP) is developed for the Met Office Unified Model. MCSP represents the top-heavy stratiform latent heating from under-resolved organized convection in general circulation models. We couple the MCSP with a mass-flux convection scheme (CoMorph-A) to improve storm lifecycle continuity. The improved MCSP trigger is specifically designed for mixed-phase deep convective cloud, combined with a background vertical wind shear, both known to be crucial for stratiform development. We also test a cloud top temperature dependent convective-stratiform heating partitioning, in contrast to the earlier fixed partitioning. Assessments from ensemble weather forecasts and decadal simulations demonstrate that MCSP directly reduces cloud deepening and precipitation areas by moderating mesoscale circulations. Indirectly, it amends tropical precipitation biases, notably correcting dry and wet biases over India and the Indian Ocean, respectively. Remarkably, the scheme outperforms a climate model ensemble by improving seasonal precipitation cycle predictions in these regions. The scheme also improves Madden-Julian Oscillation (MJO) spectra, achieving better alignment with observational and reanalysis data by intensifying the simulated MJO over the Indian Ocean during phases 4 to 5. However, the scheme increases precipitation overestimation over the Western Pacific. Shifting from fixed to temperature-dependent convective-stratiform partitioning reduces the Pacific precipitation overestimation and further improves the seasonal cycle in India. Spatially correlated biases highlight the necessity for advances beyond deterministic approaches to align MCSP with environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Urban weather modeling using WRF: linking physical assumptions, code implementation, and observational needs

The Weather Research and Forecasting (WRF) model includes urban schemes that simulate the influence of urban surfaces on the atmosphere using parameterizations for flux, and radiative exchanges. Three core schemes – the Bulk urban parameterization, Single-Layer Urban Canopy Model (SLUCM), and Multi-Layer Urban Canopy Model (MLUCM) – represent increasing levels of complexity. Although the parameterizations within these urban schemes are described in the literature, their specific implementation remains poorly documented, thus slowing down model development efforts. This manuscript provides a roadmap to the three urban schemes in WRF version 4.5.2, presenting equations using the same symbols as in the model code, along with references to code lines, and including graphics and explanations that connect the code to its physical foundations. Our thorough review of the urban parameterizations implemented in WRF version 4.5.2 highlighted a handful of parameters that may introduce discontinuities in simulations: (i) in the SLUCM, a 1 mm h −1 rain rate threshold is employed to switch between two minimum moisture availability parameterizations, thus impacting latent heat flux calculations; (ii) in the SLUCM a threshold is used to partition shortwave radiation into direct and diffuse components; (iii) in all three urban schemes, the bulk Richardson number is employed to select the similarity function, which influences the vertical distribution of heat and momentum. We also identified a highly simplified treatment of the radiative balance on roof surfaces. The implications of these simplifications can be assessed through targeted observations across relevant conditions, including varying precipitation rates, cloud cover, and transitions between stability regimes. Furthermore, the widespread application of the Monin-Obukhov similarity theory in these urban schemes warrants model evaluation under highly stable and unstable conditions and in heterogeneous urban settings with variable land cover and building heights on scales finer than model resolution. To address these challenges, we offer guidance on observational strategies, emphasizing the need for multi-parametric measurements to capture potential compensating biases and multi-height measurements that align with the levels where quantities are diagnostic and prognosed in the model (i.e., the lowest atmospheric level of the WRF model). Finally, our inspection of the code revealed implementation bugs that have now been corrected in WRF versions 4.6.0 and 4.6.1. Sensitivity tests over the Atlanta urban area show that these corrections affect surface temperatures, underscoring the importance of performing rigorous documentation and verification of the implementation of parameterizations in model code.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Light absorption enhancement of black carbon in a pyrocumulonimbus cloud

Abstract Pyrocumulonimbus (pyroCb) firestorm systems have been shown to inject significant amounts of black carbon (BC) to the stratosphere with a residence time of several months. Injected BC warms the local stratospheric air, consequently perturbing transport and hence spatial distributions of ozone and water vapor. A distinguishing feature of BC-containing particles residing within pyroCb smoke is their thick surface coatings made of condensed organic matter. When coated with non-refractory materials, BC’s absorption is enhanced, yet the absorption enhancement factor ( E abs ) for pyroCb BC is not well constrained. Here, we perform particle-scale measurements of BC mass, morphology, and coating thickness from inside a pyroCb cloud and quantify E abs using an established particle-resolved BC optics model. We find that the population-averaged E abs for BC asymptotes to 2.0 with increasing coating thickness. This value denotes the upper limit of E abs for thickly coated BC in the atmosphere. Our results provide observationally constrained parameterizations of BC absorption for improved radiative transfer calculations of pyroCb events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Shallow-to-Deep Transition of Continental Moist Convection: Cold Pools, Surface Fluxes, and Mesoscale Organization

Large-eddy simulation is used to investigate the effects of cold pools driven by rain evaporation on the shallow-to-deep convection transition over land. The physically consistent methodologies are developed to obtain a time-dependent reference ensemble without cold pools and to apply interactive surface heat fluxes without modeling of surface energy and water budgets. Three different simulation ensembles are contrasted. The reference ensemble, in the spirit of one-dimensional single-column models, eliminates cold pools by horizontally homogenizing negative buoyancy production due to rain evaporation. The additional ensembles complement the reference cold-pool-free ensemble by including cold pools and by applying either interactive or prescribed surface fluxes. Contrasting these ensembles suggests possible improvements of convection parameterization in large-scale models of weather and climate. Without cold pools, the reference ensemble preserves key features of buoyancy-driven cellular convection associated with a field of convective plumes, as assumed in a typical convection parameterization. With cold pools, a significant enhancement of surface heat and moisture fluxes and about an hour delay of their daily maximum is simulated. Cold pools enhance near-surface temperature and moisture standard deviations as well as maxima of the near-surface updraft velocity. They also lead to the reduction of cloud lateral entrainment, deeper vertical development of the cloud layer, and a few-times-larger accumulated surface precipitation. Interactive surface fluxes provide a damping mechanism that noticeably suppresses all these effects. Perhaps surprisingly, cold pools do not significantly change the cloud-base convective mass flux that approximately follows the evolution of surface heat fluxes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Removing numerical pathologies in a turbulence parameterization through convergence testing

Discretized numerical models of the atmosphere are usually intended to faithfully represent an underlying set of continuous equations, but this necessary condition is violated sometimes by subtle pathologies that have crept into the discretized equations. Such pathologies can introduce undesirable artifacts, such as sawtooth noise, into the model solutions. The presence of these pathologies can be detected by numerical convergence testing. This study employs convergence testing to verify the discretization of the Cloud Layers Unified By Binormals (CLUBB) model of clouds and turbulence. That convergence testing identifies two aspects of CLUBB's equation set that contribute to undesirable noise in the solutions. First, numerical limiters (i.e. clipping) used by CLUBB introduce discontinuities or slope discontinuities in model fields. Second, this noise can be amplified by an advective term in CLUBB's background diffusion. Smoothing the limiters and removing the advective component of the background diffusion reduces the noise and restores the expected first-order convergence in CLUBB's solutions. These model reformulations improve the results at coarser, near-operational grid spacing and time step in cumulus cloud and dry turbulence tests. In addition, convergence testing is proved to be a valuable tool for detecting pathologies, including unintended discontinuities and grid dependence, in the model equation set.

Mathematics and Computing, Geosciences↗
DOE OSTI2018

Boundary Layer Controls on the Shallow-to-Deep Cumulus Transition (Final Technical Report)

The primary goals of this project are to advance our fundamental understanding of how boundary-layer processes impact cumulus convection over land and to provide a robust observational basis for refining convective parameterizations. These goals are to be accomplished using a combination of Doppler and Raman lidar observations at ARM SGP, along with various ancillary data sets, to answer the following science questions:(1) How does the turbulent structure of the boundary layer vary across the transition from shallow to deep convection? (2) How do sub-cloud circulations affect the vertical and horizontal extent of cumulus clouds? (3) What are the relationships between bulk boundary layer statistics and cloud base updrafts? (4) Do observations support CIN-based mass flux closures? (5) Do observations support the PDF based closures assumed in CLUBB?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. Knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to improve understanding of atmospheric sulfur, aerosol/cloud dynamics, and albedo. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 82 996 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of latitude–longitude coordinates, time of day, time of year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, and silicate. Linear regressions of DMS against the environmental parameters show that on a global-scale mixed layer depth and solar radiation are the strongest predictors of DMS. These parameters capture ~9 % and ~7 % of the raw DMS data variance, respectively. Multilinear regression can capture more of the raw data variance (~39 %) but strongly underestimates DMS in high-concentration regions. In contrast, the artificial neural network captures ~66 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in surface ocean DMS with the highest concentrations and sea-to-air fluxes in the high-latitude summertime oceans. We estimate a lower global sea-to-air DMS flux (20.12±0.43 Tg S yr –1 ) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used. Our sensitivity test results show that DMS concentration does not change unidirectionally with each of the environmental parameters, which emphasizes the interactions among these parameters. The ANN model suggests that the flux of DMS from the ocean to the atmosphere will increase with global warming. Given that larger DMS fluxes induce greater cloud albedo, this corresponds to a negative climate feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

On CCN Effects upon Convective Cold Pool Timing and Features

Abstract Cold pools produced by deep convection can initiate new convection, and their representation in larger-scale weather and climate models could improve prediction of the extent and timing of upscale growth. Cold pools originate from latent cooling from precipitation changing phase, but little attention has been paid to microphysical influences on cold pool characteristics, particularly CCN effects. Datasets obtained from the CACTI and RELAMPAGO field campaigns, along with idealized numerical modeling, are utilized to investigate the hypothesis that convective storms forming in higher-CCN environments generate their first surface rainfall later, delaying cold pool initiation. Aircraft observations of CCN and shallow convection on 9 days do suggest a CCN effect. Those ingesting more CCN contained fewer drizzle drops, although a decreased cloud depth with increasing CCN was also likely a limiting factor. In three of those cases that later developed into deep convection, the timing of cold pool onset was not ubiquitously delayed in environments with more CCN. Idealized numerical simulations suggest that an ordinary thunderstorm can experience small delays in cold pool onset with increasing CCN due to changes in graupel production, but CCN effects on the cold pool from a supercell thunderstorm can be easily overpowered by its unique dynamics. A strong inverse relationship between cold pool strength, expansion rate, and depth with increasing CCN is suggested by the results of the ordinary thunderstorm simulation. Further consideration of CCN appears warranted for future cold pool parameterization development, but other environmental factors affecting storm morphology and precipitation cannot be ignored.

Meteorology & Atmospheric Sciences↗
DOE OSTI2014

Assesment of the Indirect and Semi-Direct Aerosol-Effect During ISDAC Through Integrated Observational and Modeling Studies

The Department of Energy (DOE) awarded George Mason University (GMU) with a research project. This project started on June, 2009 and ended July 2014. Main objectives of this research project are; a) to assess the indirect and semi-direct aerosol effects on microphysical structure and radiative properties of Arctic clouds, b) to assess the impact of feedback between the aerosol-cloud interactions and atmospheric boundary layer (ABL) processes on the surface energy balance, c) to better understand and characterize the important unresolved microphysical processes, aerosol effects, and ABL processes and feedbacks, over meso-γ spatial (~1-2 km) and temporal scales (a few minutes to days), and d) to investigate the scale dependency of microphysical parameterizations and its effect on simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Influence of surface morphology on the immersion mode ice nucleation efficiency of hematite particles

In this paper, the effect of the morphological modification of aerosol particles with respect to heterogeneous ice nucleation is comprehensively investigated for laboratory-generated hematite particles as a model substrate for atmospheric dust particles. The surface-area-scaled ice nucleation efficiencies of monodisperse cubic hematite particles and milled hematite particles were measured with a series of expansion cooling experiments using the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud simulation chamber. Complementary offline characterization of physico-chemical properties of both hematite subsets were also carried out with scanning electron microscopy (SEM), energy dispersive X-ray (EDX) spectroscopy, dynamic light scattering (DLS), and an electro-kinetic particle charge detector to further constrain droplet-freezing measurements of hematite particles. Additionally, an empirical parameterization derived from our laboratory measurements was implemented in the single-column version of the Community Atmospheric Model version 5 (CAM5) to investigate the model sensitivity in simulated ice crystal number concentration on different ice nucleation efficiencies. From an experimental perspective, our results show that the immersion mode ice nucleation efficiency of milled hematite particles is almost an order of magnitude higher at -35.2 °C < T < -33.5 °C than that of the cubic hematite particles, indicating a substantial effect of morphological irregularities on immersion mode freezing. Our modeling results similarly show that the increased droplet-freezing rates of milled hematite particles lead to about one order magnitude higher ice crystal number in the upper troposphere than cubic hematite particles. Finally and overall, our results suggest that the surface irregularities and associated active sites lead to greater ice activation through droplet freezing.

Hiranuma, N.↗
DOE OSTI2024

Wind-driven emissions of coarse-mode particles in an urban environment

Abstract. Quantifying surface–atmosphere exchange rates of particles is important for understanding the role of suspended particulate matter in radiative transfer, clouds, precipitation, and climate change. Emissions of coarse-mode particles with a diameter greater than 0.5 µm provide giant cloud condensation nuclei and ice nuclei. These emissions are critical for understanding the evolution of cloud microphysical properties yet remain poorly understood. Here we introduce a new method that uses lidar retrievals of the elastic backscatter and Doppler velocity to obtain surface number emissions of particles with a diameter greater than 0.53 µm. The technique is applied to study particle number fluxes over a 2-month period from 1 June to 10 August 2022 during the TRACER campaign at an urban site near Houston, TX, USA. We found that all the observed fluxes were positive (upwards), indicating particle emission from the surface. The fluxes followed a diurnal pattern and peaked near noon local time. Flux intensity varied through the 2 months with multi-day periods of strong fluxes and multi-day periods of weak fluxes. Emission particle number fluxes peaked near ∼ 100 cm−2 s−1. The daily averaged emission fluxes correlated with friction velocity and were anticorrelated with surface relative humidity. The emission flux can be parameterized as F= 3000 u*4, where u* is the friction velocity in m s−1 and the emission flux F is in cm−2 s−1. The u* dependence is consistent with emission from wind-driven erosion. Estimated values for the mass flux are in the lower range of literature values from non-urban sites. These results demonstrate that urban environments may play an important role in supplying coarse-mode particles to the boundary layer. We anticipate that quantification of these emissions will help constrain aerosol–cloud interaction models that use prognostic aerosol schemes.

54 ENVIRONMENTAL SCIENCES↗