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At least 73 records · Page 4

X-ray spectral models of Galactic bulge sources - The emission-line factor

Current difficulties in finding unique and physically meaningful models for the X-ray spectra of Galactic bulge sources are exacerbated by the presence of strong, variable emission and absorption features that are not resolved by the instruments observing them. Nine Einstein solid state spectrometer (SSS) observations of five Galactic bulge sources are presented for which relatively high resolution objective grating spectrometer (OGS) data have been published. It is found that in every case the goodness of fit of simple models to SSS data is greatly improved by adding line features identified in the OGS that cannot be resolved by the SSS but nevertheless strongly influence the spectra observed by SSS.

Vrtilek, S. D.↗

Cooling Flow Spectra in Ginga Galaxy Clusters

The primary focus of this research project has been a joint analysis of Ginga LAC and Einstein SSS X-ray spectra of the hot gas in galaxy clusters with cooling flows is reported. We studied four clusters (A496, A1795, A2142 & A2199) and found their central temperatures to be cooler than in the exterior, which is expected from their having cooling flows. More interestingly, we found central metal abundance enhancements in two of the clusters, A496 and A2142. We have been assessing whether the abundance gradients (or lack thereof) in intracluster gas is correlated with galaxy morphological gradients in the host clusters. In rich, dense galaxy clusters, elliptical and SO galaxies are generally found in the cluster cores, while spiral galaxies are found in the outskirts. If the metals observed in clusters came from proto-ellipticals and proto-S0s blowing winds, then the metal distribution in intracluster gas may still reflect the distribution of their former host galaxies. In a research project which was inspired by the success of the Ginga LAC/Einstein SSS work, we analyzed X-ray spectra from the HEAO-A2 MED and the Einstein SSS to look for temperature gradients in cluster gas. The HEAO-A2 MED was also a non-imaging detector with a large field of view compared to the SSS, so we used the differing fields of view of the two instruments to extract spatial information. We found some evidence of cool gas in the outskirts of clusters, which may indicate that the nominally isothermal mass density distributions in these clusters are steepening in the outer parts of these clusters.

White, Raymond E., III↗

Surface Salinity Variability in the North Atlantic During Recent Decades

The sea surface salinity (SSS) variability in the North Atlantic is investigated using numerical model simulations for the last 50 years based on atmospheric forcing variability from Comprehensive Atmosphere Ocean Data Set (COADS) and National Center for Environmental Prediction / National Center for Atmospheric Research (NCEP/NCAR) Reanalysis. The largest interannual and longer term variability occurs in two regions: the Labrador Sea and the North Equatorial Countercurrent (NECC) region. In both regions the seasonality of the surface salinity variability is prominent with the maximum standard deviation occurring in the summer/fall period. In the Labrador Sea the summer SSS anomalies far exceed those of wintertime in amplitude. The interannual SSS variability in the subpolar gyre can be attributed to two factors: excess ice melt and heat flux (i.e. deep mixing) variations. On the other hand, heat flux variability can also lead to meridional overturning changes on decadal time scales such that weak overturning is manifested in fresh surface conditions in the subpolar gyre. The overturning changes also influence the NECC region SSS variability. Moreover, the subpolar freshening events are expected to occur during the negative phase of North Atlantic Oscillation which is associated with a weak wintertime surface heat loss in the subpolar gyre. No excess sea ice melt or precipitation is necessary for the formation of the fresh anomalies, because with the lack of wide-spread deep mixing, the fresh water that would be expected based on climatology, would accumulate at the surface. Thus, the fresh water 'conveyor' in the Atlantic operates via the overturning circulation such that deep mixing inserts fresh water while removing heat from the water column.

Haekkinen, Sirpa↗

XMM TOO Observation

The primary research goal of this project is to perform follow-up observations of a recurrent ultraluminous supersoft X-ray source (SSS) in Ml0l. The source was first discovered by ROSAT and was confirmed as a SSS with a blackbody temperature of about l00eV by Chandra. During 2000 March, Chandra detected it at Lx=4e39 erg per second, and then in 2000 October, its luminosity dropped to around le39 erg per second. During 2004, Chandra is conducting a monitoring program for Ml0l. The SSS was near the detection limit during January, March, and May; the X-ray spectra were harder with a power-law shape, and the X-ray luminosity was about 3e37 erg/second, a factor of greater than 200 fainter than that in the previous high state. The source was found to be in outburst again during the July 5 observation, with an X-ray luminosity of about 7e39 erg/second. Data taken on July 6,7, and 8 show that the source was in a strong outburst with a peak bolometric luminosity of about 7e39 erg/second. In general, the X-ray spectra are best described with an absorbed blackbody model with temperatures of approximately 50-100eV. In addition, we found absorption edges at 0.33, 0.57, 0.66, and 0.88 keV in two of the high state spectra. These features may signal the presence of highly ionized gas in the vicinity of the accretor (e.g., warm absorber). In order to study an ultraluminous SSS in outburst in detail, we proposed a TOO XMM observation to observe the source. The observation was taken on July 23 and the source was fainter with a luminosity of 6e38 ergs, and a harder X-ray spectrum with a power-law tail seen up to 7 keV. This clearly indicates that the source was in the decline stage with spectral change. In addition to the XMM observation, we also arranged radio observation and a simultaneous CFHT observation. The X-ray results were published in ATel and ApJL. There were several more Chandra observations taken after 2004 July. The source was in a low luminosity state but it underwent another X-ray outburst in 2004 December. We are arranging more follow-up observations for this intriguing source.

Kong, Albert↗

SMOS Salinity Retrieved from New Seawater Dielectric Constant Models at L-band

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant. Two new parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements [1] (BV) and on the other hand on new laboratory measurements [3] (GW2020). These two approaches are fully independent. The brightness temperatures, Tb, simulated with the BV and GW2020 parametrizations are compared with each other and with the ones derived from dielectric constant models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Tb simulated with the BV and GW2020 parametrizations agree particularly well for most SSS and SST commonly observed over the open ocean and are found to be in closer agreement than with earlier parametrizations. Nevertheless, uncertainty remains at low SST where a ∼ 0.1 K relative difference between the two models is observed. A complete reprocessing of SMOS SSS (2010–2020) has been performed using the BV parametrization instead of the Klein and Swift (1977) model previously used in SMOS processing. When compared with Argo derived near surface salinity maps, clear improvements are observed in warm and cold regions. Remaining uncertainties in cold waters will be discussed relatively to the uncertainties in SMOS Tb linked to sea ice contamination and given the constraints given by the GW2020 laboratory measurements.

J. Boutin↗

The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System

Here we assess the impact of satellite sea surface salinity (SSS) observations on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts. The baseline experiment assimilates satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). These baseline experiments are then compared with experiments that additionally assimilate Aquarius (version 5.0 Lilly and Lagerloef, 2008) and SMAP (version 2.0 Meissner and Wentz, 2016) SSS. Twelve-month forecasts are initialized for each month from September 2011 to September 2017. We find that including satellite SSS significantly improves NINO3.4 sea surface temperature anomaly validation over 0-8 month forecast lead-times and removing the salty bias from SMAP data helps to extend useful forecasts out to 12 month lead-times.

SSS↗

Abundance gradients in cooling flow clusters: Ginga Large Area Counters and Einstein Solid State Spectrometer spectra of A496, A1795, A2142, and A2199

We analyze the Ginga Large Area Counters (LAC) and Einstein Solid State Spectrometer (SSS) spectra of four cooling flow clusters, A496, A1795, A2142, and A2199, each of which shows firm evidence of a relatively cool component. The inclusion of such cool spectral components in joint fits of SSS and LAC data leads to somewhat higher global temperatures than are derived from the high-energy LAC data alone. We find little evidence of cool emission outside the SSS field of view. Metal abundances appear to be centrally enhanced in all four clusters, with varying degrees of model dependence and statistical significance: the evidence is statistically strongest for A496 and A2142, somewhat weaker for A2199 and weakest for A1795. We also explore the model dependence in the amount of cold, X-ray-absorbing matter discovered in these clusters by White et al.

White, Raymond E., III↗

The Integrated X-Ray Spectrum of Galactic Populations of Luminous Supersoft X-Ray Sources

We compute the composite X-ray spectrum of a population of unresolved SSS's in a spiral galaxy such as our own or M31. The sources are meant to represent the total underlying population corresponding to all sources which have bolometric luminosities in the range of 10(exp 37) - 10(exp 38) ergs/s and kT on the order of tens of eV. These include close-binary supersoft sources, symbiotic novae, and planetary nebulae, for example. In order to determine whether the associated X-ray signal would be detectable, we also 'seed' the galaxy with other types of X-ray sources, specifically low-mass X-ray binaries (LMXB's) and high-mass X-ray binaries (HMXB's). We find that the total spectrum due to SSS's, LMXB's, and HMXB's exhibits a soft peak which owes its presence to the SSS population. Preliminary indications are that this soft peak may be observable.

DiStefano, R.↗

Further Studies on Oceanic Biogeochemistry and Carbon Cycling

This TM consists of two chapters. Chapter I describes the development of a coupled, one-dimensional biogeochemical model using turbulence closure mixed layer (TCMLM) dynamics. The model is applied to the Sargasso Sea at the BATS (Bermuda Atlantic Time Series) site and the results are compared with a previous model study in the same region described in NASNTP-2001-209991. The use of the TCMLM contributed to some improvements in the model simulation of chlorophyll, PAR, nitrate, phosphate, and oxygen, but most importantly, the current model achieved good agreement with the data with much more realistic background eddy diffusivity. However, off-line calculations of horizontal transport of biogeochemical properties revealed that one-dimensional dynamics can only provide a limited assessment of the nutrient and carbon balances at BATS. Future studies in the BATS region will require comprehensive three-dimensional field studies, combined with three-dimensional eddy resolving numerical experiments, to adequately quantify the impact of the local and remote forcing on ecosystem dynamics and carbon cycling. Chapter II addresses the sensitivity of global sea-air CO, flux estimates to wind speed, temperature, and salinity. Sensitivity analyses of sea-air CO, flux to wind speed climatologies, gas transfer algorithms, SSS and SST were conducted for the global oceans and regional domains. Large uncertainties in the global sea-air flux are identified, primarily due to the different gas transfer algorithms used. The sensitivity of the sea-air flux to SST and SSS is similar in magnitude to the effect of using different wind climatologies. Globally, the mean ocean uptake of CO, changes by 5 to 16%, depending upon the combination of SST and SSS used.

Signorini, S. R.↗

Correlations Between Sea-Surface Salinity Tendencies and Freshwater Fluxes in the Pacific Ocean

Temporal changes in sea-surface salinity (SSS) from 21 years of a high resolution model integration of the Pacific Ocean are correlated with the freshwater flux that was used to force the integration. The correlations are calculated on a 1 x10 grid, and on a monthly scale to assess the possibility of deducing evaporation minus precipitation (E-P) fields from the salinity measurements to be taken by the upcoming Aquarius/SAC-D mission. Correlations between the monthly mean E-P fields and monthly mean SSS temporal tendencies are mainly zonally-oriented, and are highest where the local precipitation is relatively high. Nonseasonal (deviations from the monthly mean) correlations are highest along mid-latitude storm tracks and are relatively small in the tropics. The response of the model's surface salinity to surface forcing is very complex, and retrievals of freshwater fluxes from SSS measurements alone will require consideration of other processes, including horizontal advection and vertical mixing, rather than a simple balance between the two.

Li, Zhen↗

Weekly Gridded Aquarius L-band Radiometer-Scatterometer Observations and Salinity Retrievals over the Polar Regions - Part 2: Initial Product Analysis

Following the development and availability of Aquarius weekly polar-gridded products, this study presents the spatial and temporal radiometer and scatterometer observations at L band (frequency1.4 GHz) over the cryosphere including the Greenland and Antarctic ice sheets, sea ice in both hemispheres, and over sub-Arctic land for monitoring the soil freeze-thaw state. We provide multiple examples of scientific applications for the L-band data over the cryosphere. For example, we show that over the Greenland Ice Sheet, the unusual 2012 melt event lead to an L-band brightness temperature (TB) sustained decrease of 5 K at horizontal polarization. Over the Antarctic ice sheet, normalized radar cross section (NRCS) observations recorded during ascending and descending orbits are significantly different, highlighting the anisotropy of the ice cover. Over sub-Arctic land, both passive and active observations show distinct values depending on the soil physical state (freeze-thaw). Aquarius sea surface salinity (SSS) retrievals in the polar waters are also presented. SSS variations could serve as an indicator of fresh water input to the ocean from the cryosphere, however the presence of sea ice often contaminates the SSS retrievals, hindering the analysis. The weekly grided Aquarius L-band products used a redistributed by the US Snow and Ice Data Center at http:nsidc.orgdataaquariusindex.html, and show potential for cryospheric studies.

Aquarius↗

Analysis of RFI Statistics for Aquarius RFI Detection and Mitigation Improvements

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI) which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Microwave remote sensing↗

Planning and Monitoring Multi-Job Type Swarm Search and Service Missions

To transition from control theory to real applications, it is important to study missions such as Swarm Search and Service (SSS) where vehicles are not only required to search an area, but also service all jobs that they find. In SSS missions, each type of job requires a group of vehicles to break off from the swarm for a given amount of time to service it. The required number of vehicles and the service rate are unique to each job type. Once a job has been completed, the vehicles are able to return to the swarm for use elsewhere. If not, enough vehicles are present in the swarm at the time that the job is identified, that job is dropped without being serviced. In SSS missions that occur in open environments, the arrival rate of jobs varies dynamically as vehicles move in and out of the swarm to service jobs. Human operators are tasked with effectively planning and managing these complex missions. This paper presents a user study that seeks to test the efficacy and ease-of-use of a prediction model known as the Hybrid Model as an aid in planning and monitoring tasks. Results show that the novel computational model aid allows operators to more effectively choose the necessary swarm size to handle expected mission workload, as well as, maintain sufficient situation awareness to evaluate the performance of the swarm during missions.

swarm search and service↗

Seawater Dielectric Constant At L-Band: How Consistent Are New Parametrisations Inferred from Smos and Laboratory Measurements?

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant (ε). Two new ε parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements and on the other hand on new laboratory measurements. These two approaches are fully independent. These new ε parametrizations are compared with each other and with the ε models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. The two new ε parametrizations are found to be in closer agreement than with earlier parametrizations for most common ocean conditions. We will further study to which extent the recent SMOS CCI+SSS v3 reprocessing confirms the above results and could help resolve remaining inconsistencies.

SMOS↗

The Dielectric Constant of Sea Water and Extension to High Salinity

Accurate knowledge of the dielectric constant of sea water is important for remote sensing of surface parameters such as sea surface temperature (SST) and sea surface salinity (SSS). The advent of sensors in space, SMOS [1], Aquarius [2] and SMAP [3] capable of measuring SSS motivated modern measurements [4,5] and modelling [5,6] of the dielectric constant at L-band (1.4 GHz). In the past, the range of salinity included in the data used to create these models has been restricted to values typically encountered in the open ocean (e.g., less than 40 psu). However, there are many smaller water bodies with much higher salinity. Notable examples are the Great Salt Lake in Utah with salinity on the order of 180 psu and Garabogazköl lagoon in Turkmenistan with even higher salinity. Unfortunately, existing models for the dielectric constant can’t necessarily just be extended to higher values of salinity. The problem is that the polynomials in salinity and temperature used to represent the unknown parameters in the models are not constrained outside the range of SSS and SST used to determine their coefficients. While the models for the dielectric constant may be very good within that range, outside that range they can lead to unrealistic behavior. Research is underway to develop a model that represents the dielectric constant well over the ocean and behaves well at high salinity. In preparation for possible wideband remote sensing of salinity [7,8 ,9], the laboratory measurements made at 1.413 GHz [4,5] are being repeated at 0.707 GHz (P-band) and the plan is to include values of high salinity (50, 100, 150 psu).

D.M. Le Vine↗

Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC

The 2020 ‘Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere’ (EUREC4A-OA) and the ‘Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign’ (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Kashawn Hall↗

Characterizing the California Current System through Sea Surface Temperature and Salinity

Characterizing temperature and salinity (T-S) conditions is a standard framework in oceanography to identify and describe deep water masses and their dynamics. At the surface, this practice is hindered by multiple air–sea–land processes impacting T-S properties at shorter time scales than can easily be monitored. Now, however, the unsurpassed spatial and temporal coverage and resolution achieved with satellite sea surface temperature (SST) and salinity (SSS) allow us to use these variables to investigate the variability of surface processes at climate-relevant scales. In this work, we use SSS and SST data, aggregated into domains using a cluster algorithm over a T-S diagram, to describe the surface characteristics of the California Current System (CCS), validating them with in situ data from uncrewed Saildrone vessels. Despite biases and uncertainties in SSS and SST values in highly dynamic coastal areas, this T-S framework has proven useful in describing CCS regional surface properties and their variability in the past and in real time, at novel scales. This analysis also shows the capacity of remote sensing data for investigating variability in land–air–sea interactions not previously possible due to limited in situ data.

Marisol García-Reyes↗

Analysis of fungal type isolates taken from a 90-day manned test of an advanced regenerative life support system

Fungal-like cultures isolated before, during, and after the 90-day test from samples of space station simulator (SSS) atmosphere, surfaces, subsystem componets, and crew dermal sites were identified to genus. Out of the original 525 isolates, approximately 80% were classified as bacteria. Laboratory methods (culture media, moisturization, and incubation temperatures) favored the recovery of medically significant bacteria rather than fungi. Therefore, fungal isolates were mostly, nonfastidious types which are ubiquitous in soil and air and commonly contaminate laboratory cultures of pathogens. Predominant isolates were species of Aspergillus, Penicillium, Pullularia, Rhodotorula, and various yeasts. No instances of fungal proliferation were observed; test data reflect the survival of environmental types indigenous to the SSS pretests.

Sofios, M.↗