SEARCH · Engineering Papers

Results for “cloud coverage”

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.

SourceResearch connectionFrom yearThrough year

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

At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Analyzing LF/VLF Lightning Waveforms to Estimate D-region Electron Density Profiles

Lightning waveforms in the low frequency (LF; 30-300 kHz) and the very low frequency (VLF; 3-30 kHz) bands can be exploited to produce data-driven ionospheric D-region electron density profile (EDP) estimates with significantly higher spatial and temporal coverage than previously available. The lightning waveforms used in this paper are signals detected in the LF/VLF of negative cloud-to-ground lightning by the Earth Networks Total Lightning Detection Network. Each waveform contains a ground wave and a time-delayed ionospheric reflection. The time delay between the ground wave and ionospheric reflection has previously been used to estimate a single specular reflection altitude, where LF/VLF emissions are reflected by the ionosphere. Here, we expand upon previous methods to include filtering and spectral analysis, and account for oblique propagation to produce higher-order estimates for reflection altitudes and corresponding electron densities. Once estimated, reflection altitudes and corresponding electron densities can be used to derive parameters β and h’, which define an EDP for the D-region. In this study, the lightning waveform (LW) analysis is demonstrated using a single representative 24-hour dataset over the Southeast United States, and then extended to a total of 10 separate datasets with varying locations and ionospheric conditions. The LW-derived D-region EDPs are in agreement with predictions made by the Faraday International Reference Ionosphere model, and the LW EDPs β and h’ values are consistent with previous LF/VLF-derived estimates.

D-region ionosphere↗

NASA NTRS1972

Infrared thermal mapping experiment - The Viking Mars Orbiter.

The Mars infrared thermal mapper (IRTM) will be carried on the scan platform of the orbiter of the Viking 1975 mission. The IRTM is a multichannel radiometer with several detectors in each of six spectral regions. The spectral channels are selected to be sensitive to surface emissivity variations and provide good temperature resolution over the entire range of Martian temperatures. These observations will allow determination of the surface kinetic temperature and thermal balance, and by coverage of the dark hemisphere, a search for regions with anomalous cooling can be made. Observations of ground frosts or clouds will help to determine their composition, and in the case of extensive H2O frosts, will allow the local water vapor pressure to be estimated.

Kieffer, H. H.↗

NASA NTRS1972

Evaluate the application of ERTS-A data for detecting and mapping snow cover

The author has identified the following significant results. Preliminary results of the analysis of a limited sample of ERTS-1 data from the western United States and the Arctic indicate that snow cover can be detected in the MSS-4 and MSS-5 bands by its high reflectance compared to that of the surrounding snow-free terrain. Snow can generally be distinguished from clouds because of well-defined boundaries as compared with the less distinct cloud edges, the lack of shadows characteristic of clouds, and pattern configurations that fit closely with higher elevations and terrain features. At higher latitudes where repetitive ERTS-1 coverage occurs snow can also be identified by the day-to-day continuity of the patterns. In the longer wavelengths, particularly the MSS-7 band, the contrast between snow and snow-free terrain is much lower, and, thus, snow is more difficult to detect. ERTS-1 data from the Canadian Arctic shows the seasonal increase in snow cover in several areas. In other ERTS-1 data, considerable detail is evident in glaciers located along the east and west coasts of Greenland.

Barnes, J. C.↗

NASA NTRS1972

An amplitude-steered, electronically despun antenna for the synchronous meteorological satellite.

Description of the design and performance of a dual-band electronically despun, high-gain, earth-coverage satellite antenna for use on the Synchronous Meteorological Satellite. The SMS satellite is designed to take high-resolution cloud cover pictures from synchronous altitude. Several unique design features are described, including a scheme for steering energy around the array in a continuous fashion to avoid 'phase jumps' caused by sudden energy switches.

Dietrich, F. J.↗

NASA NTRS1992

VIMS/Cassini mission at Titan: Scientific objectives and observational scenarios

The scientific objectives and observational scenarios of the Cassini/Visual Infrared Mapping Spectrometer (VIMS) Mission at Titan are addressed. The VIMS represents a powerful and effective means to both investigate, in four dimensions (latitude, longitude, altitude, and time), Titan's atmospheric structure and to map the near infrared spectral character of Titan's surface. Its broad spectral coverage from 0.35 to 5.1 micrometers together with its significant spectral resolution allows it to determine minor constituent distributions and cloud optical/microphysical properties from the surface to several hundred km. A promising means of obtaining high vertical resolution stratospheric profiles of hydrocarbons, oxides, and hazes via stellar occultation observations is discussed.

Baines, Kevin H.↗

NASA NTRSDate not supplied

Assessing the feasibility of a spaceborne 3D lightning observing concept

The distribution of electrical charge in thunderclouds results from thermodynamic, microphysical, and kinematic processes, which also modulate thunderstorm evolution. It is no surprise that the connection between lightning and these physical processes is so strong that the increase and vertical growth of lightning activity closely follows the vertical growth of the thundercloud, but unraveling these connections is not trivial and requires observations of the three-dimensional (3D) structure of electrical activity in a cloud. Ground-based 3D lightning mapping networks give excellent 3D flash-level detail but are limited to regional coverage. Satellite-based optical lightning mappers give excellent global coverage but are largely limited to 2D summaries of flash rate and radiant intensity, albeit new flash products and stereographic techniques are chipping away this limitation. New observing strategies are needed to expand and diversify the corpus of 3D lightning datasets and motivate studies that unravel connections lightning has with these key physical processes and the surrounding environment. This study examines the feasibility of using a distributed network of orbing satellites with VHF-based lightning detectors to obtain global maps of 3D lightning activity and assess efficacy of this approach for use in a new, small satellite mission concept called CubeSpark. CubeSpark combines new VHF and high-resolution, bispectral optical instruments on a constellation of low-Earth orbiting (LEO) satellites to globally map the 3D electrical structure of thunderstorms and study how it relates to thunderstorm evolution, extreme weather, nitrogen oxide production and distribution, upper atmospheric electrical phenomena, and how 3D flash observations can complement existing satellite-based lightning mappers and improve decision support tools. To locate lightning discharges, CubeSpark seeks to use the VHF time-of-arrival technique, similar to ground-based total lightning mapping networks. The vertical location accuracy of these satellite retrievals will be of poorer quality compared to a ground-based network, which has non-trivial implications for lightning flash reconstruction and lightning-based interpretations of deep convection. We adapt a Lightning Mapping Array (LMA) simulation framework to an orbiting network and use it to address feasibility of 3D lightning detection from space with particular attention to location accuracy of VHF detections of lightning in the vertical. These simulations inform a constellation design study that defines a realistic orbital configuration and depicts the global coverage for CubeSpark. Results indicate that a 3D location accuracy of <1-2 km for each dimension can be achieved across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high- latitudes.

Lightning↗

NASA NTRS2023

A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height

A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.

John E. Yorks↗

NASA NTRSDate not supplied

TPSAS-NF1676L-31966-DND

Solar eclipses provide the scientific community with a natural experiment of the processes within the Earth system. Through the rapid reduction and recovery of surface insolation, the short-term interrelationships between surface fluxes, clouds, temperature, and other meteorological components. Past observations of the eclipse-induced temperature perturbation show a wide range of values dependent on multiple factors. One of the primary factors is prevailing cloud cover, which is challenging to quantify. The large public interest in the 21 August 2017 eclipse provided an opportunity for a study of the eclipse using citizen science. Inspired by past citizen science efforts, the GLOBE Observer (GO) program organized a citizen science campaign for the 2017 eclipse. The large number of observers combined with their ability to travel to meteorologically important areas provided nearly unbroken coverage of the path of totality, and provides a useful complementary view of the eclipse with the automated networks. Primary questions: 1) What is the quantitative relationship between prevailing cloud cover and eclipse-induced temperature perturbation according to citizen scientist observations? 2) How well do the results from the citizen scientist observations compare with those from conventional ground observing stations?

J. Brant Dodson↗

NASA NTRS2022

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM1-MODIS_Edition2B)

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SHORTWAVE FLUX↗

DOE OSTI2023

Three-dimensional phenotyping of peach tree-crown architecture utilizing terrestrial laser scanning

Tree training systems for temperate fruit have been developed throughout history by pomologists to improve light interception, fruit yield, and fruit quality. These training systems direct crown and branch growth to specific configurations. Quantifying crown architecture could aid the selection of trees that require less pruning or that naturally excel in specific growing/training system conditions. Regarding peaches [Prunus persica (L.) Batsch], access tools such as branching indices have been developed to characterize tree-crown architecture. However, the required branching data (BD) to develop these indices are difficult to collect. Traditionally, BD have been collected manually, but this process is tedious, time-consuming, and prone to human error. These barriers can be circumnavigated by utilizing terrestrial laser scanning (TLS) to obtain a digital twin of the real tree. TLS generates three-dimensional (3D) point clouds of the tree crown, wherein every point contains 3D coordinates (x, y, z). To facilitate the use of these tools for peach, we selected 16 young peach trees scanned in 2021 and 2022. These 16 trees were then modeled and quantified using the open-source software TreeQSM. As a result, “in silico” branching and biometric data for the young peach trees were calculated to demonstrate the capabilities of TLS phenotyping of peach tree-crown architecture. The comparison and analysis of field measurements (in situ) and in silico BD, biometric data, and quantitative structural model branch uncertainty data were utilized to determine the reconstructive model’s reliability as a source substitute for field measurements. Mean average deviation when comparing young tree (YT) height was approx. 5.93%, with crown volume was approx. 13.26% across both 2021 and 2022. All point clouds of the YTs in 2022 showed residuals lower than 12 mm to cylinders fitted to all branches, and mean surface coverage greater than 40% for both the trunk and primary branching orders.

09 BIOMASS FUELS↗

NASA NTRS1994

Cloud properties inferred from 8-12 micron data

A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.

Strabala, Kathleen I.↗

NASA NTRS2008

High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.

Zhou, Daniel K.↗

NASA NTRS2019

The Distribution, Composition, and Particle Properties of Mars Mesospheric Aerosols: an Analysis of CRISM Visible/near-IR Limb Spectra with Context from Near-Coincident MCS and MARCI Observations

The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Reconnaissance Orbiter (MRO) obtains pole-to-pole observations (i.e., full MRO orbits) of vertical profiles for visible/near-IR spectra (λ=0.4–4.0 μm), which are ideally suited to identifying the composition and particle sizes of Mars ice and dust aerosols over 50–100 km altitudes in the Mars mesosphere. Within the coverage limitations of the CRISM limb data set, a distinct compositional dichotomy is found in Mars mesospheric ice aerosols. CO2 ice clouds appear during the aphelion period of Mars orbit (Solar Longitudes, Ls∼0–160°) at low latitudes (∼20S–10N) over specific longitude regions (Meridiani, Valles Marineris) and at typical altitudes of 55–75 km. Apart from faint water ice hazes below 55 km, mesospheric H2O ice clouds are primarily restricted to the perihelion orbital range (Ls∼160 – 350°) at northern and southern mid-to-low latitudes with less apparent longitudinal dependences. Mars mesospheric CO2 clouds are presented in CRISM spectra with a surprisingly large range of particle sizes (cross section weighted radii, Reff=0.3 to 2.2 μm). The smaller particle sizes (Reff ≤1 μm) appear concentrated near the spatial (latitude and altitude) boundaries of their global occurrences. CRISM spectra of mesospheric CO2 clouds also show evidence of iridescence, indicating very narrow particle size distributions (effective variance, Veff∼0.03) and so very abrupt CO2 cloud nucleation. Furthermore, these clouds are sometimes accompanied by altitude coincident peaks in 1.27 μm O2 dayglow, which indicates very dry, cold regions of formation. Mesospheric water ice clouds generally exhibit small particle sizes (Reff=0.1–0.3 μm), although larger particle sizes (Reff=0.4–0.7 μm) appear infrequently. On average, water ice cloud particle sizes decrease with altitude over 50–80 km in the perihelion mesosphere. Water ice mass appears similar in clouds over a large range of observed cloud particle sizes, with particle number densities increasing to ∼10 cm−3 for Reff=0.2 μm. Near coincident Mars Climate Sounder (MCS) temperature and aerosol profile measurements for a subset of CRISM mesospheric aerosol measurements indicate near saturation (H2O and CO2) conditions for ice clouds and distinct mesospheric temperature increases associated with mesospheric dust loading. Dayside (3 pm) mesospheric CO2 clouds with larger particle sizes (Reff ≥0.5 μm) scatter surface infrared emission in MCS limb infrared radiances, as well as solar irradiance in the MCS solar band channel. Scattering of surface infrared emission is most strikingly presented in nighttime (3 am) MCS observations at 55–60 km altitudes, indicating extensive mesospheric nighttime CO2 clouds with considerably larger particle sizes (Reff∼7 μm). Mesospheric CO2 ice clouds present cirrus-like waveforms over extensive latitude and longitude regions (10°×10°), as revealed in coincident Mars Color Imager (MARCI) nadir imaging. Solar tides, gravity waves, and the large orbital variation of the extended thermal structure of the Mars atmosphere influence all of these behaviors. Mesospheric dust aerosols appear infrequently over the non-global (planet encircling) dust storm era of the CRISM limb data set (2009–2016), and exhibit smaller particle sizes (Reff=0.2–0.7 μm) relative to dust in the lower atmosphere. One isolated case of an aphelion (Ls=96°) mesospheric dust layer with large dust particle sizes (Reff ∼2 μm) over Syria Planum may reflect high altitude, non-local transport of dust over elevated regions.

Clancy, Todd R.↗

NASA NTRS2019

The distribution, composition, and particle properties of Mars mesospheric aerosols: An analysis of CRISM visible/near-IR limb spectra with context from near-coincident MCS and MARCI observations

The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Reconnaissance Orbiter (MRO) obtains pole-to-pole observations (i.e., full MRO orbits) of vertical profiles for visible/near-IR spectra (λ= 0.4–4.0 μm), which are ideally suited to identifying the composition and particle sizes of Mars ice and dust aerosols over 50–100 km altitudes in the Mars mesosphere. Within the coverage limitations of the CRISM limb data set, a distinct compositional dichotomy is found in Mars mesospheric ice aerosols. CO2 ice clouds appear during the aphelion period of Mars orbit (Solar Longitudes, L(s )∼ 0–160°) at low latitudes (∼20S–10N) over specific longitude regions (Meridiani, Valles Marineris) and at typical altitudes of 55–75 km. Apart from faint water ice hazes below 55 km, mesospheric H2O ice clouds are primarily restricted to the perihelion orbital range (L(s)∼160 – 350°) at northern and southern mid-to-low latitudes with less apparent longitudinal dependences. Mars mesospheric CO2 clouds are presented in CRISM spectra with a surprisingly large range of particle sizes (cross section weighted radii, R(eff) = 0.3 to 2.2 μm). The smaller particle sizes (R(eff) ≤1 μm) appear concentrated near the spatial (latitude and altitude) boundaries of their global occurrences. CRISM spectra of mesospheric CO2 clouds also show evidence of iridescence, indicating very narrow particle size distributions (effective variance, V(eff) ∼ 0.03) and so very abrupt CO2 cloud nucleation. Furthermore, these clouds are sometimes accompanied by altitude coincident peaks in 1.27 μm O2 dayglow, which indicates very dry, cold regions of formation. Mesospheric water ice clouds generally exhibit small particle sizes (R(eff) = 0.1–0.3 μm), although larger particle sizes (R(eff) = 0.4–0.7 μm) appear infrequently. On average, water ice cloud particle sizes decrease with altitude over 50–80 km in the perihelion mesosphere. Water ice mass appears similar in clouds over a large range of observed cloud particle sizes, with particle number densities increasing to ∼10 per cu. cm for R(eff) = 0.2 μm. Near coincident Mars Climate Sounder (MCS) temperature and aerosol profile measurements for a subset of CRISM mesospheric aerosol measurements indicate near saturation (H2O and CO2) conditions for ice clouds and distinct mesospheric temperature increases associated with mesospheric dust loading. Dayside (3 pm) mesospheric CO2 clouds with larger particle sizes (R(eff) ≥0.5 μm) scatter surface infrared emission in MCS limb infrared radiances, as well as solar irradiance in the MCS solar band channel. Scattering of surface infrared emission is most strikingly presented in nighttime (3 am) MCS observations at 55–60 km altitudes, indicating extensive mesospheric nighttime CO2 clouds with considerably larger particle sizes (R(eff)∼7 μm). Mesospheric CO2 ice clouds present cirrus-like waveforms over extensive latitude and longitude regions (10°×10°), as revealed in coincident Mars Color Imager (MARCI) nadir imaging. Solar tides, gravity waves, and the large orbital variation of the extended thermal structure of the Mars atmosphere influence all of these behaviors. Mesospheric dust aerosols appear infrequently over the non-global (planet encircling) dust storm era of the CRISM limb data set (2009–2016), and exhibit smaller particle sizes (R(eff) = 0.2–0.7 μm) relative to dust in the lower atmosphere. One isolated case of an aphelion (L(s) = 96°) mesospheric dust layer with large dust particle sizes (R(eff) ∼2 μm) over Syria Planum may reflect high altitude, non-local transport of dust over elevated regions.

R. Todd Clancy↗

NASA NTRS2001

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar orbiting, sun-synchronous, platform at an altitude of 705 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

King, Michael D.↗

DOE OSTI2022

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

King, Michael D.↗