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At least 667 records · Page 37

Large, solid particles in the clouds of Venus - Do they exist?

The evidence for solid mode 3 particles in the clouds of Venus is reexamined. The sampling characteristics of the cloud particle size spectrometer (LCPS) are reviewed, and reasons are pointed out for believing that relatively small differences in interpreting the measurements of this instrument could produce systematic errors. It is shown that all of the Pioneer Venus and Venera measurements can be understood if it is assumed that the large particles observed by the LCPS form the tail of the mode 2, H2SO4 size distribution.

Toon, O. B.↗

Infrared studies of the Herbig-Haro object 1-2 region

Far-infrared (50-100 micrometers) photometric mapping and near-infrared spectroscopic mapping of the Herbig-Haro 1-2 region are presented. Both lobes of the double-lobed far-infrared source in this region are found to be nearly coincident with recently discovered radio continuum sources. The dust temperature structure around each peak is not spherically symmetric, suggesting either that the far-infrared sources are centrally heated or that the dust column density is highly nonspherically symmetric. The results are consistent with a picture in which each far-infrared lobe contains a highly obscured young star surrounded by a highly nonspherically symmetric dust cloud. A complementary study by Strom et al. (1985) is pointed out.

Harvey, P. M.↗

The X-ray morphology of the Vela X region

Further analysis of Einstein Observatory images of the Vela pulsar has revealed additional detail in the X-ray emission of the central region of the Vela supernova remnant. Components previously reported from the Einstein data are: (1) filaments within the approximately 5-degree remnant; (2) a reasonably strong (approximately 1.7 ct/sec) point-like source coincident with the pulsar; and (3) a cloud of diffuse emission about the pulsar position. Image processing of IPC data has now revealed a region of lower surface brightness emission extending as far as about 1 degree, primarily to the south of the pulsar and in the direction of the radio emission maximum known as Vela X.

Harnden, F. R., Jr.↗

Chemistry of the Antarctic stratosphere

Interferometric measurements of HCl, ClNO3, HNO3, NO2, and NO obtained over the Antarctic in 1986 are used to model the chemistry of the atmosphere in the region of the Ozone Hole. The low abundance noted in stratospheric HCl is attributed to incorporation of HCl in polar stratospheric clouds and subsequent reaction of HCl with ClNO3. The results point to a net loss of HNO3 from the stratosphere and to the suppression of the abundance of odd nitrogen at high altitudes in the vortex. O3 loss is suggested to be due to the catalytic influence of halogen radicals.

Mcelroy, Michael B.↗

Satellite retrievals of marine stratiform cloud systems

The initial validation of a satellite-based cloud retrieval scheme of the spatial-coherence type that is being used to create a marine stratiform cloudiness (MSC) climatology is discussed. Initial results are presented which describe correlations between MSC properties and SST, which could be useful for providing guidelines for assessing potential climate feedbacks regarding these cloud types. The correlation of triangle-technique- and spatial-coherence-method-derived fractional cloud covers together with the regression line for all data points is shown.

Molnar, Gyula I.↗

The Extragalactic X-ray Background in the 0.2 - 2 keV Range

We made the first measurement of the extragalactic 0.7 keV background. We detected the X-ray shadow of a neutral gas cloud in the Magellanic Bridge. We further constrained the point-like source contribution based on the mean spectrum of detected sources and on our early autocorrelation function analysis of the background. We find that our measurement extragalactic background intensity is significantly greater than the total point-like source contribution expected if sources are responsible for all the observed background intensity in the 1-2 keV range. For a further confirmation of the theoretical prediction of the hot intergalactic medium, we have conducted a pilot project to search for enhanced X-ray-emitting features near rich clusters of galaxies. We have reported the discovery of an elongated complex of extended X-ray-emitting objects in and around the galaxy cluster A2125, based on an archival deep ROSAT/PSPC observation. Using multicolor optical imaging of galaxies in the field, we find that this complex represents a hierarchical superstructure spanning approx. 11 Mpc at the redshift approx. 0.247. The multiple peak X-ray morphology and large blue galaxy fraction of A2125 indicate that the cluster is undergoing a coalescence of subunits. The superstructure contains two additional clusters, projected at distances of only 3 and 4.3 Mpc from A2125. The most interesting feature is, however, the low-surface-brightness X-ray emission from a moderate galaxy concentration away from individual clusters. The emission likely arises in a hot (approx. 10(exp 7) K) intergalactic medium, as predicted in N-body/hydro simulations of structure formation. These results demonstrate the potential of X-ray observations as a powerful tool to study the large-scale structure of the universe.

Wang, Q. Daniel↗

Reply to "Comment on the Paper ''On the Determination of Electron Polytrope Indices Within Coronal Mass Ejections in the Solar Wind'"'

We strongly disagree with the essence of the Osherovich (hereafter Osherovich) comment on one of our papers. The following paragraphs provide the basis of our disagreement and elaborate on why we believe that none of the concluding statements in his Comment are true. Our most important point is that one can apply the model developed by Osherovich and colleagues to real data obtained at a single point in space to determine the polytropic index within magnetic clouds if and only if the highly idealized assumptions of that model conform to physical reality. There is good reason to believe that those assumptions do not provide an accurate physical description of real magnetic clouds in the spherically expanding solar wind.

Gosling, J. T.↗

Observations of O VI Emission from the Diffuse Interstellar Medium

We report the first Far Ultraviolet Spectroscopic Explorer (FUSE) measurements of diffuse O(VI) (lambda lambda 1032,1038) emission from the general diffuse interstellar medium outside of supernova remnants or superbubbles. We observed a 30 arcsec x 30 arcsec region of the sky centered at l = 315.0 deg and b = -41.3 deg. From the observed intensities (2930 +/- 290 (random) +/- 410 (systematic) and 1790 +/- 260 (random) +/- 250 (systematic) photons/sq cm/s/sr in the 1032 and 1038 angstrom emission lines, respectively), derived equations, and assumptions about the source location, we calculate the intrinsic intensity, electron density, thermal pressure, and emitting depth. The intensities are too large for the emission to originate solely in the Local Bubble. Thus, we conclude that the Galactic thick disk and lower halo also contribute. High velocity clouds are ruled out because there are none near the pointing direction. The calculated emitting depth is small, indicating that the O(VI)-bearing gas fills a small volume. The observations can also be used to estimate the cooling rate of the hot interstellar medium and constrain models. The data also yield the first intensity measurement of the C(II) 3s 2S(1/2) to 2p 2P(3/2) emission line at 1037 angstrom and place upper limits on the intensities of ultraviolet line emission from C(I), C(III), Si(II), S(III), S(IV), S(VI), and Fe(III).

Shelton, R. L.↗

A Lightning Channel Retrieval Algorithm for the North Alabama Lightning Mapping Array (LMA)

A new multi-station VHF time-of-arrival (TOA) antenna network is, at the time of this writing, coming on-line in Northern Alabama. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The network will support on-going ground validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. It will also provide for many interesting and detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and will offer many interesting comparisons with other meteorological/geophysical wets associated with lightning and thunderstorms. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. In this study, a new revised channel mapping retrieval algorithm is introduced. The algorithm is an extension of earlier work provided in Koshak and Solakiewicz (1996) in the analysis of the NASA Kennedy Space Center (KSC) Lightning Detection and Ranging (LDAR) system. As in the 1996 study, direct algebraic solutions are obtained by inverting a simple linear system of equations, thereby making computer searches through a multi-dimensional parameter domain of a Chi-Squared function unnecessary. However, the new algorithm is developed completely in spherical Earth-centered coordinates (longitude, latitude, altitude), rather than in the (x, y, z) cartesian coordinates employed in the 1996 study. Hence, no mathematical transformations from (x, y, z) into spherical coordinates are required (such transformations involve more numerical error propagation, more computer program coding, and slightly more CPU computing time). The new algorithm also has a more realistic definition of source altitude that accounts for Earth oblateness (this can become important for sources that are hundreds of kilometers away from the network). In addition, the new algorithm is being applied to analyze computer simulated LMA datasets in order to obtain detailed location/time retrieval error maps for sources in and around the LMA network. These maps will provide a more comprehensive analysis of retrieval errors for LMA than the 1996 study did of LDAR retrieval errors. Finally, we note that the new algorithm can be applied to LDAR, and essentially any other multi-station TWA network that depends on direct line-of-site antenna excitation.

Koshak, William↗

Use of the X-Band Radar to Support the Detection of In-Flight Icing Hazards by the NASA Icing Remote Sensing System

The Alliance Icing Research Study-II (AIRS-II) field program was conducted near Montreal, Canada during the winter of 2003. The NASA Icing Remote Detection System (NIRSS) was deployed to detect in-flight icing hazards and consisted of a vertically pointing multichannel radiometer, a ceilometer and an x-band cloud radar. The radiometer was used to derive atmospheric temperature soundings and integrated liquid water, while the ceilometer and radar were used only to define cloud boundaries. The purpose of this study is to show that the radar reflectivity profiles from AIRS-II case studies could be used to provide a qualitative icing hazard.

Serke, David J.↗

Chemical Evolution of Presolar Organics in Astromaterials

Sub-micron, hollow organic globules reported from several carbonaceous chondrites, interplanetary dust particles, and comet Wild-2 samples returned by NASA?s Stardust mission are enriched in N-15/N-14 and D/H compared with terrestrial materials and the parent materials [1-4]. These anomalies are ascribed to the preservation of presolar cold molecular cloud material from where H, C, and N isotopic constraints point to chemical fractionation near 10 K [5]. An origin well beyond the planet forming region and their survival in meteorites suggests submicrometer organic globules were once prevalent throughout the solar nebula. The survival of the membrane structures indicates primitive meteorites and cometary dust particles would have delivered these organic precursors to the early Earth as well as other planets and satellites. The physical, chemical, and isotopic properties of the organic globules varies to its meteorite types and its lithologies. For example, organic globules in the Tagish Lake meteorite are always embedded in fined grained (poorly crystallized) saponite, and hardly encapsulated in coarse grained serpentine, even though saponite and serpentine are both main components of phyllosilicate matrix of the Tagish Lake meteorite. The organic globules are commonly observed in the carbonate-poor lithology but not in the carbonate-rich one. In Tagish Lake, isolated single globules are common, but in the Bells (CM2) meteorite, globules are mostly aggregated. We will review the evolutions of the organic globules from its birth to alteration in the parent bodies in terms of its own physical and chemical properties as well as its associated minerals.

Nakamura-Messenger, K.↗

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 μm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

cirrus correction↗

Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2

Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical sensors but very few studies have carried out quantitative intercomparison of state-of-the-art methods in this domain. This paper summarizes results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted within the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). CEOS is the forum for space agency coordination and cooperation on Earth observations, with activities organized under working groups. CMIX, as one such activity, is an international collaborative effort aimed at intercomparing cloud detection algorithms for moderate-spatial resolution (10–30 m) spaceborne optical sensors. The focus of CMIX is on open and free imagery acquired by the Landsat 8 (NASA/USGS) and Sentinel-2 (ESA) missions. Ten algorithms developed by nine teams from fourteen different organizations representing universities, research centers and industry, as well as space agencies (CNES, ESA, DLR, and NASA), are evaluated within the CMIX. Those algorithms vary in their approach and concepts utilized which were based on various spectral properties, spatial and temporal features, as well as machine learning methods. Algorithm outputs are evaluated against existing reference cloud mask datasets. Those datasets vary in sampling methods, geographical distribution, sample unit (points, polygons, full image labels), and generation approaches (experts, machine learning, sky images). Overall, the performance of algorithms varied depending on the reference dataset, which can be attributed to differences in how the reference datasets were produced. The algorithms were in good agreement for thick cloud detection, which were opaque and had lower uncertainties in their identification, in contrast to thin/semi-transparent clouds detection. Not only did CMIX allow identification of strengths and weaknesses of existing algorithms and potential areas of improvements, but also the problems associated with the existing reference datasets. The paper concludes with recommendations on generating new reference datasets, metrics, and an analysis framework to be further exploited and additional input datasets to be considered by future CMIX activities.

Sergii Skakun↗

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Coastal California's Fog as a Unique Habitable Niche: Design for Autonomous Sampling and Preliminary Aerobiological Characterization

Just as on the land or in the ocean, atmospheric regions may be more or less hospitable to life. The aerobiosphere, or collection of living things in Earth's atmosphere, is poorly understood due to the small number and ad hoc nature of samples studied. However, we know viable airborne microbes play important roles, such as providing cloud condensation nuclei. Knowing the distribution of such microorganisms and how their activity can alter water, carbon, and other geochemical cycles is key to developing criteria for planetary habitability, particularly for potential habitats with wet atmospheres but little stable surface water. Coastal California has regular, dense fog known to play a major transport role in the local ecosystem. In addition to the significant local (1 km) geographical variation in typical fog, previous studies have found that changes in height above surface of as little as a few meters can yield significant differences in typical concentrations, populations and residence times. No single current sampling platform (ground-based impactors, towers, balloons, aircraft) is capable of accessing all of these regions of interest.A novel passive fog and cloud water sampler, consisting of a lightweight passive impactor suspended from autonomous aerial vehicles (UAVs), is being developed to allow 4D point sampling within a single fog bank, allowing closer study of small-scale (100 m) system dynamics. Fog and cloud droplet water samples from low-altitude aircraft flights in nearby coastal waters were collected and assayed to estimate the required sample volumes, flight times, and sensitivity thresholds of the system under design.125 cloud water samples were collected from 16 flights of the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) instrumented Twin Otter, equipped with a sampling tube collector, occurring between 18 July and 12 August 2016 below 1 km altitude off the central coast. The collector was flushed first with 70 ethanol, then with sterile DI water, between sampling regions. Collected volumes ranged from 100 L to 12 mL. All samples were diluted serially and plated on two different types of agar, nutrient-dense (PCA) and sparse (R-2A). Plates were incubated at room temperature and counted when colonies first appeared and again at 2 weeks.Preliminary results from seven flights are consistent with generally reported colony-forming unit (CFU) values for terrestrial fog water (e.g., [4]). The PCA assay ranged from 400 to 125,000 CFU/mL, R-2A from 700 to 130,000 CFU/mL. PCA and R-2A counts were not significantly different from each other at I^ plus or minus +/- 0.05, although observationally, the R2A plates had more pigmented colonies. CFU counts from the majority of flights were not different from each other in mean at the same level of significance, but about half differed in median, indicating differences in underlying distribution. These results validate the presence of viable microorganisms in coastal California fog at levels that should be easily detectable by our sampling system. The indicated distribution differences underscore the need for small-scale, long-term sampling surveys. Future planned work includes ion chromatography for limiting nutrients, ATP quantification, and qPCR for several microbial classes of interest.

Coastal↗

microbasew.c1

The continuous baseline microphysical retrieval, Wacr-based (MICROBASEW) VAP is a baseline retrieval of cloud microphysical properties. MICROBASEW uses a combination of observations from the W-band, zenith pointing radar (WACR), the ceilometer, the micropulse lidar (MPL), the microwave radiometer (MWR) and a merged thermodynamic profile (MERGED SOUNDING) VAP in order to determine the profiles of liquid/ice water content (L/IWC), liquid/ice cloud particle effective radius (re) and cloud fraction.

54 ENVIRONMENTAL SCIENCES↗

Surface Meteorology and Solar Energy (SSE) Data Release 5.1

The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].

Arctic heating↗

Aerosol Complexity and Implications for Predictability and Short-Term Forecasting

There are clear NWP and climate impacts from including aerosol radiative and cloud interactions. Changes in dynamics and cloud fields affect aerosol lifecycle, plume height, long-range transport, overall forcing of the climate system, etc. Inclusion of aerosols in NWP systems has benefit to surface field biases (e.g., T2m, U10m). Including aerosol affects has impact on analysis increments and can have statistically significant impacts on, e.g., tropical cyclogenesis. Above points are made especially with respect to aerosol radiative interactions, but aerosol-cloud interaction is a bigger signal on the global system. Many of these impacts are realized even in models with relatively simple (bulk) aerosol schemes (approx.10 -20 tracers). Simple schemes though imply simple representation of aerosol absorption and importantly for aerosol-cloud interaction particle-size distribution. Even so, more complex schemes exhibit a lot of diversity between different models, with issues such as size selection both for emitted particles and for modes. Prospects for complex sectional schemes to tune modal (and even bulk) schemes toward better selection of size representation. I think this is a ripe topic for more research -Systematic documentation of benefits of no vs. climatological vs. interactive (direct and then direct+indirect) aerosols. Document aerosol impact on analysis increments, inclusion in NWP data assimilation operator -Further refinement of baseline assumptions in model design (e.g., absorption, particle size distribution). Did not get into model resolution and interplay of other physical processes with aerosols (e.g., moist physics, obviously important), chemistry

Predictability↗