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At least 271 records · Page 15

An Improved Weighted Least Squares Algorithm for the Analysis of Strain-Gage Balance Calibration Data

An improved version of an algorithm is presented that uses a weighted least squares fit of balance calibration data for the generation of the balance load prediction equations. The weighted least squares fit assigns a weighting factor between zero and one to each calibration data point that depends on a simple count of the number of intentionally loaded balance gages. The greater the number of the loaded gages is, the smaller a data point's weighting factor becomes. This strategy has two advantages. First, single-component loads become more influential during the regression analysis of the calibration data. In addition, the negative influence of load schedule asymmetries on the regression analysis results can more effectively be controlled. The original algorithm of 2017 was improved in 2020. Now, gage output differences relative to the natural zeros are exclusively used as input for the determination of the number of intentionally loaded gages. The improved weighted least squares fit can be applied with both the Non-Iterative Method and the Iterative Method that are used for the balance load prediction in the aerospace testing community. Machine calibration data of a force balance is used to illustrate benefits of the application of the improved weighted least squares fit of balance calibration data.

strain-gage balance↗

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

Shie, C.-L.↗

GC/MS Method Development for Separating Lunar Volatile Ice Simulant Headspace Gases

Various investigators propose the lunar surface contains widely distributed volatiles, especially water- like species, i.e. OH and H2O. Surface volatiles are theorized to exist as a hydrated regolith layer, concentrated in extremely cold polar permanently shadowed regions (PSR), and/or solar wind implantation reservoirs in lunar glasses. The proposed sources of lunar surface volatiles range from cometary impacts, solar wind, or a supply present during moon formation. Future Artemis missions aim to collect and return the samples containing volatiles collected near lunar polar craters or PSRs. We, as advanced curation scientists, are responsible for developing techniques and methodologies for preserving returned sample integrity as much as possible. Pristine volatile-bearing samples are invaluable to the scientific community seeking to unravel the history of the solar system. Realistically, a sample will experience alteration during collection, transportation back to earth, and storage. The Planetary Exploration and Astromaterials Research Lab (PEARL) seeks to understand temperature and pressure effects on high-fidelity volatile-containing regolith simulants, the foundation for the future of cold curation. This abstract outlines the separation, identification, and quantification of headspace gases over volatile ice feed stock material using gas chromatography/mass spectrometry (GC/MS). Preliminary objectives concentrated on sample handling, reproducibility, and understanding the elution characteristics for each analyte. Initial GC/MS method development experiments utilized diluted static headspace sample preparation. Diluted samples were used because sampling headspace gases directly from a vial containing liquid analyte resulted in overloading of the column and detector. Overloading is evident based on chromatogram peak shapes and instrument contamination, or carry over, between experiments. A mixture of three alcohols were used for a majority of the sample handling and reproducibility studies. Reproducibility was tested via multiple users, calibration curves, and check standards. Stock solutions of condensed lunar volatile analytes included methanol, ammonia in methanol, hydrogen sulfide in water, and an equal volume mixture of methanol, ethanol, and isopropanol. Current samples use room air as the headspace sample matrix, however future experiments will incorporate an inert purge gas, such as argon or nitrogen. Three mL of each analyte solution were capped in separate 20 mL crimp top GC vials. Dilutions were carried out by removing an aliquot of headspace gases with a calibrated 1 mL gastight syringe and immediately transferring to a 20 mL capped crimp top vial. The GC/MS is a Thermo Fisher Trace 1310/ISQ 7000 with a TriPlus RSH autosampler and split/splitless injector module. The experiments outlined in this abstract use the following hardware: a 2.5 mL gastight headspace syringe tool, 1 mm ID x 78.5 mm length ultra-inert straight injection liner, and a TG-BondQ 30 m × 0.32 mm × 10 μm column. Various parameters, such as hardware selection and the temperature, pressure, and split ratio set points, continue to evolve as the overall experiment is refined. Diluted headspace chromatograms were collected for the individual stock solutions. Retention times, peak shapes, and mass spectra were evaluated and added to the data processing method for each molecule of interest. Figure 1 shows the total ion chromatograms for the three major lunar volatile simulant stock solutions: methanol, 7 N ammonia in methanol, and 0.4% hydrogen sulfide in water. Tailing peak shapes for ammonia (2.98 min rt) and water (4.06 min rt) indicate the molecules are not properly eluting from the selected column with the current separation method. Additionally, hydrogen sulfide and ammonia have overlapping peak windows, which could impact quantification. Ongoing experiments aim to address the peak shape and overlapping via the separation method and hardware selection. Sample preparation reproducibility experiments used stock solution containing equal volumes of a non- interactive mixture of methanol, ethanol, and isopropanol. Mass spectrum ion traces were used to identify and quantify all three alcohols. Peaks were automatically detected, identified, and integrated through the mass spectra detection and processing parameters. Calibration response curves and check standards were used to evaluate the validity of the sample preparation procedure. Figure 2 shows the methanol chromatogram peak area versus total headspace dilution volume transferred from the alcohol mixture vial. The calibration response curves and check standards validate sample preparation procedure. Continuing data analysis efforts are working towards correlating the peak area and instrument response factor to the headspace analyte concentration and condensed phase composition. Static headspace gas chromatography theory relies on Dalton’s law, Raoult’s law, Henry’s Law, and the Kolb and Ettre equation to associate peak area to the analyte composition in a non-ideal solution. Equation 1 is a simplified expression derived from the aforementioned theories. Future experiments involve liquid injections of the individual stock solutions, liquid and headspace analysis of various stock solution combinations, and the addition of regolith simulants to the mixtures. Temperature is another variable expected to affect reaction rates and will be explored.

Cecilia L. Amick↗

Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

strain-gage balance↗

Shuttle Return-to-Flight IH-108 Aerothermal Test at CUBRC - Flow Field Calibration and CFD

This paper discusses one specific aspect of the Shuttle Retrun-To-Flight IH-108 Aerothermal Test at CUBRC, the test flow field calibration. It showed the versatility of the CUBRC LENS II wind tunnel for an aerothermal test with unique and demanding requirements. CFD analyses were used effectively to extend the test range at the low end of the Mach range. It demonstrated how ground test facility and CFD synergy can be utilitzed iteratively to enhance the confidence in the fedility of both tools. It addressed the lingering concerns of the aerothermal community on use of inpulse facility and CFD analysis. At the conclusion of the test program, members from the NASA Marshall (MSFC), CUBRC and USA (United Space Alliance) Consultants (The Grey Beards) were asked to independently verify the flight scaling data generated by Boeing for flight certification of the re-designed external tank (ET) components. The blind test comparison showed very good results. A more comprehensive discussion of the topics in this paper can be found in Chapter 6 of Reference [1]. The overall aspect of the test program has been discussed in an AIAA paper by Tim Wadhams [2]. The Shuttle Ascent Stack performance and related issues discussed in the Report [1] are not included in this paper. No ITAR data is included in this paper.

Lau, Kei Y.↗

Shuttle Return-to-Flight IH-108 Aerothermal Test at CUBRC - Flow Field Calibration and CFD

This paper discusses one specific aspect of the Shuttle Retrun-To-Flight IH-108 Aerothermal Test at Calspan-University of Buffalo Research Center (CUBRC), the test flow field calibration. It showed the versatility of the CUBRC Large Energy National Shock Tunnel (LENS) II wind tunnel for an aerothermal test with unique and demanding requirements. CFD analyses were used effectively to extend the test range at the low end of the Mach range. It demonstrated how ground test facility and CFD synergy can be utilitzed iteratively to enhance the confidence in the fedility of both tools. It addressed the lingering concerns of the aerothermal community on use of inpulse facility and CFD analysis. At the conclusion of the test program, members from the NASA Marshall (MSFC), CUBRC and USA (United Space Alliance) Consultants (The Grey Beards) were asked to independently verify the flight scaling data generated by Boeing for flight certification of the re-designed external tank (ET) components. The blind test comparison showed very good results.

Lau, Kei Y.↗

iGlobe Interactive Visualization and Analysis of Spatial Data

iGlobe is open-source software built on NASA World Wind virtual globe technology. iGlobe provides a growing set of tools for weather science, climate research, and agricultural analysis. Up until now, these types of sophisticated tools have been developed in isolation by national agencies, academic institutions, and research organizations. By providing an open-source solution to analyze and visualize weather, climate, and agricultural data, the scientific and research communities can more readily advance solutions needed to understand better the dynamics of our home planet, Earth

Hogan, Patrick↗

Changes in Characteristics of Future Climate Across the U.S.: Time Series Analysis of Climate Model Data by NASA POWER

NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing capabilities to provide time series of the projected future evolution of surface quantities important to future energy production and use, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We present here a range of possible future changes in these quantities at locations throughout the continental United States. We show how both average and extreme values of the quantities will evolve from present-day to future climate conditions. We plan to provide these projections for users in the energy and sustainable energy communities.

Bradley M. Hegyi↗

Numerical Model Sensitivity to Heterogeneous Satellite Derived Vegetation Roughness

The sensitivity of a mesoscale weather prediction model to a 1 km satellite-based vegetation roughness initialization is investigated for a domain within the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database, specific to the domain, that was previously derived using a physically based procedure and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and iii) a MODIS climatologic roughness database that like (i) is a function only of land cover type, but possesses domain specific mean values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations within a domain including Oklahoma, Eastern Arkansas, and Northwest Louisiana during a 4-day period within IHOP 2002. Sensitivity analysis compares the impact the three roughness initializations on time-series temperature, precipitation probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE). Overall, the results indicate that, for the current investigation, replacement of the standard look-up table values with the satellite-derived values statistically improves model performance for most observed variables. Such natural roughness heterogeneity enhances the surface wind speed, PBL height and TKE production up to 10 percent, with a lesser effect over grassland, and greater effect over mixed land cover domains.

Jasinski, Michael↗

Mode shape analysis using a commercially available peak store video frame buffer

Time exposure photography, sometimes coupled with strobe illumination, is an accepted method for motion analysis that bypasses frame by frame analysis and resynthesis of data. Garden variety video cameras can now exploit this technique using a unique frame buffer that is a non-integrating memory that compares incoming data with that already stored. The device continuously outputs an analog video signal of the stored contents which can then be redigitized and analyzed using conventional equipment. Historically, photographic time exposures have been used to record the displacement envelope of harmonically oscillating structures to show mode shape. Mode shape analysis is crucial, for example, in aeroelastic testing of wind tunnel models. Aerodynamic, inertial, and elastic forces can couple together leading to catastrophic failure of a poorly designed aircraft. This paper will explore the usefulness of the peak store device as a videometric tool and in particular discuss methods for analyzing a targeted vibrating plate using the 'peak store' in conjunction with calibration methods familiar to the close-range videometry community. Results for the first three normal modes will be presented.

Snow, Walter L.↗

The Lewice Console

Lewice (LEWis ICE accretion program) is software used by literally hundreds of users in the aeronautics community for predicting ice shapes, collections efficiencies, and anti-icing heat requirements for aircraft. LEWICE performs its analysis in minutes on a desktop PC, allowing the user to run several parameter studies for design purposes. The ice shape predictions have been used to assess performance degradation both as an input to a CFD program or experimentally in flight or in a wind tunnel. This information is important to ensure an airplane s safe passage through an icing cloud. Currently, Lewice runs as a DOS program that accepts many different inputs such as cloud conditions, wing shapes, and thermal deicing inputs. Usually, such experimental data is stored in spreadsheets. However, Lewice inputs are text files; therefore, they must be generated by the user. Lewice s outputs (collection efficiency, ice shapes and thicknesses) are also text files; to plot the data, users must generate a spreadsheet with this output. Because all Lewice J/O is in the form of text files, using Lewice can be tricky and time-consuming. Our goal was to improve Lewice s usability by creating a user interface that would automatically generate Lewice input from a spreadsheet and automatically put Lewice output into spreadsheets with charts. Additionally, this user interface would automatically convert units (as Lewice only accepts input in certain units) and offer several output options. I call this program the Lewice Console. The Lewice Console is an easy to use interface for Lewice written in Visual Basic. It allows users to run Lewice given a spreadsheet listing experimental conditions. It automatically generates the input to Lewice, does necessary unit conversions, runs Lewice, and produces a spreadsheet with charts plotting the data. It allows users to import data from previously generated Lewice inputs into a spreadsheet. It also allows users to batch run Lewice on several different inputs to automatically generate multiple output spreadsheets. You can also generate plots of actual data vs. experimental data. These capabilities are just the beginning for the Lewice Console. Lewice is capable of running a full deicing experiment given a geometry and heating apparatus information. However, users find it difficult to run such experiments due to the number of inputs and the difficult input file format. The Lewice Console would simplify experiment generation by allowing the user to interactively draw a geometry, place heating apparatus, and specify information about each part. The input to Lewice would be automatically generated from the experiment the user draws on the screen. The Lewice Console would simplify the experiment building process. Currently, Lewice runs as a DOS program that accepts many different inputs such as

Armstrong, Aaron E.↗

Development of a Climatology of Vertically Complete Wind Profiles from Doppler Radar Wind Profiler Systems

Assessment of space vehicle loads and trajectories during design requires a large sample of wind profiles at the altitudes where winds affect the vehicle. Traditionally, this altitude region extends from near 8-14 km to address maximum dynamic pressure upon ascent into space, but some applications require knowledge of measured wind profiles at lower altitudes. Such applications include crew capsule pad abort and plume damage analyses. Two Doppler Radar Wind Profiler (DRWP) systems exist at the United States Air Force (USAF) Eastern Range and at the National Aeronautics and Space Administration's Kennedy Space Center. The 50-MHz DRWP provides wind profiles every 3-5 minutes from roughly 2.5-18.5 km, and five 915-MHz DRWPs provide wind profiles every 15 minutes from approximately 0.2-3.0 km. Archived wind profiles from all systems underwent rigorous quality control (QC) processes, and concurrent measurements from the QC'ed 50- and 915-MHz DRWP archives were spliced into individual profiles that extend from about 0.2-18.5 km. The archive contains combined profiles from April 2000 to December 2009, and thousands of profiles during each month are available for use by the launch vehicle community. This paper presents the details of the QC and splice methodology, as well as some attributes of the archive.

Barbre, Robert, Jr.↗

Vermont Wildland Fires: Investigating the Role of Antecedent Conditions and Recent Environmental Trends in Exacerbating Fire Risk and Potential in Vermont

Under a changing climate, increases in dry conditions and extreme heat events are projected to exacerbate wildfire risk in the northeastern U.S. In recent years, Vermont has observed higher annual temperatures, more frequent heatwaves, increased annual precipitation, extreme flood events, and decreased snowfall. The mechanisms through which environmental factors contribute to increased fire risk in humid environments, such as Vermont, are poorly understood. The team partnered with the National Weather Service, the Vermont Division of Forests, and the University of Vermont to investigate phenological trends and antecedent conditions influencing wildland fire risk. For the phenological analysis, from 2001 to 2023, vegetation data, phenological dates, and snow water equivalent (SWE) values were accessed from Landsat 5Thematic Mapper (TM), Landsat 7Enhanced Thematic Mapper Plus (ETM+), Landsat 8Operational Land Imager (OLI), Landsat 9OLI-2, the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Snow Data Assimilation System (SNODAS), respectively. For the antecedent condition analysis, from 2008 to 2023, soil moisture, Environmental Stress Index, wind speed, minimum relative humidity, and daily precipitation data were obtained from the Global Land Data Assimilation System (GLDAS), SERVIR, gridMET Wind, gridMET Humidity, and NClimGrid, respectively. The study found that green-up dates over the study period remain relatively stable, while snowmelt dates appear increasingly variable. Minimum relative humidity was the most significant environmental variable correlated with wildfire risk in Vermont. Results from this study will inform the National Weather Service's preparation of fire forecasts before prescribed burns and support community outreach by the Vermont Agency of Natural Resources.

Wildland Fire↗

Effects of Meteorological Conditions on Reactions to Noise Exposure

More than 80,000 residents' responses to transportation noise at different times of year provide the best, but imprecise, statistical estimates of the effects of season and meteorological conditions on community response to noise. Annoyance with noise is found to be slightly statistically significantly higher in the summer than in the winter in a seven-year study in the Netherlands. Analyses of 41 other surveys drawn from diverse countries, climates, and times of year find noise annoyance is increased by temperature, and may be increased by more sunshine, less precipitation, and reduced wind speeds. Meteorological conditions on the day of the interview or the immediately preceding days do not appear to have any more effect on reactions than do the conditions over the immediately preceding weeks or months.

Shepherd, Kevin P.↗

Influence of Satellite-Based Heterogeneous Vegetation Momentum Roughness on Mesoscale Model Dynamics During IHOP 2002

The sensitivity of mesoscale weather prediction model to a vegetation roughness initialization is investigated for the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database previously derived using a physically based procedure and MODIS imagery, and iii) a MODIS climatologic roughness database that possesses the same spatial heterogeneity as (i) but with mean land class values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations from meteorological stations within the Oklahoma mesonet and surrounding region during IHOP20O2. A sensitivity analysis on the impact the MODIS-based roughness fields is also made through a time-series intercomparison of temperature bias, probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE) the results that, for the current replacement of the standard land-cover type based roughness values with the satellite-derived fields statistically improves model performance for most of the observed variables. Further, the satellite-based roughness enhances the surface wind speed, PBL height and TKE production on the order of 3 to l0 percent, with a lesser effect over grassland and cropland domains, and the greater effect over mixed land cover domains

Jasinski, Michael↗

History of the numerical aerodynamic simulation program

The Numerical Aerodynamic Simulation (NAS) program has reached a milestone with the completion of the initial operating configuration of the NAS Processing System Network. This achievement is the first major milestone in the continuing effort to provide a state-of-the-art supercomputer facility for the national aerospace community and to serve as a pathfinder for the development and use of future supercomputer systems. The underlying factors that motivated the initiation of the program are first identified and then discussed. These include the emergence and evolution of computational aerodynamics as a powerful new capability in aerodynamics research and development, the computer power required for advances in the discipline, the complementary nature of computation and wind tunnel testing, and the need for the government to play a pathfinding role in the development and use of large-scale scientific computing systems. Finally, the history of the NAS program is traced from its inception in 1975 to the present time.

Peterson, Victor L.↗

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Hou, Arthur Y.↗

Facilitating Heliophysics Research by the Virtual Wave Observatory (VWO) Context Data Search Capability

Wave phenomena, ranging from freely propagating electromagnetic radiation (e.g., solar radio bursts, AKR) to plasma wave modes trapped in various plasma regimes (e.g., whistlers, Langmuir and ULF waves) and atmospheric gravity waves, are ubiquitous in the heliosphere. Because waves can propagate, wave data obtained at a given observing location may pertain to wave oscillations generated locally or from afar. While wave data analysis requires knowledge of wave characteristics specific to different wave modes, the search for appropriate data for heliophysics wave studies also requires knowledge of wave phenomena. In addition to deciding whether the interested wave activity is electrostatic (i.e., locally trapped) or electromagnetic (with propagation over distances), considerations must be given to the dependence of the wave activity on observer's location or viewing geometry, propagating frequency range and whether the wave data were acquired by passive or active observations. Occurances of natural wave emissions i the magnetosphere (e.g, auroral kilometric radiation) are often dependent also on the state (e.e., context) of the magnetosphere that varies with the changing solar wind, IMF and geomagnetic conditions. Fung and Shao [2008] showed recently that magnetospheric state can be specified by a set of suitably time-shifted solar wind, IMF and the multi-scale geomagnetic response parameters. These parameters form a magnetospheric state vector that provides the basis for searching magnetospheric wave data by their context conditions. Using the IMAGE Radio Plasma Imager (RPI) data and the NASA Magnetospheric State Query System (MSOS) [Fung, 2004], this presentation demonstrates the VWO context data search capability under development and solicits feedback from the Heliophysics research community for improvements.

Fung, Shing F.↗