Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cloud parameterization”

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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign

Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the Southern Hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected on the ground and from a research aircraft during 7 weeks of the campaign. Large spatial and multiday variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single-particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol–cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the midlatitudes of South America and improve parameterized aerosol processes in local, regional, and global models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Initialization and assimilation of cloud and rainwater in a regional model

The initialization and assimilation of cloud and rainwater quantities in a mesoscale regional model was examined. Forecasts of explicit cloud and rainwater are made using conservation equations. The physical processes include condensation, evaporation, autoconversion, accretion, and the removal of rainwater by fallout. These physical processes, some of which are parameterized, represent source and sink in terms in the conservation equations. The question of how to initialize the explicit liquid water calculations in numerical models and how to retain information about precipitation processes during the 4-D assimilation cycle are important issues that are addressed.

Raymond, William H.↗
DOE OSTI2024

Linear Time-Invariant Models of a Large Cumulus Ensemble

Abstract Methods in system identification are used to obtain linear time-invariant state-space models that describe how horizontal averages of temperature and humidity of a large cumulus ensemble evolve with time under small forcing. The cumulus ensemble studied here is simulated with cloud-system-resolving models in radiative–convective equilibrium. The identified models extend steady-state linear response functions used in past studies and provide accurate descriptions of the transfer function, the noise model, and the behavior of cumulus convection when coupled with two-dimensional gravity waves. A novel procedure is developed to convert the state-space models into an interpretable form, which is used to elucidate and quantify memory in cumulus convection. The linear problem studied here serves as a useful reference point for more general efforts to obtain data-driven and interpretable parameterizations of cumulus convection.

Meteorology & Atmospheric Sciences↗
NASA NTRS1985

Sea breeze-induced mesoscale systems and severe weather

The relationship between thunderstorm activity during the summer months along coastal regions of the Atlantic and Gulf coasts and the dry sea breeze circulation was investigated. Satellite composites of thunderstorm activity for synoptically undisturbed conditions have been obtained for south Florida for a series of days in the summer of 1983. These data were catalogued into different low level synoptic flow regimes. Five synoptic flow regimes were found from the data. A three-dimensional mesoscale numerical model was used for each sysnoptic flow regime to quantitatively predict the location of enhanced thunderstorm activity. This model includes a parameterization of vegetation and soil moisture feedbacks as well as a sophisticated planetary boundary layer representation. Using the results of the satellite image composites, spatial and temporal characteristics of deep convective cloud patterns and their variation with synoptic flow are described. The results from the numerical model have provided explanations for the observed patterns.

Pielke, R. A.↗
NASA NTRS1984

Sensitivity of thermal inertia calculations to variations in environmental factors

The sensitivity of thermal inertia (TI) calculations to errors in the measurement or parameterization of a number of environmental factors is considered here. The factors include effects of radiative transfer in the atmosphere, surface albedo and emissivity, variations in surface turbulent heat flux density, cloud cover, vegetative cover, and topography. The error analysis is based upon data from the Heat Capacity Mapping Mission (HCMM) satellite for July 1978 at three separate test sites in the deserts of the western United States. Results show that typical errors in atmospheric radiative transfer, cloud cover, and vegetative cover can individually cause root-mean-square (RMS) errors of about 10 percent (with atmospheric effects sometimes as large as 30-40 percent) in HCMM-derived thermal inertia images of 20,000-200,000 pixels.

Kahle, A. B.↗
NASA NTRS1989

Mesoscale acid deposition modeling studies

The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts.

Kaplan, Michael L.↗
NASA NTRSDate not supplied

Enhancing Long-Term Trend Simulation of OH Through the Synergy of Model Simulations and Aura Ozone Monitoring Instrument (OMI) NO 2 and HCHO Retrievals

During the last few years, tremendous progress has been made to develop an efficient parameterization module using agile machine learning techniques. The aim of this module is to provide dynamic response of the tropospheric hydroxyl radical (OH) to its major drivers, including trace gases, aerosols, clouds, and meteorology. This module, named ECCOH (pronounced “echo”) and implemented in NASA’s GEOS-5 global model, offers an unrealized opportunity to unravel the convoluted response of OH to its underlying drivers while approaching the accuracy of full-chemistry without incurring excessive computational costs, making it suitable for climate models. However, the accurate representation of OH in ECCOH poses challenges due to the lack of representation of some of its critical inputs such as the abundance of NO 2 and HCHO concentrations. As such, we leverage the well-characterized satellite observations of NO2 and HCHO columns from Aura OMI to enhance their representation in ECCOH using an optimal interpolation method for the time period of 2005 - present. We show how the inclusion of OMI information can affect the spatiotemporal variability and long-term trends of OH, CO, and CH 4 across the globe. Additionally, we underscore the necessity of obtaining high-fidelity information regarding tropospheric ozone from the southern hemisphere from space, a region currently lacking full verification in models, posing a challenge to get a reasonable amount of chemical sink for CH 4 .

OH↗
NASA NTRS2019

Ongoing Breakthroughs in Convective Parameterization

While the increase of computer power mobilizes a part of the community towards models with explicit convection or based on machine learning, we review the part of the literature dedicated to convective parameterization development for large-scale forecast and climate models. Recent findings: Many developments are underway to overcome endemic limitations of traditional convective parameterizations, either in unified or multi-object frameworks: scale-aware and stochastic approaches, new prognostic equations or representations of new components such as cold pools. Understanding their impact on the emergent properties of a model remains challenging, due to subsequent tuning of parameters and the limited understanding given by traditional metrics. Summary: Further effort still needs to be dedicated to the representation of the life cycle of convective systems, in particular their mesoscale organization and associated cloud cover. The development of more process-oriented metrics based on new observations is also needed to help quantify model improvement and better understand the mechanisms of climate change.

parameterizations for large-scale models↗
DOE OSTI2025

Shoreline wave breaking strongly enhances the coastal sea spray aerosol population: Climate and air quality implications

Sea spray aerosol (SSA) emission is a major source of atmospheric aerosols, influencing global climate and coastal air quality. Much of our knowledge about SSA derives from coastal observations near shorelines, but whether and when these observations accurately represent open oceans remain unclear. Here, we show that strong nearshore SSA production during high-wave periods greatly enhances downwind cloud condensation nuclei (CCN) and aerosol mass concentrations. Strong shoreline wave breaking is widespread globally, and swell waves, which are decoupled from local winds, play a dominant role in many coastal regions. Therefore, extrapolating results based on coastal measurements to open oceans may significantly overestimate SSA concentration and its contribution to CCN and, by extension, the impact of SSA on clouds and climate. Additionally, the strong enhancement of coastal aerosol population by shoreline wave breaking and its environmental impact on coastal communities cannot be captured by current regional models, which do not parameterize nearshore SSA generation using wave energy or completely neglect it.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Antarctic Ultraviolet Radiation Climatology from Total Ozone Mapping Spectrometer Data

This project has successfully produced a climatology of local noon spectral surface irradiance covering the Antarctic continent and the Southern Ocean, the spectral interval 290-700 nm (UV-A, UV-B, and photosynthetically active radiation, PAR), and the entire sunlit part of the year for November 1979-December 1999. Total Ozone Mapping Spectrometer (TOMS) data were used to specify column ozone abundance and UV-A (360- or 380-nm) reflectivity, and passive microwave (MW) sea ice concentrations were used to specify the surface albedo over the Southern Ocean. For this latter task, sea ice concentration retrievals from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and its successor, the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I) were identified with ultraviolet/visible-wavelength albedos based on an empirical TOMS/MW parameterization developed for this purpose (Lubin and Morrow, 2001). The satellite retrievals of surface albedo and UV-A reflectivity were used in a delta-Eddington radiative transfer model to estimate cloud effective optical depth. These optical depth estimates were then used along with the total ozone and surface albedo to calculate the downwelling spectral UV and PAR irradiance at the surface. These spectral irradiance maps were produced for every usable day of TOMS data between 1979-1999 (every other day early in the TOMS program, daily later on).

Lubin, Dan↗
NASA NTRS2008

Cloud-System Resolving Models: Status and Prospects

Cloud-system resolving models (CRM), which are based on the nonhydrostatic equations of motion and typically have a grid-spacing of about a kilometer, originated as cloud-process models in the 1970s. This paper reviews the status and prospects of CRMs across a wide range of issues, such as microphysics and precipitation; interaction between clouds and radiation; and the effects of boundary-layer and surface-processes on cloud systems. Since CRMs resolve organized convection, tropical waves and the large-scale circulation, there is the prospect for several advances in both basic knowledge of scale-interaction requisite to parameterizing mesoscale processes in climate models. In superparameterization, CRMs represent convection, explicitly replacing many of the assumptions necessary in contemporary parameterization. Global CRMs have been run on an experimental basis, giving prospect to a new generation of climate weather prediction in a decade, and climate models due course. CRMs play a major role in the retrieval of surface-rain and latent heating from satellite measurements. Finally, enormous wide dynamic ranges of CRM simulations present new challenges for model validation against observations.

Tao, Wei-Kuo↗
NASA NTRS2010

Genesis of Pre-Hurricane Felix (2007): The Role of the Easterly Wave Critical Layer - Part 1

The formation of pre Hurricane Felix (2007) in a tropical easterly wave is examined in a two-part study using the Weather Research and Forecasting (WRF) model with a high-resolution nested grid configuration that permits the representation of cloud system processes. The simulation commences during the wave stage of the precursor African easterly-wave disturbance. Here the simulated and observed developments are compared, while in Part II of the study various large-scale analyses, physical parameterizations, and initialization times are explored to document model sensitivities. In this first part the authors focus on the wave/vortex morphology, its interaction with the adjacent intertropical convergence zone complex, and the vorticity balance in the neighborhood of the developing storm. Analysis of the model simulation points to a bottom-up development process within the wave critical layer and supports the three new hypotheses of tropical cyclone formation proposed recently by Dunkerton, Montgomery, and Wang. It is shown also that low-level convergence associated with the ITCZ helps to enhance the wave signal and extend the "wave pouch" from the jet level to the top of the atmospheric boundary layer. The region of a quasi-closed Lagrangian circulation within the wave pouch provides a focal point for diabatic merger of convective vortices and their vortical remnants. The wave pouch serves also to protect the moist air inside from dry air intrusion, providing a favorable environment for sustained deep convection. Consistent with the authors' earlier findings, the tropical storm forms near the center of the wave pouch via system-scale convergence in the lower troposphere and vorticity aggregation. Components of the vorticity balance are shown to be scale dependent, with the immediate effects of cloud processes confined more closely to the storm center than the overturning Eliassen circulation induced by diabatic heating, the influence of which extends to larger radii.

Wang, Zhuo↗
DOE OSTI2024

A coarse-grained model of clay colloidal aggregation and consolidation with explicit representation of the electrical double layer

The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Simulating Southern Ocean Aerosol and Ice Nucleating Particles in the Community Earth System Model Version 2

Southern Ocean (SO) low-level mixed phase clouds have been a long-standing challenge for Earth system models to accurately represent. While improvements to the Community Earth System Model version 2 (CESM2) resulted in increased supercooled liquid in SO clouds and improved model radiative biases, simulated SO clouds in CESM2 now contain too little ice. Previous observational studies have indicated that marine particles are major contributor to SO low-level cloud heterogeneous ice nucleation, a process that initiates a number of cloud processes that govern cloud radiative properties. In this study, we utilize detailed aerosol and ice nucleating particle (INP) measurements from two recent measurement campaigns to assess simulated aerosol abundance, number size distributions, and composition and INP parameterizations for use in CESM2. Our results indicate that CESM2 has a positive bias in simulated surface-level total aerosol surface area at latitudes north of 58°S. Measured INP populations were dominated by marine INPs and we present evidence of refractory INPs present over the SO assumed here to be mineral dust INPs. Results highlight a critical need to assess simulated mineral dust number and size distributions in CESM2 in order to adequately represent SO INP populations and their response to long-term changes in atmospheric transport patterns and land use change. Furthermore, we also discuss important cautions and limitations in applying a commonly used mineral dust INP parameterization to remote regions like the pristine SO.

58 GEOSCIENCES↗
NASA NTRS2007

Aerosol Source Plume Physical Characteristics from Space-based Multiangle Imaging

Models that assess aerosol effects on regional air quality and global climate parameterize aerosol sources in terms of amount, type, and injection height. The multiangle imaging spectroradiometer (MISR) aboard NASA's Terra satellite retrieves total column aerosol optical thickness (AOT), and aerosol type over cloud-free land and water. A stereo-matching algorithm automatically retrieves reflecting-layer altitude wherever clouds or aerosol plumes have discernable spatial contrast, with about 500-m accuracy, at 1.1-km horizontal resolution. Near-source biomass burning smoke, volcanic effluent, and desert dust plumes are observed routinely, providing information about aerosol amount, particle type, and injection height useful for modeling applications. Compared to background aerosols, the plumes sampled have higher AOT, contain particles having expected differences in Angstrom exponent, size, single-scattering albedo, and for volcanic plume and dust cloud cases, particle shape. As basic thermodynamics predicts, thin aerosol plumes lifted only by regional winds or less intense heat sources are confined to the boundary layer. However, when sources have sufficient buoyancy, the representative plumes studied tend to concentrate within discrete, high-elevation layers of local stability; the aerosol is not uniformly distributed up to a peak altitude, as is sometimes assumed in modeling. MISR-derived plume heights, along with meteorological profile data from other sources, make it possible to relate radiant energy flux observed by the moderate resolution imaging spectroradiometer (MODIS), also aboard the Terra spacecraft, to convective heat flux that plays a major role in buoyant plume dynamics. A MISR climatology of plume behavior based on these results is being developed.

aerosol plumes↗
DOE OSTI2022

Dependence of the Ratio of Total to Visible Mass on Observable Properties of Sloan Digital Sky Survey MaNGA Galaxies

Abstract Using spectroscopic observations from the Sloan Digital Sky Survey Mapping Nearby Galaxies at Apache Point Observatory Data Release 15, we study the relationships between the ratio of total to visible mass and various parameters characterizing the evolution and environment of the galaxies in this survey. Measuring the rotation curve with the relative velocities of the H α emission line across a galaxy’s surface, we estimate each galaxy’s total mass. We develop a statistical model to describe the observed distribution in the ratio of total to visible mass, from which we extract the most probable value of this mass ratio for a given sample of galaxies. We present the relationships between the ratio of total to visible mass and several characteristics describing galactic evolution, such as luminosity, gas-phase metallicity, distance to the nearest neighbor, and position on the color–magnitude diagram. We find that faint galaxies with low metallicities, typically in the blue cloud, have the highest ratios of total to visible mass. This mass ratio is significantly reduced when we include the H i mass in the total visible mass, implying that feedback mechanisms are not as strong in low-mass galaxies as previously thought. Those galaxies that exhibit the second-highest ratios of total to visible mass are the brightest with high metallicities, typically members of the red sequence or green valley. Active galactic nucleus activity is likely both the quenching mechanism and the feedback that drives the mass ratio higher in these massive galaxies. Finally, we introduce a parameterization that predicts a galaxy’s ratio of total to visible mass based only on its photometry and luminosity.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2019

Above-Cloud Aerosol Radiative Effects based on ORACLES 2016 and ORACLES 2017 Aircraft Experiments

Determining the direct aerosol radiative effect (DARE) of absorbing aerosols above clouds from satellite observations alone is a challenging task, in part because the radiative signal of the aerosol layer is not easily untangled from that of the clouds below. In this study, we use aircraft measurements from the NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) project in the southeastern Atlantic to derive it with as few assumptions as possible. This is accomplished by using spectral irradiance measurements (Solar Spectral Flux Radiometer, SSFR) and aerosol optical depth (AOD) retrievals (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research, 4STAR) during vertical profiles (spirals) that minimize the albedo variability of the underlying cloud field – thus isolating aerosol radiative effects from those of the cloud field below. For two representative cases, we retrieve spectral aerosol single scattering albedo (SSA) and the asymmetry parameter (g) from these profile measurements and calculate DARE given the albedo range measured by SSFR on horizontal legs above clouds. For mid-visible wavelengths, we find SSA values from 0.80 to 0.85 and a significant spectral dependence of g. As the cloud albedo increases, the aerosol increasingly warms the column. The transition from a cooling to a warming top-of-aerosol radiative effect occurs at an albedo value (critical albedo) just above 0.2 in the mid-visible wavelength range. In a companion paper, we use the techniques introduced here to generalize our findings to all 2016 and 2017 measurements and parameterize aerosol radiative effects.

Cloud aerosol↗
DOE OSTI2024

Causally‐Informed Deep Learning to Improve Climate Models and Projections

Abstract Climate models are essential to understand and project climate change, yet long‐standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid‐scale processes, particularly clouds and convection. Deep learning can learn these subgrid‐scale processes from computationally expensive storm‐resolving models while retaining many features at a fraction of computational cost. Yet, climate simulations with embedded neural network parameterizations are still challenging and highly depend on the deep learning solution. This is likely associated with spurious non‐physical correlations learned by the neural networks due to the complexity of the physical dynamical system. Here, we show that the combination of causality with deep learning helps removing spurious correlations and optimizing the neural network algorithm. To resolve this, we apply a causal discovery method to unveil causal drivers in the set of input predictors of atmospheric subgrid‐scale processes of a superparameterized climate model in which deep convection is explicitly resolved. The resulting causally‐informed neural networks are coupled to the climate model, hence, replacing the superparameterization and radiation scheme. We show that the climate simulations with causally‐informed neural network parameterizations retain many convection‐related properties and accurately generate the climate of the original high‐resolution climate model, while retaining similar generalization capabilities to unseen climates compared to the non‐causal approach. The combination of causal discovery and deep learning is a new and promising approach that leads to stable and more trustworthy climate simulations and paves the way toward more physically‐based causal deep learning approaches also in other scientific disciplines.

Meteorology & Atmospheric Sciences↗