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Use of the UCLA CONQUEST (CONtent-based Querying in Space and Time) is reviewed for performance of automatic cyclone extraction and detection of spatio-temporal blocking conditions on MPP. CONQUEST is a data analysis environment for knowledge and data mining to aid in high-resolution modeling of climate modeling.
Tropospheric and lower stratospheric aerosol backscatter data obtained from a calibrated backscatter lidar at Pasadena, California (34 deg N latitude)over the 1984-1993 period clearly indicate tightly coupled aerosol optical properties in the upper troposphere and lower stratosphere in the winter and early spring, due to the active mid-latitude stratospheric-tropospheric (ST) exchange processes occurring at this time of year.
Mars accretion is known to be fast compared to Earth. Basaltic samples provide a probe into the interior and allow reconstruction of siderophile element contents of the mantle. These estimates can be used to estimate conditions of core formation, as for Earth. Although many assume that Mars went through a magma ocean stage, and possibly even complete melting, the siderophile element content of Mars mantle is consistent with relatively low pressure and temperature (PT) conditions, implying only shallow melting, near 7 GPa and 2073 K. This is a pressure range where some have proposed a change in siderophile element partitioning behavior. We will examine the databases used for parameterization and split them into a low and higher pressure regime to see if the methods used to reach this conclusion agree for the two sets of data.
Presently, it is not well understood how to best model nitrogen oxides (NOx) emissions from lightning because lightning is highly variable. Peak current, channel length, channel altitude, stroke multiplicity, and the number of flashes that occur in a particular region (i.e., flash density) all influence the amount of lightning NOx produced. Moreover, these 5 variables are not the same for ground and cloud flashes; e.g., cloud flashes normally have lower peak currents, higher altitudes, and higher flash densities than ground flashes [see (Koshak, 2009) for additional details]. Because the existing satellite observations of lightning (Fig. 1) from the Lightning Imaging Sensor/Optical Transient Detector (LIS/OTD) do not distinguish between ground and cloud fashes, which produce different amounts of NOx, it is very difficult to accurately account for the regional/global production of lightning NOx. Hence, the ability to partition the LIS/OTD lightning climatology into separate ground and cloud flash distributions would substantially benefit the atmospheric chemistry modeling community. NOx indirectly influences climate because it controls the concentration of ozone and hydroxyl radicals in the atmosphere. The importance of lightning-produced NOx is empasized throughout the scientific literature (see for example, Huntrieser et al. 1998). In fact, lightning is the most important NOx source in the upper troposphere with a global production rate estimated to vary between 2 and 20 Tg (N)yr(sup -1) (Lee et al., 1997), with more recent estimates of about 6 Tg(N)yr(sup -1) (Martin et al., 2007). In order to make accurate predictions, global chemistry/climate models (as well as regional air quality modells) must more accurately account for the effects of lightning NOx. In particular, the NASA Goddard Institute for Space Studies (GISS) Model E (Schmidt et al., 2005) and the GEOS-CHEM global chemical transport model (Bey et al., 2001) would each benefit from a partitioning of the LIS/OTD lightning climatology. In this study, we introduce a new technique for retrieving the ground flash fraction in a set of N lightning observed from space and that occur within a specific latitude/longitude bin. The method is briefly described and applied to CONUS lightning that have already been partitioned into ground and cloud flashes using independent ground-based observations, in order to assess the accuracy of the retrieval method. The retrieval errors are encouragingly small.
We present the mass X-ray observable scaling relationships for clusters of galaxies using the XMM-Newton cluster catalog of Snowden et al. Our results are roughly consistent with previous observational and theoretical work, with one major exception. We find 2-3 times the scatter around the best fit mass scaling relationships as expected from cluster simulations or seen in other observational studies. We suggest that this is a consequence of using hydrostatic mass, as opposed to virial mass, and is due to the explicit dependence of the hydrostatic mass on the gradients of the temperature and gas density profiles. We find a larger range of slope in the cluster temperature profiles at radii 500 than previous observational studies. Additionally, we find only a weak dependence of the gas mass fraction on cluster mass, consistent with a constant. Our average gas mass fraction results also argue for a closer study of the systematic errors due to instrumental calibration and modeling method variations between analyses. We suggest that a more careful study of the differences between various observational results and with cluster simulations is needed to understand sources of bias and scatter in cosmological studies of galaxy clusters.
There are two slide presentations contained in this document. The first reviews the lunar missions from Surveyor, Galileo, Clementine, the Lunar Prospector, to upcoming lunar missions, Lunar Reconnaissance Orbiter (LRO), Lunar Crater Observation & Sensing Satellite (LCROSS), Acceleration, Reconnection, Turbulence and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS), Gravity Recovery and Interior Laboratory (GRAIL), Lunar Atmosphere, Dust and Environment Explorer (LADEE), ILN and a possible Robotic sample return mission. The information that the missions about the moon is reviewed. The second set of slides reviews the lunar meteorites, and the importance of lunar meteorites to adding to our understanding of the moon.
Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.
Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which can contain up to several gigabytes of data. Surprisingly, research on MTS search is very limited. Most existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two provably correct algorithms to solve this problem (1) an R-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences, and (2) a List Based Search (LBS) algorithm which uses sorted lists for indexing. We demonstrate the performance of these algorithms using two large MTS databases from the aviation domain, each containing several millions of observations Both these tests show that our algorithms have very high prune rates (>95%) thus needing actual
A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.
We have combined analyses of over 1000 high altitude aircraft observations of electrified clouds with diurnal lightning statistics from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to produce an estimate of the diurnal variation in the global electric circuit. Using basic assumptions about the mean storm currents as a function of flash rate and location, and the global electric circuit, our estimate of the current in the global electric circuit matches the Carnegie curve diurnal variation to within 4% for all but two short periods of time. The agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Mean contributions to the global electric circuit from land and ocean thunderstorms are 1.1 kA (land) and 0.7 kA (ocean). Contributions to the global electric circuit from ESCs are 0.22 kA for ocean storms and 0.04 kA for land storms. Using our analysis, the mean total conduction current for the global electric circuit is 2.0 kA.
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Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs
Modern science is increasingly dependent on computational analysis of very large data sets. Organizing, referencing, publishing those data has become a complex problem. Published research that depends on such data often fails to cite the data in sufficient detail to allow an independent scientist to reproduce the original experiments and analyses. This paper explores some of the challenges related to data identification, equivalence and reproducibility in the domain of data intensive scientific processing. It will use the example of Earth Science satellite data, but the challenges also apply to other domains.
This User Guide to the Cassini Composite Infrared Spectrometer (CIRS) has been written with two communities in mind. First and foremost, scientists external to the Cassini Project who seek to use the CIRS data as archived in the Planetary Data System (PDS). In addition, it is intended to be a comprehensive reference guide for those internal to the CIRS team.
Introduction: A preliminary exam of the Wild 2 olivine yielded a major element distribution that is strikingly similar to those for aqueously altered carbonaceous chondrites (CI, CM, and CR) [1], in which FeO-rich olivine is preferentially altered. With evidence lacking for large-scale alteration in Wild 2, the mechanism for this apparent selectivity is poorly understood. We use a statistical approach to explain this distribution in terms of relative contributions from different chondrite forming regions. Samples and Analyses: We have made a particular effort to obtain the best possible analyses of both major and minor elements in Wild 2 olivine and the 5-30 micrometer population in chondrite matrix. Previous studies of chondrite matrix either include larger isolated grains (not found in the Wild 2 collection) or lack minor element abundances. To overcome this gap in the existing data, we have now compiled greater than 10(exp 3) EPMA analyses of matrix olivine in CI, CM, CR, CH, Kakangari, C2-ungrouped, and the least equilibrated CO, CV, LL, and EH chondrites. Also, we are acquiring TEM/EDXS analyses of the Wild 2 olivine with 500s count times, to reduce relative errors of minor elements with respect to those otherwise available. Results: Using our Wild 2 analyses and those from [2], the revised major element distribution is more similar to anhydrous IDPs than previous results, which were based on more limited statistics (see figure below). However, a large frequency peak at Fa(sub 0-1) still persists. All but one of these grains has no detectable Cr, which is dissimilar to the Fa(sub 0-1) found in the CI and CM matrices. In fact, Fa(sub 0-1) with strongly depleted Cr content is a composition that appears to be unique to Kakangari and enstatite (highly reduced) chondrites. We also note the paucity of Fa(sub greater than 58), which would typically indicate crystallization in a more oxidizing environment [3]. We conclude that, relative to the bulk of anhydrous IDPs, Wild 2 may have received a larger contribution from the Kakangari and/or enstatite chondrite forming regions. Alternatively, Wild 2 may have undergone accretion in an anomalously reducing region, marked by nebular condensation of this atypical forsterite. In [4], a similar conclusion was reached with an Fe-XANES study. We will also use similar lines of reasoning, and our previous conclusions in [5], to constrain the relative contributions of silicates that appear to have been radially transported from different ordinary and carbonaceous chondrite forming regions to the Kuiper Belt. In addition, the widespread depletion of Cr in these FeO-rich (Fa(sub greater than 20)) fragments is consistent with mild thermal metamorphism in Wild 2.
Airframe noise corresponds to the acoustic radiation due to turbulent flow in the vicinity of airframe components such as high-lift devices and landing gears. The combination of geometric complexity, high Reynolds number turbulence, multiple regions of separation, and a strong coupling with adjacent physical components makes the problem of airframe noise highly challenging. Since 2010, the American Institute of Aeronautics and Astronautics has organized an ongoing series of workshops devoted to Benchmark Problems for Airframe Noise Computations (BANC). The BANC workshops are aimed at enabling a systematic progress in the understanding and high-fidelity predictions of airframe noise via collaborative investigations that integrate state of the art computational fluid dynamics, computational aeroacoustics, and in depth, holistic, and multifacility measurements targeting a selected set of canonical yet realistic configurations. This paper provides a brief summary of the BANC effort, including its technical objectives, strategy, and selective outcomes thus far.