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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparing the interactions between particulate matter and cloud properties over two populated cities in Texas using WRF-Chem fine-resolution modeling

Accurate modeling of aerosol-cloud interactions is essential for reliable weather and air quality simulations, given their significant impact on precipitation patterns, cloud dynamics, and aerosol distributions. This study employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to examine the impact of enhanced meteorological simulations, achieved through advanced microphysics parameterization supported by data assimilation techniques, on air quality across Texas on August 19 and 20, 2022. We tested four distinct configurations: (1) the Morrison two-moment bulk microphysics scheme, (2) Morrison's with observation nudging, (3) the Spectral Bin Microphysics (SBM), and (4) SBM with observation nudging. While the SBM scheme is known for its detailed representation of aerosol-cloud interactions, our focus was on how improvements in meteorological accuracy translate to more precise air quality simulations. Our findings demonstrated a progressive improvement in simulation accuracy, starting with the Morrison's scheme and further enhanced by adopting the SBM scheme, complemented by incorporating observation nudging. Specifically, the combination of the SBM scheme and the nudging substantially enhanced the model's ability to capture convective precipitation events, as shown by better alignment with NEXRAD radar reflectivity, with R increasing from –0.21 to 0.82, IOA from 0.10 to 0.87, and NMB decreasing from 99% to 34% in Houston. The enhanced meteorology translated into more accurate PM 2.5 concentration simulations, particularly through the more accurate representation of aerosol washout during precipitation events. In Houston, the SBM scheme with nudging improved the model's PM 2.5 simulations significantly, with NMB decreasing from –20% to 5% and IOA improving from 0.43 to 0.61. In San Antonio, improvements were also notable, with NMB improved from –27% to –22%, R increased from 0.48 to 0.82, and IOA increased from 0.66 to 0.86. Furthermore, our results underscore the crucial role of accurate meteorological simulations in refining our understanding of aerosol behaviors in relation to precipitation patterns, directly enhancing the reliability and effectiveness of air quality modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Turbulence and Cloudiness in Cumulus-Topped Marine Boundary Layers

Turbulence and cloudiness in cumulus-topped marine boundary layers are studied using data from the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site. The analysis includes eight periods of nonprecipitating shallow cumulus clouds, spanning 141 h and encompassing 603 individual clouds. On average, the cumulus had bases at 558 m, were 99 m thick, had a chord length of 500 m, and exhibited an hourly base-layer cloudiness of 12%. Changes in cloud fraction were primarily driven by variations in cloud number not chord length. High-resolution Doppler lidar and cloud radar observations were used to estimate updraft and downdraft mass fluxes in the cumulus base layer under both clear and cloudy regions. Cloudy updrafts contributed only ∼23% of the total updraft mass flux at cloud base, indicating that most upward mass flux originated from clear-air eddies. Updraft strength, rather than updraft fraction, was found to predominantly control both clear and cloudy updraft mass fluxes. Cloud-base cloudiness strongly correlated with cloudy updraft mass flux but showed negligible correlation with clear-air updraft mass flux. Clear-air downdraft mass flux exhibited a strong relationship with the ratio of surface buoyancy to inversion strength. Mesoscale analysis revealed that moist patches had greater cloudiness, updraft mass flux, and vertical velocity variance compared to dry patches. Additionally, mesoscale base-layer cloud fraction was highly and significantly correlated with cloudy updraft mass flux in both dry and moist environments. Results presented herein have implications for cumulus parameterization development along with climatological and model evaluation studies conducted at the ENA site.

cumulus clouds↗
NASA NTRS2009

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗
NASA NTRS1994

Relationship between ice water path and downward longwave radiation for clouds optically thin in the infrared: Observations and model calculations

A vertically pointing 3.2-cm radar is used to observe altostratus and cirrus clouds as they pass overhead. Radar reflectivities are used in combination with an empirical Z(sub i)-IWC (ice water content) relationship developed by Sassen (1987) to parameterize IWC, which is then integrated to obtain estimates of ice water path (IWP). The observed dataset is segregated into all-ice and mixed-phase periods using measurements of integrated liquid water paths (LWP) detected by a collocated, dual-channel microwave radiometer. The IWP values for the all ice periods are compared to measurements of infrared (IR) downward fluxes measured by a collocated narrowband (9.95-11.43 microns) IR radiometer, which results in scattergrams representing the observed dependence of IR fluxes on IWP. A two-stream model is used to calculate the infrared fluxes expected from ice clouds with boundary conditions specified by the actual clouds, and similar curves relating IWP and infrared fluxes are obtained. The model and observational results suggest that IWP is one of the primary controls on infrared thermal fluxes for ice clouds.

Uttal, Taneil↗
NASA NTRS1993

Heating, moisture, and water budgets of tropical and midlatitude squall lines - Comparisons and sensitivity to longwave radiation

A 2D time-dependent and nonhydrostatic numerical cloud model is presently used to estimate the heating, moisture, and water budgets in the convective and stratiform regions for both a tropical and a midlatitude squall line. The model encompasses a parameterized, three-class ice phase microphysical scheme and longwave radiative transfer process. It is noted that the convective region plays an important role in the generation of stratiform rainfall for both cases. While a midlevel minimum in the moisture profile for the tropical case is due to vertical eddy transport in the convective region, the contribution to the heating budget by the cloud-scale fluxes is minor; by contrast, the vertical eddy heat-flux is relatively important for the midlatitude case due to the stronger vertical velocities present in the convective cells.

Tao, W.-K.↗
DOE OSTI2018

The Roles of Convection Parameterization in the Formation of Double ITCZ Syndrome in the NCAR CESM: I. Atmospheric Processes

Abstract Several improvements are implemented in the Zhang‐McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST), and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long‐standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The contribution of black carbon to global ice nucleating particle concentrations relevant to mixed-phase clouds

Significance The Earth’s climate is affected by the radiative properties of clouds. In clouds containing both supercooled water droplets and ice particles (mixed-phase clouds), cloud lifetime and albedo are affected by the presence of ice nucleating particles (INP). After decades of research, the importance of black carbon (BC) as an INP remains unresolved. In this work, we determined the contribution of BC to INP concentrations ([INP]) from real-world wildfires and prescribed burns. We found that BC does not contribute significantly to [INP] in near-field biomass burning plumes. These results were applied as parameterizations to global climate model output. Combined with previous work on diesel-engine exhaust, we find that BC does not contribute significantly to global [INP] relevant to mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

The modification and application of Kuo's parameterization of cumulus convection in middle latitudes

An evaluation to reveal physical insight into the involved mechanisms through a combination of the large scale heat and moisture budgets and formulation of the latent heat released was performed. To improve upon the treatment of the interaction of deep convection with the environment, modifications consisting of considerations of the large scale moisture supply and of the vertical transport of moisture and of dry static energy inside the cloud are made. Also, a two layer cloud ensemble model is combined with the modified scheme. An examination of the modified scheme is performed by combining the large scale heat and moisture budgets and the modified formulation of the latent heat released. The modified parameterization procedures are compared with the original scheme, and the results of tests of both schemes are discussed. A variational optimization scheme is developed to analyze the wind field such that the integrated continuity equation and the global boundary condition are satisfied.

Liang, W. J.↗
DOE OSTI2018

Observational Relationship between Entrainment Rate and Environmental Relative Humidity and Implications for Convection Parameterization

Entrainment rate is a critical but highly uncertain quantity in convective parameterizations; especially, the effects of environmental relative humidity on entrainment rate are controversial, or even opposite, in different studies. Analysis of aircraft observations of cumuli from the RACORO and RICO field campaigns shows that entrainment rate is positively correlated with relative humidity. Physical analysis shows that higher relative humidity promotes entrainment by reducing buoyancy in the cloud cores and by weakening downdrafts near the cloud cores. The reduced buoyancy in the cloud cores and weakened downdrafts surrounding the cores further reduce updrafts in the cloud cores; the cloud cores with smaller updrafts are more significantly affected by their environment, resulting in larger entrainment rate. The relationship between entrainment rate and relative humidity is consistent with the buoyancy sorting concept widely used in convection parameterizations. The results provide reliable in situ observations to improve parameterizations of entrainment rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Coupling Warm Rain With an Eddy Diffusivity/Mass Flux Parameterization: 2. Sensitivities and Comparison to Observations

Abstract This is the second part of the description and validation of the coupling of a warm‐rain microphysics scheme to a stochastic multi‐plume eddy‐diffusivity/mass‐flux parameterization. Part 1 provides the model description and initial validation of the parameterization in a single column model (SCM) against large eddy simulations. This manuscript provides additional comparisons against satellite observations of 500 unique simulation cases, an analysis of model parameter‐based sensitivities in those 500 cases, and an evaluation of the idealized LES case study paradigm for parameterization development. The SCM is forced by a weather reanalysis in the subtropical northeast Pacific region characterized by the stratocumulus‐to‐cumulus cloud transition. 18 scalar outputs are examined to identify the sensitivities to 22 of the model's parameters. The model is highly sensitive to parameters that determine the behavior of convective plumes, which collectively lead to the most sensitivity in 13 of the 18 outputs. Only a few parameters contribute sensitivities that are not highly correlated with those of other parameters. While forcing the model with two canonical field campaign cases results in similar picture of which parameters lead to high sensitivity in model outputs, the sensitivity magnitudes can be overestimated compared to when the model is forced by weather reanalyzes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

The Open-Ocean Sensible Heat Flux and Its Significance for Arctic Boundary Layer Mixing During Early Fall

The increasing ice-free area during late summer has transformed the Arctic to a climate system with more dynamic boundary layer (BL) clouds and seasonal sea ice growth. The open-ocean sensible heat flux, a crucial mechanism of excessive ocean heat loss to the atmosphere during the fall freeze season, is speculated to play an important role in the recently observed cloud cover increase and BL instability. However, lack of observations and understanding of the resilience of the proposed mechanisms, especially in relation to meteorological and interannual variability, has left a poorly constrained BL parameterization scheme in Arctic climate models. In this study, we use multiyear Japanese cruise-ship observations from RV Mirai over the open Arctic Ocean to characterize the surface sensible heat flux (SSHF) during early fall and investigate its contribution to BL turbulence. It is found that mixing by SSHF is favored during episodes of high surface wind speed and is also influenced by the prevailing cloud regime. The deepest BLs and maximum ocean-atmosphere temperature difference are observed during cold air advection (associated with the stratocumulus regime), yet, contrary to previous speculation, the efficiency of sensible heat exchange is low. On the other hand, the SSHF contributes significantly to BL mixing during the uplift (low pressure) followed by the highly stable (stratus) regime. Overall, it can explain 10 of the open ocean BL height variability, whereas cloud-driven (moisture and radiative) mechanisms appear to be the other dominant source of convective turbulence. Nevertheless, there is strong interannual variability in the relationship between the SSHF and the BL height which can be intensified by the changing occurrence of Arctic climate patterns, such as positive surface wind speed anomalies and more frequent conditions of uplift. This study highlights the need for comprehensive BL observations like the RV Mirai for better understanding and predicting the dynamic nature of the Arctic climate.

boundary layer↗
NASA NTRSDate not supplied

Updated PSC Climatology Based on Caliop Measurements From 2006-2023

After more than three decades of research, the roles of polar stratospheric clouds (PSCs) in stratospheric ozone depletion are well established. Heterogeneous reactions on PSCs convert the stable chlorine reservoirs HCl and ClONO2 to chlorine radicals that destroy ozone catalytically. PSCs also prolong ozone depletion by delaying chlorine deactivation through the removal of gas-phase HNO3 and H2O by sedimentation of large nitric acid trihydrate (NAT) and ice particles. A substantial recovery of the ozone layer is expected by the middle of this century with reduced global production of ozone depleting substances in accordance with the Montreal Protocol and subsequent amendments. But as climate changes, leading to a colder and perhaps wetter stratosphere and upper troposphere, reliable model predictions of recovery of the Antarctic ozone hole and of potentially more severe ozone depletion in the Arctic are challenging. This is due both to a lack of detailed understanding of the underlying physics and the fact that many global models use simple parameterizations that do not accurately represent PSC processes. A more complete picture of PSC processes on vortex-wide scales has emerged from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instrument on the CALIPSO satellite that has been observing PSCs at latitudes up to 82 degrees in both hemispheres since June 2006. The CALIOP Version 2.0 (v2) PSC algorithm was recently developed to address known deficiencies in previous algorithms and includes additional refinements to increase the robustness of the inferred PSC composition. In this paper, we present an updated PSC reference data record and comprehensive climatology constructed by applying the v2 algorithm to the more than 17-year CALIOP spaceborne lidar dataset. In addition, we will examine the potential impact of aerosol and water vapor injections into the stratosphere from the January 2022 Hunga Tonga eruption on PSC occurrence in both the Arctic and Antarctic regions.

polar stratospheric clouds↗
NASA NTRS1978

Tropical sea surface temperature - An interactive one-dimensional atmosphere-ocean model

It is shown that the (cumulus) convective processes in the tropics may be described by a one-dimensional cloud model, while the near-surface ocean may similarly be described by a one-dimensional mixed-layer model. The coupling is achieved through a sea surface flux budget combined with the flux parameterizations implied by Monin-Obukhov similarity theory. The coupled one-dimensional atmosphere-ocean model is applied to the equilibrium situation in which all temperatures reach a steady state. For the ocean, the fluxes must vanish in equilibrium, but the atmosphere maintains a stable lapse rate by balancing cumulonimbus heating against net radiative cooling. All water precipitating from cumulonimbus clouds must have evaporated from the sea. It is shown that this equilibrium system is closed and determinable solely in terms of the solar constant.

Sarachik, E. S.↗
NASA NTRS1990

A unified view of convective transports by stratocumulus clouds, shallow cumulus clouds, and deep convection

A bulk planetary boundary layer (PBL) model was developed with a simple internal vertical structure and a simple second-order closure, designed for use as a PBL parameterization in a large-scale model. The model allows the mean fields to vary with height within the PBL, and so must address the vertical profiles of the turbulent fluxes, going beyond the usual mixed-layer assumption that the fluxes of conservative variables are linear with height. This is accomplished using the same convective mass flux approach that has also been used in cumulus parameterizations. The purpose is to show that such a mass flux model can include, in a single framework, the compensating subsidence concept, downgradient mixing, and well-mixed layers.

Randall, David A.↗
DOE OSTI2021

New insights into ice multiplication using remote-sensing observations of slightly supercooled mixed-phase clouds in the Arctic

Significance During secondary ice events, ice particle number concentrations in mixed-phase clouds can increase by orders of magnitude with profound implications for the cloud evolution. However, characterization of secondary ice events in the natural environment has been a challenge for the community for decades. We show the long-term frequency of secondary ice events in Arctic supercooled clouds for temperatures warmer than − 10 ○ C, made possible by applying a remote-sensing technique to 6 y of data. Secondary ice events are found to occur preferentially in the presence of drizzle droplets, compared with the better-known rime-splintering process, causing up to a 1,000-fold enhancement in ice number concentration. These results provide critical insights for model parameterizations and future laboratory experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

A double-moment multiple-phase four-class bulk ice scheme, Part 1: Description

A detailed ice-phase bulk microphysical scheme has been developed for simulating the hydrometeor distributions of convective and stratiform precipitation in different large-scale environmental conditions. The proposed scheme involves 90 distinct microphysical processes, which predict the mixing ratios and the number concentrations of small ice crystals, snow, graupel, and frozen drops/hail, as well as the mixing ratios of liquid water on wet precipitation ice (snow, graupel, frozen drops). The number of adjustable coefficients has been significantly reduced in comparison with other bulk schemes. Additional improvements have been made to the parameterization in the following areas: (1) representing small ice crystals with nonzero terminal fall velocities and dispersive size distributions, (2) accurate and computationally efficient calculations of precipitation collection processes, (3) reformulating the collection equation to prevent unrealistically large accretion rates, (4) more realistic conversion by riming between different classes of precipitation ice, (5) preventing unrealistically large rates of raindrop freezing and freezing of liquid water on ice, (6) detailed treatment of various rime-splintering ice multiplication mechanisms, (7) a simple representation of the Hobbs-Rangno ice enhancement process, (8) aggregation of small ice crystals and snow, and (9) allowing explicit competition between cloud water condensation and ice deposition rates rather than using saturation adjustment techniques. For the purposes of conserving the higher moments of the particle distributions, preserving the spectral widths (or slopes) of the particle spectra is shown to be more important than strict conservation of particle number concentration when parameterizing changes in ice-particle number concentrations due to melting, vapor transfer processes (sublimation of dry ice, evaporation from wet ice), and conversion between different hydrometeor species. The microphysical scheme is incorporated into a nonhydrostatic cloud model in Part 2 of this study. The model performed well in simulating the radar and microphysical structures of a midlatitude-continental squall lines and a tropical-maritime squall system with minimal tuning of the parameterization, even though the vertical profiles of radar reflectivity differed substantially between these storms.

Ferrier, Brad Shoenberg↗
DOE OSTI2022

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗