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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Parameterization of Features on Spherical Surfaces

NASA’s Planetary Systems Laboratory (PSL) at the Goddard Spaceflight Center in Greenbelt, Maryland is tasked with the study of solar system objects. This work is frequently based on analysis of imagery from visiting spacecraft, orbiting telescopes, and ground-based sensors. A consequence of this mission is the need to characterize features on the spherical surface of planets and moons, such characterization including the overall area of the feature, its center, its moments of inertia, its perimeter, its compactness, its major axis, its bounding box, its aspect ratio and its North-South orientation. Accurate assessment of these measures from a “flat” two-dimensional image is a challenge, since the scale of distance observed at the center of a spherical object distorts in any direction towards the horizon. PSL has developed a technique to guarantee accurate and automated measurement at any point on the visible surface, by overlaying an imaginary grid of equal-area cells onto the two-dimensional image of the sphere. The technique is named Grid-Oriented Normalization for Analysis of Spherical Areas (GONASA). This paper discusses the construction of the normalization grid and describes specific algorithms for feature parameterization. The algorithms are implemented in an accompanying Excel spreadsheet, both for clarity and ease of adoption, and to emphasize their aptness for automation. Finally, a concrete use case is offered where the GONASA grid and algorithms are used to characterize methane clouds on the Saturnian moon Titan.

Planetary science↗
NASA NTRS2016

WRF-Chem Simulations of Lightning-NOx Production and Transport in Oklahoma and Colorado Thunderstorms Observed During DC3

The focus of this analysis is on lightning-generated nitrogen oxides (LNOx) and their distribution for two thunderstorms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign in May-June 2012. The Weather Research and Forecasting Chemistry (WRF-Chem) model is used to perform cloud-resolved simulations for the May 29-30 Oklahoma severe convection, which contained one supercell, and the June 6-7 Colorado squall line. Aircraft and ground-based observations (e.g., trace gases, lightning and radar) collected during DC3 are used in comparisons against the model-simulated lightning flashes generated by the flash rate parameterization schemes (FRPSs) incorporated into the model, as well as the model-simulated LNOx predicted in the anvil outflow. Newly generated FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The results of these analyses will also be compared between storms to investigate which FRPSs were most appropriate for the two types of convection and to examine the variation in the LNOx production. The simulated LNOx results from WRF-Chem will also be compared against other previously studied mid-latitude thunderstorms.

Lightning↗
NASA NTRS1997

Representation of Clear and Cloudy Boundary Layers in Climate Models

The atmospheric general circulation models which are being used as components of climate models rely on their boundary layer parameterizations to produce realistic simulations of the surface turbulent fluxes of sensible heat. moisture. and momentum: of the boundary-layer depth over which these fluxes converge: of boundary layer cloudiness: and of the interactions of the boundary layer with the deep convective clouds that grow upwards from it. Two current atmospheric general circulation models are used as examples to show how these requirements are being addressed: these are version 3 of the Community Climate Model. which has been developed at the U.S. National Center for Atmospheric Research. and the Colorado State University atmospheric general circulation model. The formulations and results of both models are discussed. Finally, areas for future research are suggested.

Randall, D. A.↗
NASA NTRSDate not supplied

The Equilibrium Response of Climate and Composition to Lightning

Climate change can affect atmospheric composition through perturbation of natural processes, leading to complex feedbacks. The primary atmospheric oxidants OH and ozone are very sensitive to emissions of nitrogen oxides (NO x ) from lightning, and therefore so are the subsequent chemical perturbations to long-lived greenhouse gases (e.g., methane) and aerosol chemistry and physics. Meanwhile, cloud electrification responds to both meteorology and composition (aerosol particles). Key to understanding the ultimate impact of lightning on air quality and climate is the long-term methane feedback. Here, we present simulations from the GISS ModelE2.1 chemistry-climate model in which we isolate the response of Earth’s radiative budget and composition to lightning NO x in the present day and at the end of this century by allowing the model to re-equilibrate following removal of the source. Whereas lightning initially contributes to surface ozone enhancements, longer-term responses amplified by the methane lifetime feedback reduce surface ozone on multi-decadal time scales in the northern midlatitudes. Lightning consequently contributes a strong negative radiative effect in the present day (-0.5 W m -2 ), stronger than that estimated for the anthropogenic NOx source. In addition to influencing tropospheric composition, we find significant changes in stratospheric dynamics and composition. We test the sensitivity of our results to multiple parameterizations for global lightning activity.

Lightning↗
NASA NTRS1992

Automatic AVHRR image navigation software

This is the final report describing the work done on the project entitled Automatic AVHRR Image Navigation Software funded through NASA-Washington, award NAGW-3224, Account 153-7529. At the onset of this project, we had developed image navigation software capable of producing geo-registered images from AVHRR data. The registrations were highly accurate but required a priori knowledge of the spacecraft's axes alignment deviations, commonly known as attitude. The three angles needed to describe the attitude are called roll, pitch, and yaw, and are the components of the deviations in the along scan, along track and about center directions. The inclusion of the attitude corrections in the navigation software results in highly accurate georegistrations, however, the computation of the angles is very tedious and involves human interpretation for several steps. The technique also requires easily identifiable ground features which may not be available due to cloud cover or for ocean data. The current project was motivated by the need for a navigation system which was automatic and did not require human intervention or ground control points. The first step in creating such a system must be the ability to parameterize the spacecraft's attitude. The immediate goal of this project was to study the attitude fluctuations and determine if they displayed any systematic behavior which could be modeled or parameterized. We chose a period in 1991-1992 to study the attitude of the NOAA 11 spacecraft using data from the Tiros receiving station at the Colorado Center for Astrodynamic Research (CCAR) at the University of Colorado.

Baldwin, Dan↗
NASA NTRS2016

Understanding Cirrus Ice Crystal Number Variability for Different Heterogeneous Ice Nucleation Spectra

Along with minimizing parameter uncertainty, understanding the cause of temporal and spatial variability of the nucleated ice crystal number, Ni, is key to improving the representation of cirrus clouds in climate models. To this end, sensitivities of Ni to input variables like aerosol number and diameter provide valuable information about nucleation regime and efficiency for a given model formulation. Here we use the adjoint model of the adjoint of a cirrus formation parameterization (Barahona and Nenes, 2009b) to understand Ni variability for various ice-nucleating particle (INP) spectra. Inputs are generated with the Community Atmosphere Model version 5, and simulations are done with a theoretically derived spectrum, an empirical lab-based spectrum and two field-based empirical spectra that differ in the nucleation threshold for black carbon particles and in the active site density for dust. The magnitude and sign of Ni sensitivity to insoluble aerosol number can be directly linked to nucleation regime and efficiency of various INP. The lab-based spectrum calculates much higher INP efficiencies than field-based ones, which reveals a disparity in aerosol surface properties. Ni sensitivity to temperature tends to be low, due to the compensating effects of temperature on INP spectrum parameters; this low temperature sensitivity regime has been experimentally reported before but never deconstructed as done here.

Cirrus↗
NASA NTRSDate not supplied

Understanding Land-Atmosphere Interactions in Agricultural Areas through Improved Modeling and Monitoring of Irrigation

Irrigation increases soil moisture and evapotranspiration, often leading to cooler and more humid conditions over and downwind of irrigated areas. These changes can affect the evolution of the planetary boundary layer and ultimately influence the development of clouds and precipitation. It is for this reason that there has been a push to include irrigation processes in weather and climate models. This presentation will discuss recent efforts to model irrigation impacts in NASA’s land surface and coupled models, via both improved parameterizations and the incorporation of satellite data from platforms such as SMAP, MODIS, and ECOSTRESS. This work underscores the need to consider human water management impacts when analyzing or predicting components of the water and energy cycles, and the critical roles that NASA observations and models play in this assessment.

Patricia Lawston Parker↗
NASA NTRSDate not supplied

Assessing the Uncertainty Impact of CERES Fast Longwave and SHortwave Radiative Flux (FLASHFlux) Level 3 Product With and Without Terra Observations

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave And SHortwave radiative Flux (FLASHFlux) data product was developed to provide data for applied science research involving the renewable energy and agricultural sectors within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Monitoring and Assimilation Office (GMAO), and a surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations. 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) gridded data that combines NOAA-20 and Terra observations on a one-degree equal angle grid. FLASHFlux TISA data product interpolate on a diurnal model that assumes a satellite equilateral crossing time of 10:30 AM and 1:30 PM from Terra and Aqua, respectively. Aqua was replaced by NOAA-20 starting on September 2022. Terra is planned to be replace by the Satellite ClOud and Radiation Property retrieval System (SatCORPS) soon. We are currently using the Terra observations as it continues to drift. We assess the impact of FLASHFlux TISA data when Terra is removed. An uncertainty estimate of the Top-Of-Atmosphere (TOA) fluxes are given of FLASHFlux Version4A (before Terra drift) and Version4B (current), and Version4B (no Terra) in comparison to the CERES EBAF and SYN1deg. In addition, we compare FLASHFlux Version4B and Version4B (no Terra) surface radiative fluxes to ground base measurements to determine the impact of running without Terra data.

PC Sawaengphokhai↗
NASA NTRS2004

A Meteorological Model's Dependence on Radiation Update Frequency

Numerical weather models are used to simulate circulations in the atmosphere including clouds and precipitation by applying a set of mathematical equations over a three-dimensional grid. The grid is composed of discrete points at which the meteorological variables are defined. As computing power continues to rise these models are being used at finer grid spacing, but they must still cover a wide range of scales. Some of the physics that must be accounted for in the model cannot be explicitly resolved, and their effects, therefore, must be estimated or "parameterized". Some of these parameterizations are computationally expensive. To alleviate the problem, they are not always updated at the time resolution of the model with the assumption being that the impact will be small. In this study, a coupled land-atmosphere model is used to assess the impact of less frequent updates of the computationally expensive radiation physics for a case on June 6, 2002, that occurred during a field experiment over the central plains known as International H20 Project (IHOP). The model was tested using both the original conditions, which were dry, and with modified conditions wherein moisture was added to the lower part of the atmosphere to produce clouds and precipitation (i.e., a wet case). For each of the conditions (i.e., dry and wet), four set of experiments were conducted wherein the model was run for a period of 24 hours and the radiation fields (including both incoming solar and outgoing longwave) were updated every 1, 3, 10, and 100 time steps. Statistical tests indicated that average quantities of surface variables for both the dry and wet cases were the same for the various update frequencies. However, spatially the results could be quite different especially in the wet case after it began to rain. The near-surface wind field was found to be different most of the time even for the dry case. In the wet case, rain intensities and average vertical profiles of heating associated with cloudy areas were found to differ for the various radiation update frequencies. The latter implies that the mean state of the model could be different as a result of not updating the radiation fields every time step and has important implications for longer term climate studies

Eastman, Joseph L.↗
NASA NTRS1983

A nested-grid limited-area model for short term weather forecasting

The present investigation is concerned with a mesoscale atmospheric simulation system (MASS), incorporating the sigma-coordinate primitive equations. The present version of this model (MASS 3.0) has 14 vertical layers, with the upper boundary at 100 mb. There are 128 x 96 grid points in each layer. The earlier version of this model (MASS 2.0) has been described by Kaplan et al. (1982). The current investigation provides a summary of major revisions to that version and a description of the parameterization schemes which are presently included in the model. The planetary boundary layer (PBL) is considered, taking into account aspects of generalized similarity theory and free convection, the surface energy budget, the surface moisture budget, and prognostic equations for the depth h of the PBL. A cloud model is discussed, giving attention to stable precipitation, and cumulus convection.

Wong, V. C.↗
NASA NTRS1994

Flat spectrum T Tauri stars: The case for infall

We show that the mid- to far-infrared fluxes of 'flat spectrum' T Tauri stars can be explained by radiative equilibrium emission from infalling dusty envelopes. Infall eliminates the need for accretion disks with non-standard temperature distributions. The simplicity and power of this explanantion indicates that models employing 'active' disks, in which the temperature distribution is a parameterized power law, should be invoked with caution. Infall also naturally explains the scattered light nebulae detected around many flat spectrum sources. To match the observed spectra, material must fall onto a disk rather than the central star, as expected for collapse of a rotating molecular cloud. It may be necessary to invoke cavities in the envelopes to explain the strength of optical and near-infrared emission; these cavities could be produced by the powerful bipolar outflows commonly observed from young stars. If viewed along the cavity, a source may be lightly extincted at visual wavelengths, while still accreting substantial amounts of material from the envelope. Infall may also be needed to explain the infrared-bright companions of many optical T Tauri stars. This picture suggests that many of the flat spectrum sources are 'protostars'-young stellar objects surrounded by dust infalling envelopes of substantial mass.

Calvet, Nuria↗
NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗
NASA NTRS1984

Development and preliminary tests of a new long-wave radiation parameterization

An efficient broad band longwave radiation code for CO2 and H2O and for O3 was developed. There are two bands each in the CO2 and H2O absorption regions, one for the band center and one for the band wings. One band covers O3 absorption and the overlapping H2O continuum. Overlap is also considered in the CO2 region, and there is H2O continuum absorption where applicable. Clouds are considered nonreflecting in the longwave. Therefore partial cover or partial transmission can be allowed for, by considering a cloud fraction at each atmospheric level. A special subroutine was written to allow for maximum or random overlap of clouds that may be used in the future. All algorithms were written with vectorization in mind with identical operations made for all horizontal grid points in a latitude circle. Where possible, operations are carried out covering the vertical grid points as well, yielding long vectors for efficient computations.

HARSHVARDHAN↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRS2002

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗
NASA NTRS2001

Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds

Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.

Kawamoto, K.↗
NASA NTRS2024

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

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

General circulation models↗