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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fragmentation in Collisions of Snow with Graupel/Hail: New Formulation from Field Observations

Abstract Secondary ice production (SIP) has been attributed to the generation of most ice particles observed in precipitating clouds with cloud tops warmer than −36°C, from various aircraft- and ground-based field observations across the globe. One of the known SIP mechanisms is fragmentation during collisions among ice particles. It has been studied with our theoretical formulation, which has been applied in microphysical schemes of atmospheric models in a few studies. These have predicted an extensive impact on cloud glaciation and radiative properties. However, there has been a lack of experimental field studies, especially involving naturally falling snowflakes, to better understand this particular mechanism of SIP. This study reports the first field measurements with modern technology for fragmentation during collisions between naturally falling snowflakes and graupel/hail particles. This was observed with an innovatively designed portable chamber that was deployed outdoors in northern Sweden. Applying the observations from this field-based study, we optimized the existing formulation for predicting numbers of fragments from collisions of snow with graupel/hail. The observations show the average numbers of fragments per collision for dendritic (3–12 mm) and nondendritic (1–3 mm) snow were about 12 and 1, respectively. This represents a boost of predicted fragment numbers relative to our original formulation published in 2017. The updated formulation for breakup in ice–ice collisions can be implemented in the microphysical schemes of atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observations Pertaining to Precipitation within the Northeast Pacific Stratocumulus-to-Cumulus Transition

Three genuine stratocumulus-to-cumulus transitions sampled during the Cloud System Evolution over the Trades (CSET) campaign are documented. The focus is on Lagrangian evolution of in situ precipitation, thought to exceed radar/lidar retrieved values because of Mie scattering. Two of the three initial stratocumulus cases are pristine [cloud droplet number concentrations ($N_d$) of ~22 cm –3 ] but occupied boundary layers of different depths, while the third is polluted ($N_d$ ~ 225 cm –3 ). Hourly satellite-derived cloud fraction along Lagrangian trajectories indicate that more quickly deepening boundary layers tend to transition faster, into more intense but more occasional precipitation. These transitions begin either in the morning or late afternoon, suggesting that preceding night processes can precondition or delay the inevitable transition. The precipitation shifts toward larger drop sizes throughout the transition as the boundary layers deepen, with aerosol concentrations only diminishing in two of the three cases. Ultraclean ($N_d$ < 1 cm –3 ) cumulus clouds evolved from pristine stratocumulus cloud with unusually high precipitation rates occupying a shallow, well-mixed boundary layer. Results from a simple one-dimensional evaporation model and from radar/lidar retrievals suggest subcloud evaporation likely increases throughout the transition. This, coupled with larger drop sizes capable of lowering the latent cooling profile, facilitates the transition to more surface-driven convection. The coassociation between boundary layer depth and precipitation does not provide definitive conclusions on the isolated effect of precipitation on the pace of the transition. Differences between the initial conditions of the three examples provide opportunities for further modeling studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The NASA ACTIVATE Mission

The NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) conducted 162 joint flights with two aircraft over the northwest Atlantic to study aerosol–cloud interactions (ACIs), which represent the largest uncertainty in estimating total anthropogenic radiative forcing. The combination of a high-flying King Air and low-flying HU-25 Falcon, equipped with remote sensing and in situ instruments, characterized trace gases, aerosol particles, clouds, and meteorological variables with data collected nearly simultaneously below, within, and above marine boundary layer (MBL) clouds. Flights spanning warm and cold seasons across 3 years (2020–22) provided a broad range of conditions associated with aerosol particles, cloud properties (including particle size and phase), and meteorology, ideally suited for robust ACI calculations and assessing how well models simulate a wide range of MBL clouds from stratiform to cumulus. ACTIVATE data suggest that drivers of cloud droplet number concentration N d , including aerosol particles and MBL dynamics, vary between winter and summer months with a stronger potential to convert aerosol particles into cloud droplets in winter. Models of varying complexity not only highlight some skills in simulating winter and summer cloud types but also identify challenges that still need to be addressed such as treatment of turbulence, wet scavenging, and mesoscale organization. Remote sensing advances range from new retrieval methods for N d , cloud phase classification, vertically resolved aerosol and cloud condensation nuclei number concentration, and ocean surface wind speed. This work describes these scientific and technological advances along with efforts in outreach and open data science.

aerosol indirect effect↗
NASA NTRS2011

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Pinder, Robert W.↗
NASA NTRS2009

Spatio-Temporal Variability of Atmospheric CO2 as Observed from In-Situ Measurements over North America during NASA Field Campaigns (2004-2008)

Regional-scale measurements were made over the eastern United States (Intercontinental Chemical Transport Experiment - North America (INTEX-NA), summer 2004); Mexico (Megacity Initiative: Local and Global Research Observations (MILAGRO), March 2006); the eastern North Pacific and Alaska (INTEX-B May 2006); and the Canadian Arctic (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS), spring and summer 2008). For these field campaigns, instrumentation for the in situ measurement of CO2 was integrated on the NASA DC-8 research aircraft providing high-resolution (1 second) data traceable to the WMO CO2 mole fraction scale. These observations provide unique and definitive data sets via their intermediate-scale coverage and frequent vertical profiles (0.1 - 12 km) for examining the variability CO2 exhibits above the Earth s surface. A bottom-up anthropogenic CO2 emissions inventory (1deg 1deg) and processing methodology has also been developed for North America in support of these airborne science missions. In this presentation, the spatio-temporal distributions of CO2 and CO column values derived from the campaign measurements will be examined in conjunction with the emissions inventory and transport histories to aid in the interpretation of the CO2 observations.

Choi, Yonghoon↗
NASA NTRS1995

Response of the Tropical Boundary Layer to Weak Surface Forcing

During the Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA COARE), a series of airborne thermal infrared observations and in situ atmospheric measurements were made near the sea surface through heights exceeding 4 km. Air movements associated with the sea surface temperature and the marine atmospheric boundary layer were studied.

TOGA COARE sea surface temperature tropical weathe↗
NASA NTRS2017

The 2015-2016 El Nino and the Response of the Carbon Cycle: Findings from NASA's OCO-2 Mission

The El Nino Southern Oscillation (ENSO) is the most important mode of tropical climate variability on interannual to decadal time scales. Correlations between atmospheric CO2 growth rate and ENSO activity are relatively well known but the magnitude of this correlation, the contribution from tropical marine vs. terrestrial flux components, and the causal mechanisms, are poorly constrained in space and time. The launch of NASA's Orbiting Carbon Observatory-2 (OCO-2) mission in July 2014 was rather timely given the development of strong ENSO conditions over the tropical Pacific Ocean in 2015-2016. In this presentation, we will discuss how the high-density observations from OCO-2 provided us with a novel dataset to resolve the linkages between El Nino and atmospheric CO2. Along with information from in situ observations of ÎpCO2 from NOAA's Tropical Atmosphere Ocean (TAO) project and atmospheric CO2 from the Scripps CO2 Program, and other remote-sensing missions, we are able to piece together the time dependent response of atmospheric CO2 concentrations over the Tropics. Our findings confirm the hypothesis from studies following the 1997-1998 El Nino event that an early reduction in CO2 outgassing from the tropical Pacific Ocean is later reversed by enhanced net CO2 emissions from the terrestrial biosphere. This implies that a component of the interannual variability (IAV) in the growth rate of atmospheric CO2, which has typically been used to constrain the climate sensitivity of tropical land carbon fluxes, is strongly influenced and modified by ocean fluxes during the early phase of the ENSO event. Our analyses shed further light on the understanding of the marine vs. terrestrial partitioning of tropical carbon fluxes during El Nino events, their relative contributions to the global atmospheric CO2 growth rate, and provide clues about the sensitivity of the carbon cycle to climate forcing on interannual time scales.

CO2↗
NASA NTRS2018

The 2015-2016 El Nino and the Response of the Carbon Cycle: Findings from NASA's OCO-2 Mission

The El Nino Southern Oscillation (ENSO) is the most important mode of tropical climate variability on interannual to decadal time scales. Correlations between atmospheric CO2 growth rate and ENSO activity are relatively well known but the magnitude of this correlation, the contribution from tropical marine vs. terrestrial flux components, and the causal mechanisms, are poorly constrained in space and time. The launch of NASA's Orbiting Carbon Observatory-2 (OCO-2) mission in July 2014 was rather timely given the development of strong ENSO conditions over the tropical Pacific Ocean in 2015-2016. In this presentation, we will discuss how the high-density observations from OCO-2 provided us with a novel dataset to resolve the linkages between El Nino and atmospheric CO2. Along with information from in situ observations of CO2 from NOAA's Tropical Atmosphere Ocean (TAO) project and atmospheric CO2 from the Scripps CO2 Program, and other remote-sensing missions, we are able to piece together the time dependent response of atmospheric CO2 concentrations over the Tropics. Our findings confirm the hypothesis from studies following the 1997-1998 El Nino event that an early reduction in CO2 outgassing from the tropical Pacific Ocean is later reversed by enhanced net CO2 emissions from the terrestrial biosphere. This implies that a component of the interannual variability (IAV) in the growth rate of atmospheric CO2, which has typically been used to constrain the climate sensitivity of tropical land carbon fluxes, is strongly influenced and modified by ocean fluxes during the early phase of the ENSO event. Our analyses shed further light on the understanding of the marine vs. terrestrial partitioning of tropical carbon fluxes during El Nino events, their relative contributions to the global atmospheric CO2 growth rate, and provide clues about the sensitivity of the carbon cycle to climate forcing on interannual time scales.

OCO-2↗
NASA NTRS2014

Science Enhancements by the MAVEN Participating Scientists

NASA implemented a Participating Scientist Program and released a solicitation for the Mars Atmosphere and Volatile EvolutioN mission (MAVEN) proposals on February 14, 2013. After a NASA peer review panel evaluated the proposals, NASA Headquarters selected nine on June 12, 2013. The program's intent is to enhance the science return from the mission by including new investigations that broaden and/or complement the baseline investigations, while still addressing key science goals. The selections cover a broad range of science investigations. Included are: a patching of a 3D exosphere model to an improved global ionosphere-thermosphere model to study the generation of the exosphere and calculate the escape rates; the addition of a focused study of upper atmosphere variability and waves; improvement of a multi-fluid magnetohydrodynamic model that will be adjusted according to MAVEN observations to enhance the understanding of the solar-wind plasma interaction; a global study of the state of the ionosphere; folding MAVEN measurements into the Mars International Reference Ionosphere under development; quantification of atmospheric loss by pick-up using ion cyclotron wave observations; the reconciliation of remote and in situ observations of the upper atmosphere; the application of precise orbit determination of the spacecraft to measure upper atmospheric density and in conjunction with other Mars missions improve the static gravity field model of Mars; and an integrated ion/neutral study of ionospheric flows and resultant heavy ion escape. Descriptions of each of these investigations are given showing how each adds to and fits seamlessly into MAVEN mission science design.

Thermosphere↗
NASA NTRS2014

Science Enhancements by the MAVEN Participating Scientists

NASA implemented a Participating Scientist Program and released a solicitation for the Mars Atmosphere and Volatile EvolutioN mission (MAVEN) proposals on February 14, 2013. After a NASA peer review panel evaluated the proposals, NASA Headquarters selected nine on June 12, 2013. The program’s intent is to enhance the science return from the mission by including new investigations that broaden and/or complement the base-line investigations, while still addressing key science goals. The selections cover a broad range of science investigations. Included are: a patching of a 3D exosphere model to an improved global ionosphere-thermosphere model to study the generation of the exosphere and calculate the escape rates; the addition of a focused study of upper atmosphere variability and waves; improvement of a multi-fluid magnetohydrodynamic model that will be adjusted according to MAVEN observations to enhance the understanding of the solar-wind plasma interaction; a global study of the state of the ionosphere; folding MAVEN measurements into the Mars International Reference Ionosphere under development; quantification of atmospheric loss by pick-up using ion cyclotron wave observations; the reconciliation of remote and in situ observations of the upper atmosphere; the application of precise orbit determination of the spacecraft to measure upper atmospheric density and in conjunction with other Mars missions improve the static gravity field model of Mars; and an integrated ion/neutral study of ionospheric flows and resultant heavy ion escape. Descriptions of each of these investigations are given showing how each adds to and fits seamlessly into MAVEN mission science design.

Mars↗
NASA NTRS1990

Deep atmospheric probe missions to Uranus and Neptune

The impressive results of the Voyager 2 flybys of Uranus (January 1986) and Neptune (August 1989) revealed many surprises and produced a new set of scientific questions regarding the formation and evolution of the planets, their atmospheres, the rings that surround them, and their satellite systems. A new set of intensive exploration missions to these outer planets is currently being examined by NASA and the scientific community. These missions, like Galileo to Jupiter and Cassini to Saturn, are to provide longer-term high-resolution orbital observations together with in situ atmospheric measurements. This paper will examine the feasibility of using deep atmospheric probes in connection with orbital missions to Uranus and Neptune to obtain the desired scientific measurements down to atmospheric pressure levels of at least 200 bars. The key design parameters of the atmospheric mission and system are defined, examined in some detail, and feasible options are suggested for further study.

Swenson, Byron L.↗
NASA NTRS2017

The Role of DYNAMO in Situ Observations in Improving NASA Ceres-like Daily Surface and Atmospheric Radiative Flux Estimates

The daily surface and atmospheric radiative fluxes from NASA Clouds and the Earths RadiantEnergy System (CERES) Synoptic 1 degree (SYN1deg) Ed3A are among the most widely used data to studycloud-radiative feedback. The CERES SYN1deg data are based on Fu-Liou radiative transfer computations thatuse specific humidity (Q) and air temperature (T) from NASA Global Modeling and Assimilation Office (GMAO)reanalyses as inputs and are therefore subject to the quality of those fields. This study uses in situ Q and Tobservations collected during the Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign toaugment the input stream used in the NASA GMAO reanalysis and assess the impact on the CERES dailysurface and atmospheric longwave estimates. The results show that the assimilation of DYNAMOobservations considerably improves the vertical profiles of analyzed Q and T over and near DYNAMO stationsby moistening and warming the lower troposphere and upper troposphere and drying and cooling themid-upper troposphere. As a result of these changes in Q and T, the computed CERES daily surface downwardlongwave flux increases by about 5 W m(exp -2), due mainly to the warming and moistening in the lowertroposphere; the computed daily top-of-atmosphere (TOA) outgoing longwave radiation increases by2-3 W m(exp -2) during dry periods only. Correspondingly, the estimated local atmospheric longwave radiativecooling enhances by about 5 W m(exp -2) (7-8 W m(exp -2)) during wet (dry) periods. These changes reduce the bias inthe CERES SYN1deg-like daily longwave estimates at both the TOA and surface and represent animprovement over the DYNAMO region.

DYNAMO↗
DOE OSTI2025

Long-Range Transport of Biomass Burning Aerosols from Southern Africa: A Case Study Using Layered Atlantic Smoke Interactions with Clouds Observations

A case study of an incoming biomass burning aerosol plume at Ascension Island is analyzed for the peak of the 2017 fire season using satellites, reanalysis and in situ observations. Measurements from the Atmospheric Radiation Measurement Mobile Facility 1 reveal an abrupt change from relatively clean conditions (~70 parts per billion by volume of carbon monoxide) to a more polluted state (~150 parts per billion by volume of carbon monoxide). Corresponding changes in aerosol size reveal a broadening of size distributions toward larger optical diameters, consistent with the arrival of aged aerosols. Within a 24 h period, black carbon fraction increases ~500% from ~300 ng m e to ~1500 ng m 3 , while light absorption coefficients increase ~300%. Long-range transport of these aerosols is primarily confined between 2 and 5 km above sea level along the northwesterly trade winds. Our results show that the primary driver of increases in aerosol loading over Ascension Island is an intensification of the St. Helena high-pressure system (anticyclone) that leads to a weakening of trade winds and increases westward transport on its northern flank. A better understanding of the complex interactions between air quality, meteorology and long-range aerosol transport is important for future modeling studies focused on aerosol–cloud–radiation interactions over the open ocean and reducing its associated uncertainties.

aerosol size distribution↗
NASA NTRS1982

Fabry-Perot interferometer measurements of thermospheric neutral wind gradients and reversals at Arecibo

Direct measurements of the meridional neutral winds in the thermosphere made with the Fabry-Perot interferometer at the Arecibo Observatory show the postmidnight meridional wind reversal that was inferred from previous incoherent scatter radar ion-drift data and airglow intensity maps and observed in-situ with the Atmosphere Explorer-E satellite. Data for three nights between October 29 and December 9, 1981, are presented. For this period, the meridional wind is observed to be northward after sunset and to turn south before midnight; the velocities often exceed 100 m/sec. After midnight, its direction is seen to reverse to northward for one to two hours. The reversal after midnight is recurrent and propagates from the equator, as predicted on the basis of previous meridional airglow intensity measurements.

Friedman, J. F.↗
NASA NTRS1980

Coordinated study of equatorial scintillation and in situ and radar observations of nighttime F region irregularities

A coordinated set of Atmospheric Explorer E (AE-E) satellite in situ, VHF radar backscatter, and scintillation measurements performed during 1977 over a common ionospheric volume is used to study the relationship between the plasma depletions or bubbles, the extended 3-m irregularity structures known as plumes, and bursts of scintillation activity or patches in the nighttime equatorial F region. The implications of the observed spatial structures and the level of ambient concentration on the generation of 3-m irregularities and scintillation modeling are discussed.

Basu, S.↗
NASA NTRS2024

Maximizing the Volume of Collocated Data from Two Coordinated Suborbital Platforms

Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na ) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.

Atmosphere↗