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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.

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NASA NTRS1974

Cratering on Mars. I - Cratering and obliteration history. II Implications for future cratering studies from Mariner 4 reanalysis

It is pointed out that Mars is especially well adapted to statistical studies of crater morphologies for deciphering its geological history. A framework for understanding planetary geomorphological histories from the diameter-frequency relations of different morphological classes of craters described by Chapmam et al. (1970) is extended in order to understand Martian cratering, erosional, and depositional history. The cratering-obliteration history derived is compared with global interpretations considered by Hartman (1973) and Soderblom et al. (1974). An idealized dust-filling model is employed.

Chapman, C. R.↗
NASA NTRS2019

Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction

Developments in ocean data assimilation (DA) and observing system technologies are intertwined. New observation types lead to new DA methods, and new DA methods such as Coupled Data Assimilation can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners are encouraged to make better use of observations that are already available, for example in strongly coupled data assimilation where ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate,as well as initializing operational long-range prediction models. There are remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean observing system throughout its history, the presence of biases and drifts in models, and simplifying assumptions made in the DA methods. From a governance point of view, more support is needed to interface the observing community and the ocean DA community. For prediction applications, the ocean DA community must work with the ocean observing community to establish protocols for rapid communication of ocean observing data on NWP timescales. There is potential for new observations to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of numerical weather prediction covering hours to weeks, out to multiple decades. It is highly encouraged that communication be fostered between thesecommunities to allow operational prediction centers the ability to provide guidance to the design of a sustained and adaptive observing network.

Ocean reanalysis↗
NASA NTRS2000

Towards a Comprehensive Dynamic-chemistry Assimilation for Eos-Chem: Plans and Status in NASA's Data Assimilation Office

In order to support the EOS-Chem project, a comprehensive assimilation package for the coupled chemical-dynamical system is being developed by the Data Assimilation Office at NASA GSFC. This involves development of a coupled chemistry/meteorology model and of data assimilation techniques for trace species and meteorology. The model is being developed using the flux-form semi-Lagrangian dynamical core of Lin and Rood, the physical parameterizations from the NCAR Community Climate Model, and atmospheric chemistry modules from the Atmospheric Chemistry and Dynamics branch at NASA GSFC. To date the following results have been obtained: (i) multi-annual simulations with the dynamics-radiation model show the credibility of the package for atmospheric simulations; (ii) initial simulations including a limited number of middle atmospheric trace gases reveal the realistic nature of transport mechanisms, although there is still a need for some improvements. Samples of these results will be shown. A meteorological assimilation system is currently being constructed using the model; this will form the basis for the proposed meteorological/chemical assimilation package. The latter part of the presentation will focus on areas targeted for development in the near and far terms, with the objective of Providing a comprehensive assimilation package for the EOS-Chem science experiment. The first stage will target ozone assimilation. The plans also encompass a reanalysis (ReSTS) for the 1991-1995 period, which includes the Mt. Pinatubo eruption and the time when a large number of UARS observations were available. One of the most challenging aspects of future developments will be to couple theoretical advances in tracer assimilation with the practical considerations of a real environment and eventually a near-real-time assimilation system.

Pawson, Steven↗
NASA NTRS1992

Overview for the reanalysis of Mariner 9 UV spectrometer data for ozone, cloud, and dust abundances, and their interaction over climate timescales

Mariner 9 UV spectrometer data were reinverted for the ozone abundance, cloud abundance, dust abundance, and polar-cap albedo. The original reduction of the spectra ignored the presence of atmospheric dust and clouds, even though their abundance is substantial and can mask appreciable amounts of ozone if not accounted for (Lindner, 1988). The Mariner 9 ozone data has been used as a benchmark in all theoretical models of atmospheric composition, escape, and photochemistry. A second objective is to examine the data for the interrelationship of the ozone cycle, dust cycle, and cloud cycle, on an annual, inter-annual, and climatic basis, testing predictions by Lindner (1988). This also has implications for many terrestrial ozone studies, such as the ozone hole, acid rain, and ozone-smog. A third objective is to evaluate the efficacy of the reflectance spectroscopy technique at retrieving the ozone abundance on Mars. This would be useful for planning ozone observations on future Mars missions or the terrestrial troposphere.

Lindner, Bernhard Lee↗
NASA NTRS1995

Photochemistry of Triton's Atmosphere and Ionosphere

The photochemistry of 32 neutral and 21 ion species in Triton's atmosphere is considered. Parent species N2, CH4, and CO (with a mixing ratio of 3 x 10(exp -4) in our basic model) sublime from the ice with rates of 40, 208, and 0.3 g/sq cm/b.y., respectively. Chemistry below 50 km is driven mostly by photolysis of methane by the solar and interstellar medium Lyman-alpha photons, producing hydrocarbons C2H4, C2H6, and C2H2 which form haze particles with precipitation rates of 135, 28, and 1.3 g/sq cm/b.y., respectively. Some processes are discussed which increase the production of HCN (by an order of magnitude to a value of 29 g/sq cm/b.y.) and involve indirect photolysis of N2 by neutrals. Reanalysis of the measured methane profiles gives an eddy diffusion coefficient K = 4 x 10(exp 3)sq cm/s above the tropopause and a more accurate methane number density near the surface, (3.1 +/- 0.8)x IO(exp 11)/cu cm. Chemistry above 200 km is driven by the solar EUV radiation (lambda less than 1000 A) and by precipitation of magnetospheric electrons with a total energy input of 10(exp 8) W (based on thermal balance calculations). The most abundant photochemical species are N, H2, H, 0, and C. They escape with the total rates of 7.7 x 10(exp 24)/ s, 4.5 x 10(exp 25)/s, 2.4 x 10(exp 25)/s, 4.4 x 10(exp 22)/s, and 1.1 x 10(exp 24), respectively. Atomic species are transported to a region of 50-200 km and drive the chemistry there. Ionospheric chemistry explains the formation of an E region at 150-240 km with HCO(+) as a major ion, and of an F region above 240 km with a peak at 320 km and C(+) as a major ion. The ionosphere above 500 km consists of almost equal densities of C(+) and N(+) ions. The model profiles agree with the measured atomic nitrogen and electron density profiles. A number of other models with varying rate coefficients of some reactions, differing properties of the haze particles (chemically passive or active), etc., were developed. These models show that there are four basic unknown values which have strong impacts on the composition and structure of the atmosphere and ionosphere. These values and their plausible ranges are the CO mixing ratio f(sub co) = 10(exp -4) - 10(exp -3), the magnetospheric electron energy input (1 +/- 0.5) x 10(exp 8) W, the rate coefficient of charge-exchange reaction N2(+) + C(kappa) = 10(exp -11) - 10(exp -10)cu cm/s, and the ion escape velocity upsilon(sub i) approx. equals 150 cm/s.

Krasnopolsky, Vladimir A.↗
NASA NTRS1995

Photochemistry of Triton's Atmosphere and Ionosphere

The photochemistry of 32 neutral and 21 ion species in Triton's atmosphere is considered. Parent species N2, CH4, and CO (with a mixing ratio of 3 x 10(exp -4) in our basic model) sublime from the ice with rates of 40, 208, and 0.3 g/sq cm/b.y., respectively. Chemistry below 50 km is driven mostly by photolysis of methane by the solar and interstellar medium Lyman-alpha photons, producing hydrocarbons C2H4, C2H6, and C2H2 which form haze particles with precipitation rates of 135, 28, and 1.3 g/sq cm/b.y., respectively. Some processes are discussed which increase the production of HCN (by an order of magnitude to a value of 29 g/sq cm/b.y.) and involve indirect photolysis of N2 by neutrals. Reanalysis of the measured methane profiles gives an eddy diffusion coefficient K = 4 x 10(exp 3) sq cm/s above the tropopause and a more accurate methane number density near the surface, (3.1 +/- 0.8) x 10(exp 11)/cc cm. Chemistry above 200 km is driven by the solar EUV radiation (lambda less than 1000 A)) and by precipitation of magnetospheric electrons with a total energy input of 10(exp 8) W (based on thermal balance calculations). The most abundant photochemical species are N, H2, H, O, and C. They escape with the total rates of 7.7 x 10(exp 24)/ s, 4.5 x 10(exp 25)/ s, 2.4 x 10(exp 25)/ s, 4.4 x 10(exp 22)/ s, and 1.1 x 10(exp 24)/ s, respectively. Atomic species are transported to a region of 50-200 km and drive the chemistry there. Iono- spheric chemistry explains the formation of an E region at 150-240 km with HCO(+) as a major ion, and of an F region above 240 km with a peak at 320 km and C(+) as a major ion. The ionosphere above 500 km consists of almost equal densities of C(+) and N(+) ions. The model profiles agree with the measured atomic nitrogen and electron density profiles. A number of other models with varying rate coefficients of some reactions, differing properties of the haze particles (chemically passive or active), etc., were developed. These models show that there are four basic unknown values which have strong impacts on the composition and structure of the atmosphere and ionosphere. These values and their plausible ranges are the CO mixing ratio f(sub co) = 10(exp -4)- 10(exp -3), the magnetospheric electron energy input (1 +/- 0.5) x 10(exp 8) W, the rate coefficient of charge-exchange reaction N2(+) + Ck = 10(exp -11)-10(exp -10)cc cm/s, and the ion escape velocity upselon(sub i) approx. 150 cm/s.

Krasnopolsky, Vladimir A.↗
NASA NTRS2021

PBL Height from AIRS, GPS RO, and MERRA-2 Products in NASA GES DISC and Their 10 Year Seasonal Mean Intercomparison

Within the planetary boundary layer (PBL), surface forcing response, drag, turbulence, and vertical mixing are important processes and play a more critical role here than in the overlying “free atmosphere”. The PBL Height (PBLH) is an important parameter in climate models, weather forecasts, and air quality prediction. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides data processing, archiving, and distribution services for numerous Earth science products. PBLH is a parameter in three products served by GES DISC, which are from the Atmospheric Infrared Sounder (AIRS), the Global Positioning System (GPS) radio occultation (RO) experiment, and the NASA reanalysis product Modern-Era Retrospective analysis for Research and Applications – 2 (MERRA-2). These products have different spatial and temporal resolutions and coverages, and their PBLH definitions are also different. To better serve the PBL research community, we have summarized the specifications of these products. A ten-year seasonal mean intercomparison is also conducted to provide further guidance to users. The intercomparison results show that MERRA-2 has a much shallower PBL than AIRS and GPS RO. An experimental study indicates the different PBLH definition in MERRA-2 caused smaller values of PBLH. The improvement of the water vapor retrieval in AIRS version 7 over version 6 results in the version 7 PBLH agreeing better with GPS RO and MERRA-2 than version 6, especially near the equator and low latitudes.

Feng Ding↗
NASA NTRSDate not supplied

Reanalysis of Rat Data from Spacelab Life Sciences 2 (SLS-2) to Reveal Research Gaps in Spaceflight Data

Using and analyzing the legacy data obtained in space life sciences missions has the potential to provide researchers a complete picture of the molecular changes associated with space without further experimentation. This project’s objective is to extract, filter, organize, and analyze all Rattus norvegicus data and metadata obtained from Columbia’s Spacelab Life Sciences 2 (SLS-2, STS-58) mission to explore the ways that we can compile information from model organisms, in our case rats, to create a reliable model to understand biological mechanisms in response to these space flight changes. By reusing rare space legacy data coupled with data analysis techniques, we can combine individual preexisting datasets with current ones to gain new, comprehensive insights about the effects of spaceflight on our bodies. Our methods can also lead to the creation of a standardized pipeline that could be applied to other space life science datasets for analysis. In this review, every biological experiment conducted on rats in the SLS-2 Mission was studied with our pipeline to create a new biological library and model that could be used by scientists from around the world to make novel discoveries and develop new hypotheses from this priceless information without the limitation of the costs of spaceflight experimentation.

rats↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
NASA NTRSDate not supplied

Hailstorm Analyses and Detection Derived from Current and Historical Satellite Data and Convective Environmental Parameters

We seek to demonstrate the extent to which hailstorms can be detected using a combination of geostationary (GEO) visible and infrared metrics of storm intensity and convective environmental parameters from reanalysis. Hailstorm identifications from low-Earth-orbiting (LEO) passive microwave sensors and maximum expected size of hail (MESH) from ground-based radar serve as a proxy for hail events. Data are analyzed for two warm seasons over the contiguous United States (CONUS). A neural network (NN) is trained to predict hailstorm detection dependent on optimal multi-variate weighting of observed and modeled input. The NN results are then applied to a 15-year Meteosat Second Generation climatology over South Africa to depict where hailstorms are most likely to occur. We also explore the impact of GEO imager resolution on our ability to discriminate hailstorms by matching GOES-13 (4 km) and GOES-16 (2 km) storm intensity metrics against hail characteristics using LEO, MESH, and spotter reports over CONUS during 2017, when both satellites were simultaneously imaging. Such analysis allows us to assess the feasibility of assembling a severe storm climate data record back to GOES-8, in the mid-1990’s. Finer spatial resolution of GOES-16 better resolves the updraft characteristics and intensities that are inherently linked to hail formation; however, GOES-13 can be normalized to achieve comparable detection capability. When intelligently combined with model-derived convective environmental parameters, GEO-derived storm intensity metrics enable high-spatial resolution hail risk assessment at hourly intervals throughout the diurnal cycle anywhere around the world and an improved understanding of hailstorms in the climate system.

Kyle F Itterly↗
NASA NTRS2022

A NASA-Air Force Precipitation Analysis for Near-Real-Time Operations

This article describes a new precipitation analysis algorithm developed by NASA for time-sensitive operations at the United States Air Force. Implemented as part of the Land Information System—a land modeling and data assimilation software framework—this NASA–Air Force Precipitation Analysis (NAFPA) combines numerical weather prediction model outputs with rain gauge measurements and satellite estimates to produce global, gridded 3-h accumulated precipitation fields at approximately 10-km resolution. Input observations are subjected to quality control checks before being used by the Bratseth analysis algorithm that converges to optimal interpolation. NAFPA assimilates up to 3.5 million observations without artificial data thinning or selection. To evaluate this new approach, a multiyear reanalysis is generated and intercompared with eight alternative precipitation products across the contiguous United States, Africa, and the monsoon region of eastern Asia. NAFPA yields superior accuracy and correlation over low-latency (up to 14 h) alternatives (numerical weather prediction and satellite retrievals), and often outperforms high-latency (up to 3.5 months) products, although the details for the latter vary by region and product. The development of NAFPA offers a high-quality, near-real-time product for use in meteorological, land surface, and hydrological research and applications.

Africa↗
NASA NTRS2016

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

big data↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
NASA NTRS1975

Evidence for the nonuniform distribution of microwave attenuating clouds in the atmosphere of Venus - Mariner 2

Data obtained by Mariner 2 in three microwave-radiometer scans of Venus are reanalyzed using model Venusian atmospheres based on observations by Veneras 4 through 8 as well as by Mariners 5 and 10. It is noted that a previous analysis of this microwave data revealed a CO2 percentage and surface pressures that were considerably lower than those measured in situ as well as a longitudinal temperature gradient that was much larger than that indicated by the more recent measurements. The reanalysis shows that the measured scan ratios require different average values of microwave-cloud opacity for each scan and that the anomalous temperature decrease observed in the south polar region of the terminator scan requires a very opaque microwave cloud between local zenith angles of 40 and 70 deg. It is suggested that a nonuniform microwave-attenuating cloud is located below the IR and visible cloud deck of Venus.

Jones, D. E.↗
NASA NTRS1990

Observations of the galactic plane by the zodiacal infrared project

The two rocket flights of the Zodiacal Infrared Project (ZIP), flown 18 August 1980 and 31 July 1981, were intended to provide data on the near-infrared thermal emission of the interplanetary dust cloud over a broad range of ecliptic coordinates (latitudes -60 to +85 degrees, solar elongation angles 22 to 90 degrees and 140 to 180 degrees). In addition, their multiple crossings of the Galactic plane provided low resolution spectral data (delta lambda/lambda ranging from 1. to 0.1, for effective wavelengths from 3 to 30 microns) for most of the first quadrant (longitudes 30 to 100 degrees). Examples are displayed. Having made a thorough reanalysis of the calibration of the ZIP database, researchers present the salient features of the Galactic plane as observed by ZIP. The binned, in-plane data, corrected for zodiacal emission, generally show an exponential decrease with increasing longitude. The fitted exponential scale-length is 0.038/degree, and can be inverted to derive a radial density profile. Channel ratios are converted to temperatures by using model spectra in which thermal emitters with emissivity approx. 1/lambda are convolved with the filter responses. The results for channels 5 (11 microns) and 12 (21 microns) are shown, along with similarly derived temperatures from Infrared Astronomy Satellite (IRAS) 12 microns and 25 microns data. The ZIP data show little variation with longitude, consistent with IRAS results. A narrow spectral feature at 13 microns appears consistently in data for the plane (uncorrected for zodiacal emission). However, this is strongly contaminated by calibration problems for channel 8. Researchers suggest that residual emission at 13 microns arises from the (NeII) line at 12.8 microns.

Rickard, L. J.↗
NASA NTRS2001

The Evolution of Stratospheric Data Assimilation Systems

The use of model-assimilated meteorological observations for stratospheric research has become routine since the late 1980's. The first stratospheric assimilation systems were straightforward extensions of systems developed for tropospheric weather forecasting. During the 1990's systems were developed that more directly addressed the specifics of stratospheric applications. These developments include better treatment of the satellite observations and improved models that better represent the residual circulation in the assimilated data sets. This talk will review the evolution of stratospheric data assimilation and its application, especially to problems of tracer transport. The new data assimilation currently under validation at NASA will be described in some detail, and results from the validation exercise will be presented. This data assimilation system sits at the foundation of a proposed stratospheric reanalysis that covers the era of the Upper Atmosphere Research Satellite (UARS).

Rood, Richard B.↗
NASA NTRS2011

Hurricane Data Analysis Tool

In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of interest and time, single imagery, overlay of two different products, animation,a time skip capability and different image size outputs. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. Since the tool can directly access the real data, more features and functionality can be added in the future.

Liu, Zhong↗
NASA NTRS1996

Analysis of IUE Observations of Supernovae

This program supported the analysis of IUE observations of supernovae. One aspect was a Target-of-Opportunity program to observe bright supernovae which was applied to SN 1993J in M81, and another was continuing analysis of the IUE data from SN 1987A. Because of its quick response time, the IUE satellite has continued to provide useful data on the ultraviolet spectra of supernovae. Even after the launch of the Hubble Space Telescope, which has much more powerful ultraviolet spectrometers, the IUE has enabled us to obtain early and frequent measurements of ultraviolet radiation: this information has been folded in with our HST data to create unique observations of supernova which can be interpreted to give powerful constraints on the physical properties of the exploding stars. Our chief result in the present grant period was the completion of a detailed reanalysis of the data on the circumstellar shell of SN 1987A. The presence of narrow high-temperature mission lines from nitrogen-rich gas close to SN 1987A has been the principal observational constraint on the evolution of the supernova's progenitor. Our new analysis shows that the onset of these lines, their rise to maximum, and their subsequent fading can be understood in the context of a model for the photoionization of circumstellar matter.

Kirshner, Robert P.↗